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11,600 | Please write an abstract with title: Understanding and Improving Reliability for Wafer Level Chip Scale Package: A Study Based on 45nm RFSOI Technology for 5G Applications, and key words: Reliability, Stress, 5G mobile communication, Soldering, Radio frequency, Moisture, Finite element analysis. Abstract: Wafer level chip scale package (WLCSP) is true chip scale package with low cost by eliminating package substrate. The direct chip-to-board attach through solder joints provides low interconnect inductance and resistance, as well as improved thermal performance. These properties make WLCSP a packaging format well suited for 5G radio frequency (RF) applications where minimized package size and parasitics as well as thermal performance are critical. Due to the dissimilar properties between chip and board, the reliability of WLCSP can be challenging. This article reports a reliability study of WLCSP using 45nm RFSOI technology for 5G RF applications. Dedicated test chips and boards were designed and used for board level reliability tests. The test vehicles passed bHAST and drop test, whereas it is found that temperature cycling on board (TCoB) is challenging for solder joint reliability in some cases. Thorough tests were carried out based on Kelvin test on specially designed individual bump and bump pair structures and developed fail criterion. Finite element modeling was adopted to simulate the reliability performance in different configurations. The impact on reliability performance from bump depopulation, die thickness, bump size, UBM to board pad alignment, and board wiring trace were thoroughly investigated. Based on comprehensive testing and deep understanding of the failure mechanisms, design optimizations for chip, board and interconnect were implemented. WLCSP reliability was significantly improved. |
11,601 | Please write an abstract with title: Impact of on-die decoupling on the core and IO supplies of high performance microprocessors, and key words: Microprocessors, Power supplies, Impedance, Circuits, Silicon, Packaging, Predictive models, Voltage, Capacitance, Costs. Abstract: In this paper, we present an empirical validation of the power supply decoupling with particular emphasis on on-die capacitance. We investigate the effect of the decoupling on both the core and IO performance. The validation approach consists of building several silicon wafers of high performance processors with various amounts of decoupling. Extensive measurements are then done at the silicon, package, and system levels. Finally we offer some theoretical insights to explain the unexpected behavior. |
11,602 | Please write an abstract with title: Characteristics of Inhomogeneous Broadside-Coupled Striplines, and key words: Stripline, Strips, Inductance, Circuits, Microstrip components, Conformal mapping, Fourier transforms, Dielectric materials, Attenuation, Directional couplers. Abstract: A variational method for the analysis of inhomogeneous broadside-coupled striplines is described. The data for even- and odd-mode characteristic impedances, effective dielectric constants, and mode phase velocity ratios are presented. It is found that the phase velocity ratio may be varied over the range 1.14 /spl les/ ( V/sub e/ / V/sub 0/) /spl les/ 3.6 for broadside-coupled suspended microstrip lines (BSML) and 0.36 /spl les/ ( V/sub e/ / V/sub 0/) /spl les/ 0.93 for broadside-coupled inverted microstrip lines (BIML) using materials with dielectric constant less than 16 and S/b /spl ges/ 0.05, W/b /spl les/ 2.0. The effect of nonzero strip thickness is also calculated. It is noticed that the effect of thickness is more pronounced for the odd-mode case than for the even mode. Losses are obtained using the incremental inductance rule of Wheeler. The odd-mode attenuation constant is always higher than the even-mode value. |
11,603 | Please write an abstract with title: Localized Data Transfer System by Vehicles and Cellular Base Station in Local Area, and key words: Base stations, Cloud computing, Conferences, Heuristic algorithms, Vehicular ad hoc networks, Distributed databases, Data transfer. Abstract: Dynamic map system is one of key elements for autonomous driving (AD) car. Semi-dynamic data and semi-static data of Dynamic Map are locally collected and used. Volume of these is some Megabytes, and the time-life of these is sub second to several minutes. A concept of such localized data transfer system is proposed. An effect of Vehicle to Vehicle communication (V2V) using wide range communication technology for Vehicle to Network communication (V2N) is estimated and an effect of off-loading cloud computing to edge computing and vehicle computing is estimated. Require for data base system of these data transfer system realization is proposed. |
11,604 | Please write an abstract with title: An investigation of forward error correcting codes for a meteor burst communication channel, and key words: Forward error correction, Redundancy, Encoding, Decoding, Automatic repeat request, Reed-Solomon codes, Protocols. Abstract: Meteor Burst Communication Links offer the facility for transmitting data via trails of ionised particles, which form continually as meteors enter our atmosphere. Unfortunately, this propagation medium is exposed to countless external disturbances, and is therefore inherently noisy. Most commercial systems have overcome this difficulty by means of Automatic Repeat Request (AHQ) protocols, where received frames containing errors are simply retransmitted. This paper investigates the viability of an alternative system, viz. the Forward Error Correcting (FEC) protocol, where sufficient redundancy is inserted at the transmitter to enable correction of the noise-corrupted bits by the receiver. An accurate simulation of the complete link was implemented in software (C), effectively modelling the encoding, modulation, noise-corruption, demodulation and decoding processes. Four coding schemes were examined (Reed-Solomon, Golay, Viterbi and Iwadare), and comprehensive testing was performed using live trail data. Analyses of our results and tentative conclusions are presented. |
11,605 | Please write an abstract with title: Rotation and scale insensitive image watermarking, and key words: Watermarking, Fourier transforms, Copyright protection, Interpolation, Discrete Fourier transforms, Communication system control, Underwater tracking, Noise robustness, Image resolution, Detectors. Abstract: Using electronic watermarks as copyright protection for still images requires robustness against attacks. In this paper we propose a watermarking scheme that is robust to rotation, scaling and translation (RST) distortions. The watermark is embedded in a 1D invariant domain that is a projection of the polar Fourier transform. Roc curves depicting false positives versus detection probability of the watermark are provided, under various geometrical attacks and JPEG coding. |
11,606 | Please write an abstract with title: Formation Control for Time-delayed Second-order Multi-agent Systems with Switching Topology, and key words: Switches, Topology, Protocols, Delay effects, Multi-agent systems, Laplace equations. Abstract: Formation control problems for time-delayed second-order multi-agent systems with switching topology are investigated in this study. A formation control protocol with time delays and switching topology is presented. A specific expression of the time-varying formation reference function is given to indicate the movement of the formation. Sufficient conditions for time-delayed second-order multi-agent systems with switching topology to achieve time-varying formation are given. Numerical examples are given to show the effectiveness of the presented results. |
11,607 | Please write an abstract with title: Power Efficient Simple Technique to Convert a Reset-and-Hold Into a True-Sample-and-Hold Using an Auxiliary Output Stage, and key words: Capacitors, Power dissipation, Switching circuits, Clocks, Capacitance, Silicon. Abstract: A technique to implement true-sample-and-hold circuits that hold the output for almost the entire clock cycle without resetting to zero is introduced, alleviating the slew rate requirement on the op-amp. It is based on a Miller op-amp with an auxiliary output stage that increases power dissipation by only 1.3%. The circuit is offset-compensated and has close to rail-to-rail swing. Experimental results of a test chip prototype in 130nm CMOS technology with 0.3mW power dissipation are provided, which validate the proposed technique. |
11,608 | Please write an abstract with title: Secure and Reliable Multidimensional Orthogonal Code aided RF Watermark Design for NB-IoT Systems, and key words: Watermarking, Radio frequency, Receivers, Reliability, Transmitters, Wireless communication. Abstract: Narrow band Internet of Things (NB-IoT) systems support massive devices to connect with the wide area network with the low energy consumption. However, due to the broadcasting property and variant conditions of wireless channels, both the security and the reliability performances are required to be improved for NB-IoT terminals. In this paper, we propose a multidimensional orthogonal code (MOC) aided radio frequency (RF) watermark scheme to enhance both the security and the reliability performances. In our design, we exploit the repeat transmission mechanism in NB-IoT systems, and propose to use the repeated signal as the host signal to carry multiple low-power watermark signals, wherein different orthogonal codewords are utilized as the embedding coefficients to hide the host signals. Thanks to the orthogonality of MOC watermarks, the mutual interferences among the transmitted signals can be effectively suppressed, thus the reliability performances could be improved. Furthermore, we derive the theoretical bit error rate (BER) and analyze the efficiency as well as the covertness. Simulation results validate the theoretical analysis. Moreover the results demonstrate that using the proposed MOC aided RF watermark design, NB-IoT systems can achieve better reliability and covertness performances as well as higher security performances than counterpart schemes. |
11,609 | Please write an abstract with title: Multiple description coding using transforms and data fusion, and key words: Image coding, Distortion, Image reconstruction, Vector quantization, Decoding, Computer aided manufacturing, Pulp manufacturing, Fusion power generation, Signal design, IP networks. Abstract: A new multiple description coding technique is proposed, in which multiple descriptions are generated using different transforms and a linear fusion is employed to reconstruct the central description. This new method exhibits some of the advantages of multiple description vector quantization while having the complexity of multiple description scalar quantization. When this method is applied to fixed level scalar quantization of a memoryless Gaussian signal, the distortion of the central description is about half the distortion of side descriptions if the side descriptions have been designed to have the least distortion achievable at a fixed rate. When applied to image coding, the new technique yields result, which is better than current state-of-the-art MD image coders in terms of description distortions and complexity of implementation. |
11,610 | Please write an abstract with title: CausalRD: A Causal View of Rumor Detection via Eliminating Popularity and Conformity Biases, and key words: Industries, Deep learning, Social networking (online), Conferences, Media, Predictive models, Prediction algorithms. Abstract: A large amount of disinformation on social media has penetrated into various domains and brought significant adverse effects. Understanding their roots and propagation becomes desired in both academia and industry. Prior literature has developed many algorithms to identify this disinformation, particularly rumor detection. Some leverage the power of deep learning and have achieved promising results. However, they all focused on building predictive models and improving forecast accuracy, while two important factors - popularity and conformity biases - that play critical roles in rumor spreading behaviors are usually neglected.To overcome such an issue and alleviate the bias from these two factors, we propose a rumor detection framework to learn debiased user preference and effective event representation in a causal view. We first build a graph to capture causal relationships among users, events, and their interactions. Then we apply the causal intervention to eliminate popularity and conformity biases and obtain debiased user preference representation. Finally, we leverage the power of graph neural networks to aggregate learned user representation and event features for the final event type classification. Empirical experiments conducted on two real-world datasets demonstrate the effectiveness of our proposed approach compared to several cutting-edge baselines. |
11,611 | Please write an abstract with title: Federated Transfer Learning Based Cross-Domain Prediction for Smart Manufacturing, and key words: Transfer learning, Data privacy, Collaborative work, Data models, Smart manufacturing, Training data, Servers. Abstract: Smart manufacturing aims to support highly customizable production processes. Therefore, the associated machine intelligence needs to be quickly adaptable to new products, processes, and applications with limited training data while preserving data privacy. In this article, a new federated transfer learning framework, federated transfer learning for cross-domain prediction, is proposed to address the challenges of data scarcity and data privacy faced by most machine learning approaches in modern smart manufacturing with cross-domain applications. The framework architecture consists of a central server and several groups of smart devices, where each group handles a different application. The existing applications can share their knowledge through the central server as base models, while new applications can convert a base model to their target-domain models with limited application-specific data using a transfer learning technique. Meanwhile, the federated learning scheme is deployed within a group to further enhance the accuracy of the application-specific model. The integrated framework allows model sharing across the central server and different smart devices without exposing any raw data and, hence, protects the data privacy. Two public datasets, COCO and PETS2009, which represent the source and target applications, are employed for evaluations. The simulation results show that the proposed method outperforms two state-of-the-art machine learning approaches by achieving better learning efficiency and accuracy. |
11,612 | Please write an abstract with title: Efficient barrier using remote memory operations on VIA-based clusters, and key words: Protocols, Local area networks, Clustering algorithms, Context, Switches, Communication switching, Kernel, Laboratories, Delay, LAN interconnection. Abstract: Most high performance scientific applications require efficient support for collective communication. Point-to-point message-passing communication in current generation clusters are based on the Send/Recv communication model. Collective communication operations built on top of such point-to-point message-passing operations might achieve suboptimal performance. VIA and the emerging InfiniBand architecture support remote DMA operations, which allow data to be moved between the nodes with low overhead; they also allow to create and provide a logical shared memory address space across the nodes. In this paper we focus on barrier, a frequently-used collective operations. We demonstrate how RDMA write operations can be used to support an inter-node barrier in a cluster with SMP nodes. Combining this with a scheme to exploit shared memory within a SMP node, we develop a fast barrier algorithm for a cluster of SMP nodes with a cLAN VIA interconnect. Compared to current barrier algorithms using the Send/Recv communication model, the new approach is shown to reduce barrier latency on a 64 processor (32 dual nodes) system by up to 66%. These results demonstrate that high performance and scalable barrier implementations can be delivered on current and next generation VIA/Infiniband-based clusters with RDMA support. |
11,613 | Please write an abstract with title: A Lightweight Deep Learning Model for COVID-19 Detection, and key words: Diseases, X-ray imaging, Lung, Machine learning, Feature extraction, Computational modeling. Abstract: COVID-19 is a contagious disease that has caused more than 230,000 deaths worldwide at the end of April 2020. Within a span of just a few months, it has infected more than 4 million peoples across the globe due to its high transmittance rate. Thus, many governments have tried their best to increase the diagnostic capability of their hospitals so that the disease can be identified as early as possible. However, in most cases, the results only come back after a day or two, which directly increases the possibility of disease spreadness because of the delayed diagnosis. Therefore, a fast screening method using existing tools such as x-ray and computerized tomography scans can help alleviate the burden of mass diagnosis tests. A chest x-ray is one of the best modalities in diagnosing a pneumonia symptom, which is the primary symptom for COVID-19. Hence, this paper proposes a lightweight deep learning model to screen the possibility of COVID-19 accurately. A lightweight model is important, as such it allows the model to be deployed on various platforms that include mobile phones, tablets, and normal computers without worrying about the memory storage capacity. The proposed model is based on 14 layers of convolutional neural network with a modified spatial pyramid pooling module. The multiscale ability of the proposed network allows it to identify the COVID-19 disease for various severity levels. According to the performance results, the proposed SPP-COVID-Net achieves the best mean accuracy of 0.946 with the lowest standard deviation among the training folds accuracy. It comprises of just 862,331 total number of parameters, which uses less than 4 MegaBytes memory storage. The model is suitable to be implemented for fast screening purposes so that better-targeted diagnoses can be performed to optimize the test time and cost. |
11,614 | Please write an abstract with title: Representative feeders for spatial scaling of stochastic PV hosting capacity, and key words: Photovoltaic systems, Low voltage, Europe, Distribution networks, Feature extraction, Threshold voltage, Planning. Abstract: The photovoltaics (PV) hosting capacity (HC) of the power system infrastructure is an important planning problem. The energy transition is happening now, resulting in the addition of new load types and generation in the low voltage distribution network. With these new loads and generation devices connected to the distribution network, a new planning approach is required that considers their stochastic nature. Computing the stochastic HC for all individual low voltage distribution feeders is challenging, as a small service area can have hundreds of feeders. This work aims to capture appropriate clustering schemes and the most relevant features of low voltage distribution feeders so that an accurate estimate of the hosting capacity of the full service area can be calculated by scaling up the hosting capacity of a small number of representative feeders. A case study using actual feeders from suburban Spain showed that representative feeders obtained from feature reduction and using appropriate cluster size enables to scale the stochastic PV HC of an extensive service area. The case study showed that using 3% of the total feeders enables to estimate the PV HC of the LVDS feeders in the large service area. |
11,615 | Please write an abstract with title: Control-Theoretic, Recursive Smoothing Splines, and key words: Interpolation, Smoothing methods, Aerospace electronics, Calculus, Control theory, Splines (mathematics). Abstract: Interpolating or smoothing splines both require the inversion of a matrix of a size proportional to the total number of data points. This becomes a prohibitively costly proposition for large data sets and constitutes an inappropriate approach when the data is incremental or the underlying distribution from which the data is drawn is time-varying. In this paper, an algorithm is developed for the construction of recursive smoothing splines based on Calculus of Variations that can handle incremental and intermediate-sized batches of data sets, as well as data sets that are modified over time. The algorithm uses the previous data in the construction of the updated curve and a numerically efficient algorithm is developed to solve the problem. |
11,616 | Please write an abstract with title: Exploring major events and the accumulated user forecasting model to support building Web-based learning communities - preliminary analysis from the school for all, and key words: Predictive models, Learning systems, Buildings, Information analysis, Computer science, Computer networks, Communications technology, Recruitment, Educational institutions, Humans. Abstract: Many researchers used computer technology over the last decade to build a virtual learning community in Web-based learning environment. However, building and managing a sustainable learning community remains challenging. One of the goals of this study is to try to identify some major events that affect learning community growth, and another goal is employ these events to develop a regression model for forecasting accumulated effective users in learning communities in the future. This study uses a Web-based learning system, as a preliminary analysis environment. Four major events that influence learning communities were identified, and these events were used to establish a regression model for calculating accumulated effective users. Future works will attempt to prove that the forecast regression model affects community building. |
11,617 | Please write an abstract with title: Input Regulated Soft Switched Ripple Free Current LED Driver, and key words: Inverters, Bridge circuits, Inductors, Switches, Voltage control, LED lamps. Abstract: This paper furnish an input voltage controlled full-bridge inverter based LED driver. A Double-ended forward converter(DEFC) is used along with full-bridge inverter to regulate the input of full bridge inverter for variations in the supply voltage. Input voltage to the full bridge inverter is sum of primary DC voltage and output of DEFC. Input to DEFC is from primary source. Supply obtained for the proposed configuration can be from DC micro grid. Thus the full bridge inverter is operated with fixed frequency and fixed duty ratio to achieve ZVS over wide range of input voltage variations. Full bridge converter with interleaved operation of output inductor currents is used to achieve ripple free constant current for LED string. In this configuration, power processed by DEFC is low which doesn't influence significantly, the overall efficiency is expected to be high. The proposed circuit configuration analyzed and simulation results are presented. |
11,618 | Please write an abstract with title: A new method of measuring temperature, inversion ratio, and pressure-broadened linewidth in a CW molecular laser, and key words: Temperature measurement, Laser tuning, Oscillators, Laser transitions, Wavelength measurement, Resonance light scattering, Optical scattering, Pressure measurement, Photonic band gap, Tunable circuits and devices. Abstract: This correspondence describes a new technique for measuring temperature, inversion ratio, and the extent of pressure broadening in a CW molecular laser oscillator. All three quantities can be obtained from one set of measurements performed on the oscillator itself. |
11,619 | Please write an abstract with title: Deep Learning based Segmentation Pipeline for Label-Free Phase-Contrast Microscopy Images, and key words: Image segmentation, Phase change materials, Training, Computer architecture, Microscopy, Cells (biology), Feature extraction. Abstract: The segmentation of cells is necessary for biologists in the morphological statistics for quantitative and qualitative analysis in Phase-contrast Microscopy (PCM) images. In this paper, we address the cell segmentation problem in PCM images. Deep Neural Networks (DNNs) commonly is initialized with weights from a network pre-trained on a large annotated data set like ImageNet have superior performance than those trained from scratch on a small dataset. Here, we demonstrate how encoder-decoder type architectures such as U-Net and Feature Pyramid Network (FPN) can be improved by an alternative encoder which pre-trained on the ImageNet dataset. In particular, our experimental results confirm that the image descriptors from ResNet-18 are highly effective in accurate prediction of the cell boundary and have higher Intersection over Union (IoU) in comparison to the classical U-Net and require fewer training epochs. |
11,620 | Please write an abstract with title: Dark Reciprocal-Rank: Teacher-to-student Knowledge Transfer from Self-localization Model to Graph-convolutional Neural Network, and key words: Visualization, Costs, Codes, Automation, Conferences, Neural networks, Convolutional neural networks. Abstract: In visual robot self-localization, graph-based scene representation and matching have recently attracted research interest as robust and discriminative methods for self-localization. Although effective, their computational and storage costs do not scale well to large-size environments. To alleviate this problem, we formulate self-localization as a graph classification problem and attempt to use the graph convolutional neural network (GCN) as a graph classification engine. A straightforward approach is to use visual feature descriptors that are employed by state-of-the-art self-localization systems, directly as graph node features. However, their superior performance in the original self-localization system may not necessarily be replicated in GCN-based self-localization. To address this issue, we introduce a novel teacher-to-student knowledge-transfer scheme based on rank matching, in which the reciprocal-rank vector output by an off-the-shelf state-of-the-art teacher self-localization model is used as the dark knowledge to transfer. Experiments indicate that the proposed graph-convolutional self-localization network (GCLN) can significantly outperform state-of-the-art self-localization systems, as well as the teacher classifier. The code and dataset are available at https://github.com/KojiTakeda00/Reciprocal_rank_KT_GCN. |
11,621 | Please write an abstract with title: Robot navigation in corridor environments using a sketch floor map, and key words: Navigation, Floors, Robot sensing systems, Data mining, Humans, Information science, Feature extraction, Sensor phenomena and characterization, Character generation. Abstract: This paper presents a new robot navigation system that can operate on a sketch floor map provided by a user. This sketch map is similar to floor plans as shown at the entrance of buildings, which does not contain accurate metric information and details such as obstacles. The system enables a user to give navigational instructions to a robot by interactively providing a floor map and pointing out goal positions on the map. Since metric information is unavailable, navigation is done using an augmented topological map which described the structure of the corridors extracted from a given floor map. Multiple hypotheses of the robot's location are maintained and updated during navigation in order to cope with sensor aliasing and landmark-matching failures due to factors such as unknown obstacles inside the corridors. |
11,622 | Please write an abstract with title: The nonlinear Choke Parameter Identification based on the Modified Artificial Neural Network, and key words: Voltage measurement, Parameter estimation, Recurrent neural networks, Simulation, Mathematical model, Integrated circuit modeling, Inductors. Abstract: The method of identification of the Nonlinear Choke Parameter (NCP) identification via a Modified artificial Recurrent Neural Network (MRNN) has been proposed and researched. The method makes it possible to use knowledge about the object for the synthesis of an MRNN structure and the computation of their coefficients from measured instantaneous values of currents and voltages in the circuit. NCP in the proposed MRNN were realized by expanding the input signal space of the network, using the normalized signals of polynomial terms. The proposed method can estimate MRNN structure to meets with NCP accuracy requirements. The NCP approximation in the one and a few function forms were also provided. The proposed method of NCP identification is based on the weighted MRNN coefficients. A comparison is made of the accuracy of identification of NCP for different MRNN structures and previously known measurement object data. An accuracy estimation for the models NCP in the form of a MRNN was made on mathematical models and on a real object. |
11,623 | Please write an abstract with title: GloptiPoly: global optimization over polynomials with Matlab and SeDuMi, and key words: Polynomials, MATLAB, Computational efficiency, Robust stability, World Wide Web, Linear matrix inequalities, MONOS devices, Robust control, Optimal control, Automatic control. Abstract: GloptiPoly is a Matlab/SeDuMi add-on to build and solve convex linear matrix inequality relaxations of the (generally non-convex) global optimization problem of minimizing a multivariable polynomial function subject to polynomial inequality, equality or integer constraints. It generates a series of lower bounds monotonically converging to the global optimum. Global optimality is detected and isolated optimal solutions are extracted automatically. Numerical experiments show that for most of the small- and medium-scale problems described in the literature, the global optimum is reached at low computational cost. |
11,624 | Please write an abstract with title: Deep Learning in Image Classification using VGG-19 and Residual Networks for Cataract Detection, and key words: Cataracts, Deep learning, Training, Biological system modeling, Medical services, Blindness, Retina. Abstract: Cataracts are often touted as the number one cause of blindness in Indonesia. In fact, referring to data from the World Health Organization (WHO), cataracts account for about 48% of blindness cases in the world and are number one in Indonesia. The research that has been done on cataracts is classified through various objects such as blood vessels, optic disc, the object used is the optical disk in the retinal fundus camera image. The purpose of this study is to produce an automatic cataract early detection application program by classifying cataracts into two categories, normal cataracts, and cataracts. Early examination of cataract patients for people who have less economic capacity such as most of the population in developing countries is considered very helpful. Classification is needed to assist doctors in deciding when to operate on cataract patients. Processing of 1088 patient retinal fundus image data consisting of 500 normal retinal images and 594 cataract images. Furthermore, the classification process is carried out using VGG-19, ResNet-50 and ResNet-101 which is processed with Jupyter Notebook. From the results of training and testing, the average accuracy of VGG19 is 91.06%, ResNet-50 93,50% and ResNet-101 is 93,50% in all retinal classes. |
11,625 | Please write an abstract with title: Replica allocation considering power consumption in mobile ad hoc networks, and key words: Energy consumption, Intelligent networks, Mobile ad hoc networks, Ad hoc networks, Batteries, Frequency, Mobile computing, Information science, Radio link, Pervasive computing. Abstract: In ad hoc networks, it is effective that each mobile host creates replicas of data items held by other hosts for improving data accessibility. However, a mobile host holding data items frequently accessed by other hosts needs to transmit them many times and consumes more power than other hosts. In this paper, we propose a replica allocation method for not only improving data accessibility but also balancing the power consumption among mobile hosts. In this method, each mobile host replicates data items considering their access frequencies, the numbers of their replicas, and the remaining amount of its battery. We present simulation results to evaluate the performance of our proposed method |
11,626 | Please write an abstract with title: Distributed Localization of Networked Agents in GPS-Denied 3D Environments, and key words: Location awareness, Jacobian matrices, Three-dimensional displays, Heuristic algorithms, Estimation, Distance measurement, Reliability. Abstract: This paper studies the distributed localization of networked agents using only distance measurements in a GPS-Denied 3D environment, which extends the existing results to the 3D localization in the presence of measurement noise and greatly improves its applications in internet of things. To deal with the distributed 3D localization, the barycentric coordinates of an agent in a tetrahedron are introduced by employing the Cayley-Menger determinants, which enables the localization problem of networked agents to be equivalently transformed into a linear estimation problem. Then, a recursive estimation algorithm is developed under the Jacobi Over-Relaxation (JOR) framework which recursively solves the linear estimation problem in a distributed manner; as a result, the proposed method can be scaled to the localization of large-scale networked agents. Finally, a simulation example is given to show the effectiveness of the proposed algorithm. |
11,627 | Please write an abstract with title: Understanding time-varying vulnerability accross GPU Program Lifetime, and key words: Fault tolerance, Fault tolerant systems, Discrete Fourier transforms, Graphics processing units, Very large scale integration, Parallel processing, Behavioral sciences. Abstract: Time-varying behaviors of GPU program vulnerability could be exploited to reduce overheads for fault-tolerant designs. However, the inherent parallelism and performance overheads for massive fault injection (FI) hindered such assessments using FI. NVBitFI, a GPU FI tool featuring high-performance and good compatibility, allows time-varying vulnerability evaluations using FI within a reasonable time. We extended NVBitFI to control FI tests on the temporal dimension. A scalable workflow characterizing the time-varying vulnerability of GPU programs at two granularities is presented. A convenient approach to profile vulnerability with actual GPU time is also proposed. Results obtained from 60K fault injections demonstrated the feasibility of the proposed methodologies. A case study exploring the improved instruction-level grouping is presented. More than 340K faults are injected into the vectorAdd kernel to show the possibility to generalize the time-varying behavior of smaller inputs to realistic workloads with large inputs. |
11,628 | Please write an abstract with title: Finite Element Study on Electric Field Distortion and Maxwell Stress Distribution Characteristics of XLPE Insulation Considering Water tree under Different Conditions, and key words: Power cables, Power cable insulation, Voltage, Distortion, Finite element analysis, Trees - insulation, Electric fields. Abstract: Water tree is one of the important factors that affect the service life of XLPE insulation cable and seriously threaten the safety of cable operation. In order to study the electric field distortion and Maxwell stress distribution characteristics considering water tree under different circumstances, the paper takes position, length and dispersion into consideration, and then a cable insulaton model with water tree defects under different conditions is established in the finite element simulation software. By applying a fixed voltage on both sides of the insulation, the axial electric field intensity of water tree is scanned, the maximum electric field intensity in the insulation is counted, and the influence characteristics of water tree on the electric field distortion of cable XLPE insulation are studied. At the same time, the Maxwell stress caused by electric field distortion is calculated, and the maximum axial stress of water tree is extracted and analyzed. The results show that when the size is approximately the same, the electric field distortion caused by Inner dispersed water tree is significantly higher than that on Outer dispersed water tree, and the electric field distortion caused by the Butterfly-shaped water tree whose size is approximately twice that of the dispersed water tree is between the two; The effect of length and dispersion on electric field distortion varies with water tree type and location.In terms of stress, the Maxwell stress caused by the Inner dispersed water tree is greater than the Outer dispersed water tree with approximately the same size and the Butterfly-shaped water tree with approximately twice the size. The increase of length is conducive to the reduction of the maximum Maxwell stress caused by the dispersed water tree. |
11,629 | Please write an abstract with title: Analysis on the Innovation Mode of Public Management in Big Data Age, and key words: Computer science, Technological innovation, Big Data, Personnel. Abstract: Under the background of the rapid development of computer technology and data technology, public management has also entered the field of vision of many people. There are also some people who study how to innovate public management and connect public management with big data. These researchers will also study how to innovate public management with the help of big data technology. This paper also analyzes the purpose and characteristics of public management in mode innovation, and explains the difficulties encountered by public management in mode innovation. At the same time, this paper also points out the methods and ways of public management innovation in the era of big data, which also enriches the methods of public management innovation. |
11,630 | Please write an abstract with title: A Reinforcement Learning-Based Vehicle Platoon Control Strategy for Reducing Energy Consumption in Traffic Oscillations, and key words: Training data, Autonomous vehicles, Fuels, Heuristic algorithms, Vehicle dynamics, Reinforcement learning, Multi-agent systems. Abstract: The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowledge, few reinforcement learning (RL) algorithms have been applied in vehicle platoon control, which has large-scale action and state spaces. Some RL-based methods were applied to solve single-agent problems. If we need to tackle multiagent problems, we will use multiagent RL algorithms since the parameters space grows exponentially with the increasing number of agents involved. Previous multiagent RL algorithms generally may provide redundant information to agents, indicating a large amount of useless or unrelated information, which may cause to be difficult for convergence training and pattern extractions from shared information. Also, random actions usually contribute to crashes, especially at the beginning of training. In this study, a communication proximal policy optimization (CommPPO) algorithm was proposed to tackle the above issues. In specific, the CommPPO model adopts a parameter-sharing structure to allow the dynamic variation of agent numbers, which can well handle various platoon dynamics, including splitting and merging. The communication protocol of the CommPPO consists of two parts. In the state part, the widely used predecessor–leader follower typology in the platoon is adopted to transmit global and local state information to agents. In the reward part, a new reward communication channel is proposed to solve the spurious reward and “lazy agent” problems in some existing multiagent RLs. Moreover, a curriculum learning approach is adopted to reduce crashes and speed up training. To validate the proposed strategy for platoon control, two existing multiagent RLs and a traditional platoon control strategy were applied in the same scenarios for comparison. Results showed that the CommPPO algorithm gained more rewards and achieved the largest fuel consumption reduction (11.6%). |
11,631 | Please write an abstract with title: Open vocabulary Chinese name recognition with the help of character description and syllable spelling recognition, and key words: Character recognition, Vocabulary, Natural languages, Speech recognition, Writing, User interfaces, Research and development, Automatic speech recognition, Telephony, Robustness. Abstract: The open vocabulary name recognition technique is one of the very challenging tasks in the application of automated Chinese speech recognition technology. It can be applied to the free name input of any telephony speech application or automatic directory assistance system. A Chinese name usually has two to three characters, with each pronounced as a single syllable. It is a high perplexity task to recognize a word from a long list of candidates, like more than billions of names in our experiments. Two novel approaches under an interactive framework were proposed in our previous paper for five hundred thousand names and are now applied for open vocabulary Chinese name recognition - character description recognition (CDR) and syllable spelling recognition (SSR). Together with our robust finite-state recognizer and given a graph-structured syllable lexicon for the full names, we achieved a very promising name recognition success rate, 86.7%, in our system-initiative dialogue system. |
11,632 | Please write an abstract with title: Enhancing Web Authentication Security Using Random Forest, and key words: Runtime, Authentication, Forestry, Browsers, Security, Ensemble learning, Random forests. Abstract: A web browser extension that enhances web security by selectively applying cookie attributes to authentication cookies detected using random forest binary classifier. |
11,633 | Please write an abstract with title: Multi-Sensor Embedded System with Multiple Communications Based on EDU-CIAA, and key words: Hardware, Radio frequency, Embedded systems, Internet of Things, Bluetooth, GSM. Abstract: The argentinian CIAA project carries out the development and production of embedded systems, for educational, industrial and scientific purposes. The present work consists in designing a comprehensive embedded system based on the EDU-CIAA NXP version, for educational and applied research purposes. The hardware and software are developed in order to provide a shield of Internet of Things (IoT), providing multiple technologies such as: wifi, bluetooth, GSM, SD portability, and RF. A practical application is developed for sensing and monitoring multiple agricultural variables remotely. The development has two main parts. The first is based on an ATMEL microcontroller and it consists of the use of sensors nodes and communication modules. In the second part, a central node with processing capability is designed. For specifications, the national development platform EDU-CIAA NXP and the designed IoT expansion board are used in the second stage. The development has an HMI interface for Smartphones and PCs, using an Android App and web server. All software and hardware develped are shared in an open repository on GitHub. |
11,634 | Please write an abstract with title: Study on forward continuous operation characteristics of bidirectional double transistor flyback converter, and key words: Inductance, Buck converters, Voltage, Transformers, Topology, Batteries, Transistors. Abstract: Power battery is the core component of electric vehicle. Due to certain differences in the capacity and self-discharge rate of single battery, it is necessary to complete two-way energy flow between battery pack and single cell in the pack, so as to realize the charging and discharging of single cell and achieve the purpose of battery pack balance. Balanced topology converter is the basis of energy adjustment between battery cells. Aiming at the problem of leakage inductance overvoltage during the operation of balanced topology converter, this paper constructs the topology of bidirectional double transistor flyback converter, which can clamp the maximum voltage borne by the controllable power switch near the DC input voltage, reduce the switching loss of the switch, and the clamping diode provides a channel for the leakage inductance energy of the transformer to return to the input. The efficiency of the converter is improved and the overvoltage caused by the leakage inductance current is reduced. The simulation results show that during the forward operation of the converter, there is no peak current at the moment when the fully controlled devices S1 and S2 are turned on, which proves that the topology can well reduce the influence of leakage inductance. |
11,635 | Please write an abstract with title: Extracting Satellite Laser Altimetry Footprints With the Required Accuracy by Random Forest, and key words: Satellites, Altimetry, Three-dimensional displays, Lasers, Training, Laser noise, Clouds. Abstract: Due to its high elevation accuracy and wide coverage, satellite laser altimetry plays an important role in many scientific fields, such as polar ice sheet monitoring, vegetation canopy height measurement, and topography mapping. However, the elevation accuracy of satellite laser altimetry data is affected by many factors, such as the atmosphere, instrument noise, terrain fluctuation, etc., which leads to an uncertain accuracy. In this letter, to solve this problem, we propose a method based on random forest to extract satellite laser altimetry footprints that meet the elevation accuracy requirements of certain applications in complex terrain. Using ICESat, we take the elevation control point accuracy requirement for 1:10 000 mapping as an example to verify the proposed method. Experimental results show that the elevation root mean square errors (RMSEs) of the selected high-quality footprints are 0.41, 0.70, and 0.87 m in flat land, hills land, and mountainous areas, respectively, which meets the requirements of 1:10 000 topography mapping. The percentage of extracted footprints that meet the elevation accuracy requirement from the three terrains are all higher than 90%. |
11,636 | Please write an abstract with title: Augmenting images of non-rigid scenes using point and curve correspondences, and key words: Layout, Shape, Spline, Eyebrows, Cameras, Lips, Apertures, Stereo vision, Interpolation, Clothing. Abstract: Our goal is to augment images of non-rigid scenes coming from single-camera footage. We do not assume any a priori information about the scene being viewed, such as for example a parameterized 3D model or the motion of the camera. One possible solution is to use non-rigid factorization of points, from which a dense interpolating function modeled by a thin-plane spline can be computed. However, in many cases, point correspondences fail to capture precisely all the deformations occurring in the scene. Examples include the eyebrows or the lips when augmenting sequences of a face. Such deformations can be captured by tracking curves, but then point correspondences are not obtained directly due to the aperture problem. We propose an integrated method for non-rigid factorization and thin-plate spline interpolant estimation using point and curve correspondences over multiple views. The main novelties lie in the introduction of curves into the non-rigid factorization framework and in a direct global solution for the registration map, obtained by minimizing the registration error over all points and curves while taking all the images into account. The parameters of the registration map are set using cross-validation. The fidelity of the map is demonstrated by augmenting video footage undergoing various types of deformation. |
11,637 | Please write an abstract with title: Noise immune laser systems with the one-threshold scheme of quantizing and with an optimum procedure of detection and signal recovery against noise background, and key words: Laser noise, Signal processing, Semiconductor device noise, Noise shaping, Background noise, Shape, Signal to noise ratio, Electronics packaging, Interference, Filters. Abstract: On the example of application of square wave and action of thermal and shot noise, root-mean-square value of which is superior to the desired signal by some orders, the solution of the problem of selection of object by distance is submitted under the action of aerosolic interference at the restricted time of processing the adopted signal. |
11,638 | Please write an abstract with title: An Overview of Converter Topologies and Their Derivations and Interrelationships, and key words: Switches, Voltage, Topology, Inductors, DC-DC power converters, Inverters, Capacitors. Abstract: Canonical switching cell is known as the basic building block of dc-dc buck, boost, buck-boost, Ćuk converters, voltage/current source inverters (VSI/CSI) as well as multilevel converters (MLCs). This article reveals the existence of another basic switching cell as a singular structure of the canonical switching cell. The proposed new basic cell can constitute single-ended primary-inductor converter (SEPIC), Zeta converters, and Z-source converters. Each of the basic switching cells has the simplest form with two complementary switches, one inductor and one capacitor. An approach to construct a dc-dc converter by connecting source/load to the basic switching cells’ terminals is demonstrated. Some existing topologies of dc-dc converters are correlated following the proposed approach. Further, this article reviews Z-source/quasi-Z-source (qZS) converters, universal converters, and multiple-source converters to uncover some general approaches for topology manipulating. Z-source/qZS converters and the emerging classes of universal converters are used as examples to demonstrate the incorporation of their switches. Multiple source converters are fabricated by combining basic switching cells, in both the voltage source and current source form, using the duality principle. With the ever-increasing research efforts on converter topologies, it is hoped that this article will improve the understanding of the existing converter relationships and inspire insights for new topological developments and applications. |
11,639 | Please write an abstract with title: Multi-Modal COVID-19 Discovery With Collaborative Federated Learning, and key words: COVID-19, Data privacy, Hospitals, Computational modeling, Computed tomography, Collaboration, Collaborative work. Abstract: An effective and accurate method of detecting COVID-19 infection is to analyze medical diagnostic images (e.g. CT scans). However, patients’ information is privacy, and it is illegal to share diagnostic images among medical institutions. In this case, a critical issue faced by the model that detects the CT images is lacking enough training images dataset, then the features of COVID-19 cannot be accurately obtained. The data privacy attracts extensive attentions recently and is particularly important for the fast-developing medical institution database and. Considering this point, this paper presents a blockchain federated learning model, which overcomes the burden of centralized collection of large amounts of sensitive data. The model uses a trained model to recognize CT scans, and shares data between hospitals with privacy protection mechanism. This model is able to learn from shared resources or data between different hospital repositories to discover patients with new coronary pneumonia by detecting the computed tomography (CT) images. Finally, we conduct extensive experiments to verify the performance of the model. |
11,640 | Please write an abstract with title: Scene context dependent key frame selection in streaming, and key words: Layout, Video recording, Motion analysis, Surveillance, Image motion analysis, Multimedia systems, Cameras, Optical computing, Weather forecasting, Multimedia databases. Abstract: In this paper, we describe the development of our scene context dependent key frame selection method to reduce the amount of recorded video data. We propose the use of motion analysis (MA) to adapt to scene content in our key frame selection process. Based on the information generated by the motion analysis stage, frames in the video sequence which contain significant motion information are selected to retain for recording. We also show that our proposed method performs better than the traditional time-lapse recording method. |
11,641 | Please write an abstract with title: Online Hybrid CTC/Attention End-to-End Automatic Speech Recognition Architecture, and key words: Decoding, Computer architecture, Hidden Markov models, Speech recognition, Training, Heuristic algorithms, Speech processing. Abstract: Recently, there has been increasing progress in end-to-end automatic speech recognition (ASR) architecture, which transcribes speech to text without any pre-trained alignments. One popular end-to-end approach is the hybrid Connectionist Temporal Classification (CTC) and attention (CTC/attention) based ASR architecture, which utilizes the advantages of both CTC and attention. The hybrid CTC/attention ASR systems exhibit performance comparable to that of the conventional deep neural network (DNN)/ hidden Markov model (HMM) ASR systems. However, how to deploy hybrid CTC/attention systems for online speech recognition is still a non-trivial problem. This article describes our proposed online hybrid CTC/attention end-to-end ASR architecture, which replaces all the offline components of conventional CTC/attention ASR architecture with their corresponding streaming components. Firstly, we propose stable monotonic chunk-wise attention (sMoChA) to stream the conventional global attention, and further propose monotonic truncated attention (MTA) to simplify sMoChA and solve the training-and-decoding mismatch problem of sMoChA. Secondly, we propose truncated CTC (T-CTC) prefix score to stream CTC prefix score calculation. Thirdly, we design dynamic waiting joint decoding (DWJD) algorithm to dynamically collect the predictions of CTC and attention in an online manner. Finally, we use latency-controlled bidirectional long short-term memory (LC-BLSTM) to stream the widely-used offline bidirectional encoder network. Experiments with LibriSpeech English and HKUST Mandarin tasks demonstrate that, compared with the offline CTC/attention model, our proposed online CTC/attention model improves the real time factor in human-computer interaction services and maintains its performance with moderate degradation. To the best of our knowledge, this is the first work to provide the full-stack online solution for CTC/attention end-to-end ASR architecture. |
11,642 | Please write an abstract with title: The physical optics fields of an aperture on a perfectly conducting screen in terms of line integrals, and key words: Physical optics, Apertures, Optical surface waves, Integral equations, Optical diffraction, Electromagnetic diffraction, Geometrical optics, Electromagnetic fields, Surface waves, Electromagnetic scattering. Abstract: The physical optics fields due to an aperture on a perfectly conducting screen are expressed in terms of line integrals over the boundary of the aperture. These line-integral representations have the same properties as the ones in terms of surface integrals over the aperture; in particular, they admit arbitrary, source distributions, and are continuous everywhere in the source-free half-space, including the geometric optics shadow boundary. |
11,643 | Please write an abstract with title: Comparison of Naïve Bayes, C4.5 and K-Nearest Neighbor for Covid-19 Data Classification, and key words: COVID-19, Technological innovation, Antigens, Urban areas, Prediction algorithms, Classification algorithms, Information technology. Abstract: Covid-19 is a new virus that appeared in the city of Wuhan in 2019. This virus spreads very quickly even to Indonesia. One effort that can be done to detect the presence of this virus is the PCR and antigen test. Increasing this case resulted in a medical team having difficulty detecting suspects exposed to viruses. This research was conducted to find the best classification algorithm in predicting and classifying status on the suspected Covid-19 both exposed or not exposed. The method used in this study is Naïve Bayes, C4.5 and K-Nearest Neighbor which have very high accuracy using secondary data from the Dumai City Health Agency. From this study it was found that the algorithm C4.5 as the best algorithm in predicting the status of COVID-19 patients, especially in the city of Dumai with an accuracy of 86.54%, recall 71.51%and precision 85.14%. This study has implications for further researchers in choosing an algorithm to predict the COVID-19 case. |
11,644 | Please write an abstract with title: Randomized Algorithms for Platform-based Design, and key words: Algorithm design and analysis, Control systems, Design methodology, Automotive engineering, Automatic control, Costs, Manufacturing, Libraries, Prototypes, Technological innovation. Abstract: The design of automotive control systems is becoming increasingly complex as the level of performance required by car manufactures grows continuously and the constraints on cost and development time imposed by the market become tighter. A successful design, without costly and time consuming re-desing cycles, can be achieved only be using an efficient design methodology that allows for component re-use and evaluation of platform requirements at the early stages of the design flow. In this paper, we illustrate a control-implementation design methodology for the development of embedded controllers by composition of algorithms picked up from libraries. Randomized algorithms and hybrid system theory are used to develop techniques for functional and architecture evaluations, which are implemented in a prototype tool. |
11,645 | Please write an abstract with title: A morphing with geometric continuity between two arbitrary planar polygons, and key words: Equations, Interpolation, Computer graphics, Turning, Image segmentation, Animation, Roads, Fractal art, Shape, Length measurement. Abstract: This paper introduces the geometric continuity equations of the closed planar polygons and gives the definition of a morphing with geometric continuity between two arbitrary planar polygons, including simple, non-3 and even degenerated polygons. A simple morphing technique based on linear interpolation of the geometric continuity equations is proposed. The closureness of the in-between polygons is precisely achieved. Two global invariants: rotation indexes and winding numbers are introduced to describe the most general polygons. The demo shows that this technique is efficient and natural for morphing between polygons with arbitrary rotation indexes and winding numbers. |
11,646 | Please write an abstract with title: An AI Model for Neurodegenerative Diseases, and key words: Neuromorphics, Computational modeling, Medical services, Brain modeling, Artificial intelligence, Biological neural networks, Diseases. Abstract: Models of neural networks are receiving widespread attention as potential new architectures for computing systems. The models considered here consist of highly interconnected networks of simple computing elements. A computation is performed collectively by the whole network with the activity distributed over all the computing elements. This collective operation results in a high degree of parallel computation and gives the network the potential to solve complex problems quickly. Furthermore, this computational model is meant to be burnt onto a neuromorphic chip and with the use of the surgical procedure, it can then be given to the healthcare department and can thus be used to cure the patients suffering from neurodegenerative diseases. The application software involved maps the patients with the concerned healthcare department for making this model feasible and practical to use. |
11,647 | Please write an abstract with title: Retrieval of Forest Water Potential from L-Band Vegetation Optical Depth, and key words: Permittivity measurement, Vegetation mapping, Forestry, Vegetation, Transforms, Soil, Radiometry. Abstract: A retrieval methodology for forest water potential from ground-based L-band radiometry is proposed. It contains the estimation of the gravimetric and the relative water content of a forest stand and tests in situ- and model-based functions to transform these estimates into forest water potential. The retrieval is based on vegetation optical depth data from a tower-based experiment of the SMAPVEX 19–21 campaign for the period from April to October 2019 at Harvard Forest, MA, USA. In addition, comparison and validation with in situ measurements on leaf and xylem water potential as well as on leaf wetness and complex permittivity are foreseen to understand limitations and potentials of the proposed approach. As a first result the radiometer-based water potential estimates of the forest stand are concurrent in time and similar in value with their in situ (xylem) counterparts from single trees in the radiometer footprint. |
11,648 | Please write an abstract with title: A low-power 2.4-GHz transmitter/receiver CMOS IC, and key words: Transmitters, CMOS integrated circuits, CMOS image sensors, Filtering, CMOS technology, Stacking, Baseband, Power dissipation, Local oscillators, Transceivers. Abstract: A 2.4-GHz CMOS receiver/transmitter incorporates circuit stacking and noninvasive baseband filtering to achieve a high sensitivity with low power dissipation. Using a single 1.6-GHz local oscillator, the transceiver employs two upconversion and downconversion stages while providing on-chip image rejection filtering. Realized in a 0.25-μm digital CMOS technology, the receiver exhibits a noise figure of 6 dB and consumes 17.5 mW from a 2.5-V supply, and the transmitter delivers an output power of 0 dBm with a power consumption of 16 mW. |
11,649 | Please write an abstract with title: IoT based Smart Helmet System for Accident Prevention, and key words: Vibrations, Head, Road accidents, Tactile sensors, Alcoholic beverages, Safety, Sensors. Abstract: The smart helmet's purpose is to provide features for detecting and reporting whether a person has drunk alcohol while wearing a helmet. Because riders don't wear helmets and drink alcohol, road accidents are on the rise. Thousands of people die every year in vehicle accidents in today's world. Accidents can often be reduced by using a smart helmet. The project's main goal is to build a practical helmet that can prevent accidents without the use of a helmet and detect alcohol. The touch sensor identifies whether the user is wearing a helmet. The Gas sensor detects the presence of alcohol in the rider's breath. The bike will not start if the rider is not wearing a helmet or has consumed alcohol. The bike can only be started if there are no signs of intoxication and a helmet is worn. Sensor operations are used to construct the system. |
11,650 | Please write an abstract with title: A current access, self-structured, multilayered bubble domain memory, and key words: Magnetic separation, Magnetostatics, Magnetic domains, Bars, Lattices, NASA, Magnetic multilayers, Coupling circuits, Lithography, Proportional control. Abstract: Preliminary experimental results are reported on a self-structured, multilayer bubble memory with buried data layer. Stripe domains are used to move carrier bubbles by magnetostatic coupling. An expression is derived for that coupling as a function of thickness of the GGG separation layer. Experimental values of coupling are given as a function of bias field. An expression for stripe curvature as a function of bias field is derived. The performance of seven different current access stripe propagation circuits is reported. |
11,651 | Please write an abstract with title: Calibration and Compensation of The Misalignment Angle Errors For The Disk Resonator Gyroscopes, and key words: Gyroscopes, Force, Electrodes, Angular velocity, Sensors, Mathematical model, Calibration. Abstract: This paper reports a new method of calibration and compensation for the misalignment angle between the pickoff axis and the forcing directions of the disk resonator gyroscopes. With this error eliminated, the driving control loop will be free of the disturbance from the couple of the angular velocity. Meanwhile, the scale factor nonlinearity could be obviously improved from approximate 140ppm to less than 14 ppm. This method could be applied to other gyroscopes with the same structure like disk resonator gyroscopes. |
11,652 | Please write an abstract with title: Practical experience of benchmarking to estimate distribution companies' revenues, and key words: Costs, Regulators, Investments, Business, Power generation economics, Clustering methods, Power industry, Helium, Monopoly, Electricity supply industry deregulation. Abstract: This paper presents a complete overview of a practical process to estimate regulated distribution-companies (DISCOS) revenues. An international benchmarking method is used to compare the performance of three DISCOS to the performance of a set of utilities that have been selected as a reference. Advantages and disadvantages of the applied method are shown. |
11,653 | Please write an abstract with title: Correlated microwave-ultrasonic multi-sensor for reliable measurements of velocity and range, and key words: Microwave measurements, Velocity measurement, Intelligent sensors, Ultrasonic variables measurement, Ultrasonic imaging, Microwave sensors, Sensor fusion, Noise robustness, Calibration, Monitoring. Abstract: The potential of the combination of ultrasound and microwaves to improve existing sensors in terms of sensitivity and reliability is demonstrated. While noise and disturbances affect both waves differently, signal returns form target reflectors will be coherent. With data fusion performed on the signal level, the applicability is significantly improved compared with multisensors based on complementary sensor outputs. A compact low-cost sensor for the robust measurement of presence, velocity and distance of objects, using 24 GHz microwaves and 40 kHz ultrasound, has been designed. Key issues for a smart sensor design, inherently exploited by the multisensor approach, are the adaptation to the environment, self calibration and function monitoring. The design and operating parameters of the multisensor system are discussed and evidence for the satisfactory performance is given. |
11,654 | Please write an abstract with title: Self-Organised Direction Aware Data Partitioning for Type-2 Fuzzy Time Series Prediction, and key words: Measurement, Uncertainty, Shape, Time series analysis, Predictive models, Tools, Prediction algorithms. Abstract: Time series forecasting is an essential research field that provides significant data to help professionals in several areas. Thus, growing research and development in this area have been conducted, aiming at developing new forecasting methods with higher performance levels, but always also with low processing costs. One of this methods is Fuzzy Time Series - FTS. However, one great problem of FTS prediction is how to properly deal with the uncertainty associated to the time series and to model's design. Thus, in this paper we propose a univariate interval type-2 fuzzy time series model combined with the concept of Self-organised Direction Aware Data Partitioning Algorithm (SODA) for universe of discourse partitioning. All experiments were performed using the TAIEX data set and the results were then compared to other forecasting models from literature. A sliding window methodology was applied and the forecast error metric chosen was the Root Mean Squared Error (RMSE) for all methods. SODA-T2FTS results show that it outperformed other forecasting methods confirming that interval type-2 fuzzy logic can be a reliable tool for time series prediction. |
11,655 | Please write an abstract with title: Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003), and key words: Fluorescence, Reflectivity, Spectroscopy, Breast cancer, Principal component analysis, Support vector machines, Support vector machine classification, Surges, Testing, Sensitivity and specificity. Abstract: Nonmalignant (n = 36) and malignant (n = 20) tissue samples were obtained from breast cancer and breast reduction surgeries. These tissues were characterized using multiple excitation wavelength fluorescence spectroscopy and diffuse reflectance spectroscopy in the ultraviolet-visible wavelength range, immediately after excision. Spectra were then analyzed using principal component analysis (PCA) as a data reduction technique. PCA was performed on each fluorescence spectrum, as well as on the diffuse reflectance spectrum individually, to establish a set of principal components for each spectrum. A Wilcoxon rank-sum test was used to determine which principal components show statistically significant differences between malignant and nonmalignant tissues. Finally, a support vector machine (SVM) algorithm was utilized to classify the samples based on the diagnostically useful principal components. Cross-validation of this nonparametric algorithm was carried out to determine its classification accuracy in an unbiased manner. Multiexcitation fluorescence spectroscopy was successful in discriminating malignant and nonmalignant tissues, with a sensitivity and specificity of 70% and 92%, respectively. The sensitivity (30%) and specificity (78%) of diffuse reflectance spectroscopy alone was significantly lower. Combining fluorescence and diffuse reflectance spectra did not improve the classification accuracy of an algorithm based on fluorescence spectra alone. The fluorescence excitation-emission wavelengths identified as being diagnostic from the PCA-SVM algorithm suggest that the important fluorophores for breast cancer diagnosis are most likely tryptophan, NAD(P)H and flavoproteins. |
11,656 | Please write an abstract with title: Multiagent System-Based Integrated Design of Security Control and Economic Dispatch for Interconnected Microgrid Systems, and key words: Microgrids, Switches, Security, Optimization, Telecommunications, Computational modeling. Abstract: Hybrid and intermittent characteristics of the distributed energy resources (DERs) bring great challenges to the security control and economic dispatch (ED) of the microgrids. To bypass these hurdles, this article proposes a multiagent system-based integrated design of security control and ED to guarantee the effective and economical operation of the interconnected microgrids. First, a hierarchical control scheme is constructed by two-level unit agents, in which the switching control and dynamic regulation are fully implemented with the corresponding hybrid behaviors based on the differential hybrid Petri-net (DHPN) model. Based on the DHPN model, a novel dynamic ED integrated with security control is proposed to overcome the issues that cannot be solved in conventional models. Furthermore, to reduce the computational complexity and unified the mathematical model of the DERs, the inverter-based power control strategy is converted to a predictive control model which can be decomposed into several subsystems. In the optimization process, all the subsystems are implemented in a fully distributed, communication free, and rolling optimization manner based on the distributed model predictive control (DMPC). The validity of the proposed design is demonstrated according to the simulation results in case studies. |
11,657 | Please write an abstract with title: Light Gradient Boosting Machine for General Sentiment Classification on Short Texts: A Comparative Evaluation, and key words: Sentiment analysis, Twitter, Training, Boosting, Support vector machines, Adaptation models. Abstract: Recently, the focus on sentiment analysis has been domain dependent even though the expressions used by the public are unsophisticatedly familiar regardless of the topics or domains. Online social media (OSNs) has been a daily venue for informal conversational contents from various domains ranging from sports and cooking to politics and human rights. Generating specific resources for every domain independently requires high cost and extensive efforts. In response, we propose to build a general multi-class sentiment classifier using our Domain-Free Sentiment Multimedia Dataset (DFSMD). Based on the proven capabilities of Light Gradient Boosting Machine (LGBM) in dealing with high dimensional and imbalance data, we have trained an LGBM model to recognize one of three sentiments of tweets: positive, negative, or neutral. We have conducted extensive comparisons and evaluations for six other standard sentiment classification algorithms and different sets of features including OSNs-specific ones. Our results have shown that LGBM model is the winner among the other six algorithms. It has been also shown that our dataset contains distinguishing characteristics in the three classes. Moreover, hashtag words are shown to be significantly important in capturing the sentiments of tweets. In addition, our findings have revealed the effectiveness of our approach in adapting general-domain sentiment to domain-specific sentiment analysis. |
11,658 | Please write an abstract with title: The influence of alumina particle size on the fluid dynamics of a laser-induced plasma, and key words: Nanoparticles, Shock waves, Laser theory, Drag, Ionization, Oxidation, Plasmas. Abstract: The interaction of a laser-induced shock wave with nanoparticles and microparticles of aluminum oxide is investigated through experiments and modeling. The chemistry and physics of the interaction between the particles and plasma generated from laser ablation shows similarities and discrete differences for the two particle sizes. For both particle sizes, early stage (less than 10 microseconds) ionization was dominant and evidenced by higher concentrations of Al II. While both sizes exhibit ionization over the same duration, the intensity of emission was greater for nanoparticles indicating greater concentrations of ionized species. Moreover, the dispersion of species was notably more elongated for microparticles while radial dispersion was more pronounced for nanoparticles with elevated drag forces. At later stages (i.e., greater than 10 microseconds), oxidation reactions were dominant for both particle sizes, but the same distinctions in flow field were observed and attributed to particle drag. In all stages of interaction, microparticles expand axially with less drag that suppresses their radial expansion. As a result, the dispersion of reactive species was mapped over an up to 80 perccent larger area for nanoparticles relative to microparticles. Results shown here can be applied toward advancing experimental diagnostics and particle-shock wave modeling and simulation efforts for energetic materials. |
11,659 | Please write an abstract with title: Design Of Anti-steam Scald Alarm System For Electric Rice Cooker, and key words: Employee welfare, Infrared heating, Senior citizens, Clothing, Alarm systems, Infrared sensors, Standards. Abstract: With the rapid development of our country, people's living standard is improving day by day. While pursuing food and clothing, we also have higher requirements for quality. Food is the most important thing for us, and rice is our main food. Compared with the past, people should pursue eating well on the basis of satiety. In the process of cooking, the steam generated by the electric cooker can easily scald the elderly and children without paying attention. Human heat energy Infrared sensor In this case, The cooker is in working condition, by using BISS0001 heat processor in the single chip computer C52. When the human is too close to the steam emitted by the electric cooker cooking, the alarm will be sent out and the warning light will be on. |
11,660 | Please write an abstract with title: Multipath cancellation using a maximum likelihood approach, and key words: Sea measurements, System testing, Signal processing, Array signal processing, Apertures, Adaptive signal processing, Interference, Signal generators, Acoustic testing, Acoustic arrays. Abstract: Summary form only given. Results of Coastal Systems Station at-sea and test pool experiments with multipath signals using synthetic aperture arrays are presented. It was found that multipath signals are often as strong and sometimes stronger than direct path signals, although the phase of the multipath signals is characteristically quasi-random over the length of the aperture. This randomness leads to some suppression of the multipath signals in conventional synthetic aperture processing. For better multipath cancellation, adaptive methods need to be used. A maximum likelihood method approach for array signal processing that effectively cancels multipath signals is presented. This approach is based on exploiting the orthogonal nature of the signals in the maximum likelihood parameter space. In this space the axes correspond to the primary desired look direction and the various multipath directions. This construction leads to a decoupling of the desired signal from the multipath interference by using maximum likelihood generated array weights. This method is applied to the acoustic data collected in the Coastal Systems Station test pool with a 4-channel vertical array. Results are compared to conventional beamforming methods. |
11,661 | Please write an abstract with title: Snap Pump: A Snap-Through Mechanism for a Pulsatile Pump, and key words: Strips, Robots, Actuators, Force, Biology, Prototypes, Propulsion. Abstract: Pulsatile flow is widespread in nature, but replicating such impulsive periodic pumping routines with traditional rotary actuators is complex and energetically inefficient. We demonstrate the feasibility of an actuator capable of generating impulsive flow displacement by exploiting the bistable equilibrium of a simple mechanism. These kind of mechanisms, commonly known as snap-through mechanisms, offer the benefit of sudden release of elastic energy at the interface between two stable structural configurations. This property has been employed in certain actuators to drive abrupt motions of mechanical systems. Here, we use this principle to drive an inflation/deflation routine of a fluid-filled cavity, thus generating a peaked, pulsatile flow, comparable to that encountered in biological systems. Assessment of the various stages of actuation of this system shows that a sharp drop in the energy occurs from elastic to hydraulic work, highlighting the need for improved design elements involved in this stage of the actuation. |
11,662 | Please write an abstract with title: Parallel differential evolution, and key words: Concurrent computing, Genetic mutations, Costs, Parallel processing, Computer interfaces, Computer networks, Mathematics, Systems engineering and theory, Computational intelligence, Topology. Abstract: Parallel processing has emerged as a key enabling technology in modern computing. Recent software advances have allowed collections of heterogeneous computers to be used as a concurrent computational resource. In this work we explore how differential evolution can be parallelized, using a ring-network topology, so as to improve both the speed and the performance of the method. Experimental results indicate that the extent of information exchange among subpopulations assigned to different processor nodes, bears a significant impact on the performance of the algorithm. Furthermore, not all the mutation strategies of the differential evolution algorithm are equally sensitive to the value of this parameter. |
11,663 | Please write an abstract with title: A quantum algorithm for single parity check code, and key words: Quantum algorithm, Communication channels, Digital communication, Parity check codes, Encoding, Error correction codes, Error correction. Abstract: In coding theory, error-detecting and error-correcting codes are used to enable digital communication over a noisy communication channel. One of the most uncomplicated error-detecting codes is the single parity check code. The single parity check code detects the number of ones (1s) in a string of bits. If the number of ones is even, then the bit string is said to have even parity. On the other hand, if the number of ones is odd, then the string is said to have odd parity. The challenge with this approach is that it cannot be detected if there are an even number of errors. Also, it can not tell which bit is in error (the error may even be the parity bit itself); thus, it cannot fix the error. This means the single parity check has a one-bit error detection capability but no error correction capability. Therefore, in this work, we propose a novel quantum algorithm that can be used to implement a single parity check code. Quantum algorithms run on a quantum computer and achieve a speedup, or other efficiency improvements, over any possible classical algorithm. The critical advantage of this algorithm is that it maintains a constant circuit depth regardless of the length of the bit string. Thus, the circuit depth of our proposed algorithm does not increase with bit string length. This demonstrates the power and efficiency of quantum computing in performing a single parity check. |
11,664 | Please write an abstract with title: Electromagnetic Modeling Using an FDTD-Equivalent Recurrent Convolution Neural Network: Accurate computing on a deep learning framework, and key words: Finite difference methods, Time-domain analysis, Deep learning, Computational modeling, Mathematical models, Convolutional neural networks, Recurrent neural networks. Abstract: In this study, a recurrent convolutional neural network (RCNN) is designed for full-wave electromagnetic (EM) modeling. This network is equivalent to the finite difference time domain (FDTD) method. The convolutional kernel can describe the finite difference operator, and the recurrent neural network (RNN) provides a framework for the time-marching scheme in FDTD. The network weights are derived from the FDTD formulation, and the training process is not needed. Therefore, this FDTD-RCNN can rigorously solve a given EM modeling problem as an FDTD solver does. |
11,665 | Please write an abstract with title: Preliminary analysis of Risso's dolphin social structure in the Gulf of Taranto (Northern Ionian Sea, Central Eastern Mediterranean Sea), and key words: Pediatrics, Sociology, Standards organizations, Sea measurements, Organizations, Metrology, Indexes. Abstract: The investigation into the social organization and population biology of cetaceans, as top predator and important sentinels of the health of the marine ecosystems, provides opportunities to study responses to anthropogenic disturbance and provides useful information for the development of conservation and management plans. Thus, in the present work the association pattern of 76 photo-identified individuals of Risso's dolphin sighted at least 5 times in the Gulf of Taranto, from July 2013 to September 2021, was analyzed to describe their population social structure, providing new important evidence for the conservation of the species. Indeed, even though most of our results seems to describe a fission fusion social structure, characteristic of a not isolated or socially segregated community, a certain degree of preferred association within individuals, sex and age classes supports the hypothesis of a more complex and structured society. Further studies are needed to investigate this scenario. |
11,666 | Please write an abstract with title: Low Carbon Economic Dispatch of Integrated Energy System with Liquid Storage Carbon Capture Power Storage Considering Integrated Demand Response, and key words: integrated energy system, carbon capture storage, demand response, peak-shaving, low carbon economic dispatch. Abstract: Based on the background of "carbon peaking" and "carbon neutrality", this paper proposes a low carbon economic operation strategy for integrated energy system with liquid storage considering demand response in order to improve energy utilization, optimize equipment operation flexibility, and further reduce carbon emission level and operation cost of integrated energy system. In this paper, we propose a low-carbon economic operation strategy for integrated energy systems with liquid storage that takes into account demand response. First, we introduce a carbon capture device with liquid storage in an integrated energy system to flexibly dispose of the CO2 generated from the operation of a thermal power unit. Second, we introduce a demand response policy to guide power users to modify their inherent power consumption patterns and adjust their power demand through an incentive mechanism, thereby modifying the power load curve and reducing the peak-to-valley difference. Finally, a low-carbon economic operational model of an integrated energy system with optimal total system operation cost is constructed, the CPLEX commercial solver is used to solve the constructed model, and the effectiveness of the proposed strategy is compared and validated by setting several operational scenarios. |
11,667 | Please write an abstract with title: Pub/Sub in the Air: A Novel Data-centric Radio Supporting Robust Multicast in Edge Environments, and key words: Wireless communication, Prototypes, Receivers, Complexity theory, Peer-to-peer computing, Wireless fidelity, Edge computing. Abstract: Peer communication among edge devices (e.g., mobiles, vehicles, IoT and drones) is frequently data-centric: most important is obtaining data of desired content from suitable nodes; who generated or transmitted the data matters much less. Typical cases are robust one-to-many data sharing: e.g., a vehicle sending weather, road, position and speed data streams to nearby cars continuously. Unfortunately, existing address-based wireless communication is ill-suited for such purposes. We propose V-MAC, a novel data-centric radio that provides a pub/sub abstraction to replace the point-to-point abstraction in existing radios. It filters frames by data names instead of MAC addresses, thus eliminating complexities and latencies in neighbor discovery and group maintenance in existing radios. V-MAC supports robust, scalable and high rate multicast with consistently low losses across receivers of varying reception qualities. Experiments using a Raspberry Pi and a commodity WiFi dongle based prototype show that V-MAC reduces loss rate from WiFi broadcast's 50-90% to 1-3% for up to 15 stationary receivers, 4-5 moving people, and miniature and real vehicles. It cuts down filtering latency from 20μs in WiFi to 10μ s for up to 2 million data names, and improves cross stack latency 60-100× for TX/RX paths. We have ported V-MAC to 4 major WiFi chipsets (including 802.11 a/b/g/n/ac radios), 6 different platforms (Android, embedded and FPGA systems), 7 Linux kernel versions, and validated up to 900Mbps multicast data rate and interoperation with regular WiFi. We will release V-MAC as a mature, reusable asset for edge computing research. |
11,668 | Please write an abstract with title: Workbook approach to algorithm design and service accounting in a component orientated environment, and key words: Algorithm design and analysis, Search engines, Solids, Software systems, Robustness, Relational databases, Telephony, Web and internet services, Protocols, Refining. Abstract: As the shift towards the next generation of Internet services runs its course, the emphasis within accounting for such services has moved towards robust and flexible components. Rating is the process of applying an algorithm to a set of usage data to produce a charge for a particular service. An accounting architecture with the ability to scale, based on the foundation of a solid core of rating components, incorporating transaction management, object pooling and queuing is presented. Using the workbook approach to algorithm modelling is a logical option that allows for the decoupling of the algorithm from the architecture of the rating component. Decoupling the algorithm, allows for the design of core functionality that will rate for any service based on the concept of "pluggable" algorithms for each respective service. |
11,669 | Please write an abstract with title: A Comparative Study of Different Machine Learning Algorithms on Bitcoin Value Prediction, and key words: Machine learning algorithms, Recurrent neural networks, Supervised learning, Bitcoin, Tools, Prediction algorithms, Task analysis. Abstract: Machine learning is growing rapidly and has made many theoretical breakthroughs which find its application in many fields. Bitcoin is a very secure, decentralized, peer to peer currency with no third-party involvement. The price prediction of Bitcoin in the following years is a difficult task. The objective is to take a dig in the prediction of the future prices, dealing with real world data. A comparative study of the results produced by different machine learning models, along with graphs for epoch vs price, error and accuracy for each model using both linear and non-linear functions is done. We are using both neural network algorithms, such as artificial neural network (ANN), recurrent neural network (RNN) and convolutional neural network (CNN), as well as some famous supervised learning algorithms such as Random Forest (RF) and k-nearest neighbors (k-NN), to form the analysis. The time price prediction graphs and the epoch loss accuracy graphs are used for the analysis of each algorithm working on the same data and produces different results. Finally, the best suited algorithm are used for the prediction of future Bitcoin price. |
11,670 | Please write an abstract with title: Opponent Modeling Based Dynamic Resource Trading for UAV-Assisted Edge Computing, and key words: UAV-assisted mobile edge computing, dynamic resource trading, stochastic Stackelberg game, reinforcement learning, opponent modeling. Abstract: This paper proposes a dynamic resource trading scheme in unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) network. A UAV-assisted MEC server adaptively adjusts its trajectory to sell the computation offloading services to the mobile users (MUs), where the MUs have stochastic task arrivals. In this context, we formulate the sequential resource trading problem as a stochastic Stackelberg game, which is composed of two stages for each trading round. In the first stage, the self-interested UAV jointly optimizes its trajectory and service price to maximize its long-term profits. In the second stage, the non-cooperative MUs optimize their binary offloading decisions to minimize the average task processing delay and service payment. However, it is challenging to obtain the equilibrium across the fully decentralized agents with constantly evolving and tightly coupled policies, where each agent is confronted with a non-stationary environment. To solve this problem, we propose an opponent modeling based double deep Q learning (OM-DDQN) algorithm, where each agent adopts opponent modeling to effectively predict the trading strategies of other agents in the network. Simulation results demonstrate that, compared with the baseline algorithms, the proposed algorithm can achieve a win-win resource trading outcome that not only enhances the UAV's profit but also reduces the MUs' costs. |
11,671 | Please write an abstract with title: Review of thermal characteristics simulation analysis of electronic components, and key words: Couplings, Analytical models, Temperature distribution, Electronic equipment, Thermal resistance, Electronic components, Electronic packaging thermal management. Abstract: With the rapid development of electronic technology, the integration of electronic equipment has an obvious upward trend compared with the past, and the requirement of miniaturization of electronic equipment is also rising. High power devices are widely used. At the same time, the application environment of electronic equipment is becoming more and more diverse. Under the background of these development trends, the problem of overheating of electronic components is becoming more and more prominent. According to statistical data, in all failed electronic components, the number of failed individuals due to temperature exceeding the limit value exceeds 55%. When the temperature of electronic components increases by 10 ℃ , the reliability decreases by 50%. Overheating seriously limits the performance, reliability and service life of electronic components.To solve the problem of overheating of electronic equipment, it is necessary to study the thermal performance of electronic components, in which thermal analysis and thermal experiment are the main research methods. Thermal analysis is mainly based on the numerical simulation method to simulate the thermal characteristics of electronic components. There are errors between the results of thermal analysis and the actual situation. Both modeling methods and numerical analysis methods have an impact on the error. Thermal analysis is mainly used in the conceptual design stage to provide support for designers to grasp the design direction.This paper sorts out the thermal analysis modeling methods of electronic components, compares the characteristics of different modeling methods, combs the current technical achievements of thermal analysis of electronic components and analyzes the development trend of thermal performance research of components.Thermal analysis simulation modeling still needs to be promoted in dealing with the problem of complex geometry. In order to simulate the thermal characteristics of electronic components more quickly and accurately, it is necessary to simplify the complex geometry with acceptable errors. It is an important direction of thermal analysis simulation to establish the simplification criteria of electronic components and their auxiliary structures and balance the simulation accuracy and calculation scale of the model.The simulation analysis of thermal characteristics of electronic components under extreme environmental conditions is of great value to its application. On the one hand, the application temperature range of electronic components is becoming wider and wider, and the thermal characteristics and mechanisms of electronic components are different in extremely low temperature and extremely high temperature environment. The simulation of extreme temperature environment of electronic components are important research directions in the future.Multiple physical fields coupled thermal analysis is a new research hotspot in recent years. In the application of electronic components, there are many kinds of physical fields coupling effects, such as temperature-structure, temperature-current and so on. The research on the simulation of thermal characteristics of electronic components under coupled multiple physical fields has attracted more and more attention of relevant researchers.The analysis shows that the research on the thermal performance of electronic components is of great significance to improve the performance and reliability of electronic components and heat dissipation design. |
11,672 | Please write an abstract with title: Investigating the Use of Deep Neural Networks for Software Defect Prediction, and key words: Software, Predictive models, Measurement, Neurons, Object oriented modeling, Neural networks, Machine learning. Abstract: Many software projects are shipped to customers containing defects. Defective software cost money, time, and lives. To reduce this harm, software companies allocate testing and quality assurance budgets. The enormous sizes of modern software pose challenges to traditional testing approaches due to the need for scalability. Defect prediction models have been used to direct testing efforts to probable causes of defects in the software. Early approaches for software defect prediction relied on statistical approaches to classify software modules and decide whether each module is a defect-prone module or not. Lately, many researchers used machine learning techniques to train a model that can classify software modules to defect-prone modules and not defect-prone modules. Starting from the new millennium, neural networks and deep learning won many competitions in machine learning applications. However, the use of deep learning to build a software defect prediction model was not investigated thoroughly. In this paper, we used a deep neural network to build a software defect prediction model and compared our proposed model with other machine learning algorithms like random forests, decision trees, and naive Bayesian networks. The result shows small improvement over the other learning models in most of the comparisons. These results prove the value of using deep learning for defect prediction and open the door for more experiments. |
11,673 | Please write an abstract with title: Theory of Resonant Modes and its Application, and key words: Antenna theory, Integral equations, Mathematical model, Electric fields, Current distribution, Transmission line measurements, Method of moments. Abstract: This paper proposes a unified procedure for evaluating the resonant frequencies and the corresponding resonant modes for an arbitrary source region, based on the general expression for the difference between the stored magnetic and electric field energies in terms of the source current distribution. It is shown that the resonant frequencies and the corresponding resonant modes are governed by a homogeneous integral equation. By following a standard procedure of the method of moments (MoM), the integral equation can be discretized into a real homogenous algebraic equation, from which the resonant frequencies and the corresponding resonant modes can be determined by requiring that a non-trivial solution exists for the real homogeneous algebraic equation. Different from other modal theories that expand the fields by a linear combination of fundamental field patterns that are derived from the boundary conditions, the proposed theory of resonant modes is derived from the difference of stored field energies for an arbitrary source region. As an application of the theory of the resonant modes, a crossed-dipole antenna, a dual-band bowtie antenna, and a dual-band circular polarization antenna are designed through the appropriate excitations of the resonant modes on the three selected source regions, and they are validated by independent simulations and experiments. |
11,674 | Please write an abstract with title: A Multi-perspective Study on Quantitative Evaluation Index System of Smart Port, and key words: Correlation, Systematics, Energy measurement, Transportation, Production, Analytic hierarchy process, Real-time systems. Abstract: Smart port construction is the key direction of next generation's port upgrading and transformation. The initial trials on the application of multi-mode perception and real-time analysis, big data and intelligent scheduling, and other emerging technologies have been conducted in some advanced ports from various perspectives of port production and operation. However, effects of those new techniques on the smart port construction are difficult to measure, and there is still a lack of consensus on the systematic evaluation methods and indicators. To deal with this and promote the scientific and systematical measurement of the port intelligence construction level, this paper made an initial trial to propose a quantitative port evaluation index system with five measurement dimensions, including management benefit, production scale, port operation, intelligent decision-making, and energy and environment. Then, indicators of the evaluation system have been analyzed from three stake-holders' perspectives, e.g., investors, ship operators and port managers. The analytic hierarchy process and fuzzy comprehensive evaluation method are utilized to evaluate the effect of port intelligence construction. Through a comparative analysis of two domestic ports in China, as a case study, the validity of the evaluation system has been testified. Results in this study show that the evaluation system proposed can reasonably reflect the construction effect of the intelligent port and provide potential theoretical supports and hints for future smart port construction. |
11,675 | Please write an abstract with title: Unified Virtual Oscillator Control for Synchronization Under Ultra-Weak Grid Conditions, and key words: Reactive power control, Systematics, Power control, Switches, Power system stability, Control systems, Stability analysis. Abstract: A unified virtual oscillator controller (uVOC) with fast power control response is proposed for enhanced synchro-nization under ultra-weak grid conditions. The recently proposed uVOC offers a unified analysis, design, and implementation framework for both grid-following and grid-forming converters; leveraging its superior synchronization capability, enhanced fault ride-through response is achieved without the need for a back-up controller during faults. In this work, we propose an improved uVOC design and implementation which enables fast power-flow control. Through analysis, we demonstrate that the proposed controller retains synchronization as long as a feasible equilibrium exists. Furthermore, using dynamic reactive power control the feasible power-flow range is extended under ultra-weak grid conditions. Systematic design guidelines for controller parameters are presented. The analysis and design are validated through hardware experiments. |
11,676 | Please write an abstract with title: Autonomous Voltage Regulation by Distributed PV Inverters with Minimal Inter-Node Interference, and key words: Reactive power, Voltage control, Inverters, Voltage measurement, Interference, Substations, Reactive power control. Abstract: Reactive power capability of distributed photovoltaic (PV) inverters is exploited to mitigate voltage violations under high PV penetration in the distribution grid. Coordinating the reactive power compensations of individual PV inverters to obtain desired voltage regulation performance is a major challenge. In this paper, a decentralized method is proposed to enable PV inverters to autonomously regulate terminal node voltages. The proposed method minimizes the effect of a terminal node's reactive power compensation on the voltage profile of its respective parent-to-terminal node. This ensures that the interference between the voltage regulation of terminal nodes by individual PV inverters is minimized. The performance of the proposed decentralized scheme is verified by extensive powerflow simulations of the EPRI Circuit 24 test feeder in open-source distribution system simulation platform OpenDSS. |
11,677 | Please write an abstract with title: A new approach for the sliding mode control based on fuzzy reaching law, and key words: Sliding mode control, Fuzzy control, Automatic control, Fuzzy systems, Automation, Machinery, Nonlinear systems, Uncertainty, Fuzzy logic, Control system synthesis. Abstract: A scheme of the sliding mode control based on fuzzy reaching law for a class of nonlinear systems with uncertainties is proposed in this paper. Since the proper fuzzy logic control is applied to the reaching law, the quality is improved. At the same time, the chattering phenomenon is avoided. Simulation results show that the control system exhibits not only strong robustness and better quality control, but also avoiding the chattering phenomenon. |
11,678 | Please write an abstract with title: Similarity Measure with Additional Modality Information for Multimodal Remote Sensing Images, and key words: Training, Earth, Artificial satellites, Neural networks, Optical imaging, Optical sensors, Convolutional neural networks. Abstract: This paper considers the problem of learning efficient similarity measure (SM) for multimodal remote sensing (RS) images. It is desirable to have a single SM that is efficient for different combinations of modes. We first consider the influence of training dataset balancing on SM efficiency. We demonstrate that it is possible to improve overall SM performance. However, this improvement is observed only for some combinations of modes. To cope with this problem, we propose to include information about the modes compared as additional input to the proposed Convolutional Neural Network (CNN). With this additional information, SM performance for all combinations of modes was improved. We confirm SM efficiency improvement for the real data from Sentinel 2, Landsat 8, Hyperion, SIR-C, and Sentinel 1 platforms, ASTER Global DEM 2, and ALOS World 30m global DEMs and for combinations of modes including optical-to-optical, optical-to-radar, optical-to-DEM and radar-to-DEM and compare the proposed CNN performance with existing SMs. |
11,679 | Please write an abstract with title: Translator Eccentricity Analysis in Tubular Linear Machines Using Quasi-3-D Finite Element Method Modeling, and key words: Solid modeling, Three-dimensional displays, Computational modeling, Finite element analysis, Error analysis, Integrated circuit modeling, Atmospheric modeling. Abstract: This article attempts to present a quasi-3-D finite element method (FEM) technique for modeling and analyzing tubular linear permanent magnet machines (TLPMs) with translator eccentricity. Normal tubular linear machines can be modeled effectively using 2-D axisymmetric models, but, with the introduction of the eccentricity factor into the geometry, the axis symmetry is no longer valid, and hence, 3-D modeling techniques become the only way for studying the machine. However, sometimes, 3-D modeling can become time-consuming and requires a huge amount of resources especially for non-linear problems, so the interest in modeling techniques that can represent the problem at hand with less computation time and relatively accurate results is high. A quasi-3-D technique was specifically developed to be able to represent the eccentricity in TLPMs. The FEM was used for modeling. The eccentricity analysis has been carried on two different TLPM structures using the proposed quasi-3-D, and the results from the quasi-3-D model were compared to those obtained using the 3-D FEM model. Both the open-circuit and on-load operating conditions were studied with the magnetic saturation taken into account. The behavior and the accuracy of the proposed model varied between the two studied structures and for the different operating conditions, and with very low computation time and cost, the results obtained from the quasi-3-D model were satisfactory in general except for certain cases. |
11,680 | Please write an abstract with title: Fingerprinting Edge and Cloud Services in IoT, and key words: Data privacy, Cloud computing, Systematics, Image edge detection, Phishing, Digital forensics, Machine learning. Abstract: Today, Internet of Things (IoT) devices, web browsers, phones, and even cars may be fingerprinted for tracking, and their connections routed through or to malicious entities. When IoT devices interact with a remote service, the integrity or authentication of that service is not guaranteed. IoT and other edge devices could be subject to man-in-the-middle (MiTM) attacks, with IoT devices attempting to connect to remote services. It is also straight-forward to use phishing or pharming to convince a user to accept a connection to a potentially malicious unfamiliar device. These risks could be mitigated by leveraging information on the edge of the network about the path to and destination of a connection. In this work we sample packets, then use packet analysis and local history to identify risky or suspicious connections. In contrast to other machine learning and big data approaches, the use of local data enables risk detection without loss of privacy. |
11,681 | Please write an abstract with title: Fuzzy two-stage mathematical programming problems, and key words: Mathematical programming, Linear programming, Fuzzy systems, Uncertainty, Stochastic processes, Possibility theory, Dynamic programming, Mathematics, Computer science, Operations research. Abstract: In this paper, a new class of fuzzy programming problems, called fuzzy two-stage programming, is first presented. Then some basic properties of the two-stage model are discussed. In addition, three solution concepts, wait-and-see solution, here-and-now solution and expected value solution are defined for fuzzy programming. After that, two important indexes, the expected value of perfect information (EVPI) and the value of fuzzy solution (VFS), are introduced, and their relations are illustrated via numerical examples. |
11,682 | Please write an abstract with title: New DNA Coded Fuzzy Based (DNAFZ) S-Boxes: Application to Robust Image Encryption Using Hyper Chaotic Maps, and key words: DNA, Encryption, Security, Ciphers, Random sequences, Heuristic algorithms, Transforms. Abstract: This article proposes a novel approach of improvising the cryptographic features of substitution-boxes (S-Box) based on the Choquet Fuzzy Integral (CFI) and DNA techniques. First, we propose a strong structure for the construction of four S-Boxes using CFI. The key for generating the CFI based (FZ) S-Boxes consists of two parts, namely, an external secret key and a secret image. Each of these FZ S-boxes is then encoded using DNA techniques, with dynamic rules selection which is dictated by a secret control code. The resultant four S-boxes are designated as DNAFZ S-Boxes. To apply for image encryption, the plain image is, at first 8-bit binary-coded, shuffled by an M-sequence, and down-sampled into four sub-images. Subsequently, the pixel values of each sub-image are replaced with the corresponding values of one of the four DNAFZ S-Boxes. Next, each DNAFZ encoded sub-image is diffused with a different DNA encoded chaotic sequence from Chen's hyper-chaotic map. Finally, the four DNAFZ/Chaotic encoded sub-images are combined to build the final encrypted image. The proposed DNAFZ S-boxes shows excellent statistical properties under majority logic criterions such as correlation, homogeneity, energy, entropy, and contrast. Moreover, numerical simulation is used to examine the efficacy of encrypted images against different attacks. In particular, the values of the pixel correlation coefficient are found to be quite small either horizontally, vertically, or diagonally (between 7.8597e-04 and 0.00527, between 8.7856e-04 and 0.00452, and between 0.00241 and 0.00021, respectively). In addition, the information entropy of the encrypted image is found to be within the range of (7.9965:7.9989) which is very near to the ideal value of 8. As for the UACI and the NPCR, they are in the ranges between 33.46 and 33.32 and between 99.58 and 99.62, respectively. These values are also very close to the optimum ones. The results are compared to those of other encryption algorithms and proved that the proposed encryption method delivers better results than other conventional ones including LSS chaotic map, Arnold transforms, Dynamic Henon map, Hybrid chaotic map optimized substitution, and cubic S-Box. |
11,683 | Please write an abstract with title: Information-Centric Cyberattack Analysis and Spatiotemporal Networks Applied to Cyber-Physical Systems, and key words: Measurement, Heuristic algorithms, Tools, Cyber-physical systems, Spatiotemporal phenomena, Cyberattack, Resilience. Abstract: Cyber-physical systems (CPS) depend on cybersecurity to ensure functionality, data quality, cyberattack resilience, etc. There are known and unknown cyber threats and attacks that pose significant risks. Information assurance and information security are critical. Many systems are vulnerable to intelligence exploitation and cyberattacks. By investigating cybersecurity risks and formal representation of CPS using spatiotemporal dynamic graphs and networks, this paper investigates topics and solutions aimed to examine and empower: (1) Cybersecurity capabilities; (2) Information assurance and system vulnerabilities; (3) Detection of cyber threat and attacks; (4) Situational awareness; etc. We introduce statistically-characterized dynamic graphs, novel entropy-centric algorithms and calculi which promise to ensure near-real-time capabilities. |
11,684 | Please write an abstract with title: “An Iot Enabled Smart Health Care Kit for Expedite Living”, and key words: Monitoring, Temperature sensors, Cloud computing, Conferences, Biomedical monitoring, Internet of Things. Abstract: Day by day checking of wellbeing condition is imperative for a powerful plan for early treatment and counteractive action of way of life related ailments. It is also expected to perform checking of the wellbeing state of a patient with cluttered amid every day exercises. IoT empowered shrewd social insurance unit can be utilized for checking indispensable parameters of the patients, for example, temperature, pulse and fall recognition utilizing sensors which are associated with the board. The task includes telling the nearest hospital and furthermore to the guardian if the patient is observed to be in abnormal condition. The key advantages of such social insurance unit incorporates simple establishment, profoundly secure two way correspondence, long battery life and ease. |
11,685 | Please write an abstract with title: Feature Interaction Prototypical Network for Few-Shot Fine-Grained Image Classification, and key words: Training, Prototypes, Training data, Feature extraction, Information filters, Natural language processing, Classification algorithms. Abstract: In recent years, although the task of fine-grained image classification has achieved remarkable results, these algorithms need to be trained on large datasets in order to obtain good results, otherwise it is easy to cause model overfitting and reduce the effect. However, fine-grained image datasets need to distinguish different subcategories under the same category. It is difficult to collect and label fine-grained images in practical application, so it is not easy to obtain a large number of good training data. Few-shot learning provides a solution for this. However, the traditional few-shot learning algorithm has limited feature extraction ability, and it is difficult to effectively classify fine-grained images with large intra class differences and small inter class differences. To this end, this paper utilizes the idea of model fine-tuning to extract features using a pre-trained model. In addition, the SimAM non-parametric attention mechanism is introduced to enhance features and filter backgrounds while reducing model parameters. Secondly, feature maps of different convolutional layers are fused using hierarchical bilinear pooling (HBP), thus effectively utilizing information from different convolutional layers to further enhance feature representation. Finally, the classification is completed by calculating the distance between the embedding vectors of the test samples and the well-distributed prototypes generated using the fused features. Experiments show that this algorithm performs well on few-shot fine-grained image classification tasks and achieves excellent performance on traditional few-shot image classification. |
11,686 | Please write an abstract with title: Synthesis of Information System Elements with Ensuring Their Security, and key words: Distributed databases, Information security, Data protection, Control systems, Mathematical models, Energy efficiency, Data models. Abstract: A model is proposed for the synthesis of optimal logical structures of distributed databases in an organization’s information system, in which, due to the lack of sufficient statistical information on the parameters of the system’s functioning at the initial stage of development, some of the variables are assigned as fuzzy LR-type numbers. In connection with the need to ensure information security requirements for such systems, the determination of the optimal structure of a distributed database is expanded by the task of determining forbidden trajectories of transitions between its elements by analyzing the correctness of access matrices and determining errors in them. |
11,687 | Please write an abstract with title: Subarea Division for Urban Road Network Based on Causality, and key words: Roads, Transportation, Planning. Abstract: In this paper, a data-driven causal inference method used for intersection relationship detection of urban road network is proposed. Based on the detected causal relationship between intersections, a directed weighted logical network of the urban road network is constructed. Furthermore, a subarea division method based on modularity division is proposed. This method can divide the urban road network into any number of subareas by maximizing the degree of network modularity. The internal links of each subarea network reflect the close logical relationship between intersections, which may in turn facilitate urban road network planning in different areas. |
11,688 | Please write an abstract with title: Building a Large Comprehensive Medical Image Set of Sinus Diseases, and key words: Hospitals, Communication systems, Computed tomography, Buildings, Machine learning, Medical diagnostic imaging, Diseases. Abstract: Sinuses disorders are among the most common disorders that affect people’s lives worldwide. Diagnosing such disorders requires highly skilled specialists to carefully inspect Computed Tomographic (CT) scans of the patient. The diagnosis process is time-consuming and very costly. To build a machine learning based computer system for the diagnosis process, an annotated set of CT scans representing different sinus disorders is needed to train and test such a system. In this work, we build an image set by collecting CT scans of 100 patients with an average of 94 slices per patient. In each scan, ten different sinuses and sinus parts are captured. These sinuses and sinus parts are distinguished as Frontal (right side), Frontal (left side), Maxillary (right side), Maxillary (left side), Anterior Ethmoid (right side), Anterior Ethmoid (left side), Posterior Ethmoid (right side), Posterior Ethmoid (left side), Sphenoid (right side), and Sphenoid (left side). The scans are segmented and annotated by specialists, where each segment is labeled with the sinus (or sinus part) it depicts (one out of the ten classes mentioned above) along with one of the following six classes representing the status of this part: Normal, Cyst, Osteoma, Chronic Rhinosinusitis (CRS), Antrochoanal polyp (ACP), and Missing sinus. The dataset is acquired from the King Abdullah University Hospital (KAUH) in Jordan and it consists of 48,324 different annotated samples making it the largest and most comprehensive dataset for sinus diseases to the best of our knowledge. |
11,689 | Please write an abstract with title: Open-loop Unstable Feedback Systems with Double-Sided Inputs: an Explicit Demonstration of Self-Consistency, and key words: Stability, Output feedback, Optimal control, Feedback loop, Helium, Mathematical model, Signal analysis, Control theory, Open loop systems, Control systems. Abstract: The standard formulation of linear shift-invariant feedback systems in the doubly infinite time axis setting lacks self-consistency with seemingly irreconcilable difficulties having been identified when the system is open-loop unstable. The available options for circumventing these difficulties for discrete-time SISO systems are highlighted and the manner in which they are exploited to obtain a self-consistent framework by reformulating the feedback systems in the space of distributions is clarified. In addition, it is explicitly demonstrated that causality and stability of a standard example are implied by the causality and stability of the equivalent system when reformulated in the self-consistent framework. |
11,690 | Please write an abstract with title: A monitoring system implementation in China, and key words: Hardware, Power system reliability, Maintenance, Switches, Remote monitoring, Telecommunication network reliability, Mission critical systems, Real time systems, Application software, Computer architecture. Abstract: Today's network structures within datacom and telecom networks with a large number of sites, high requirements of availability, reliability and profitability puts high demands on the operation and maintenance organization to handle the mission critical systems including DC power, AC power, climate and battery systems in an efficient way. This paper will describe a monitoring system used for the mission critical systems within telecom and datacom networks. More than 50,000 sites all over China have the monitoring system installed. The paper will present the design and architecture of the present monitoring system. An enhanced site solution, which is based on the existing site solution, will also be presented. |
11,691 | Please write an abstract with title: Covariance Attention for Semantic Segmentation, and key words: Semantics, Covariance matrices, Feature extraction, Image segmentation, Task analysis, Neural networks, Image edge detection. Abstract: The dependency between global and local information can provide important contextual cues for semantic segmentation. Existing attention methods capture this dependency by calculating the pixel wise correlation between the learnt feature maps, which is of high space and time complexity. In this article, a new attention module, covariance attention, is presented, and which is interesting in the following aspects: 1) covariance matrix is used as a new attention module to model the global and local dependency for the feature maps and the local-global dependency is formulated as a simple matrix projection process; 2) since covariance matrix can encode the joint distribution information for the heterogeneous yet complementary statistics, the hand-engineered features are combined with the learnt features effectively using covariance matrix to boost the segmentation performance; 3) a covariance attention mechanism based semantic segmentation framework, CANet, is proposed and very competitive performance has been obtained. Comparisons with the state-of-the-art methods reveal the superiority of the proposed method. |
11,692 | Please write an abstract with title: Polarization Encoding for Multi-channel Optical Encryption using Twisted Nematic Liquid Crystal Displays, and key words: Optical polarization, Encoding, Cryptography, Liquid crystal displays, Liquid crystals, Optical modulation, Optical sensors, Azimuth, Liquid crystal devices, Voltage. Abstract: This study proposes and demonstrates the multiple polarization-encoding scheme with the cascaded twisted nematic liquid crystal spatial light modulators for multi-channel exclusive OR logic optical encryption. Both analytical and experimental results are presented and discussed. |
11,693 | Please write an abstract with title: Automated Audio Captioning with Epochal Difficult Captions for curriculum learning, and key words: Training, Measurement, Estimation, Information processing, Frequency estimation, Task analysis. Abstract: In this paper, we propose an algorithm, Epochal Difficult Captions, to supplement the training of any model for the Automated Audio Captioning task. Epochal Difficult Captions is an elegant evolution to the keyword estimation task that previous work have used to train the encoder of the AAC model. Epochal Difficult Captions modifies the target captions based on a curriculum and a difficulty level determined as a function of current epoch. Epochal Difficult Captions can be used with any model architecture and is a lightweight function that does not increase training time. We test our results on three systems and show that using Epochal Difficult Captions consistently improves performance by up to 0.013 SPIDEr score. |
11,694 | Please write an abstract with title: Fundus Image Segmentation Using Step Time Signal Polynomial Fitting, and key words: Image segmentation, Biomedical optical imaging, Time series analysis, Fitting, Lighting, Optical imaging, Retina. Abstract: Image segmentation is a basic and important strategy to extract the region of interesting (ROI). However the ROI of retinal fundus image, such as the foreground or optic disc, often could not be generated correctly, due to poor lighting environments, physiological features or improper imaging equipment. Hence, a novel fundus image segmentation method is proposed in this paper. Briefly speaking, considering each line of fundus image as a time series signal, we adopt a step time series signal polynomial curve fitting methodology to smooth the noise and to exclude all features in the fundus image without any loss of the target margin. After fitting the fundus image, a refinement tactic with Kmeans algorithm is used to obtain the final segmentation results. This unsupervised segmentation approach is a completely robust method, because all break points in the signal are detected automatically by the Buishand Range (BR) homogeneity breakpoint detection algorithm. To demonstrate the experimental performance of our new proposal, the test results of foreground segmentation have been compared with their ground truth on DRIVE and STARE datasets, and yield an encouraging performance. Based on these two public datasets and our private database which have been annotated by the medical experts, the experimental outputs of optic disk segmentation achieve the average overlap area ratio of 92.88%, outperforming existing unsupervised methods in this field. |
11,695 | Please write an abstract with title: Existence of Effective Media Properties for Clouds of Metallic and Magnetic Particles, and key words: Solid modeling, Monte Carlo methods, Meetings, Containers, Media, Standards, Method of moments. Abstract: This paper presents a model for mean field electromagnetic propagation through a volume of metallic and magnetic spheres. Particles are assumed to be randomly distributed throughout the medium, and electrically small. Mean field is calculated by coherently averaging the field scattered by many configurations of this random medium enclosed within a container sphere. Fields scattered by individual configurations of the scattered field are calculated using the Method of Moments. Mean field is then compared to the field scattered by a homogeneous, magneto-dielectric sphere the size of the container to determine the effective medium that represents mean field propagation in this random medium. Medium parameters are compared to predictions given by a mixing formula. |
11,696 | Please write an abstract with title: From Optimal to Industrial Antenna: The Designer Dilemma for Compact NB-IoT Terminal, and key words: Q-factor, Prototypes, Europe, Bandwidth, Reflector antennas, Distance measurement, Reflection coefficient. Abstract: This work presents the design of a NB-IoT integrated antenna for LTE band 20 on a compact 50x30 mm terminal. The study will start from the Q factor limitation analysis and finish with a simulated prototype considering the different techniques to enlarge frequency bandwidth. |
11,697 | Please write an abstract with title: RHL-Butterfly: A Scalable IoT-Based Breadboard Prototype for Embedded Systems Laboratories, and key words: Remote laboratories, Actuators, Embedded systems, Transducers, Microcontrollers, Scalability, Breadboard. Abstract: This Research to Practice Work-In-Progress paper presents a virtualized breadboard solution for FPGAs and ARM microcontrollers in remote laboratories. The circumstances that rose amidst the COVID-19 pandemic demonstrated the vulnerability of current engineering education practices, particularly in dealing with hardware resources. Pivoting to the emergency online instruction presented challenges to the traditional practices in delivering hands-on engineering labs, which necessitated a solution that handles hardware prototyping without compromising creativity and instruction. One vital aspect of the embedded systems learning experience is ensuring students and faculty members alike have opportunities to learn and build custom prototyping circuits that interact with microprocessors on breadboards. In this paper, we build on the prior work that our group implemented on using virtualization to interface a virtual breadboard with physical hardware through web applications. Our previous work was limited to interfacing with one particular kind of hardware, designed to explore the capabilities of fundamental transducers and actuators that interface with hardware I/O pins. In hardware engineering practice, however, designers are not constrained by a single microprocessor selection to control their system and designs and are not limited by the type of transducers and actuators that provide the external circuit functionality. This paper presents a solution by scaling the existing virtual breadboard research to support FPGAs and ARM microcontrollers and intermediate logic gate integrated circuits for practical use in engineering curriculums. Providing this increased selection of supporting hardware helps facilitate student learning and simulates hardware development in an industrial setting. Due to the rising popularity of FPGAs and ARM microcontrollers in industry and in education, we expect that our solution will serve a larger audience through this broader selection of supported hardware. Our solution virtualizes the breadboard prototyping experience without sacrificing the nature of real-time embedded systems by taking the user prototyped inputs and outputs and directly programming the functionality of the surrounding system to physical hardware. This balance between a virtualized interface and physical hardware implementation preserves a hardware curriculum embedded systems engineering education and brings a promising solution to expand the scalability and accessibility of engineering labs. |
11,698 | Please write an abstract with title: Statistical analysis of TEC distributions observed over South and Central America, and key words: Global Positioning System, Receivers, Magnetometers, Magnetosphere, South America, Observatories, Magnetic resonance imaging. Abstract: Total electron content (TEC) values measured with several arrays of dual-frequency GPS receivers operating continuously and simultaneously at equatorial and low latitudes are used to construct regional maps of TEC over South and Central America and the Caribbean region. This extended database comprises TEC values collected by 126 stations that operated in South America in 2008, 181 stations in 2009, and 324 stations in 2010. The latter year includes GPS stations in Central America and the Caribbean region, extending the TEC coverage from the southern tip of South America to the northern boundary of Mexico (∼30°N latitude). The TEC maps contain high (0.5° × 0.5°) spatial resolution and good (30 min) temporal resolution. The most prominent feature of these maps is the day-to-day variability that is observed during all seasons and under quiet and active magnetic conditions. Single station plots display TEC variations with time scales of few hours and the appearance of TEC enhancements near-midnight that can be accounted for by electric fields associated with disturbed magnetic conditions and the reverse fountain effect, respectively. To assess the TEC dependencies upon season, solar flux, magnetic activity, and local time over South and Central America, two statistical procedures were employed. First, we constructed monthly averages of TEC values along three field lines that intersect the magnetic equator at 70°, 60°, and 50°W longitudes that show a complex pattern of variability and symmetry/asymmetry of the equatorial anomaly depending on the season, the longitude, and the solar flux. Our second analysis consists of a non-linear least-square fit to simultaneously extract the solar flux, magnetic, and seasonal dependencies of TEC for each square cell (0.5° × 0.5°) of the regional maps and for each 30-min time sector. It is found that during low solar flux conditions, the anomaly is weak or non-existent. When the solar flux F10.7 index increases to 85 units the anomaly shows to be fully developed but contains a pronounced longitudinal/ seasonal dependence. During the equinoxes and afternoon hours, the northern crest extends across the South American continent, but the southern crest prevails in the eastern side of South America. It is found that the non-linear numerical fitting of the TEC distributions can reproduce only 70% of the TEC variability. |
11,699 | Please write an abstract with title: Preventing the Insider – Blocking USB Write Capabilities to Prevent IP Theft, and key words: Image edge detection, Organizations, Drives, Data breach, Universal Serial Bus, Security, Monitoring. Abstract: The Edward Snowden data breach of 2013 clearly illustrates the damage that insiders can do to an organization. An insider's knowledge of an organization allows them legitimate access to the systems where valuable information is stored. Because they belong within an organizations security perimeter, an insider is inherently difficult to detect and prevent information leakage. To counter this, proactive measures must be deployed to limit the ability of an insider to steal information. Email monitoring at the edge is can easily be monitored for large file exaltation. However, USB drives are ideally suited for large-scale file extraction in a covert manner. This work discusses a process for disabling write-access to USB drives while allowing read-access. Allowing read-access for USB drives allows an organization to adapt to the changing security posture of the organization. People can still bring USB devices into the organization and read data from them, but exfiltration is more difficult. |
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