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9,200 | Please write an abstract with title: Object recognition and cognitive map formation using active stereo vision in a virtual world, and key words: Object recognition, Stereo vision, Cognitive robotics, Intelligent robots, Mobile robots, Humans, Biological system modeling, Computational modeling, Robot sensing systems, Navigation. Abstract: In this paper we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties such as focusing, accommodation, field of view are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot (agent). By applying our disparity algorithm on stereo image pairs, depth map for the current view is obtained. Using the depth information for the current view, a cognitive map of the environment is updated gradually while the virtual agent is exploring the environment. The agent explores its environment in an intelligent way using the current view and environmental map information obtained up to date. Also, during exploration if a new object is observed, from its view from different directions, it is labeled with its shape such as sphere, cylinder, cone |
9,201 | Please write an abstract with title: Video Flame Recognition Based on Feature Fusion and Extreme Learning Machine, and key words: Fires, Feature extraction, Image color analysis, Histograms, Image segmentation, Gravity, Training. Abstract: This paper proposes a video flame detection method based on Extreme Learning Machine (ELM). Visual Background Extractor++(ViBE++) algorithm is used to extract the dynamic foreground features of flame video images, and combined with color histogram threshold analysis, the flame region in the image is segmented. By extracting and processing the flame geometrical features such as roundness, sharpness and gravity center, the dynamic and static features of flame image are fused, thus the suspected flame area is screened out. Using the geometric features of suspected flame area and based on ELM model, the training and classification of sample sets are performed. Experimental results show that this method has higher operating speed and accuracy under the condition of less environmental interference. |
9,202 | Please write an abstract with title: A Data Mining based Optimization of Selecting Learning Material in an Intelligent Tutoring System for Advancing STEM Education, and key words: Analytical models, Technological innovation, Scientific computing, Computational modeling, Education, Machine learning, Software. Abstract: Subsequent to the data deluge of the internet era and the recent advancement in big data technologies, it is easy to affirm the continuous application of such technological innovation to tackling a wide array of students' educational needs. The field of artificial intelligence and machine learning have improved education learning outcomes. However, the problem of generalized traditional supportive collaboration scripts for all students irrespective of the student's learning traits and position on the learning spectrum leads to less than optimum result in their educational pursuits. This paper presents a novel approach that uses data mining algorithm to optimize the selection of educational resources for students based on their learning traits and the six factors that cofound instructional content and delivery with a focus on students with learning disabilities for STEM subjects. |
9,203 | Please write an abstract with title: Comparison between Expected and Observed Fisher Information in Interval Estimation, and key words: Maximum likelihood estimation, Gaussian distribution. Abstract: Maximum likelihood estimates and corresponding confidence regions of the estimates are commonly used in statistical inference. In practice, people usually construct approximate confidence regions with the Fisher information at given sample data based on the asymptotic normal distribution of the MLE (maximum likelihood estimator). Two common Fisher information matrices (FIMs, for multivariate parameters) are the observed FIM (the Hessian matrix of negative log-likelihood function) and the expected FIM (the expectation of the observed FIM). In this article, we prove that under certain conditions and with MSE (mean-squared error) criterion, approximate confidence interval of each element of the MLE with the expected FIM is at least as accurate as that with the observed FIM. |
9,204 | Please write an abstract with title: A fault-tolerant architectural approach for dependable systems, and key words: Fault tolerant systems, Software systems, Connectors, Fault tolerance, Collaborative work, Computer architecture, Application software, Software architecture, Fault diagnosis, Mechanical factors. Abstract: A system's structure enables it to generate its intended behavior from its components' behavior. A well-structured system simplifies relationships among components, which can increase dependability. With software systems, the architecture is an abstraction of the structure. Architectural reasoning about dependability has become increasingly important because emerging applications are increasingly complex. We've developed an architectural approach for effectively representing and analyzing fault-tolerant software systems. The proposed solution relies on exception handling to tolerate faults associated with component and connector failures, architectural mismatches, and configuration faults. Our approach, a specialization of the peer-to-peer architectural style, hides inside the architectural elements the complexities of exception handling and propagation. Our goal is to improve a system's overall reliability and availability by making it tolerant of nonmalicious faults. |
9,205 | Please write an abstract with title: An Intrusion Detection Method Integrating KNN and Transfer Extreme Learning Machine, and key words: Training, Computer science, Correlation, Extreme learning machines, Transfer learning, Intrusion detection, Training data. Abstract: As a network security defence technology, an intrusion detection system (IDS) can effectively detect network attack behaviour, significantly protecting network security. Machine learning has been widely used in intrusion detection to improve network intrusion detection and shows the advantages of more intelligence and accuracy than traditional methods. However, intrusion detection based on conventional machine learning requires that the training samples meet the conditions of independent and identical distribution, and data imbalance affects modelling and training. This paper proposes a new intrusion detection model KnTrELM, which integrates KNN and transfer extreme-learning-machine to solve the problems. KnTrELM first applies KNN to detect and delete outlier data to obtain a small-scale and high-quality training data set. Then, based on the transfer learning and extreme learning machine, a transfer extreme learning machine method is proposed. It utilizes the correlation between a large number of labelled data in the source and the target domain data with only a small number of samples, through the probability adaptation between domains, transferring the similar knowledge of source to the target domain, to improve the learning ability of unbalanced samples. Compared with the other four benchmark algorithms, KnTrELM dramatically shortens the training time, increases the training efficiency, and enhances the detection accuracy. |
9,206 | Please write an abstract with title: Guided Robot Skill Learning: A User-Study on Learning Probabilistic Movement Primitives with Non-Experts, and key words: Robot motion, Statistical analysis, Service robots, Education, Humanoid robots, Production, Probabilistic logic. Abstract: Intelligent robots can potentially assist humans in everyday life and industrial production processes. However, the variety of different tasks for such robots renders pure preprogramming infeasible, and learning new tasks directly from non-expert users becomes desirable. Hereby, imitation learning and the concept of movement primitives are promising and widely used approaches. In particular, Probabilistic Movement Primitives (ProMPs) provide a representation that can capture and exploit the variance in human demonstrations. While ProMPs have already been applied for different robotic tasks, an evaluation of how non-expert users can actually teach full tasks based on ProMPs is missing in the literature. We present a framework for Guided Robot Skill Learning which enables inexperienced users to teach a robot combinations of ProMPs and basic robot motions such as gripper commands or Point-to-Point movements. The proposed approach represents the learned skills in the form of sequential Behavior Trees, which can be easily incorporated into more complex robotic behaviors. In a pilot user study with 10 participants, we investigate on two robotic tasks how inexperienced users train ProMP based skills and how they use the concept of modular skill creation. The experimental results show that ProMPs enable more successful task execution compared to teaching Point-to-Point motions. Additionally, our evaluation reveals specific problems that are relevant to consider in future ProMP based teaching systems for non-expert users such as multimodality and missing variance in the demonstrations. |
9,207 | Please write an abstract with title: Comments on periodic and absolute stability for switched linear systems, and key words: Linear systems, Counting circuits, Asymptotic stability, Ear, Artificial intelligence, Upper bound, Eigenvalues and eigenfunctions, Control systems, Sufficient conditions. Abstract: In this contribution we discuss the connection between periodic stability and absolute stability of switched linear systems. We consider the conjecture that periodic stability implies absolute stability (PSAS) and discuss it from a practical perspective. We present detailed observations about a class of systems that provide a counter example for PSAS and make suggestions for exploring the nature of these counter examples. |
9,208 | Please write an abstract with title: Research on Calculation Method of Two-Dimensiona Dual-Limit Speed Safety Protection Curve for High Speed Maglev, and key words: Magnetic levitation vehicles, Safety, Resistance, Eddy currents, Force, Friction, Transportation. Abstract: Determining the safety protection curve of the high-speed maglev train is the first problem to be solved by the high-speed maglev operation control system. The ground-based calculation of the safety protection curve for the high-speed maglev at the speed of 600km/h obviously cannot meet its design requirements. Therefore, this paper proposes an active calculation method of the safety protection curve, establishes a kinematic model of a high-speed maglev train, and combines the characteristics of high-speed maglev two-dimensional protection to give a calculation method of its safety protection curve. Finally, a practical example is used to verify the safety protection performance of the high-speed maglev train based on the calculation method. The results show that the vehicle-based two-dimensional dual-speed safety curve calculation method proposed in this paper can improve the safety of maglve operation without reducing the operating efficiency. |
9,209 | Please write an abstract with title: Model for Estimating Time-Varying Properties of an Inductively Coupled Plasma, and key words: Plasmas, Propulsion, Antenna measurements, Inductance, Integrated circuit modeling, Impedance, Electron tubes. Abstract: A developing application of inductively coupled plasmas is in the field of electrodeless (propellant-flexible) electric propulsion. A significant issue facing this application is the need for diagnostic techniques that do not disturb the plasma (are nonintrusive), are propellant-agnostic, can resolve time variance, and are suitable for use in-flight. A new technique meeting these criteria is presented in this work. The technique makes use of the transformer model of inductive coupling to estimate the plasma impedance from the antenna current and resonant frequency, both of which can be measured nonintrusively. Having an estimate of the plasma impedance, it is possible to estimate a variety of plasma properties under the assumption of a uniform tubular plasma volume. Starting with a circuit representation of a high-power inductive plasma source, governing equations are derived and a solution method is described. Experimental data from the plasma source showing transient behavior (fluctuations within 300-Hz cycle) in oxygen plasmas with various input powers and flow rates are analyzed to demonstrate the technique and investigate trends. The technique produces results that are self-consistent and align well with previous theoretical work. |
9,210 | Please write an abstract with title: A SOM-based classifier with enhanced structure learning, and key words: Data mining, Fuzzy neural networks, Clustering algorithms, Feature extraction, Radio access networks, Neural networks, Robustness, Unsupervised learning, Management training, Network topology. Abstract: This work introduces an innovative synergistic model that aims to improve the efficiency of a neuro-fuzzy classifier, providing the means of online adaptation and fast learning. It combines the advantages of a self-organized map (SOM) network, as well as the benefits of a structure allocation fuzzy neural network. The system initializes its parameters using the clustering result on the SOM structure, while a novel approach of evaluating the input features leads to a more efficient way of handling the on-line learning rate of the training process. Experimental results on benchmark classification problems showed that this robust combination can also tackle tasks of great dimensionality in a successful manner. |
9,211 | Please write an abstract with title: Social Relationship Recognition Based on Relational Self-Attention Mechanism, and key words: Computers, Measurement, Image recognition, Computational modeling, Conferences, Neural networks, Feature extraction. Abstract: Social relations are closely related to each of us and are a crucial part of society. Recognizing the social relationships of people in pictures can improve AI’s understanding of human behavior, thereby facilitating collaborative interactions between computers and humans. Previous work only focused on a single picture, so too little information can be obtained. In this paper, we proposed Picture Reasoning Model(PRM) to achieve relationship classification, which innovatively uses the self-attention method to learn the association between relationships. The association between relationships is at the social level, thus using it to assist relationship recognition can get rid of the problem of insufficient information in a single picture. In addition, the model also adopts a two-stream approach, extracting both characters and global features for getting multiple perspectives information. We conduct extensive experiments on two benchmark datasets PIPA and PISC. Experimental results show that our model has improved the accuracy metric of the datasets compared with SOTA. On the PIPA dataset, the accuracy increases from 64.4% to 65.6%, and on the PISC dataset, the mAP raises from 72.7% to 73.2%, which validates the effectiveness of our proposals. |
9,212 | Please write an abstract with title: Modeling finite-memory nonlinearity in unit DAC elements, binary storage channels, and BPSK data channels, and key words: Binary phase shift keying, Intersymbol interference, Convolutional codes, Magnetic separation, Quantization, Noise shaping, Noise level, Magnetic memory, Convolution, Filters. Abstract: Spectral shaping of quantization noise can allow a few (or one) oversampled D/A converters restricted to two output levels, unit DAC elements, to replace high-resolution converters. In high-resolution or high-speed settings however, even the performance of systems with only two output levels can be limited by conversion-circuit nonlinearities that introduce quantization-noise intermodulation products into the signal band through nonlinear intersymbol interference (ISI). Nonlinear ISI also affects the communication and magnetic storage of data. Here a simple but very general model structure for such binary-in, analog-out nonlinearities is proposed. Curiously, its structure is that of a convolutional coder whose output bits are separately LTI filtered before being finally summed to form the analog output. The largest-energy filter responses have natural interpretations if this convolutional code is chosen carefully. One such code is presented here. |
9,213 | Please write an abstract with title: The effect of cursor shape and size on pointing efficiency, and key words: Shape, Testing, Aging, Psychology, Computer displays, Mice, Neck, Fatigue, Performance analysis, Error analysis. Abstract: Graphical interfaces contribute to the ease of use of computers. Interfaces based on WIMP (windows, icons, menus, and pointer) have made it possible for users to perform tasks efficiently with a few mouse clicks. However, problems like deteriorating eyesight make it difficult for many middle-aged and older people to see the cursor. There is an extensive range of literature demonstrating selection strategies which address such problems. However, the effect of the shape of the tip of a cursor on pointing efficiency is still not clear. The most commonly used cursor shape is an arrow. It's hard to say at this stage what shape of cursor is the best. The minute tip of the cursor is difficult to see and to place precisely into a target. Accurate placement of the cursor requires a keen eye, a steady hand and delicate motion of the hand. This causes significant physical and psychological burdens such as shoulder and neck stiffness and emotional fatigue. Thus, this research focused on the effect of the shape and size of the cursor on pointing efficiency for middle-aged and older adults. Thus, we seek to find the best shape for cursors. |
9,214 | Please write an abstract with title: Memory/Disk Operation Aware Lightweight VM Live Migration, and key words: Hidden Markov models, Bandwidth, Quality of service, Prediction algorithms, Cloud computing, Memory management, IEEE transactions. Abstract: Live virtual machine migration technique allows migrating an entire OS with running applications from one physical host to another, while keeping all services available without interruption. It provides a flexible and powerful way to balance system load, save power, and tolerate faults in data centers. Meanwhile, with the stringent requirements of latency, scalability, and availability, an increasing number of applications are deployed across distributed data-centers. However, existing live migration approaches still suffer from long downtime and serious performance degradation in cross data-center scenes due to the mass of dirty retransmission, which limits the ability of cross data-center scheduling. In this paper, we propose a system named Memory/disk operation aware Lightweight VM Live Migration across data-centers with low performance impact (MLLM). It significantly improves the cross data-center migration performance by reducing the amount of dirty data in the migration process. In MLLM, we predict disk read workingset (i.e., more frequently read contents) and memory write workingset (i.e., more frequently write contents) based on the access sequence traces. And then we adjust the migration models and data transfer sequence by the workingset information. We further proposed an improved algorithm for workingset estimation. Moreover, we discussed the potential use of machine learning (ML) to enhance the performance of the VM migration and also propose a two-level hierarchical network model to make the ML-based prediction more efficient. We implement MLLM and its improved versions on the QEMU/KVM platform and conduct several experiments. The experimental results show that 1) MLLM averagely reduces 62.9% of total migration time and 36.0% service downtime over existing methods; 2) The improved workingset estimation algorithm reduces 9.32% memory pre-copy time on average over the original algorithm. |
9,215 | Please write an abstract with title: Compressing CNNs by Exponent Sharing in Weights using IEEE Single Precision Format, and key words: Performance evaluation, Computer vision, Computational modeling, Hardware, Convolutional neural networks. Abstract: The performance of convolutional neural networks for computer vision and other applications has crossed human accuracy levels on high-end systems. The demand for these applications in small, mobile hardware is increasing while expecting the same performance. These devices have considerably smaller memory and power budgets. Prior work on model compression for inference on edge devices has sacrificed some accuracy to compress the models. We propose a novel model compression approach by sharing exponents of weights stored in IEEE floating-point format. This approach does not require any fine-tuning after compression. We demonstrate our technique on different trained models resulting in nearly 10% compression in storage and requiring less than 1.5 times the original execution time. |
9,216 | Please write an abstract with title: On The Role Of Execution Order In Hybrid Evolutionary Algorithms, and key words: Iron, Optimization, Sociology, Statistics, Evolutionary computation, Heuristic algorithms, Atmospheric measurements. Abstract: Many real-world problems can be formulated as the optimization of a continuous function. Furthermore, these problems are becoming increasingly more complex every year, reaching, or even exceeding, the thousand of variables. Evolutionary Algorithms have been traditionally successful at solving this kind of problems, due to their good balance in terms of solution quality and computation time. However, the aforementioned growth in the size of the problems requires of novel approaches to deal with the increased complexity of larger solutions spaces. Hybrid evolutionary algorithms are a powerful alternative in these scenarios as they are able to combine the strengths of multiple search methods to solve more complex problems. These hybrid approaches normally do not pay attention to the execution order of their components, being the most frequent strategy to always run them in a predefined sequence. In this contribution we study the role of execution order in hybrid evolutionary algorithms within the context of the multiple offspring sampling framework, one of the best algorithms in large-scale global optimization. As shown in the experimentation, a proper execution order policy can boost the performance of MOS to improve the results of other state-of-the-art algorithms. |
9,217 | Please write an abstract with title: Towards Understanding the Monetization and Censorship Aspect of Streaming Media, and key words: Support vector machines, Machine learning algorithms, Production, Streaming media, Media, Prediction algorithms, Censorship. Abstract: The high production and utilization of digital content have led to an increase in content censorship. YouTube censors its digital content by Demonetization of videos. Demonetization is a process in which content creators are denied paid ads in their YouTube videos. The creators are refused income. In cases, their income on the video-hosting platform is lessened, and their video is less likely to be promoted or recommended, eventually getting censored. There is little known about YouTube's censorship algorithm as it exists as a Blackbox to the world. The Work-in-Progress (WIP) proposes a methodology that employs four machine learners, i.e., C 4.5, Random Forest, Logistic Regression and Support Vector Machine, to predict if changes in the meta-data of the YouTube video will lead to (demonetization) censorship of the video. Our methodology requires little time to train and achieve an accuracy of up to 79%. |
9,218 | Please write an abstract with title: An Energy Storage System for Recycling Regenerative Braking Energy in High-Speed Railway, and key words: Rail transportation, Supercapacitors, Power grids, Recycling, Rails, Master-slave. Abstract: This paper proposes an energy storage system (ESS) for recycling the regenerative braking energy in the high-speed railway. In this case, a supercapacitor-based storage system is integrated at the DC bus of the back to back converter that is connected to the two power phases of the traction power system (TPS). In order to ensure the suitability of the ESS in the TPS, the operation modes are classified by considering the load conditions of the TPS and the state-of-charge limit of the supercapacitor. Then, a master-slave control strategy with a central controller is proposed. In which, the central controller realizes the flexible management for all operation modes, by means of the state machine logic. Meanwhile, the master-slave control serves for coordinating the operation of the multiple converters according to the commands from the central controller. Finally, the capabilities of the proposed ESS are validated by sufficient experiments under different operation modes and the simulation based on the field data. |
9,219 | Please write an abstract with title: Internal Power Net Defect Localization Via Holistic Fault Isolation With FIB Edit Pico Probe, and key words: Location awareness, Rails, Scanning electron microscopy, Optical microscopy, Transmission electron microscopy, Microscopy, Failure analysis. Abstract: Effective test coverage served as a gate keeper for device failure screening, this is to ensure none of the failing part escaped to customer side. Samples that failed electrically be means in class test and reliability stress test will need failure analysis for defect root causing. This is crucial for continuous product quality improvement. Physical defect localization to enable defect finding highly depends on optical fault isolation (FI) for defect localization and physical failure analysis (PFA) techniques ranging from sample delayering, secondary electron microscope (SEM) imaging and transmission electron microscopy (TEM) to reveal the physical defect. In certain cases where the failure is suspected to be internal regulated power line induced the section on area for SEM will be much too large. Extensive nano probing is required to isolate the failing region. This along with FIB edit and pico probe will be able to provide electrical failure correlation and to create a hypothesis. In this work, a complete failure analysis fault isolation (FAFI) method using the afore mentioned techniques to lock down the physical defect caused by power rail short reported in power-up-power-down (PUSPDS) test is presented. |
9,220 | Please write an abstract with title: Compositional Fault Propagation Analysis in Embedded Systems using Abstract Interpretation, and key words: Embedded systems, Codes, Systematics, Simulation, Single event upsets, Static analysis, Software systems. Abstract: Resilience against hardware faults is a major concern for safety-critical embedded systems which has been addressed in several standards. These standards demand a systematic and thorough safety evaluation, especially for the highest safety levels. In order to provide the data for this evaluation, we propose a scalable and formal approach to fault propagation analysis for hardware/software systems. We consider soft errors by single event upsets (SEUs) which corrupt data in hardware registers and examine their effect on the high-level software. Our method identifies all faults of a given fault list that can have an effect on selected objects of the high-level software, such as the specified safety functions, and gives formal guarantees for other faults that do not do any harm.Scalability of our approach results from combining an analysis at the binary and hardware level with an analysis of the high-level source code using Abstract Interpretation. The result is a mapping between a fault in the hardware and affected locations in the source code. Effectiveness and scalability of this method are demonstrated on an industry-oriented software system with about 138 k lines of C code. |
9,221 | Please write an abstract with title: Design and Implementation of Improved Three Port Converter and B4-Inverter Fed Brushless Direct Current Motor Drive System for Industrial Applications, and key words: Batteries, Voltage control, Inverters, Motor drives, Inductors, Renewable energy sources, Maximum power point trackers. Abstract: With the proliferation of renewables and energy storage, inverters and converters are being updated to outperform their antecedents in every possible aspect for numerous applications in fields and industries. The proposed research involves the design and implementation of improved three interface converter, and B4-Inverter fed brushless direct electric current motor drive for industrial uses. The proposed integrated Three Port Converter (ITPC) and B4-Inverter fed Brushless Direct Current Motor (BLDC) drive is proposed targeting low or medium applications. The ITPC has been operated in unidirectional and going in both directions for accomplishing a built-in dual electric potential and power rate of flow control. besides, efficiency and the losses of the proposed converter are analyzed using three different domains, i.e., battery charging, discharging, and photovoltaic (PV) effectively. The results are validated by performing simulations of the proposed systems in MATLAB/Simulink. The validation results reveal that the proposed converter works under all three domains and that the losses in the PV domain are reduced compared to the other converters. Also, the average efficiency achieved is 80.95%. These results authenticate the application of the proposed converter to numerous applications pertaining to renewable energy resources and energy systems. |
9,222 | Please write an abstract with title: Simultaneous Evalulation of Contrast Pulse Sequences for Super-Resolution Ultrasound Imaging – Preliminary In Vitro and In Vivo Results, and key words: Imaging, Animals, Ultrasonic imaging, Signal to noise ratio, In vitro, In vivo, Image resolution. Abstract: Super-resolution ultrasound imaging (SR-US) has enabled a tenfold improvement in resolution of the microvasculature with clinical application in many disease processes such as cancer, diabetes and cardiovascular disease. Plane wave ultrasound (US) platforms in turn are capable of the very high frame rates needed to track microbubble (MB) contrast agents used in SR-US. Both B-mode US imaging and contrast enhanced US imaging (CEUS) have been effectively used in SR-US, with B-mode US having higher signal-to-noise ratio (SNR) and CEUS providing higher contrast-to-tissue ratio (CTR). Lengthy imaging time needed for SR-US to allow perfusion and MB detection is an impediment to clinical adoption. Both SNR and CTR improvements can enhance SR-US imaging by enhancing the detection of MBs thus reducing imaging time. This study simultaneously evaluated nonlinear contrast pulse sequences (CPS) employing different amplitude modulation (AM) and pulse inversion (PI) nonlinear CEUS imaging techniques as well as combinations of the two, (AMPI) with B-mode US imaging. The objective was to improve the detection rate of MB during SR-US. Imaging was performed in vitro and in vivo in the rat hind limb using a Vantage 256 research scanner (Verasonics Inc.). Comparisons of four CPS compositions with B-mode US imaging was made based on the number of MB detected and localized in SR-US images. The use of a PI nonlinear CEUS imaging strategy improved SR-US imaging by increasing the number of MB detected in a sequence of frames by an average of 28.3% and up to 52.6% over a B-mode US imaging strategy, which would decrease imaging time accordingly. |
9,223 | Please write an abstract with title: Towards Better Bus Networks: A Visual Analytics Approach, and key words: Visual analytics, Planning, Transportation, Data visualization, Decision making, Urban areas, Knowledge engineering. Abstract: Bus routes are typically updated every 3–5 years to meet constantly changing travel demands. However, identifying deficient bus routes and finding their optimal replacements remain challenging due to the difficulties in analyzing a complex bus network and the large solution space comprising alternative routes. Most of the automated approaches cannot produce satisfactory results in real-world settings without laborious inspection and evaluation of the candidates. The limitations observed in these approaches motivate us to collaborate with domain experts and propose a visual analytics solution for the performance analysis and incremental planning of bus routes based on an existing bus network. Developing such a solution involves three major challenges, namely, a) the in-depth analysis of complex bus route networks, b) the interactive generation of improved route candidates, and c) the effective evaluation of alternative bus routes. For challenge a, we employ an overview-to-detail approach by dividing the analysis of a complex bus network into three levels to facilitate the efficient identification of deficient routes. For challenge b, we improve a route generation model and interpret the performance of the generation with tailored visualizations. For challenge c, we incorporate a conflict resolution strategy in the progressive decision-making process to assist users in evaluating the alternative routes and finding the most optimal one. The proposed system is evaluated with two usage scenarios based on real-world data and received positive feedback from the experts. |
9,224 | Please write an abstract with title: Impact of finite buffers on the optimal scheduling of a single-machine two-part-type manufacturing system, and key words: Optimal scheduling, Manufacturing systems, Job shop scheduling, Cost function, Flexible manufacturing systems, Single machine scheduling, Dynamic scheduling, Dynamic programming, Processor scheduling, Stochastic systems. Abstract: We give a complete solution to a scheduling problem for a two-part-type, single-machine, flexible manufacturing system, with finite-capacity buffers. Backlogged and rejected requests incur a cost which must be minimized over an infinite time interval. If buffer capacities were infinite, the well-known c/spl mu/ rule would have solved the problem. We find the optimal policy for the finite-capacity case and give a computation procedure and some illustrative examples. |
9,225 | Please write an abstract with title: TDMR With Machine Learning Data Detection Channel, and key words: Training, Detectors, Interference, Magnetic heads, Bit error rate, Signal to noise ratio, Sensitivity. Abstract: In this article, we present a systematic study of using a machine learning (ML) data detection channel consisting of a convolutional neural network (CNN) for data recovery in a two-dimensional magnetic recording (TDMR) setting with two displaced readers. To mimic the actual head skew angle change over the entire disk platter, data recovery over a wide range of inter-track interference (ITI) has been investigated. During training, the CNN-based ML channel only “learns” to detect the main track data although the sampled input signals from both readers are taken as input. It is found that with reasonable training, the ML channel can almost completely eliminate the ITI-caused degradation of bit error rate (BER). Moreover, it is also found that the training processes are only needed at very few head skewing angles, adding to the viability of the possible practical implementation. We believe the understanding elucidated in this article could serve the basis for developing viable and robust ML-based data detection channels leading to significant areal density gain for TDMR technology. |
9,226 | Please write an abstract with title: Investigation on Single Pulse Avalanche Failure of 1200-V SiC MOSFETs via Optimized Thermoelectric Simulation, and key words: Silicon carbide, MOSFET, Junctions, Semiconductor process modeling, Thermal conductivity, Transistors, Thermal resistance. Abstract: The dynamic avalanche reliability of 1200-V silicon carbide (SiC) power metal-oxide semiconductor field-effect transistors (MOSFETs) is studied in this article. The unclamped inductive switching (UIS) tests are conducted to locate failure points. An optimized thermal network model with the definition of the material above the epitaxial layer is used to simulate the avalanche process of SiC MOSFETs. The simulation and experiment results are matched, which verifies the validity of this model. Further simulation results show that a slight change in the doping profile of the p-well region will make the avalanche capability significantly different. Then, the effect of the deviation in cell parameters on the avalanche capability is studied by multicell simulation. The results demonstrate that uneven distribution of internal parameters makes the parasitic bipolar junction transistor (BJT) of some cells turn-on first, causing a significant concentration of current and heat in a very short time, and eventually forming hot spots often observed in failed devices. |
9,227 | Please write an abstract with title: Intrusion detection system based on Global-feature Contribution Network, and key words: Correlation, Computational modeling, Conferences, Intrusion detection, Network security, Feature extraction, Performance analysis. Abstract: In recent years, network security has been frequently threatened by complex network attacks. Intrusion detection system(IDS) is an active network security protection, which can effectively detect the network system when it is attacked. However, most intrusion detection system only consider the contribution of each feature to the result. In this paper, we proposes an intrusion detection system based on Global-feature Contribution Net-work(GCN). The Global-feature Contribution Network consists of two parts: Factorization Machine(FM) part and Global-Local network part. Factorization machine carry out second-order combination of features to consider the correlation between different features in attack samples and reduce the impact of sparse sample features on detection results. Global-Local network continuously integrates the global features of samples into local features, so that the network can learn the local features of samples under the grasp of global information. We evaluated our model on KDDCup99 dataset to show the effectiveness of our method. Compared with traditional methods, the model improves the accuracy and recall rate, and makes an accurate judgment on the perception of network security situation. |
9,228 | Please write an abstract with title: Poisons that are learned faster are more effective, and key words: Training, Data privacy, Privacy, Computer vision, Toxicology, Correlation, Perturbation methods. Abstract: Imperceptible poisoning attacks on entire datasets have recently been touted as methods for protecting data privacy. However, among a number of defenses preventing the practical use of these techniques, early-stopping stands out as a simple, yet effective defense. To gauge poisons’ vulnerability to early-stopping, we benchmark error-minimizing, error-maximizing, and synthetic poisons in terms of peak test accuracy over 100 epochs and make a number of surprising observations. First, we find that poisons that reach a low training loss faster have lower peak test accuracy. Second, we find that a current state-of-the-art error-maximizing poison is 7× less effective when poison training is stopped at epoch 8. Third, we find that stronger, more transferable adversarial attacks do not make stronger poisons. We advocate for evaluating poisons in terms of peak test accuracy. |
9,229 | Please write an abstract with title: Accuracy of dynamical models for analog iterative error control decoders, and key words: Error correction, Iterative decoding, Parity check codes, Circuit simulation, Bit error rate, Circuit testing, SPICE, Turbo codes, Hardware, Block codes. Abstract: This paper examines the accuracy of an abstract dynamical model for continuous-time analog iterative error-control decoders. An existing compact dynamical model formulates iterative decoding as a fixed point problem. The dynamics of each analog cell are modeled by a non-linear differential equation with a single time-constant, which is solved numerically using Euler's method. We propose a fitness test to evaluate the accuracy of this abstract model. For randomly constructed codes and random stimuli, circuit descriptions are synthesized using both the abstract dynamical model and SPICE. A comparison is performed to measure the correspondence between the two simulations for codes of increasing length and complexity. |
9,230 | Please write an abstract with title: Wireless Communication Technologies for Internet of Things and Precision Agriculture: A Review, and key words: Wireless communication, Bluetooth, Zigbee, Agriculture, Communications technology, Internet of Things, Monitoring. Abstract: Precision Agriculture is an important application of the Internet of Things (IoT). Precision Agriculture is the solution to the food shortage that may hit the world due to the large population, about 9.5 billion by 2050, and other environmental impacts like water scarcity due to conventional agricultural practices. IoT provided field and weather information to farmers and relies on communication technologies for the sharing of information. Wireless communication technologies provide the means to transmit the collected information in an IoT network. ZigBee, RFID, NFC, Bluetooth, BLE, LTE, 6LoPWAN, Sigfox, and LoRa are the major technologies deployed in IoT for agriculture. Wireless communication technologies differ in their data communication range and power efficiency. Some are suitable for short-distance monitoring while few offer the long communication range for monitoring and control. Various available wireless communication technologies are revied in this article for their technical specifications and their applicability in Precision Agriculture. |
9,231 | Please write an abstract with title: Machine Learning Methods to identify Hindi Fake News within social-media, and key words: Machine learning algorithms, Social networking (online), Machine learning, Tools, Safety. Abstract: Over the last decades, Fake news has exploded online. Fabricated stories go viral on digital media. The rise in the use of digital media has accelerated the pace of fake news. It affects the offline public and also threatens human safety. It is critical to check the veracity of news over social media platforms to mitigate its grave impacts. Finding accurate information within this ocean of data is where fake news detection comes into the picture. Most of the existing work is based on the English language. A little work is done using resource scare language for fake news identification. This paper presents an Indian dataset for Hindi Language using Devanagari lipi. Indian Hindi news is collected using the Parsehub scrapping tool. We performed several experiments by using an existing machine learning algorithm and achieved satisfactory results. The outcome reflects the effectiveness of our proposed dataset. |
9,232 | Please write an abstract with title: A statistical comparison of grammatical evolution strategies in the domain of human genetics, and key words: Humans, Genetics, Evolution (biology), Biological system modeling, Diseases, Semiconductor device measurement, DNA, Sequences, Genomics, Bioinformatics. Abstract: Detecting and characterizing genetic predictors of human disease susceptibility is an important goal in human genetics. New chip-based technologies are available that facilitate the measurement of thousands of DNA sequence variations across the human genome. Biologically-inspired stochastic search algorithms are expected to play an important role in the analysis of these high-dimensional datasets. We simulated datasets with up to 6000 attributes using two different genetic models and statistically compared the performance of grammatical evolution, grammatical swarm, and random search for building symbolic discriminant functions. We found no statistical difference among search algorithms within this specific domain. |
9,233 | Please write an abstract with title: Two-Phase DC-Biased Vernier Reluctance Machines, and key words: Torque, Stator windings, Rotors, Windings, Modulation. Abstract: This article proposes a novel two-phase dc-biased current Vernier reluctance machine (DCBVRM) equipped with concentrated windings. Compared with the existing three-phase DCBVRMs, the number of power electronic switching devices has been greatly reduced without sacrificing performance. Consequently, the overall system cost is greatly reduced, and thus, it is competitive for low-cost applications such as household appliances. To highlight the advantages of the proposed topology, the theories of coil connection, current configuration, and so on are illustrated, and some electromagnetic characteristics, such as flux density, back electromotive force, and electromagnetic torque, are predicted by finite-element analysis (FEA) with two eight-stator slot machines. Finally, the comparison with three-phase counterpart shows that the proposed eight stator slots, seven rotor slots, and two-phase machine can exhibit 21% higher torque with much lower inverter cost. |
9,234 | Please write an abstract with title: Capacity Bounds for One-Bit MIMO Gaussian Channels With Analog Combining, and key words: Receivers, MIMO communication, Quantization (signal), Signal to noise ratio, Upper bound, Hardware, Receiving antennas. Abstract: The use of 1-bit analog-to-digital converters (ADCs) is seen as a promising approach to significantly reduce the power consumption and hardware cost of multiple-input multiple-output (MIMO) receivers. However, the nonlinear distortion due to 1-bit quantization fundamentally changes the optimal communication strategy and also imposes a capacity penalty to the system. In this paper, the capacity of a Gaussian MIMO channel in which the antenna outputs are processed by an analog linear combiner and then quantized by a set of zero threshold ADCs is studied. A new capacity upper bound for the zero threshold case is established that is tighter than the bounds available in the literature. In addition, we propose an achievability scheme which configures the analog combiner to create parallel Gaussian channels with phase quantization at the output. Under this class of analog combiners, an algorithm is presented that identifies the analog combiner and input distribution that maximize the achievable rate. Numerical results are provided showing that the rate of the achievability scheme is tight in the low signal-to-noise ratio (SNR) regime. Finally, a new 1-bit MIMO receiver architecture which employs analog temporal and spatial processing is proposed. The proposed receiver attains the capacity in the high SNR regime. |
9,235 | Please write an abstract with title: Toward to usage of regularized Stefan problem solution in icing modeling, and key words: Heating systems, Atmospheric modeling, Computational modeling, Ice, Numerical models, Mathematical model, Finite difference methods. Abstract: In 2019 Tong Liu and coauthors proposed the development of the Messinger-Myers models for modeling the icing of aircraft. Their proposal consists in replacing the quasi-stationary heat equation for the ice region with a non-stationary heat equation. In our work, we propose to consider the same replacement for the water film region also. Then in the region of ice and water film, the temperature is described by a unified equation of thermal conductivity with discontinuous coefficients at the interface is known as Stefan problem. Stefan problem is a fundamental problem describing phenomena in phase transitions of substance. It was investigated as analytically and numerical both by various authors. Due to complexity of the considering problem the analytics is available only in simple cases. The main complexity of this problem relates with the internal boundary moving. The numerical solution of this incorrect problem is not simple. To date, a few of regularization methods proposed for the solution of Stefan problems by various authors. The main goal of this paper is investigate regularization of considering problem by omitting of classic Stefan condition at interface boundary. For solving of regularized problem we apply two different finite difference schemes of the second order approximation. The first is a second order hybrid finite difference scheme in and the second is a uniform second order finite difference scheme. Computations in Open Source Octave environment were provided and numerical results obtained by different schemes compared together, and with analytical solution. Computations of ice accretion on the NACA 0012 airfoil computed by iceFoam solver and Messenger-Mayer model are presented. |
9,236 | Please write an abstract with title: Electric Field Regulation by Multi-dimensional Functional Materials for DC-GIS Spacer, and key words: Doping, Insulators, Regulation, Steady-state, Dielectrics, Electric fields, Transient analysis. Abstract: This paper offers a simulation study on the application of a novel approach to control the electric field around a basin-type spacer by combining permittivity functionally graded materials ($\varepsilon$-FGM) and superficially nonlinear conductivity materials (SNCM), namely multi-dimensional functional materials (MDFM). The permittivity distribution of the $\varepsilon$-FGM spacer is designed by the iteration optimization algorithm, and the epoxy/SiC composites with 30 and 60 phr (parts per hundred) doping contents are assigned as the coating materials of two SNCM spacers, namely SNCM30 and SNCM60. The MDFM spacer combines $\varepsilon$-FGM in its bulk and SNCM60 on its surface. The electric field regulation effect of each functional spacer is investigated under variable conditions, i.e., DC steady state (DC-steady), DC turn-on state (DC-on), DC polarity reversal (DC- PR). Results show that the applicability of $\varepsilon$-FGM and SNCM is limited to transient and stationary conditions, respectively. The MDFM spacer combines the advantages of $\varepsilon$-FGM and SNCM for adaptively relaxing the electric field under all the above conditions. |
9,237 | Please write an abstract with title: Active and cooperative learning in signal processing courses, and key words: Signal processing, Physics, Books, Force feedback, Problem-solving, Remuneration, Protocols, Education, Digital signal processing, Computer aided instruction. Abstract: This work describes positive effects of using active and cooperative learning (ACL) methods to improve signal processing instruction. It provides examples, references, and assessment data that encourage other instructors to consider this approach. Conclusions are based on impressions gathered through conversations with students during office hours as well as on responses from anonymous student opinion surveys. In addition to these subjective assessments, preliminary quantitative data measured with the signals and systems concept inventory (SSCI) support the benefits of ACL techniques in signal processing courses. |
9,238 | Please write an abstract with title: Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals, and key words: Anomaly detection, Predictive models, Data models, Autoregressive processes, Image reconstruction, Forecasting, Computational modeling. Abstract: Nowadays, multi-sensor technologies are applied in many fields, e.g., Health Care (HC), Human Activity Recognition (HAR), and Industrial Control System (ICS). These sensors can generate a substantial amount of multivariate time-series data. Unsupervised anomaly detection on multi-sensor time-series data has been proven critical in machine learning researches. The key challenge is to discover generalized normal patterns by capturing spatial-temporal correlation in multi-sensor data. Beyond this challenge, the noisy data is often intertwined with the training data, which is likely to mislead the model by making it hard to distinguish between the normal, abnormal, and noisy data. Few of previous researches can jointly address these two challenges. In this paper, we propose a novel deep learning-based anomaly detection algorithm called Deep Convolutional Autoencoding Memory network (CAE-M). We first build a Deep Convolutional Autoencoder to characterize spatial dependence of multi-sensor data with a Maximum Mean Discrepancy (MMD) to better distinguish between the noisy, normal, and abnormal data. Then, we construct a Memory Network consisting of linear (Autoregressive Model) and non-linear predictions (Bidirectional LSTM with Attention) to capture temporal dependence from time-series data. Finally, CAE-M jointly optimizes these two subnetworks. We empirically compare the proposed approach with several state-of-the-art anomaly detection methods on HAR and HC datasets. Experimental results demonstrate that our proposed model outperforms these existing methods. |
9,239 | Please write an abstract with title: Spectral-approximation-based intelligent modeling for distributed thermal processes, and key words: Curing, Ovens, State estimation, Reduced order systems, Neural networks, Differential equations, Semiconductor device packaging, Distributed parameter systems, Boundary conditions, System identification. Abstract: A spectral-approximation-based intelligent modeling approach is proposed for the distributed thermal processing of the snap curing oven that is used in semiconductor packaging industry. The snap curing oven can be described by a nonlinear parabolic distributed parameter system (DPS) in the time-space domain. After finding a proper approximation of the complex boundary conditions of the system, the spectral methods can be applied to time-space separation and model reduction, and neural networks (NNs) can be used for state estimation and system identification. With the help of model reduction techniques, the dynamics of the curing process derived from physical laws can be described by a model of low-order nonlinear ordinary differential equations with a few uncertain parameters and unknown nonlinearities. A neural observer can then be designed to estimate the states of the ordinary differential equation model from measurements taken at specified locations in the field. Using the estimated states, a hybrid general regression NN is trained to be a nonlinear model of the curing process in state-space formulation, which is suitable for the further application of traditional control techniques. Real-time experiments on the snap curing oven show that the proposed modeling method is effective. This modeling methodology can be applied to a class of nonlinear DPSs in industrial thermal processing. |
9,240 | Please write an abstract with title: 2Deep: Enhancing Side-Channel Attacks on Lattice-Based Key-Exchange via 2-D Deep Learning, and key words: Resistance, Performance evaluation, Deep learning, Protocols, Power measurement, Side-channel attacks, NIST. Abstract: Advancements in quantum computing present a security threat to classical cryptography algorithms. Lattice-based key exchange protocols show strong promise due to their resistance to theoretical quantum-cryptanalysis and low implementation overhead. By contrast, their physical implementations have shown vulnerability against side-channel attacks (SCAs) even with a single power measurement. The state-of-the-art SCAs are, however, limited to simple, sequentialized executions of post-quantum key-exchange (PQKE) protocols, leaving the vulnerability of complex, parallelized architectures unknown. This article proposes 2Deep-a deep-learning (DL)-based SCA-targeting parallelized implementations of PQKE protocols, namely, Frodo and NewHope with data augmentation techniques. Specifically, we explore approaches that convert 1-D time-series power measurement data into 2-D images to formulate SCA an image recognition task. The results show our attack's superiority over conventional techniques including horizontal differential power analysis (DPA), template attacks (TAs), and straightforward DL approaches. We demonstrate improvements up to 1.5× to recover a 100% success rate compared to DL with 1-D input data while using fewer data. We furthermore show that machine learning improves the results up to 1.25× compared to TAs. Furthermore, we perform cross-device attacks that obtain profiles from a single device, which has never been explored. Our 2-D approach is especially favored in this setting, improving the success rate of attacking Frodo from 20% to 99% compared to the 1-D approach. Our work thus urges countermeasures even on parallel architectures and single-trace attacks. |
9,241 | Please write an abstract with title: Assessment-based use of CAD tools in electromagnetic field courses, and key words: Electromagnetic fields, Design automation, Computational modeling, Electromagnetic analysis, Electrical engineering education, Electrical engineering, Reliability theory, Reliability engineering, Laboratories, Test facilities. Abstract: Undergraduate electromagnetic field courses entail significant teaching and learning challenges. The use of simulation technologies in these courses can be an effective teaching strategy if designed properly. An assessment-based approach for identifying difficult concepts to incorporate into simulation-oriented learning is investigated. The potential benefits of the approach are illustrated with a case study. |
9,242 | Please write an abstract with title: Ignition Energy Discharge of Oscillating Plasma Waveforms Under Atmospheric Conditions, and key words: Plasmas, Discharges (electric), Ignition, Plasma measurements, Voltage measurement, Current measurement, Engines. Abstract: Oscillating plasma ignition is a promising technique to produce larger initial ignition volume. In this study, an energy waveform analysis of oscillating plasma discharge is investigated. To suffice the industrial applications, the challenges of plasma generation and control platforms are first discussed in this work. A flexible modulation for oscillating plasma generation is established, with the measurements of discharge voltage, secondary current, and discharge current. The phase difference between voltage and current is a critical effect on the energy waveform of oscillating plasma. In relevance to the command pulse train, the energy waveforms corresponding to various plasma discharging events are analyzed, which include normal, arc, and void cases. High-speed imaging, simultaneous with the electrical waveform measurements, is applied to record the plasma formation. Under elevated background pressures, the ignition volume of oscillating plasma is suppressed, and fewer plasma streamers can be observed. The prolonged duration and increased voltage consistently demonstrated positive impacts on flame propagation. This research added a foundation for the plasma diagnostics under engine-like conditions with variations of pressure, temperature, gas composition, and flow pattern. |
9,243 | Please write an abstract with title: Optimal Non-Coherent Detector for Ambient Backscatter Communication System, and key words: Detectors, Radio frequency, Backscatter, Probability density function, RF signals, Channel estimation. Abstract: The joint probability density function (pdf) of the received signal of an ambient backscatter communication system is derived, assuming that on-off keying (OOK) is performed at the tag to form non-return to zero (NRZ) line codes, and that the ambient radio frequency (RF) signal is white Gaussian. The pdf of the received signal is then utilized to design two different types of non-coherent detectors. The first detector directly uses the received signal to perform a hypothesis test. The second detector first estimates the channel based on the observed signal and then performs the hypothesis test. Test statistics and the optimal decision threshold of the detectors are derived. The energy detector is shown to be an approximation of the second detector. For cases where the reader is able to avoid or cancel the direct interference from the RF source (e.g., through successive interference cancellation), a third detector is given as a special case of the first detector. Numerical results show that the first detector outperforms the second detector, although the second detector is computationally simpler. |
9,244 | Please write an abstract with title: Distribution Network Reconfiguration to Increase Photovoltaic Hosting Capacity, and key words: Photovoltaic systems, Uncertainty, Systems operation, System performance, Stochastic processes, Distribution networks, Topology. Abstract: A stochastic model is developed for analyzing the impact of network reconfiguration on improving photovoltaic hosting capacity (PVHC) of distribution networks. System voltage is used as the criterion to determine the PVHC of the network. The distribution network reconfiguration is modeled as an optimization problem to minimize voltage violations associated with increasing solar penetration in the network. The proposed methodology is evaluated in a three-phase, unbalanced, IEEE 37-node distribution test system. The effect of optimal reconfiguration on PV deployments in specific locations is also investigated. Results show that network reconfiguration could significantly improve PVHC, especially when PV units are located nearer to feeder ends and tie switches. |
9,245 | Please write an abstract with title: The design of peak-constrained least squares FIR filters with low-complexity finite-precision coefficients, and key words: Finite impulse response filter, Least squares methods, IIR filters, Digital filters, Circuits, Signal processing, Adaptive signal processing, Nonlinear filters, Attenuation. Abstract: A method for the design of peak-constrained least squares (PCLS) finite-impulse response (FIR) digital filters with low-complexity finite-precision coefficients (FPC) based on Adams' optimality criterion and an efficient local search is presented. Simple quantization of the infinite precision coefficients typically leads to filter designs which fail to meet the frequency response, passband to stopband energy ratio (PSR) and coefficient complexity (number of coefficient adders and subtractors) specifications. It is shown that it is possible to design a filter with an acceptable PSR that meets the frequency response specification while using a reduced number of adders and subtractors. |
9,246 | Please write an abstract with title: Fast Structural Representation and Structure-aware Loop Closing for Visual SLAM, and key words: Point cloud compression, Visualization, Simultaneous localization and mapping, Laser radar, Three-dimensional displays, Harmonic analysis, Robustness. Abstract: Perceptual Aliasing is one of the main problems in simultaneous localization and mapping (SLAM). Wrong associations between different places may lead to failure of the whole map. Research on structure information is rarely investigated among existing solutions to this problem. In cases of visual SLAM without sensors, such as LiDAR or Inertial Measurement Unit (IMU), structure information can rarely be obtained due to the sparsity of 3D points, which also makes structure analysis complex. This study provides a spherical harmonics (SH) based fast structural representation (SH-FS) in visual SLAM using sparse point clouds, which extracts the structure information from sparse points into single vector. SH-FS was applied in conventional feature-based loop closing process. Furthermore, a structure-aware loop closing method in visual SLAM was proposed to improve the robustness of SLAM systems. Moreover, our methods show a favorable performance in extensive experiments on different large-scale real world datasets. |
9,247 | Please write an abstract with title: Feature Extraction and Deep Neural Network Method Based Research on Cognitive Law of Students in Reading Comprehension in Chinese, and key words: Machine Learning, Decision Tree, Deep Neural Network (DNN), students' cognitive law, text feature extraction. Abstract: The problem of students' cognitive differences in reading comprehension in Chinese was modeled as a binary classification problem in Machine Learning. The average score of the student group in reading comprehension was normalized and binarized to obtain the difficulty label as the dependent variable for the study. Reading comprehension was affected by the genre of the article, the number of words, the number of sentences, the average number of Chinese characters contained in each sentence, the proportion of rare characters, and so on. These features were selected as independent variables for this study. Based on the Decision Tree (DT) method and the Deep Neural Network (DNN) method, two classification models were constructed. The F1 score was 82.3 and 86.7%, respectively, for the two methods with high accuracy. Although the accuracy of the DT model was slightly lower, the model was more interpretable. The result showed the pictorial features of the difficulty in reading comprehension in Chinese for teaching. |
9,248 | Please write an abstract with title: Issues in the convergence of control with communication and computing: proliferation, architecture, design, services, and middleware, and key words: Convergence, Communication system control, Computer architecture, Middleware, Actuators, Control systems, Contracts, Sensor systems, Wireless sensor networks, Information technology. Abstract: We anticipate that a possible next phase in the information technology revolution could be the convergence of control, i.e., sensing and actuation, with communication and computing. We address the broad set of issues that we believe to be important to the design, implementation, and proliferation of such systems. In particular, we expound on the topics of the architecture of such systems, methodologies for design, distributed time, services, and middleware. We describe our efforts in the Convergence Lab at the University of Illinois with respect to each of these topics. |
9,249 | Please write an abstract with title: An Effective Method for Lane Detection in Complex Situations, and key words: Deep learning, Lane detection, Image edge detection, Fitting, Transforms, Complexity theory, Next generation networking. Abstract: It is difficult to extract the lane lines accurately in the current auxiliary driving system due to the complexity of the driving environment. In this paper, a new detection method which provides an improved accuracy is proposed. Firstly, a deep learning network of the Unet is adopted to get the potential lane lines. Secondly, the Canny edge detection and Hough transform are used to fit the vanishing point. Thirdly, the position of the vanishing point is used to segment the region of interest (ROI). Finally, the slope of the lines and the relationship between front and back frames in the video are used to select the lane lines. The experimental results show the effectiveness of the proposed method. |
9,250 | Please write an abstract with title: A discrete-time model for spatio-temporally correlated MIMO WSSUS multipath channels, and key words: MIMO, Multipath channels, Receiving antennas, Rayleigh channels, Fading, Filters, Transmitting antennas, Wideband, Rayleigh scattering, Statistical analysis. Abstract: In this paper, a statistical discrete-time model is proposed for simulating wideband MIMO channels which experience spatially and temporally correlated, widesense stationary uncorrelated scattering (WSSUS) multipath Rayleigh fading. A new method is also presented to efficiently generate the correlated MIMO channel coefficients, which can be used for accurate simulation of physical continuous-time MIMO channel. The statistic accuracy of the discrete-time MIMO channel model is rigorously verified through theoretical analysis and extensive simulations in different criteria. |
9,251 | Please write an abstract with title: Fiscalization Instruments and Concepts for Digital Economy Enhancement, and key words: Electrical engineering, Smart cities, Instruments, Smart contracts, Process control, Software, Hardware. Abstract: This article explores modern fiscal instruments and their use as an integrated framework in the digital economy focused on efficiency and interoperability improvement. An overview of modern research in the field of the fiscalization process is presented. The types of fiscal instruments are analysed. A new concept of the single fiscal framework is proposed and described. As a result of the study, the main recommendations for fiscalization process efficiency growth are offered and introduced. |
9,252 | Please write an abstract with title: A novel framework for object removal from digital photograph, and key words: Image color analysis, Filling, Digital images, Interpolation, Image texture analysis, Fault detection, Image sampling, Image segmentation, Switches, Multimedia communication. Abstract: This work aims for a novel function for smart camera-redundant object removal from digital photograph. The proposed novel framework can fill the left lacuna region in the digital image. In previous related researches, texture synthesis and image inpainting construct the fundamentals of filling the lost image region. Texture synthesis can be used to fill the large hole of input texture, while image inpainting can be used to repair the small image gaps. In this paper, we propose an object removal framework by the sub-patch texture synthesis algorithm and weighted interpolation method with automatic repainting mechanism. In the filling process, the color distribution analysis is used to choose different methods. The exhaustive computation time is reduced by the weighted interpolation method. In order to repaint the faulty texture region intelligently, we use the color ratio gradients to detect the synthesized artifact region. The automatic artifact detection can lead repainting the faulty region without user intervention. The proposed algorithm can achieve better performance with seamless output images. The regular computation is also suitable for hardware architecture different from previous existing algorithms. |
9,253 | Please write an abstract with title: Fast error recovery algorithm for Internet video using feedback channel and multi-reference frame, and key words: Internet, Feedback, Video compression, Robustness, Resilience, Propagation losses, Video coding, Enterprise resource planning, Image communication, Information processing. Abstract: Hybrid compressed video is very vulnerable for packet loss when transmitted over Internet. Feedback channel is very useful to combat error propagation. Multi-reference frame is another useful tool to enhance both coding efficiency and robustness. In this paper, we propose an algorithm which combines feedback channel and multi-reference frame. Both theoretical analysis and experimental results show that our scheme can best utilize the feedback message to recover rapidly from packet loss. No additional delay is incurred and no coding efficiency loss is penalized. |
9,254 | Please write an abstract with title: Thick and thin film p-type conducting perovskite hydrocarbon sensors - a comparative study, and key words: Thin film sensors, Hydrocarbons, Gas detectors, Thick film sensors, Temperature sensors, Strontium, Titanium compounds, Iron, Temperature distribution, Thick films. Abstract: Hydrocarbon sensitivity of a series of p-type conducting strontium titanate-ferrate, Sr(Ti/sub 1-x/Fe/sub x/)O/sub 3-/spl delta// conductometric sensors was investigated It was shown that in the temperature range between 350/spl deg/C and 450/spl deg/C, the resistance of thick film and thin film devices changes considerably in the presence of propane. The sensor response is rapid and reversible. However, cross interference experiments show a different behaviour of thick and thin film sensors when exposed to hydrogen. A model for this behaviour based on differential gas diffusion into the sensor material is proposed. |
9,255 | Please write an abstract with title: Violation Probability of Age of Information in a Multi-Source Status Update System, and key words: Closed-form solutions, Probability density function, Information age, Stability analysis, Real-time systems, Internet of Things, Numerical stability. Abstract: In the ever more real-time applications in Internet of Things (IoT), age of information (AoI) is usually applied to analyze system timeliness. The violation probability and distribution of AoI are sometimes alternatives to the average AoI since they are more practical for stricter timeliness requirements, especially when the AoI fluctuates greatly. This paper investigates the timeliness of a real-time IoT based multi-source system, which is abstracted as a multi-source M/M/1/1 bufferless preemptive queue. The violation probability and probability density function of the per-stream AoI are derived in closed form. It is proved that the violation probability and stability of per-stream AoI monotonically decrease with the arrival rate of the corresponding source. Numerical results verify the correctness of theoretical analyses. |
9,256 | Please write an abstract with title: HID: The Hybrid Image Decomposition Model for MRI and CT Fusion, and key words: Transforms, Magnetic resonance imaging, Computed tomography, Tensors, Image fusion, Feature extraction, Medical diagnostic imaging. Abstract: Multimodal medical image fusion can combine salient information from different source images of the same part and reduce the redundancy of information. In this paper, an efficient hybrid image decomposition (HID) method is proposed. It combines the advantages of spatial domain and transform domain methods and breaks through the limitations of the algorithms based on single category features. The accurate separation of base layer and texture details is conducive to the better effect of the fusion rules. First, the source anatomical images are decomposed into a series of high frequencies and a low frequency via nonsubsampled shearlet transform (NSST). Second, the low frequency is further decomposed using the designed optimization model based on structural similarity and structure tensor to get an energy texture layer and a base layer. Then, the modified choosing maximum (MCM) is designed to fuse base layers. The sum of modified Laplacian (SML) is used to fuse high frequencies and energy texture layers. Finally, the fused low frequency can be obtained by adding fused energy texture layer and base layer. And the fused image is reconstructed by the inverse NSST. The superiority of the proposed method is verified by amounts of experiments on 50 pairs of magnetic resonance imaging (MRI) images and computed tomography (CT) images and others, and compared with 12 state-of-the-art medical image fusion methods. It is demonstrated that the proposed hybrid decomposition model has a better ability to extract texture information than conventional ones. |
9,257 | Please write an abstract with title: FraudTrip: Taxi Fraudulent Trip Detection From Corresponding Trajectories, and key words: Public transportation, Trajectory, Anomaly detection, Feature extraction, Clustering algorithms, Hidden Markov models, Urban areas. Abstract: A passenger is overcharged by the taxi driver is one common type of fraudulent trip, and it brings negative impacts to modern cities. Most existing fraudulent trip detection works rely on the assumption that the trip is correctly recorded by the taximeter. However, there are many taxi drivers in China carrying passengers without activating the taximeter, especially when the taxi driver is trying to overcharge the passengers. Hence, existing detection methods cannot be directly applied to such real-world scenario. In this article, we propose a system, called “FraudTrip,” which detects “unmetered” taxi trips based on a novel fraud detection algorithm and a heuristic maximum fraudulent trajectory construction algorithm. Based on the experiments on both synthetic and real-world trajectory data sets, FraudTrip can effectively and efficiently detect fraudulent trips without the help of taximeters. |
9,258 | Please write an abstract with title: Robust Image Wafer Inspection, and key words: Image segmentation, Image registration, Layout, Very large scale integration, Inspection, Tools, Topology. Abstract: This paper presents a deep improvement of template matching technique for detecting defects in VLSI, very large-scale integration, wafer images. This method is more robust to the large device size, distortion due to image acquisition and wafer rotations. Image registration includes several steps. A golden template of the patterned wafer image under inspection can be obtained from the wafer image itself mixed to the VLSI design layout. A mapping between physical space and pixel space is needed. In addition, a more robust topology based on template matching is applied for a more accurate alignment between wafer device and template. Finally, a segmented comparison is used for finding out possible defects. A comparison between the results of the proposed method and the previous template matching technique is presented. |
9,259 | Please write an abstract with title: IAS’2019 Cryptographic Protocol Allowing to Protect the Key in the Open Communication Channel, and key words: Cryptography, Cryptographic protocols, Authentication, Communication channels. Abstract: The proposed work considers the development of the cryptographic protocol IAS2019, which allows you to protect the public key in an open communication channel. The advantage of this protocol is that it can be integrated with other cryptographic protocols, thereby increasing their security properties, and also has a higher level of security compared to foreign counterparts. |
9,260 | Please write an abstract with title: On using reputations in ad hoc networks to counter malicious nodes, and key words: Intelligent networks, Ad hoc networks, Counting circuits, Relays, Throughput, Mobile ad hoc networks, Routing protocols, Computer science, History, Costs. Abstract: Nodes in mobile ad hoc networks have a limited transmission range. Hence the nodes expect their neighbors to relay packets meant for far off destinations. These networks are based on the fundamental assumption that if a node promises to relay a packet, it relays it and does not cheat. This assumption becomes invalid when the nodes in the network have tangential or contradictory goals. The reputations of the nodes, based on their past history of relaying packets, can be used by their neighbors to ensure that the packet is relayed by the node. This paper introduces a reputation scheme for ad hoc networks. Instead of choosing the shortest path to the destination, the source node chooses a path whose next hop node has the highest reputation. This policy, when used recursively, in the presence of 40% malicious nodes, improves the throughput of the system to 65%, from 22 % throughput provided by AODV. This improvement is obtained at the cost of a higher number of route discoveries with a minimal increase in the average hop length according S. Bansal and M. Baker (2003). |
9,261 | Please write an abstract with title: Virtual sensor design for coating thickness estimation in a hot dip galvanising line based on interpolated SOM local models, and key words: Coatings, Electronics packaging, Galvanizing, Zinc, Steel, Strips, Lead compounds, Neural networks, Modems, Corrosion. Abstract: The galvanising process is usually complex and difficult to model. However, as a result of production requirements this process usually works on a reduced set of working points leading to process data with a cluster structure. An accurate description of process data can be given at a low computational cost by specifically assigning a local model to each cluster in process data space. This paper describes a virtual sensor design for coating thickness estimation in a hot dip galvanising line based on local models using SOM and GRNN neural networks. |
9,262 | Please write an abstract with title: A Dual-Tone Multifrequency Receiver Using Synchronous Additions and Subtractions, and key words: Synthetic aperture sonar, Sampling methods, Filters, Detection algorithms, Frequency, Signal detection, Pulse generation, Microcomputers, Hardware, Signal to noise ratio. Abstract: This paper describes a new detection algorithm for a dualtone multifrequency (DTMF) signal. The new algorithm basically uses only additions and subtractions but no multiplications. A signaling tone can be detected by sampling an input signal at four times each frequency involved in a signaling tone and accumulating these sampled values synchronously by additions and subtractions. This algorithm is referred to as the synchronous additions and subtractions (SAS) method. Many conventional methods have used various types of filters to detect signaling tones. In the SAS method in which the design of filters is unnecessary, only the generation of sampling pulses is required, and main operations are additions and subtractions. These features are useful to implement flexible receivers and various types of receivers. The simplicity of the SAS method is demonstrated by the implementation of a DTMF receiver using a conventional 8-bit microcomputer without any special hardware. The minimum signal-to-noise ratio is 5.7 dB when the receiver operates for the signaling tones to be accepted. Four easily measurable parameters are used to distinguish signaling tones from noise inputs. Only two false detections occurred for severe noise inputs of thirty hours. |
9,263 | Please write an abstract with title: A subworld-parallel multiplication and sum-of-squares unit, and key words: Digital signal processing, Delay estimation, Very large scale integration, Digital signal processors, Signal mapping, Hardware, Signal design, Equations, Computer Society. Abstract: Several recent digital signal processors, multimedia processors, and general-purpose processors with multimedia extensions support subword parallelism. With subword parallelism, each operand is partitioned into multiple lower-precision operands, called subwords. A single subword-parallel instruction performs the same operation on multiple sets of subwords in parallel. This paper presents the design of a subword-parallel multiplication and sum-of-squares unit (SPMSSU). The SPMSSU uses novel subword partitioning and partial product mapping techniques to perform one 32-bit, two 16-bit, or four 8-bit multiplications or sum-of-squares operations in parallel. The SPMSSU efficiently performs subword-parallel operations with area and delay estimates that are comparable to those of a conventional 32-bit multiplier. |
9,264 | Please write an abstract with title: A new convex edge-preserving median prior with applications to tomography, and key words: Tomography, Materials requirements planning, Image reconstruction, Iterative algorithms, Radiology, Biomedical engineering, Bayesian methods, Minimization methods, Image quality, Spatial resolution. Abstract: In a Bayesian tomographic maximum a posteriori (MAP) reconstruction, an estimate of the object f is computed by iteratively minimizing an objective function that typically comprises the sum of a log-likelihood (data consistency) term and prior (or penalty) term. The prior can be used to stabilize the solution and to also impose spatial properties on the solution. One such property, preservation of edges and locally monotonic regions, is captured by the well-known median root prior (MRP), an empirical method that has been applied to emission and transmission tomography. We propose an entirely new class of convex priors that depends on f and also on m, an auxiliary field in register with f. We specialize this class to our median prior (MP). The approximate action of the median prior is to draw, at each iteration, an object voxel toward its own local median. This action is similar to that of MRP and results in solutions that impose the same sorts of object properties as does MRP. Our MAP method is not empirical, since the problem is stated completely as the minimization of a joint (on f and m) objective. We propose an alternating algorithm to compute the joint MAP solution and apply this to emission tomography, showing that the reconstructions are qualitatively similar to those obtained using MRP. |
9,265 | Please write an abstract with title: Chinese Foreign Direct Investments in the EU: Challenges and Solutions, and key words: Investment, National security, Conferences, Wireless communication, Smart grids, Industries, Organizations. Abstract: This study focuses on an analysis of Chinese investments in Europe. Special attention is being given to identifying the challenges that Chinese investors face while investing in the EU. The research describes the main parts of the trade and investment relationships between the EU and China, focuses in-depth on the investment part. An important part of the research aimed at the discussion of Chinese FDI in the EU. It provides information about the investment flows, industries for investments, receiver states, and forms of investments. Special attention in the research is given to the reason why the EU is postponing the signing of the bilateral investment agreement between China and the EU and what is behind it. The main method of research is comparative analysis. Based on the analyzes of the data and publications, the results of the research indicate the five main challenges. Such challenges as political opposition, national security concerns, style of managing a company, difficulties with regulations, and FDI control - create an additional limitation for Chinese companies in the EU. EU companies in China still have many more regulations and restrictions than Chinese companies in the EU. |
9,266 | Please write an abstract with title: High-performance 1.55 /spl mu/m resonant cavity enhanced photodetector, and key words: Resonance, Optical receivers, Optical filters, Optical noise, Photodetectors, Optical sensors, Active filters, Optical fiber devices, Tunable circuits and devices, Vertical cavity surface emitting lasers. Abstract: In conclusion, we have demonstrated highspeed, and high-efficiency resonant cavity enhanced (RCE) InGaAs based p-i-n photodetectors. A peak quantum efficiency of 66% was measured along with 31 GHz bandwidth which corresponds to 20 GHz bandwidth-efficiency product. The photoresponse was linear up to 6 mW optical power, where the devices exhibited 5 mA photocurrent. |
9,267 | Please write an abstract with title: A New Exoskeleton Robot for Human Motion Assistance, and key words: Analytical models, Computational modeling, Exoskeletons, Dynamics, Kinematics, Three-dimensional printing, Software. Abstract: This paper presents studies on the kinematics and dynamics of a new robotic system of the exoskeleton type to assist human locomotion. Based on previous achievements, we designed an original robotic system solution. Based on this structural solution, we created a virtual model using SolidWorks computerized design software. This virtual model is used for two purposes, namely in the first stage we will perform a motion simulation using the software of dynamic analysis of mobile mechanical systems ADAMS_View and then based on the virtual construction prototype we will manufacture the robotic system by classical techniques and additive manufacturing. The results presented in the paper prove the technical feasibility of the proposed solution for assisting the locomotion of people with disabilities. |
9,268 | Please write an abstract with title: Experimental and theoretical analyses of GAWBS depolarization noise in digital coherent transmission, and key words: guided acoustic-wave Brillouin scattering, polarization-crosstalk, digital coherent transmission. Abstract: We present experimentally and analytically the intensity noise effect resulting from depolarization caused by guided acoustic-wave Brillouin scattering (GAWBS) in a digital coherent transmission. The TR2m GAWBS modes produce polarization-crosstalk of −42.3∼-37.9 dB in a 150∼160 km fibre, and this is detrimental to long-haul transmission. |
9,269 | Please write an abstract with title: A new approach to gain-bandwidth problems, and key words: Impedance, Equalizers, Microwave amplifiers, Frequency, Topology, Transfer functions, Arithmetic, Diodes, Reflection, Microwave FETs. Abstract: A new idea for treating the broad-band matching of an arbitrary load to a resistive generator leads to a simple technique for the design of a lossless 2-port equalizer. The method is a numerical one, and only utilizes real frequency (e.g., experimental) load impedance data. No model or analytic impedance function for the load is necessary. Nor is the equalizer topology or analytic form of the system transfer function assumed. The arithmetic is well conditioned and the intricacies of gainbandwidth theory are bypassed. An example comparing the method with analytic gain-bandwidth theory is given. Two examples proceeding directly from experimental data are presented. One is the broad banding of a microwave avalanche diode reflection amplifier. The other is the gainbandwidth equalization of a microwave FET amplifier for gain taper and impedance mismatch. |
9,270 | Please write an abstract with title: On connectivity of flying ad hoc networks in the presence of ground terminal, and key words: Interference, Unmanned aerial vehicles, Three-dimensional displays, Receivers, Power control, Signal to noise ratio, Aggregates. Abstract: The Unmanned Aerial Vehicle (UAV) technologies are envisioned to play an important role in the era of Air-Space-Ground integrated networks. In this paper, we investigate the connectivity of a Flying Ad hoc Network (FANET) in the presence of a ground-based terminal. In particular, the connected probability of the UAV-to-UAV (U2U) link as well as that of the UAV-to-Ground (U2G) link in a three dimensional (3D) space are analyzed. Furthermore, to mitigate the aggregate interference from UAV individuals, a priority based power control scheme is implemented for enhancing the connectivity of both U2U and U2G links. Numerical results illustrate the effectiveness of the proposed analysis. |
9,271 | Please write an abstract with title: Robust Path Following Control of Underactuated Unmanned Surface Vehicle With Disturbances and Input Saturation, and key words: Vehicle dynamics, Sea surface, Adaptive systems, Navigation, Uncertainty, Trajectory, Surges. Abstract: This paper focuses on the accurate path following problem for an underactuated unmanned surface vehicle with uncertainties and environment disturbances. The proposed scheme can be divided into guidance loop and control loop: in the guidance loop, the proposed guidance law is utilized to calculate the desired yaw angle, as well as estimating unknown currents and sideslip angle simultaneously; in the control loop, a novel robust path following control law is developed by enhanced trajectory linearization control (TLC) technology, nonlinear tracking differentiator (NTD), sigmoid function based disturbance observer (SDO) and auxiliary dynamic system. The enhanced TLC is used as the main control framework to design the concise yaw rate and surge speed control laws, which makes the designed control law be simple and easy to implement in practice. SDO and auxiliary dynamic system are adopted to deal with unknown disturbances and input saturation, respectively. Meanwhile, NTD can provide an ideal differential and filtering effect. Theoretical analysis indicates that all the signals in the entire system are uniformly ultimately bounded. Finally, a comparative simulation substantiates the availability and superiority of the proposed scheme. |
9,272 | Please write an abstract with title: Pricing for enabling forwarding in self-configuring ad hoc networks, and key words: Pricing, Ad hoc networks, Costs, Algorithm design and analysis, Geometry, Aggregates, Relays, Mobile ad hoc networks, Wireless networks, Microeconomics. Abstract: The assumption that all nodes cooperate to relay packets for each other may not be realistic for commercial wireless ad hoc networks. An autonomous (selfish) node in a wireless network has two disincentives for forwarding for others: energy expenditure (real cost) and possible delays for its own data (opportunity cost). We introduce a mechanism that "fosters cooperation through bribery" in the context of forwarding in ad hoc networks. Using a microeconomic framework based on game theory, we design and analyze a pricing algorithm that encourages forwarding among autonomous nodes by reimbursing forwarding. Taking a joint network-centric and user-centric approach, the revenue maximizing network and utility (measured in bits-per-Joule) maximizing nodes interact through prices for channel use, reimbursements for forwarding, transmitter power control, as well as forwarding and destination preferences. In a three-node (two-sources, one-access-point) network, the network converges to an architecture that induces forwarding only when the network geometries are such that forwarding is likely to increase individual benefits (network revenue and node utilities). For other geometries, the network converges to architectures that do not favor forwarding. We then generalize to a multinode network, where it is seen that the nodes' willingness to forward decrease for large ratios of the average internodal distance to the smallest distance between the access point and any source node. Pricing with reimbursement generally improves the network aggregate utility (or aggregate bits-per-Joule), as well as utilities and revenue compared with the corresponding pricing algorithm without reimbursement. |
9,273 | Please write an abstract with title: Finite element analysis of inrush currents in three-phase transformers, and key words: Finite element methods, Surges, Phase transformers, Magnetic analysis, Magnetic flux, Saturation magnetization, Current measurement, Circuits, Transformer cores, Poisson equations. Abstract: A new method for analyzing inrush currents in transformers is conceived by modifying the finite element method. Using this method, the detailed behaviour of the transient flux can be analyzed taking into account the residual magnetism and three-dimensional leakage flux. The new method is especially effective in the calculation of the inrush currents of three-phase transformers. The inrush currents are examined experimentally by using a new method for measuring the residual magnetism and an equipment which controls switching angles. |
9,274 | Please write an abstract with title: Assessing the impact of substation-related outages on the network reliability, and key words: Substations, Power system reliability, Power transmission lines, Distributed parameter circuits, Power system simulation, Power system modeling, Equipment failure, Load flow analysis, Power system analysis computing, Power grids. Abstract: This paper presents a modern probabilistic reliability assessment method that includes the modeling of substation configurations and simulation of breaker and switching operations in response to equipment failures in the evaluation of transmission grid reliability. Such features are not generally available in conventional power flow analysis tools. The method has been applied to study two 500 kV substations in the East China power system as part of the development of along-term transmission expansion plan for the EHV power grid. The first stage of the analysis is to assess the impact of the substation layouts on transmission component outages. Reliability models for the substations, including detailed bus-breaker arrangements, are developed. Failures of substation components, such as in-coming and out-going transmission lines, transformers, bus sections, circuit breakers and disconnect switches, are represented by their respective outage statistics. A failure mode and effect analysis of each substation is then performed and reliability indices consisting of frequencies and durations of events leading to outages of multiple transmission lines are calculated. Next, the substation-related transmission line outages are input to a power flow model for assessing their impact on,the reliability of the overall grid. This paper contributes to the area of transmission planning studies using probabilistic reliability methods. |
9,275 | Please write an abstract with title: An Easy-implemented Optimization Method of Trajectory Planning Based on Polynomial Interpolation, and key words: Interpolation, Actuators, Trajectory planning, Simulation, Optimization methods, Kinematics, Manipulators. Abstract: Firstly, the forward kinematics and inverse kinematics of a five axis manipulator are deduced. Secondly, an easy-implemented optimization method of trajectory planning based on seventh order polynomial interpolation is proposed. The proposed optimization method can capture the time optimal trajectory, while the actuators specifications including speed, acceleration of motor can be guaranteed as well. Finally, simulation results validate the effectiveness and efficiency of proposed optimization method. The research provides an insight for the application of trajectory optimization on the controller with low computing capability and real-time requirement. |
9,276 | Please write an abstract with title: An Improved Fourier-Series-Based IGBT Model by Mitigating the Effect of Gibbs Phenomenon at Turn on, and key words: Mathematical model, Insulated gate bipolar transistors, Load modeling, Integrated circuit modeling, Fourier series, Switches, Predictive models. Abstract: The Fourier-series-based insulated-gate bipolar transistor (IGBT) model has been very effective in simulating its switching behaviors and meanwhile, reflecting carrier dynamics. However, in turn-on process, such a model has difficulty in distinguishing the boundary between undepleted area and depletion layer of the drift region due to Gibbs phenomenon and therefore, cannot accurately describe the carrier behavior of carrier storage region (CSR). In this study, the Fourier-series-based model is modified to determine the more precise depletion layer edge for turn on. This is achieved by utilizing the actual characteristics of the carrier concentration gradient at the edge of CSR in turn-on process. Such a modified model is implemented in MATLAB/Simulink and it can better reflect the depletion layer and simulate the distribution of both the carrier concentration and electric field during turn-on process. It corrects the unreasonable voltage tail caused by the error of drift region voltage calculation in previous models. The results of the proposed model under both the resistive load and inductive load are in good agreement with TCAD. Such a modified model can more accurately simulate both carrier dynamics and switching behaviors in the turn-on process. |
9,277 | Please write an abstract with title: Improvement of robustness against write disturbance by novel cell design for high density MRAM, and key words: Robustness, Magnetic switching, Thermal stability, Magnetic tunneling, Robust stability, Thermal factors, Shape, Magnetization, Magnetic fields, Switches. Abstract: A new bit cell designed to have an excellent astroid is presented from the viewpoints of both theory and experiment. The switching mechanism is unique. The robustness against the disturbance of half-selected bits is improved. Its excellent astroid improves thermal stability and has the potential to achieve extremely high density magnetoresistive random access memory (MRAM). |
9,278 | Please write an abstract with title: Scene Aware Semantic Crack Segmentation from Oblique Drone Imagery, and key words: Degradation, Image segmentation, Roads, Semantics, Buildings, Feature extraction, Computational efficiency. Abstract: Cracks are one of the earliest indications of structure degradation relevant to buildings, roads, or widgets. How-ever, false alarms and misjudgments are easy to occur when segmenting cracks from large scenes. Thus, robustly detecting and precisely segmenting non-salient cracks are always difficult, especially for large oblique drone images. To handle the problems above, we propose a novel scene-aware semantic crack segmentation model, M-CrackNet. The contributions of the proposed algorithm can be mainly concluded as: (1) it decomposes the task of building crack detection into crack related scene activation and semantic crack segmentation so that the method can be transferred to other scenes with cracks; (2) by parallelly processing images with two decomposed modules, the computational cost has been largely reduced. Meanwhile, most of the false alarms and misjudgments are avoided, enhancing the accuracy of semantic crack segmentation. The effectiveness of the proposed method is evaluated upon CPRI, CrackForest, and the CrackODI proposed in this paper. Compared with the state-of-the-art methods, the mIoU and BFScore of the M-CrackNet are improved by 0.64%∼8.01% and 3.12%∼33.29% on datasets, which demonstrate that the M-CrackNet is effective for semantic crack segmentation. |
9,279 | Please write an abstract with title: Chance Constrained Covariance Control for Linear Stochastic Systems With Output Feedback, and key words: Stochastic processes, Vehicle dynamics, Noise measurement, Estimation error, Stochastic systems, Standards, Kalman filters. Abstract: We consider the problem of steering, via out-put feedback, the state distribution of a discrete-time, linear stochastic system from an initial Gaussian distribution to a terminal Gaussian distribution with prescribed mean and max-imum covariance, subject to probabilistic path constraints on the state. The filtered state is obtained via a Kalman filter, and the problem is formulated as a deterministic convex program in terms of the distribution of the filtered state. We observe that, in the presence of constraints on the state covariance, and in contrast to classical Linear Quadratic Gaussian (LQG) control, the optimal feedback control depends on both the process noise and the observation model. The effectiveness of the proposed approach is verified using a numerical example. |
9,280 | Please write an abstract with title: Design of degenerate observers, and key words: Observers, Vectors, Observability, State estimation, Linear systems, Yield estimation, Differential equations. Abstract: A procedure [1] for the design of an observer of reduced order, with arbitrary dynamics, to provide an estimate of a single linear functional of the state vector of a linear system, is extended to the case in which a number of linear functionals are required. |
9,281 | Please write an abstract with title: Transient overvoltage studies of AC filter systems for HDVC treminals, and key words: Voltage control, Reactive power, Harmonic filters, Switching converters, Switching circuits, Circuit simulation, Virtual manufacturing, Switched capacitor circuits, Inductors, Analog-digital conversion. Abstract: Many ac filter configurations have been implemented on various hvdc installations thoughtout the world. This paper attempts to make an initial documentation of the transient overvoltage studies performed during the various design stages of the ac filters for the Sylmar Terminal of the Pacific Intertie. Included in the paper are the results of these studies made to determine the transient voltage levels. The application of arresters is considered utilizing two application criteria based on the duty the arresters would experience in various locations for the particular filter configurations. |
9,282 | Please write an abstract with title: Iterative, Deep, and Unsupervised Synthetic Aperture Sonar Image Segmentation, and key words: Training, Image segmentation, Oceans, Semantics, Training data, Clustering algorithms, Feature extraction. Abstract: Deep learning has not been routinely employed for semantic segmentation of seabed environment for synthetic aperture sonar (SAS) imagery due to the implicit need of abundant training data such methods necessitate. Abundant training data, specifically pixel-level labels for all images, is usually not available for SAS imagery due to the complex logistics (e.g., diver survey, chase boat, precision position information) needed for obtaining accurate ground-truth. Many hand-crafted feature based algorithms have been proposed to segment SAS in an unsupervised fashion. However, there is still room for improvement as the feature extraction step of these methods is fixed. In this work, we present a new iterative unsupervised algorithm for learning deep features for SAS image segmentation. Our proposed algorithm alternates between clustering superpixels and updating the parameters of a convolutional neural network (CNN) so that the feature extraction for image segmentation can be optimized. We demonstrate the efficacy of our method on a realistic benchmark dataset. Our results show that the performance of our proposed method is considerably better than current state-of-the-art methods in SAS image segmentation. |
9,283 | Please write an abstract with title: A caster-wheel-aware MPC-based motion planner for mobile robotics, and key words: Torque, Trajectory tracking, Navigation, Wheels, Robot sensing systems, Planning, Trajectory. Abstract: Differential drive mobile robots often use one or more caster wheels for balance. Caster wheels are appreciated for their ability to turn in any direction almost on the spot, allowing the robot to do the same and thereby greatly simplifying the motion planning and control. However, in aligning the caster wheels to the intended direction of motion they produce a so-called bore torque. As a result, additional motor torque is required to move the robot, which may in some cases exceed the motor capacity or compromise the motion planner's accuracy. Instead of taking a decoupled approach, where the navigation and disturbance rejection algorithms are separated, we propose to embed the caster wheel awareness into the motion planner. To do so, we present a caster-wheel-aware term that is compatible with MPC-based control methods, leveraging the existence of caster wheels in the motion planning stage. As a proof of concept, this term is combined with a model-predictive trajectory tracking controller. Since this method requires knowledge of the caster wheel angle and rolling speed, an observer that estimates these states is also presented. The efficacy of the approach is shown in experiments on an intralogistics robot and compared against a decoupled bore-torque reduction approach and a caster-wheel agnostic controller. Moreover, the experiments show that the presented caster wheel estimator performs sufficiently well and therefore avoids the need for additional sensors. Video: https://youtu.be/NXXZKEZUi30 |
9,284 | Please write an abstract with title: A technique to analize populist discourse : The Peruvian case, and key words: Semantics, Information systems. Abstract: There are different techniques that have been evaluated to identify whether a political discourse is populist or not. This research analyzes the debates in the plenary session of the Peruvian Congress during the first legislature of 2020 using NVivo and clause-based text semantic analysis (CBSTA). It is concluded that this technique allows us to observe that there is no populist discourse in the entire Congress but a partial use of it, more aimed at highlighting the demands of the people. However, there is a populist discourse when addressing some issues and within some political parties when they address certain issues. The use of populist discourse is not constant, it has variations and is applied to some issues more than others. |
9,285 | Please write an abstract with title: Multi-stratification feature selection for diagnostic analysis of Alzheimer's disease, and key words: Neuroimaging, Brain, Magnetic resonance imaging, Digital images, Feature extraction, Alzheimer's disease, Task analysis. Abstract: In current neuroimaging analysis, feature selection majorly focuses on analysis within single brain regions. However, the fact that brain activities are usually associated with multiple brain regions highlights the importance of the multi-brain-region interaction, which is underexplored. To address this challenge, we propose a multi-stratification feature selection framework for analysing multiple brain regions in Magnetic Resonance Imaging (MRI). This framework consists of two major modules: intra-Region of Interest (ROI) module and inter-ROI module. Intra-ROI module selects representative features for each brain region by analysing both of the statistical difference of features and the classifier performance of the candidate subset. Inter-ROI module employs the evaluation function to guide the search, sequentially adding features from brain regions based on the corresponding predictive capacity. Only relevant and maximum joint significance features that improve the evaluation performance would be selected in this module. The proposed framework was validated on the diagnostic task of Alzheimer's disease. T1-MR images were collected from 196 Alzheimer's disease patients and 259 normal control subjects. The experiments demonstrated that the proposed multi-stratification feature selection outperformed the state-of-the-art single-brain-region analysis and the radiomics early integration methods applied to multiple-brain-region, achieving AUC 0.913. |
9,286 | Please write an abstract with title: A CMOS voltage-controlled grounded resistor using a single power supply, and key words: Resistors, Power supplies, Adders, Circuit simulation, Threshold voltage, Low voltage, Signal generators, MOSFET circuits, Power dissipation, Power engineering and energy. Abstract: The paper proposes a voltage-controlled grounded resistor. The principle of the proposed circuit is nonlinearity term cancellation of a MOS operating in the ohmic region. The circuit consists of a nonsaturation-operated MOS transistor and a voltage adder circuit. Its advantage over other grounded resistors is that this circuit uses a single low voltage power supply. Simulation results are carried out by using PSpice. |
9,287 | Please write an abstract with title: Design and control of a 6-DOF high-precision integrated positioner, and key words: Magnetic levitation, Signal resolution, Transmission line matrix methods, Permanent magnet motors, Gravity, Signal design, Digital control, Digital signal processors, Digital signal processing, Aerodynamics. Abstract: This work presents the design and control of a high-precision 6-degree-of-freedom (6-DOF) multi-dimensional positioner. This high-precision positioning system consists of a novel concentrated-field magnet matrix and a triangular single-moving platen that carries three 3-phase permanent-magnet linear levitation motor armatures. With a combination of six independent force components, the moving platen can generate any 6-DOF motion. Three aerostatic bearings are used to provide the suspension force against gravity for the system. We designed and implemented digital lead-lag controllers running on a digital signal processor (DSP). To improve the dynamic performance in the vertical direction, we implemented a controller in the feedback path as well. Currently, the positioner has a position resolution of 20 nm and position noise of 10 nm rms in x and y and 100 nm in z. The angular resolution around the x-, y-, and z-axes is in sub-micron order. The planar travel range is 160 mm /spl times/ 160 mm, and the maximum velocity achieved so far is 0.5 m/s with 5-m/s/sup 2/ acceleration in the y-direction, which is highly suitable for semiconductor manufacturing applications. Several 2-dimensional motion profiles are presented to demonstrate the stage's capability of accurately tracking any extended planar paths. |
9,288 | Please write an abstract with title: Performance evaluation of cyanate ester resin, and key words: System testing, Epoxy resins, Temperature, Insulation testing, Copper, Tensile stress, Manufacturing, Compressive stress, Glass, Geometry. Abstract: Traditional epoxy resin systems have long been used for vacuum impregnation of large electro-magnets. However, the mechanical strength of these systems is disappointingly low when operated at temperatures above about 70/spl deg/C where the failure mechanism is more often by adhesion at the copper interface than by cohesion within the resin. A range of resin systems based on cyanate ester are currently being developed by CTD Inc. which are suitable for vacuum impregnation and may offer advantages over the epoxy resin systems. In order to assess the thermo-mechanical performance of these newly developed materials a programme of testing and evaluation of the basic cyanate ester resin (CTD 403) has been carried out and the results are presented here. |
9,289 | Please write an abstract with title: A Compact Representation of Indoor Trajectories, and key words: Trajectory, Maintenance engineering, Medical services, Receivers, Proposals, Tracking. Abstract: In this article, we present a system that combines indoor positioning with a compression algorithm for trajectories in the context of a nursing home. Our aim is to gather and effectively represent the location of the residents and caregivers along time, while allowing for efficient access to those data. We briefly show the system architecture that enables the automatic tracking of user’s movements and consequently the gathering of their locations. Then, we present indRep, our compact representation to handle positioning data using grammar-based compression, and provide two basic operations that enable pseudorandom access to the data. Finally, we include experiments that show that indRep is competitive with well-known general-purpose compressors in terms of compression effectiveness and also provides fast access to the compressed data. We expect both features would enable exploitation functionalities even in computers with rather low computational resources. |
9,290 | Please write an abstract with title: Trouble with scan, and key words: Built-in self-test, Design for testability, System testing, Circuit testing, Finance, Test pattern generators, Automatic test pattern generation, Automatic testing, Fault detection, Routing. Abstract: The benefits of scan are well known. The intent here is to point out what kind of trouble we have with scan and BIST. The author then argues that functional testing methods might give a better quality if one can afford resources for manual test generation. Scan DFT is based on only two major fault models: stuck-at-fault and transition fault. Beyond these two fault models, the effectiveness of scan DFT is debatable. To achieve the kind of quality level we are looking for, more fault models will need to be applied in order to capture all types of defects. But even if we know how to create additional fault models (other than stuck-at and transition faults), how will we automatically generate test patterns for these additional models? And, how can any test generator or tester handle such a huge test data volume? How are we going to fault isolate these additional defect types?. |
9,291 | Please write an abstract with title: Deploying an e-commerce website using Amazon Web Services, and key words: Servers, Cloud computing, Web services, Operating systems, Informatics, Reliability, Random access memory. Abstract: The main objective of this project is to get a better understanding in how to make a Website using AWS and utilizing different cloud computing services in order to acquire great performance with less cost. Amazon EC2 is used here since it is very popular in providing good cloud computing services. In this report, I'll tell you, step by step, via the procedure of using the AWS Marketplace to provision and produce a new AWS Cloud server. And since AWS offers a Free Tier valid for 12 months, you'll have a lot of time to experiment with your server and Bitnami images without worrying about being billed for usage. |
9,292 | Please write an abstract with title: Recognition of Mild Cognitive Impairment in the Elderly Based on Machine Learning, and key words: Analytical models, Adaptation models, Computational modeling, Senior citizens, Support vector machine classification, Artificial neural networks, Data models. Abstract: As the prodromal stage of Alzheimer's disease, effective recognition of mild cognitive impairment can reduce the prevalence of Alzheimer's disease. At present, most of the research on the recognition of mild cognitive impairment is carried out through biomarkers and neuroimaging, which is not conducive to large-scale analysis and research. Based on neuropsychological evaluation and life habits questionnaires, this article applies machine learning methods to the recognition of mild cognitive impairment and conducts experimental research. A questionnaire survey of the elderly was conducted to obtain raw data, including demographic variables, daily habits and neuropsychological data. Feature selection is carried out through filter screening method and the influence of factors such as lifestyle, physical health and learning ability on the morbidity of mild cognitive impairment is analyzed. The classifier mainly uses three methods: artificial neural network, support vector machine and random forest. The experimental results show that the random forest classification effect is the best and the accuracy rate is as high as 92%. Artificial neural network has strong generalization ability with 91% accuracy rate. Support vector machine has inferior effect. |
9,293 | Please write an abstract with title: Analysis of the prospects for distributed generation (DG) for Colombian electric power sector, and key words: Distributed control, Power generation, Water heating, Cogeneration, Distributed power generation, Standby generators, Reactive power, Power system reliability, Technological innovation, Power system economics. Abstract: The main aim of this paper is to present the results of an analysis of the prospective for the distributed generation (DG) in the Colombian electric power sector applying the Delphi technique. This study helped us understand the expert's opinion directly and systematically on the introduction of the DG in fields like: technology, product innovations, materialization process, effect on the country's political and social situation, economic, technologic and commercial restrictions. The results of this work are intended to provide support for the electric and productive sectors to analyze the feasibility of using the DG in the medium and long term in Colombia, since its application would have a very strong effect on the company's planning and operation activities regarding electric issues. |
9,294 | Please write an abstract with title: Packet acquisition in upstream transmission of the DOCSIS standard, and key words: Frequency estimation, Phase estimation, Timing, Communication cables, Time division multiple access, Phase detection, Phase frequency detector, Standardization, System performance, Computer simulation. Abstract: In upstream transmission of the DOCSIS (data over cable service interface specification) 1.0/1.1 and the TDMA mode of DOCSIS 2.0 standard, a packet begins with a preamble, the length and value of which are programmable by the headend. The acquisition process includes packet detection, symbol timing estimation, carrier frequency offset estimation and carrier phase estimation by means of the preamble so that the following information packet can be correctly demodulated. Methods to solve these tasks are not subject to standardization and are left to the system designer. However, they have a great impact on the system performance and thus are key elements for implementation. We present dedicated algorithms. A specific preamble is created and the corresponding scheme for packet acquisition is described in some detail. The packet detecting algorithm is independent of the carrier and symbol timing. The symbol timing estimate is obtained by using the minimum mean square algorithm regardless of the carrier frequency deviation and carrier phase. Algorithms for estimating the carrier frequency offset and carrier phase are proposed. Computer simulation results are given for all algorithms presented. |
9,295 | Please write an abstract with title: College Students’ Online Behavior Analysis During Epidemic Prevention and Control, and key words: Epidemics, Mechatronics, Education, Prototypes, Lung, Predictive models, Internet. Abstract: During the novel coronavirus pneumonia epidemic prevention and control period, various network applications have increased, resulting in massive network user behavior data in log form. In order to detect the abnormal behavior, K- means clustering algorithm based on Hadoop is used to cluster the user behavior, and the association rules obtained by mining are used to explain the preference of the campus network users on the access. Then, a prototype system of mobile application network behavior analysis is designed and implemented, which supports feature extraction and application network behavior analysis of mobile application network behavior. The results show that the model can effectively improve the efficiency and accuracy of students' online user behavior analysis, and achieve the purpose of accurate prediction. |
9,296 | Please write an abstract with title: Bound Analysis of Number Configuration for Reflecting Elements in IRS-Assisted D2D Communications, and key words: Resource management, Optimization, Device-to-device communication, Transmitters, Three-dimensional displays, Receivers, Upper bound. Abstract: Intelligent reflecting surface (IRS)-assisted communication has emerged as a promising technology for 6G, and has drawn increasing attention in recent years. However, the problem on how to configure the number of reflecting elements has received little attention so far. In this letter, we investigate and analyze the number configuration for IRS-assisted D2D communications, where multiple transmitters send their signals to their corresponding receivers via the IRS. Our goal is to minimize the number of reflecting elements subject to the individual outage performance and the total/individual power consumption constraints. However, the intractable outage performance renders the formulated problem hard to solve. In order to circumvent this problem, we relax the optimization problem and propose two new optimization problems, in which we are able to derive two closed-form expressions for the optimized number of reflecting elements for bound analysis of the original problem. Simulation results demonstrate the derived bounds can be utilized to represent the optimal number configuration under certain noise/power regions or proper placement of the IRS. |
9,297 | Please write an abstract with title: A High-Power Switching Network for a Dual-Mode Antenna, and key words: Switches, Directional couplers, Transmitting antennas, Impedance, Transmitters, Directive antennas, Radio frequency, Bandwidth, Level control, Polarization. Abstract: A novel hybrid switching network is described in which high levels of RF power (2-3 kW) are controlled and switched over an octave bandwidth in low L band by the use of a relatively low-power level switch matrix used in conjunction with a pair of 8.34-dB (nominal) directional couplers and a phasing network. An alternate design to compactly achieve the same results is also described. The device is for use with a switchable (dual-mode) airborne transmitting antenna. Theoretically predicted performance parameters are grapbically presented along with correlated measured data. |
9,298 | Please write an abstract with title: Extending integrated-circuit yield-models to estimate early-life reliability, and key words: Yield estimation, Circuit testing, Semiconductor device modeling, Integrated circuit yield, Integrated circuit reliability, Probes, Integrated circuit modeling, Integrated circuit testing, Manufacturing, Digital integrated circuits. Abstract: The integrated yield-reliability model for integrated circuits allows one to estimate the yield, following both wafer probe and burn-in testing. The model is based on the long observed clustering of defects and the experimentally verified relation between defects causing wafer probe failures, and defects causing infant mortality failures. The 2-parameter negative binomial distribution is used to describe the distribution of defects over a semiconductor wafer. The clustering parameter /spl alpha/, while known to play a key role in accurately determining wafer probe yields, is shown, for the first time, to play a similar role in determining burn-in fall-out. Numerical results indicate that the number of infant mortality failures predicted by the clustering model can differ appreciably from calculations that ignore clustering. This is particularly apparent when wafer probe yields are low, and clustering is high. |
9,299 | Please write an abstract with title: Anti-Gan: Discriminating 3D reconstructed and real faces for robust facial Identity in Anti-spoofing Generator Adversarial Network, and key words: Three-dimensional displays, Face recognition, Feature extraction, Generative adversarial networks, Security, Data mining, Task analysis. Abstract: 3D face reconstruction is an attractive topic in computer vision. We have seen dramatic rise in its development recently. Now the state-of-the-art method can reconstruct a face from a single 2D face image freely, which brings a threat to facial security society. Since they are very similar in feature distributions, an efficient work to discriminate reconstructed face and real face is vital. Since Generative Adversarial Nets (GAN) has been proposed by Ian J. Goodfellow in 2014, it is extensively trained to approximate data distributions of many applications. For its adversarial mechanism, GAN shows a powerful generative ability to get the state of art. Inspired by its adversarial mechanism, we propose a similar framework called Anti-GAN to discriminate an adversarial dataset from real 3D face datasets and reconstructed face datasets. Considering the computation of backpropagation, G and D all adopt convolutional neural network architecture. Additionally, experiments show that Anti-GAN is a powerful way to distinguish real faces and reconstructed faces. At the same time, it can also offer robust features for a facial identity task. |
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