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7,300 | Please write an abstract with title: Joint frame synchronization and frequency offset estimation in OFDM system, and key words: Frequency estimation, Frequency synchronization, OFDM, Wireless communication, Bandwidth, Frequency conversion, Timing, Fading, Intersymbol interference, Digital modulation. Abstract: One new joint frame synchronization and carrier frequency offset estimation method for orthogonal frequency-division multiplexing (OFDM) system is proposed. The same training-symbol-block (TSB) is needed for both frame synchronization and carrier frequency offset estimation. The carrier frequency offset estimation including acquisition and tracking, and acquisition can be further divided into preacquisition and fine acquisition. As soon as frequency offset acquisition finished, timing synchronization is also performed at the same time. The acquisition range is as large as one half of overall signal bandwidth. The theoretical variance error lower bound for our frequency offset tracking algorithm is also derived in this paper. |
7,301 | Please write an abstract with title: Interface disorder of In incorporated AlGaAs/GaAs quantum well grown by molecular beam epitaxy, and key words: Gallium arsenide, Molecular beam epitaxial growth, HEMTs, MODFETs, Photoluminescence, Quantum well lasers, Laser excitation, Spectroscopy, Transmission electron microscopy, Temperature. Abstract: The interface quality plays an important role in novel heterostructure devices such as quantum well lasers and high electron mobility transistors (HEMTs). The AlGaAs/GaAs heterointerface has been extensively investigated by photoluminescence (PL), Photoluminescence excitation spectroscopy (PLE), and transmission electron microscope (TEM) using the interruption and high growth temperature techniques. In this letter, we compare the effect of interface roughness on In incorporated AlGaAs/GaAs quantum wells (QWs) with non In incorporated AlGaAs/GaAs QWs with and without interruption by PL spectra. The schematic structures of the samples grown at 610/spl deg/C are shown. All the excitonic recombination peaks from 77 K related to SQW's are single peaks, which indicate that the lateral size of growth island is not so large as the exciton diameter (/spl sim/150 /spl Aring/). |
7,302 | Please write an abstract with title: A Machine Learning Regression Approach for Throughput Estimation in an IoT Environment, and key words: Measurement, Training, Social computing, Uncertainty, Smart buildings, Linear regression, Quality of service. Abstract: The success of Internet of Things (IoT) has significantly increased the volume of data generated by various smart applications. However, as many of these applications are characterized by strict Quality of Service (QoS) requirements, there is a growing need for accurately predicting typical performance parameters such as throughput. This prediction should be based on the applications' traffic profiles and at the same time reflect the network uncertainty that IoT access networks add to the overall communication. In this work, we deployed 6 different smart building applications in a real testbed while creating a considerable traffic contention in an IEEE 802.15.4 access network. After preprocessing the raw data and following a feature engineering mechanism, we apply five different regression learning approaches to each application and predict its throughput. By resorting to several prediction error metrics and time metrics such as training and inference time, we show that the multiple linear regression achieves high accuracy while outperforming other well known machine learning methods. |
7,303 | Please write an abstract with title: A short pulse radar for sensing ocean wave structure, and key words: Ocean waves, Radar remote sensing, Spaceborne radar, Gravity, Space vehicles, Aircraft, Analytical models, Radar scattering, Surface waves, Rough surfaces. Abstract: A real-aperture radar technique is under development at the Goddard Space Flight Center to remotely sense ocean gravity waves from spacecraft. Experimental data obtained from aircraft demonstrations indicate correlation between wave profilometer and radar-derived spectra, and results from an analytical model for scattering from rough surfaces shows promise of explaining the sensor response. This paper will present the basic concept of the sensing system and a summary of the research program and results. |
7,304 | Please write an abstract with title: On the Visualization of Time-Varying Structured Grids Using a 3D Warp Texture, and key words: Grid computing, Extrapolation, Mesh generation, Interpolation, Lattices, Data visualization, Approximation algorithms, Sampling methods, Error analysis, Root mean square. Abstract: We present a novel scheme to interactively visualize time-varying scalar fields defined on a structured grid. The underlying approach is to maximize the use of current graphics hardware by using 3D texture mapping. This approach commonly suffers from an expensive voxelization of each time-step as well as from large size of the voxel array approximating each step. Hence, in our scheme, instead of explicitly voxelizing each scalar field, we directly store each time-step as a three dimensional texture in its native form. We create the function that warps a voxel grid into the given structured grid. At rendering time, we reconstruct the function at each pixel using hardware-based trilinear interpolation. The resulting coordinates allow us to compute the scalar value at this pixel using a second texture lookup. For fixed grids, the function remains constant across time-steps and only the scalar field table needs to be re-loaded as a texture. Our new approach achieves excellent performance with relatively low texture memory requirements and low approximation error. |
7,305 | Please write an abstract with title: Joint Multichannel-Spatial Diversity for Efficient Opportunistic Routing in Low-Power Wireless Networks, and key words: Routing, Correlation, Spatial diversity, Wireless networks, Estimation, IEEE transactions, Computer science. Abstract: Low-power wireless networks (LPWNs) are of paramount importance for the pervasive deployment of Internet-of-Things (IoT). To deal with the lossy nature of LPWNs, opportunistic routing (OR) and multichannel communications (MC) have received significant research interests. In particular, coupling OR with MC has become an important way to further enhance the communication performance in LPWNs. However, as OR requires nodes in the same channel while MC separates nodes into different channels, the benefits of MC-OR combination are largely under-utilized. To address this problem, we investigate the challenging issue of establishing opportunistic routing in multichannel LPWNs. Different from the existing studies that separately assign channels and select forwarders, we propose a synergistic multichannel and opportunistic routing (SMOpp) approach, which jointly combines the benefits of both OR and MC by considering link correlation. SMOpp explicitly evaluates the routing opportunities of each channel/forwarder set and then employs a forwarder-initiated scheme to select the best combinations of senders, forwarders, and channels. The testbed evaluation shows that compared to the existing methods, SMOpp significantly improves the transmission efficiency for LPWNs. |
7,306 | Please write an abstract with title: A Risk Assessment for Utilities to Prevent Transformer OLTC Failures Caused by Silver Sulphide Corrosion, and key words: Oil insulation, Silver, Oils, Power transformer insulation, Corrosion, Contacts, Sulfur compounds. Abstract: Silver sulphide corrosion is a recently identified failure mechanism of transformer onload tap changers (OLTC). The corrosive sulphur in transformer oil reacts with the silver coated components of OLTC tap selector and forms silver sulphide films. During OLTC operation, the silver sulphide flakes can be detached from the tap selector and mix with the transformer oil. The silver sulphide is a semi conductive material. As a result, the dielectric strength in the transformer oil around the OLTC silver coated contacts or elsewhere in the transformer, wherever the semi conductive particles travel, will be reduced. Eventually, due to either high electric field stress or aged oil with a low dielectric strength, oil breakdown can occur between adjacent contacts. This can cause a catastrophic failure of the OLTC and quite often the tapping winding as well. Since such failures affect the transformer reliability, utilities are interested in methods of detecting and mitigating silver sulphide corrosion on OLTCs. This paper presents a risk assessment criterion to identify the degree of significance of silver sulphide corrosion in transformers using existing diagnostic techniques. |
7,307 | Please write an abstract with title: Crop drought monitoring using serial NDVI & NDWI in Northern China, and key words: Crops, Remote monitoring, Vegetation mapping, Condition monitoring, Large-scale systems, Reflectivity, Infrared detectors, Soil moisture, Civil engineering, Decision making. Abstract: Drought is one of the major environmental disasters in north China, and it is very important to detect and monitor drought periodically at large scale for decision making. The Normalized Difference Vegetation Index (NDVI) has been widely used to monitor moisture-related vegetation condition. To better understand the relationship between vegetation vigor and moisture availability, the Normalized Difference Water Index (NDWI) was calculated in addition to the NDVI. In this study, the analysis was conducted on time series compositing NDVI and NDWI of the period of ten days. With the support of land use map and soil humidity of crop for the growing season, we build the simple model of northern China for crop drought monitoring. The results of July 2002 show that the large scale temporal and spatial characteristics of drought in Northern China can be effectively detected by this way. Based on this method, we have developed a operational crop drought monitoring system for whole China land areas. |
7,308 | Please write an abstract with title: Semi-Supervised Sea Ice Classification of SAR Imagery Based on Graph Convolutional Network, and key words: Training, Radar remote sensing, Navigation, Radar, Machine learning, Radar imaging, Radar polarimetry. Abstract: Monitoring sea ice in polar regions is essential for environmental modeling and ship navigation. National ice agencies expect robust sea ice classification methods for operational use. However, fully supervised machine learning models require large training datasets, which are usually limited to the sea ice classification domain. Therefore, a semi-supervised sea ice classification model is proposed to address this challenge. First, the IRGS segmentation is applied to generate superpixels that construct the graph. Then, two graph convolutional layers are utilized to learn the features of each node. Finally, a softmax layer assigns labels to the nodes in the graph. The proposed model is named IRGS-GCN and tested on four RADARSAR-2 dual-polarized scenes. The experimental results show that the IRGS-GCN achieves an overall accuracy of 95.17% and outperforms fully-supervised random foreset and ResNet trained on limited data. Most of the sea ice boundary and leads are successfully preserved in the results. |
7,309 | Please write an abstract with title: A Deep Learning Approach for Automatic Scoliosis Cobb Angle Identification, and key words: Deep learning, Image analysis, Computer network reliability, Pipelines, Medical services, Computer architecture, Benchmark testing. Abstract: Efficient and reliable medical image analysis is indispensable in modern healthcare settings. The conventional approaches in diagnostics and evaluations from a mere picture are complex. It often leads to subjectivity due to experts' various experiences and expertise. Using convolutional neural networks, we proposed an end-to-end pipeline for automatic Cobb angle measurement to pinpoint scoliosis severity. Our results show that the Residual U-Net architecture provides vertebrae average segmentation accuracy of 92.95% based on Dice and Jaccard similarity coefficients. Furthermore, a comparative benchmark between physician's measurement and our machine-driven approach produces an acceptable mean deviation of 1.57 degrees and a T-test p-value of 0.9028, indicating no significant difference. This study has the potential to help doctors in prompt scoliosis magnitude assessments. |
7,310 | Please write an abstract with title: Recent advances in optical phase conjugation and its application to 40 Gb/s transmission, and key words: Optical pumping, Nonlinear optics, Optical mixing, Optical harmonic generation, Optical distortion, Optical modulation, Optical crosstalk, Bit error rate, Stimulated emission, Wavelength division multiplexing. Abstract: Optical phase conjugation is effective in compensating intra-channel nonlinearities in pseudolinear systems. Results of optical phase conjugation in 40 Gb/s optical systems with different transmission distances and modulations formats, and varying conjugator locations will be presented. |
7,311 | Please write an abstract with title: Fractal Modulation Scheme for Optical Camera Communication, and key words: Bit error rate, Communication channels, Cameras, Optical imaging, Fractals, Optical receivers, Adaptive optics. Abstract: This paper proposes a novel spatial modulation scheme for optical camera communication based on the use of a fractal structure on the transmission. This system is able to send different amounts of data depending on the distance between the transmitter (Tx) and the receiver (Rx). Two simulation experiments were carried out to validate the proposed system. In the first experiment, the number of received bits was obtained as a function of the distance between the Tx and the Rx and compared to a theoretical expression that defines a lower bound. In the second experiment, the communication channel was tested by analyzing the behaviour of the bit error rate against the quantity of noise in the image using the peak signal-to-noise-ratio. It was found that for a PSNR value of 40 dB or more, the system is able to achieve a bit error rate below the forward error correction limit of $3. 8\cdot 10^{-3}$. This architecture has potential applications in: hierarchization of data in vehicle-to-vehicle communications, distance multiplexing of data streams in cultural spaces, and security applications. |
7,312 | Please write an abstract with title: EDS Region 9 Annual Biennial Outstanding Student Paper Award Ceremony, and key words: Awards. Abstract: The award winners and the titles of their award winning papers are listed. |
7,313 | Please write an abstract with title: Thermal analysis of induction heating roll with heat pipes, and key words: Eddy currents, Skin, Coils, Temperature distribution, Equations, Thermal conductivity, Temperature control, Heating, Power engineering and energy, Furnaces. Abstract: In this paper, we analyze thermal characteristic of induction heating roll with heat pipes using FEA first. And we make a comparative study about effect on heat pipes to a thermal characteristic. Lastly, we will make a study about the effect on the position and a number of the heat pipes after. |
7,314 | Please write an abstract with title: A critical appraisal of opportunities for wearable medical sensors, and key words: Appraisal, Wearable sensors, Medical diagnostic imaging, Biomedical monitoring, Mechanical sensors, Surveillance, Cardiac disease, Ambient intelligence, Medical tests, Blood pressure. Abstract: This paper provides an appraisal of the sensor requirements and prospects available for the growing field of wearable medical sensors. The results of a literature survey for various sensor use-models indicate that the design goals for each intended sensor application must focus on task specific criteria for ultimate sensor acceptance. Provided use-models include the examination of the relevant medical problems, the diagnostic utility of the available physiologic signals, and the impact of false alarms on the specific implementation area. |
7,315 | Please write an abstract with title: The Impact of Digital Transformation on Sustainability in Fashion Retail, and key words: Sustainable development, Industries, Companies, Market research, Interviews. Abstract: In recent years there are significant advancements in communication technologies that have a direct impact on any business. Different digital technologies such as cloud, data managements, mobile applications, manufacturer software and analytics are a creating new technology revolution - digital transformation of organizations. Fashion and clothing are one of the fastest-growing online categories, but also the slowest one to adopt new technologies. Retailers play a significant role in fashion supply chain management. The aim of the study is to analyze how new digital technologies have impacted on sustainability in fashion retail and to evaluate possibilities of fashion retailers to incorporate sustainability issues. |
7,316 | Please write an abstract with title: A Graph-Convolutional-Network based Prototype Mixing Model for Few-shot Segmentation, and key words: Measurement, Image segmentation, Semantics, Education, Prototypes, Information filters, Data mining. Abstract: Over the past few years, deep convolutional neural networks (CNNs) based semantic segmentation methods reached the state-of-the-art performance. To train a model with the ability to know a concept, a lot of pixel level annotated images are required, which is time consuming and hard to cover unseen object categories. Thus, few-shot semantic segmentation has been developed to implement segmentation with a few annotation images. In this paper, we proposed a novel prototype mixing model for few shot segmentation. Different with other works which only produce prototypes form support set, our proposed model learn a group of concept-specific prototypes from support set and then generate prototypes from query set. With prototypes from both query set and support set, we proposed a GCN(Graphic Convolutional Network) module to generate mixing prototypes for better utilizing of informations from different categories. We also proposed a clustering module to produce multi-prototypes for representing different parts of a single semantic class, which reach better performance than single prototype. Our model achieve 48.8% and 55.9%mIoU score on PASCAL-5i for 1-shot and 5-shot settings respectively. |
7,317 | Please write an abstract with title: High-level performance and power exploration of DSP applications realized on programmable processors, and key words: Digital signal processing, Energy consumption, Arithmetic, Video compression, Computational complexity, Algorithm design and analysis, Motion estimation, Computer applications, Data analysis, Time to market. Abstract: The continuous increase of the computational power of programmable processors has established them as an attractive design alternative, for implementation of the most computationally intensive applications, like video compression. To enforce this trend, designers implementing applications on programmable platforms have to be provided with reliable and in-depth analysis data that will allow for the early selection of the most appropriate application for a given set of specifications. To address this need, we introduce a new methodology for early and accurate estimation of the number of instructions required for the execution of an application, together with the number of data memory transfers on a programmable processor. The high-level estimation is achieved by a series of mathematical formulas; these describe not only the arithmetic operations of an application, but also its control and addressing operations, if it is executed on a programmable core. The comparative study, which is done using three popular processors (Pentium, ARM and MIPS), shows the high efficiency and accuracy of the methodology proposed, in terms of the number of executed (micro-)instructions (i.e. performance) and the number of data memory transfers (i.e. memory energy consumption). |
7,318 | Please write an abstract with title: An architects' guide to enterprise application integration with J2EE and .NET, and key words: Application software, Australia, Computer architecture, Buildings, Information systems, Appropriate technology, Large scale integration, Software architecture, Data security, Computer languages. Abstract: Architects are faced with the problem of building enterprise scale information systems, with streamlined, automated internal business processes and Web-enabled business functions, all across multiple legacy applications. The underlying architectures for such systems are embodied in a range of diverse products known as enterprise application integration (EAI) technologies. We highlight some of the major problems, approaches and issues in designing EAI architectures and selecting appropriate supporting technology. An architect's perspective on designing large-scale integrated applications is taken, and we discuss requirements elicitation, architecture patterns, EAI technology and features, and risk mitigation. J2EE and .NET technologies are used to illustrate the capabilities of state-or-the-art integration technologies. |
7,319 | Please write an abstract with title: Core Loss Model for Arbitrary Excitations With DC Bias Covering a Wide Frequency Range, and key words: Magnetic cores, Core loss, Shape, Frequency measurement, Ferrites, Magnetic hysteresis, Loss measurement. Abstract: Core loss prediction is quite complex as the excitation of magnetic materials varies depending on the topology and the operating mode of switched-mode power supplies. In particular, the waveform of the magnetic flux density, including its dc bias, affects core losses. This article presents the results of an extensive core loss study performed on Mn-Zn ferrites. The investigation comprises core excitations with, among others, sinusoidal and triangular shapes of the magnetic flux density with and without dc bias. Based on the obtained core loss data, an empirical core loss model has been derived for the prediction of specific core losses in Mn-Zn ferrites that is valid for arbitrary excitations, including dc bias of the magnetic flux density. Multiplying the quasi-static energy losses depending on the swing and the dc bias of the magnetic flux density by an effective frequency yields the core losses. The proposed model covers a wide frequency range and only requires the quasi-static energy losses at low frequencies and two frequency-independent parameters. These parameters can be easily extracted from a limited number of measurements or from the data provided by manufacturers. The verification of the proposed approach demonstrates an adequate accuracy of 15% for all investigated Mn-Zn ferrites and for the broad range of studied waveforms and parameters. |
7,320 | Please write an abstract with title: Taking mixed-signal substrate noise coupling simulation to the behavioral level using SystemC, and key words: Noise level, Circuit simulation, Coupling circuits, Circuit noise, Circuit testing, Power systems, Information technology, Noise generators, Wire, Costs. Abstract: We present methods and models to simulate substrate noise coupling at the behavioral level. The models are implemented as a part of the SystemC based behavioral level noise coupling (BeNoC) simulation application. The application is designed as a wrapper to SystemC component modules, enabling designers to simulate substrate noise coupling in their modules during the entire circuit refinement process. This is enabled through the two main contributions presented in this paper: (1) methods to connect the behavioral level with low level circuit simulations and (2) generation of a fast and accurate circuit model for substrate coupling simulations. The accuracy of the generated substrate noise coupling model is verified against device simulations. The same verification test case is used to demonstrate the connection between behavioral simulations and circuit simulations. |
7,321 | Please write an abstract with title: DC Side Voltage Monitoring Model of Transformer based on Pattern Recognition, and key words: Process design, Energy consumption, Voltage transformers, Signal processing, Pattern recognition, Mathematical model, Monitoring. Abstract: Aiming at the problem that the transformer DC side voltage is affected by the voltage quality during the monitoring process, its monitoring performance is greatly reduced. In order to improve the monitoring effect of the transformer DC side voltage, a transformer DC side voltage monitoring model based on pattern recognition is designed. Pattern recognition based on the RMS method using DC voltage transformer discrete signal processing using a pure sinusoidal AC signal with the average RMS mathematical relationship, by calculating the average of the AC voltage, indirectly, of the DC voltage transformer Valid values. From the OPP-CI model that ignores the influence of the ZIB node and the OPP-CI model that considers the influence of the ZIB node, pattern recognition is used to establish the transformer DC side voltage OPP-CI model, and the transformer DC side voltage monitoring process design is combined to realize the transformer DC Monitoring of side voltage. The experimental results show that the error of the monitoring results of the proposed model is relatively low, indicating that the method can improve the monitoring effect of the transformer DC side voltage. |
7,322 | Please write an abstract with title: Performance Evaluation of Highly Efficient Information Collection Methods by Trend Analysis of Sensor Information Using Pre-learning, and key words: Performance evaluation, Design methodology, Computer simulation, Computational modeling, Modulation, Sensor phenomena and characterization, Market research. Abstract: LPWA (Low Power Wide Area), a low-power, long-distance communication method, has been attracting attention. Level Index Modulation (PLIM) has a problem of missing information due to packet collision when multiple sensors select the same index. In this study, we established an optimal design based on a mathematical model that minimizes the probability of packet collision by using a trend analysis of prior sensor information in the index design, which is the correspondence between packet transmission time, selected channel, and transmitted information. In this paper, we proceeded with the characterization by computer simulation and showed that the proposed design method can suppress the packet collision probability better than the conventional method. |
7,323 | Please write an abstract with title: An open-source FPGA-based control and data acquisition hardware platform, and key words: Performance evaluation, Automation, Scalability, Data acquisition, Programmable logic devices, Process control, Programmable logic arrays. Abstract: Industrial automation since the early 70s has mostly implemented control and monitoring systems through the use of PLCs (Programmable Logic Controllers) which for the most part remain as microcontroller or microprocessor based devices. Yet more advanced solutions to satisfy the demand of higher performance, scalability and exibility are required. In order to implement hardware platforms with these characteristics and that allow the end user to adapt the controller according to the application, it is required to combine a high-performance application processor with a programmable logical network, such as those found in modern FPGAs (Field Programmable Gate Arrays), for customization and implementation of purpose specific hardware. Although FPGAs are often used embedded in industrial automation control products, they do not provide direct access to the full functionality of the FPGA, reconfiguration, or are locked as closed source ecosystems. The goal with this project is to develop an open-source, feature rich and low cost, compared with similar commercially available devices, hardware platform for industrial control and data acquisition applications. |
7,324 | Please write an abstract with title: Shakespeer: Verifying the Co-presence of Smart Devices and Users via Vibration, and key words: Vibrations, Wearable Health Monitoring Systems, Face recognition, Passwords, Muscles, Fingerprint recognition, Haptic interfaces. Abstract: Securely and unobtrusively authenticating a user is an important problem given the pervasiveness of smartphones. Existing approaches, such as password, fingerprints, or facial recognition, are vulnerable to various attacks, and/or degrade usability. To overcome this problem, we propose Shakespeer, which differentiates users based on uniqueness in the propagation of haptic vibrations through hand, forearm muscles and bones. These vibrations are generated by the user’s smartphone and sensed by their smartphone and smartwatch. The unobtrusive haptic vibrational response makes this biometric feature hard to be replicated. Meanwhile, it provides the co-presence detection function, which allows the devices to confirm the co-presence on the user’s body. We implement Shakespeer using smartphones and smartwatches and tested it across 32 subjects under real-world settings. From our preliminary exploratory evaluation, Shakespeer achieves an equal error rate (EER) of 0.59 %, demonstrating its feasibility. |
7,325 | Please write an abstract with title: Optical Switches, and key words: Optical switches, Optical waveguides, Optical variables control, Optical refraction, Optical device fabrication, Optical fibers, Refractive index. Abstract: Optical switches are of great importance for the development of the optical communication system and high data transfer speed in integrated optical circuits. The function of optical switches is to switch the optical signal from one route to another route effectively. In this chapter, several optical switches are discussed by providing the different principles for the operation of the different switches. These switches are implemented by several methods and each method depends on a different mechanism for its operation. The various methods used are briefly described in this chapter. |
7,326 | Please write an abstract with title: Acousto-optically tunable integrated Ti:Er:LiNbO/sub 3/ laser, and key words: Tunable circuits and devices, Pump lasers, Power lasers, Frequency, Laser tuning, Laser excitation, Signal resolution, Stimulated emission, Optical pumping, Optical tuning. Abstract: Wavelength tunable, narrow linewidth lasers are of growing importance for optical communication systems using wavelength-division multiplexing (WDM). A diode-pumped packaged acousto-optically tunable integrated Ti:Er:LiNbO/sub 3/ waveguide laser could be tuned (not continuously) over 31 nm in the wavelength range 1530 nm </spl lambda/<1610 nm with an emission linewidth of 0.3 nm. Here we report an improved version of the laser with a modified design; its tuning range is extended to 47 nm with a linewidth smaller than 12 pm in appropriate operating conditions adjusted. |
7,327 | Please write an abstract with title: A Self-Tuning Fuzzy PID Controller for SEPIC Based on Takagi-Sugeno Inference System, and key words: Resistance, Photovoltaic systems, Voltage measurement, Switches, Control systems, Mathematical models, Robustness. Abstract: This research paper presents the design and simulation of the proportional integral derivative (PID) controller whose gains are controlled by an adaptive fuzzy tuning mechanism based on a Takagi-Sugeno (TS) inference system to alleviate the computational burden. The classic PID controller is of linear nature which reduces the operational performance of the DC-DC single-ended primary-inductor converter (SEPIC). To address this problem, the self-tuning fuzzy PID controller (STFPID) is designed for SEPIC for photovoltaic systems (PV) to control the duty cycle applied to the switching element of the converter. Comparative performance analysis of fuzzy tuned PID controller in comparison with the conventional PID controller is performed on MATLAB/SIMULINK environment using Fuzzy Logic Toolbox. The use of the self-tuning fuzzy logic PID controller achieved better performance than the conventional linear PID controller under input disturbances and different loads, in terms of maintaining constant output reference voltage, substantially reducing rise and settling time and overshoot. |
7,328 | Please write an abstract with title: Wireless optical spread spectrum communications. Data security improvement in wireless links, and key words: Communication system security, Spread spectrum communication, Data security, Optical modulation, Military communication, Cryptography, Interference, Jamming, Signal processing, Optical control. Abstract: This paper introduces new techniques for improving the security level of the wireless optical systems. In this way, we are going to use modulation schemes based on spread spectrum theory. These techniques had been developed for military applications in order to obtain reliable and secure communications, so they seem to be a good candidate for our systems. Spread spectrum systems perform a data encryption in the modulation process, and they are able to work in presence of high level interference and intentional jamming signals. On the other hand, these schemes can be also applied to optical barriers and perimeter control systems, because the spread spectrum signal improves the robustness and invulnerability of the security barriers |
7,329 | Please write an abstract with title: CSI-MIMO: K-nearest Neighbor applied to Indoor Localization, and key words: MIMO communication, Correlation, Estimation, Stability analysis, Transmitting antennas, Mathematical model. Abstract: Indoor Localization has attracted interest in both academia and industry for its wide range of applications. In this paper, we propose an indoor localization solution based on Channel State Information (CSI). CSI is a fine-grain measure of the effect of the channel on the transmitted signal. It is computed for each subcarrier and each antenna in the Multiple-Input-Multiple-Output (MIMO) antenna case. It is also becoming a trend for indoor position fingerprinting. By using a K-nearest neighbor learning method a highly accurate indoor positioning is achieved. The input feature is the magnitude component of CSI which is preprocessed to reduce noise and allow for a quicker search. The euclidean distance between CSI is the criteria chosen for measuring the closeness between samples. The method is applied to a CSI dataset estimated at an 8 × 2 MIMO antenna that is published by the organizers of the Communication Theory Workshop Indoor Positioning Competition. The proposed method is compared with three other methods all based on deep learning approaches and tested with the same dataset. The K-nearest neighbor method presented in this paper achieves a Mean Square Error (MSE) of 2.4 cm which outperforms its counterparts. |
7,330 | Please write an abstract with title: IoT Enabled Smart Farming: A Review, and key words: Control systems, Sensor systems, Internet of Things, Computer security, Intelligent sensors, Faces, Digital agriculture. Abstract: Agriculture is giving the major contribution to the Indian economy. The rapid growth in digitization forced to convert many marketing sectors to adapt the modern technologies. The agriculture sector identified as a fast growing technology in recent years. The immense use of technologies provide major benefits to agriculture. The internet of things (IoT) is the obvious choice to agriculture even though it is not fully satisfied. The integration of agriculture with smart technologies helps the farmers with great profit. The example of such advancement is exchange of information between the deployed devices in farm field. This paper gives review on technologies used in smart farming as well as attacks on the confidential data. This paper gives detailed direction towards the recent progress on farming using IoT. |
7,331 | Please write an abstract with title: BBS: Micro-Architecture Benchmarking Blockchain Systems through Machine Learning and Fuzzy Set, and key words: Benchmark testing, Measurement, Fabrics, Peer-to-peer computing, Computer architecture, Protocols. Abstract: Due to the decentralization, irreversibility, and traceability, blockchain has attracted significant attention and has been deployed in many critical industries such as banking and logistics. However, the micro-architecture characteristics of blockchain programs still remain unclear. What's worse, the large number of micro-architecture events make understanding the characteristics extremely difficult. We even lack a systematic approach to identify the important events to focus on. In this paper, we propose a novel benchmarking methodology dubbed BBS to characterize blockchain programs at micro-architecture level. The key is to leverage fuzzy set theory to identify important micro-architecture events after the significance of them is quantified by a machine learning based approach. The important events for single programs are employed to characterize the programs while the common important events for multiple programs form an importance vector which is used to measure the similarity between benchmarks. We leverage BBS to characterize seven and six benchmarks from Blockbench and Caliper, respectively. The results show that BBS can reveal interesting findings. Moreover, by leveraging the importance characterization results, we improve that the transaction throughput of Smallbank from Fabric by 70% while reduce the transaction latency by 55%. In addition, we find that three of seven and two of six benchmarks from Blockbench and Caliper are redundant, respectively. |
7,332 | Please write an abstract with title: Tunable Nonlinear Activation Functions for Optical Neural Networks, and key words: Nonlinear optics, Optical interferometry, Optical computing, Optical imaging, Neural networks, Optical fiber networks, Optical waveguides. Abstract: We introduce an electro-optic hardware platform for realizing optical nonlinearities and demonstrate that, as a nonlinear activation function, it can substantially improve the classification performance of optical neural networks. |
7,333 | Please write an abstract with title: A low-complexity multiuser detection method based on mean field annealing, and key words: Multiuser detection, Annealing, Multiaccess communication, Interference cancellation, Multiple access interference, Convergence, Maximum likelihood detection, NP-complete problem, Fading, Detectors. Abstract: Multiuser detection is an important technique used to suppress multiple access interference (MAI) in CDMA system. A novel reduced-order multistage PIC multiuser detection method based on mean field annealing in an asynchronous multipath CDMA system is presented in this paper to solve the problem that the conventional optimal multiuser detection methods have the characteristics of larger calculation and slower convergence. This method employs mean field annealing technique, and then the NP-complete problem of minimizing the objective function of the optimal multiuser detection can be translated into minimizing a mean field annealing network energy function. This method uses the block Toeplitz characteristics of matrix, and then larger matrix can be replaced by small matrix, which leads to reduced order and calculation effectively. Theory and experimental results reveal that this method has the better performance to cancel MAI, suppress inter-symbol interference and multipath fading, and this method has small calculation so it can be implemented in real-time. Finally the reduced-order multistage PIC multiuser detection method based on mean field annealing given in this paper is a better scheme for asynchronous multipath CDMA systems. |
7,334 | Please write an abstract with title: Vibroacoustic Metamaterials for enhanced acoustic Behavior of Vehicle Doors, and key words: Vibrations, Manufacturing processes, Production, Bending, Metamaterials, Acoustics, Manufacturing. Abstract: The presented work addresses an industry-oriented design process of vibroacoustic metamaterials for automotive components with enhanced acoustic properties. The procedure involves numerical prediction of the resulting dynamic behavior in regard to stop band characteristics as well as manufacturing techniques suited for series production. Vibroacoustic metamaterials from sheet metal are developed for future implementation to a vehicle door to create a stop band in the frequency region around 600 Hz. Production is done using punching and bending techniques, followed by an experimental verification of the stop band characteristics. |
7,335 | Please write an abstract with title: Radially balanced error diffusion, and key words: Pixel, Convolution, Information systems, Australia, Minimization methods, Algorithm design and analysis, Distributed computing. Abstract: The paper is concerned with digital halftoning by error diffusion. It discusses error diffusion where the error distribution from a pixel to the next scanline, resulting from the complete processing of the current scanline, approximates a standard Cauchy distribution, having the form (1//spl pi/)1/(1+x/sup 2/). Such error diffusion is capable of generating sparse halftone patterns, which are free of worm artifacts, no matter how sparse the halftone patterns. It is argued that the well spread sparse halftone patterns are due to the remarkable properties of this particular distribution: the distribution is radially balanced, being equal within equiangular radial slices; and further, the distribution maintains this radial balance under self-convolution, spreading in proportion to the degree of self-convolution. Approximating this error distribution is an effective tool for designing error diffusion masks. |
7,336 | Please write an abstract with title: Transceiver optimization for multiuser MIMO systems, and key words: Transceivers, MIMO, Transmitters, Receiving antennas, Transmitting antennas, Signal processing algorithms, Algorithm design and analysis, Array signal processing, Feedback, Multiaccess communication. Abstract: We consider the uplink of a multiuser system where the transmitters as well as the receiver are equipped with multiple antennas. Each user multiplexes its symbols by a linear precoder through its transmit antennas. We work with the system-wide mean squared error as the performance measure and propose algorithms to find the jointly optimum linear precoders at each transmitter and linear decoders at the receiver. We first work with the case where the number of symbols to be transmitted by each user is given. We then investigate how the symbol rate should be chosen for each user with optimum transmitters and receivers. The convergence analysis of the algorithms is given, and numerical evidence that supports the analysis is presented. |
7,337 | Please write an abstract with title: Managing multi-configuration hardware via dynamic working set analysis, and key words: Hardware, Microarchitecture, Change detection algorithms, Phase detection, Algorithm design and analysis, Optimization methods, Power engineering computing, Design engineering, Power engineering and energy, Microprocessors. Abstract: Microprocessors are designed to provide good average performance over a variety of workloads. This can lead to inefficiencies both in power and performance for individual programs and during individual phases within the same program. Microarchitectures with multiconfiguration units (e.g. caches, predictors, instruction windows) are able to adapt dynamically to program behavior and enable/disable resources as needed. A key element of existing configuration algorithms is adjusting to program phase changes. This is typically done by "tuning" when a phase change is detected - i.e. sequencing through a series of trial configurations and selecting the best. Algorithms that dynamically collect and analyze program working set information are studied. To make this practical, we propose working. set signatures - highly compressed working set representations (e.g. 32-128 bytes total). Algorithms use working set signatures to 1) detect working set changes and trigger re-tuning; 2) identify recurring working sets and re-install saved optimal reconfigurations, thus avoiding the time-consuming tuning process; 3) estimate working set sizes to configure caches directly to the proper size, also avoiding the tuning process. Multi-configuration instruction caches are used to demonstrate the performance of the proposed algorithms. When applied to reconfigurable instruction caches, an algorithm that identifies recurring phases achieves power savings and performance similar to the best algorithm reported to date, but with orders-of-magnitude savings in the number of re-tunings. |
7,338 | Please write an abstract with title: Learning Data Representation and Emotion Assessment from Physiological Data, and key words: Schedules, Correlation, Neural networks, Feature extraction, Electroencephalography, Physiology, Task analysis. Abstract: Aiming a deeper understanding of human emotional states, we explore deep learning techniques for the analysis of physiological data. In this work, raw two-channel pre-frontal electroencephalography and photoplethysmography signals of 25 subjects were collected using EMOTAI's headband while watching commercials. Taking as input the raw data, convolutional neural networks were used to learn data representations and classify the acquired signals according to the Positive and Negative Affect Schedule. This approach achieved promising results, with average F1-scores of 76.6% for Positive Affect and 83.3% for Negative Affect. Interpretation of the learned data representation was attempted by computing correlation values between features extracted from the raw inputs and the final classification. The features with the most significant correlations were the alpha band power, and the asymmetry and phase synchronization indexes. The extracted features seem to match the ones learnt by the neural network, hence endorsing their validity for emotional studies. |
7,339 | Please write an abstract with title: Polymer nanocomposites as dielectrics and electrical insulation-perspectives for processing technologies, material characterization and future applications, and key words: Polymers, Nanocomposites, Dielectrics and electrical insulation, Plastic insulation, Dielectric materials, Chemical technology, Biomedical engineering, Biological materials, Biomedical materials, Mechanical factors. Abstract: Polymer nanocomposites are defined as polymers in which small amounts of nanometer size fillers are homogeneously dispersed by only several weight percentages. Addition of just a few weight percent of the nanofillers has profound impact on the physical, chemical, mechanical and electrical properties of polymers. Such change is often favorable for engineering purpose. This nanocomposite technology has emerged from the field of engineering plastics, and potentially expanded its application to structural materials, coatings, and packaging to medical/biomedical products, and electronic and photonic devices. Recently these 'hi-tech' materials with excellent properties have begun to attract research people in the field of dielectrics and electrical insulation. Since new properties are brought about from the interactions of nanofillers with polymer matrices, mesoscopic properties are expected to come out, which would be interesting to both scientists and engineers. Improved characteristics are. expected as dielectrics and electrical insulation. Several interesting results to indicate the foreseeable future have been revealed, some of which are described on materials and processing in the paper together with basic concepts and future direction. |
7,340 | Please write an abstract with title: Different viable torque control schemes of induction motor for electric propulsion systems, and key words: Torque control, Induction motors, Propulsion, Stators, Electric resistance, Rotors, Inductance, Sensorless control, Adaptive control, Control systems. Abstract: This work presents a detailed comparison between various control strategies, emphasizing advantages and disadvantages. The scope of This work is to choose an adaptive induction motor drive for an electric propulsion system. Recent advances in induction motor control have made it suitable for fast dynamic response applications. In this paper, the performance of the various control schemes such as indirect field oriented control (IFOC), direct field oriented control (DFOC), direct torque control (DTC) and neuro-fuzzy DTC (DTNFC) are evaluated. The analysis has been carried out on the basis of the results obtained by numerical simulations. A new estimator is also designed to estimate the stator resistance of induction motor. The sensitivity of DTC to temperature variations, leading to stator resistance changes, is eliminated by online estimation of stator resistance. In this paper, detailed analysis and investigation are carried out and an adaptive control is proposed for electric propulsion system. |
7,341 | Please write an abstract with title: Conversation pattern-based anticipation of teammates' information needs via overhearing, and key words: Collaboration, Computer architecture, Collaborative work, Teamwork, Pattern recognition, Humans, Computational modeling, Buildings, Multiagent systems, Face detection. Abstract: One research focus of human-centered teamwork is on advanced decision architectures that can help people make effective and timely decisions. This requires distributed team members to effectively establish shared situation awareness and to collaboratively develop explanations on how an unfamiliar situation might have been emerging. One key to achieve this goal is the ability to anticipate others' future information needs and to offer help proactively. In this paper we investigate a novel approach to anticipating teammates' information needs based on step-wise conversation pattern recognition, leveraging the idea of multi-party communication. This approach can be further extended to build a computational model for collaborative story building as needed in recognition-primed, naturalistic decision architectures. |
7,342 | Please write an abstract with title: Adaptive Resilient Event-Triggered Control Design of Autonomous Vehicles With an Iterative Single Critic Learning Framework, and key words: Autonomous vehicles, Vehicle dynamics, Process control, Mathematical model, Trajectory, Optimal control, Cost function. Abstract: This article investigates the adaptive resilient event-triggered control for rear-wheel-drive autonomous (RWDA) vehicles based on an iterative single critic learning framework, which can effectively balance the frequency/changes in adjusting the vehicle’s control during the running process. According to the kinematic equation of RWDA vehicles and the desired trajectory, the tracking error system during the autonomous driving process is first built, where the denial-of-service (DoS) attacking signals are injected into the networked communication and transmission. Combining the event-triggered sampling mechanism and iterative single critic learning framework, a new event-triggered condition is developed for the adaptive resilient control algorithm, and the novel utility function design is considered for driving the autonomous vehicle, where the control input can be guaranteed into an applicable saturated bound. Finally, we apply the new adaptive resilient control scheme to a case of driving the RWDA vehicles, and the simulation results illustrate the effectiveness and practicality successfully. |
7,343 | Please write an abstract with title: Machine Learning Enabled Adaptive Wireless Power Transmission System for Neuroscience Study, and key words: Wireless communication, In vivo, Neuroscience, Heuristic algorithms, Transmitting antennas, Machine learning, Tools. Abstract: We propose a novel machine learning (ML) approach for the adaptive control of wireless power transmission systems for neuroscience studies. Recent advances in wireless technologies have led to new tools and techniques for neuroscience research, particularly in the context of techniques for optogenetics. Such tools eliminate the need for a battery or a tether to an external power supply and enable experiments that can examine complex behaviors such as social interactions in ways. However, current strategies for radio frequency power control, even with optimized transmission antenna designs, fail more often than they succeed in three-dimensional cages or complex environments that demand coverage over large areas. Here, we propose a ML-based algorithm that can effectively address these issues. In our proposed algorithm, we use deep convolutional network networks (CNN) to automatically track the movement and predict the posture of a lab animal, based on which the antenna system is dynamically switched to activate the antenna that maximizes the power efficiency. This dramatically improves the volumetric and angular coverage in the cage as well as the efficiency of the overall power transmission system in in vitro and in vivo experiments, which showcase the potential for their widespread use in various neuroscience studies. |
7,344 | Please write an abstract with title: Analysis of Shaft Voltage of Large Turbo-generators for rotor defect detection purposes, and key words: Shafts, Windings, Stator windings, Magnetic flux, Rotors, Harmonic analysis. Abstract: In the case of large turbo-generators, the analysis of the shaft voltage could be interesting to diagnose some defects such as eccentricities or field winding inter-turn short circuits. To this aim, a first step consists in determining in an accurate way the effect of these defects on the shaft voltage. In this paper, a 4-pole high-power non-salient pole synchronous generator is studied in a didactic way. The study is carried out gradually, with the aim to determine the effect of the parallel coupling of the armature windings. |
7,345 | Please write an abstract with title: Research on Massive Electric Power Big Data Transmission Encryption Based on Improved K-means Algorithm, and key words: Seminars, Big Data, Programming, Hybrid power systems, Encryption, Power systems, Classification algorithms. Abstract: Since the massive electric power data is too big, the time required to transmit the electric power data transmission encryption is too long. To this end, a massive electric power big data transmission encryption method based on improved K-means algorithm is designed. Using the improved K-means algorithm to classify the electric power big data, for the classified data, filter it through attribute reduction and gene expression programming algorithms to obtain the data to be encrypted, ECC-AES hybrid encryption algorithm is used to encrypt electric power big data, which completes the design of electric power big data encryption. Through comparative experiments, it is compared with two electric power big data encryption methods. Experimental results show that, in terms of the time to obtain the data to be encrypted, the proposed electric power big data encryption method is 135ms less than the electric power big data transmission encryption method 1, and 271ms less than the electric power big data transmission encryption method 2. In terms of the time required for the entire encryption process, the proposed electric power big data encryption method is 225ms less than the electric power big data transmission encryption method 1, and 352ms less than the electric power big data transmission encryption method 2. |
7,346 | Please write an abstract with title: Comparison of SVM, KNN, and NB Classifier for Genre Music Classification based on Metadata, and key words: Support vector machines, Seminars, Music, Metadata, Feature extraction, Data mining, Kernel. Abstract: Music recommendations are one of the important things, such as music streaming platforms. Classification of music genres is one of the important initial stages in the process of music recommendation based on genre. Many music classifications are proposed by extracting audio features that require a not light computing process. This research aims to analyze and test the performance of music genre classification based on metadata using three different classifiers, namely Support Vector Machine (SVM) with radial kernel base function (RBF), K Nearest Neighbors (K-NN), and Naïve Bayes (NB). The Spotify music dataset was chosen because it has complete metadata on each of its music. Based on the results of tests conducted by the SVM classifier has the best classification performance with 80% accuracy, then followed by KNN with 77.18% and NB with 76.08%. The accuracy results are relatively the same as music classification based on audio feature extraction, so the classification with the extraction of metadata features can continue to be developed if the metadata in the dataset is well managed. |
7,347 | Please write an abstract with title: Study of Land Surface Temperature (LST) and Land Cover for Urban Heat Island (UHI) Analysis in Dubai, and key words: Land surface, Land surface temperature, Urban areas, Thermal pollution, Temperature distribution, Silicon, Satellites. Abstract: Cities have been growing and evolving over time to meet the needs of space and fulfilment of function. The growth has been both in the horizontal and vertical direction with varied densities creating an effect of urban heat island. This has different factors being the cause for the temperature increase directly effecting the human comfort level in the outdoor spaces. The desert climate of Dubai being extremely hot from June to September, warm and dry from October to April adds to make the problems severe to have the spaces habitable during the peak summers. In addition, built structures in urban area with impervious surface area (ISA) is a major factor associated with UHI. The objective of this study was to evaluate the data of land cover and land surface temperature (LST) responsible for causing UHI effect. The study on the land surface temperature of Dubai Silicon Oasis (DSO), a fast growing and well-planned example of industrial city was carried out using the satellite data collected over the years of development to the seasons of the year. Mapping of these urban mass in correlation to open spaces based on the patterns of urban development and land surface temperature gave an understanding of the microclimate and its effect on the environment. |
7,348 | Please write an abstract with title: Noninvasive MapReduce Performance Tuning Using Multiple Tuning Methods on Hadoop, and key words: Tuning, Optimization, Task analysis, Search methods, Monitoring, Big Data, Structured Query Language. Abstract: There are more than 190 configuration parameters affecting the performance of MapReduce jobs on Hadoop. It is time-consuming and tedious for general users who have no deep knowledge of Hadoop configuring to tune the parameters of a MapReduce job for optimal performance. Therefore, a self-tuning system to improve MapReduce performance in an automated and efficient manner in a complicated Hadoop environment is needed. This article explores multiple tuning methods to improve tuning efficiency for MapReduce performance on Hadoop. The proposed Catla system employs succinct templates and proper schemes of MapReduce algorithms, which can be incorporated in facilitating the tuning and optimization of MapReduce performance. A comprehensive evaluation of the Catla system, with the support of multiple tuning approaches, is discussed in this article. Direct search-based and derivative-free optimization-based tuning techniques for improved efficiency and usability are evaluated using a series of tuning experiments. The experimental results reveal that our work can identify optimal Hadoop parameters for deployed MapReduce jobs in a noninvasive, flexible, automated, and comprehensive manner. |
7,349 | Please write an abstract with title: Concatenated hybrid ARQ - a flexible scheme for wireless real-time communication, and key words: Concatenated codes, Automatic repeat request, Wireless communication, Real time systems, Quality of service, Iterative decoding, Protocols, Telecommunication computing, Fault tolerance, Remote monitoring. Abstract: The concept of deadline dependent coding (DDC) has previously been suggested by the authors for maximizing the probability of delivering the required information before a given deadline in a wireless communication system.. In this paper, these principles are further developed using concatenated codes with iterative decoding, providing a new level of flexibility and robustness for DDC protocols. The strategy of DDC is to combine different coding and decoding methods with automatic repeat request (ARQ) techniques in order to fulfill the application requirements within a wireless realtime communication system. These requirements are formulated as two quality of service (QoS) parameters: deadline (t/sub DL/) and probability of correct delivery before the deadline (P/sub d/), leading to a probabilistic view of realtime communication. An application can negotiate these QoS parameters with the DDC protocol, thus creating a flexible and fault-tolerant scheme. |
7,350 | Please write an abstract with title: A New Image Simulation Technique for Deep-Learning-Based Radar Target Recognition, and key words: Deep learning, physical model, radar image, scattering center, target recognition. Abstract: Radar target recognition via deep learning has been an active research area recently. However, this family of methods depends on the quality of radar images and the number of training samples. Given limited training samples of poor quality, these methods will cause severe overfitting. To solve this problem, this article proposes a new method combining the physical model and deep learning. A new radar measurement simulation technique is presented. The radar measurements are first modeled by the attributed scattering center model. The target is reconstructed by the estimated model parameters. The corresponding residual is formed simultaneously. The reconstructed target and the residual are then frozen. A mask with random shape is imposed on the frequency data. The masked components are reset accordingly. The resulting data are combined and transformed from the frequency domain into the image domain. The new radar measurement can be then generated via the reimaging process of target. We aim to simulate the unforeseen disturbances during data collection. The simulated radar measurements are used to improve the learning efficiency of deep models under limited sample environments. Multiple comparative studies are performed to demonstrate the advantages of the proposed method. |
7,351 | Please write an abstract with title: A Novel Wind Energy Conversion System with DFIG DC-Side Connected to SST for Medium-Voltage DC Grid Integration, and key words: Current control, Reactive power, Doubly fed induction generators, Rotors, Medium voltage, Wind turbines, Wind energy conversion. Abstract: This paper investigates a novel DFIG Low-Voltage DC connected to SST type wind energy conversion system for direct medium-voltage AC grid integration. The novel DFIG-based wind turbine can support active power to DC bus through both SSC and RSC, and the active power through these two converters can be adjusted by changing the rotor speed. The DC side of the generator is combined with the medium-voltage grid through solid state transformer (SST) instead of the fundamental frequency transformer. In this paper, an improved independent phase current control is adopted. The unified mathematical model of high voltage stage and isolation stage is reduced from (n+1) to 1 order by using CLLC resonant converter structure, which greatly reduces the number of signals acquisition and simplifies the control structure. What’s more, the proposed configuration can not only realize reactive power compensation without a reactive power compensator, but also can maintain stable operation even when the voltage of the grid is unbalanced. A detailed simulation study in PSCAD is conducted to verify the performance of the proposed structure. |
7,352 | Please write an abstract with title: Fuzzy stochastic automata for intelligent vehicle control, and key words: Fuzzy control, Stochastic processes, Automata, Intelligent vehicles, Automatic control, Sliding mode control, Remotely operated vehicles, Mobile robots, Fuzzy logic, Robust control. Abstract: Fuzzy stochastic automata (FSA) are proposed for the control of autonomous vehicles. FSA merge the concept of sliding-mode control with fuzzy logic and have interesting robustness properties. Sufficient conditions for the convergence of the FSA control are provided. |
7,353 | Please write an abstract with title: Performance analysis of Brain Tumour Image Classification using CNN and SVM, and key words: Support vector machines, Tumors, Feature extraction, Brain modeling, Biological neural networks, Computational modeling, Gabor filters. Abstract: Tumour is the undesired mass in the body. Brain tumour is the significant growth of brain cells. Manual method of classifying is time consuming and can be done at selective diagnostic centers only. Brain tumour classification is crucial task to do since treatment is based on different location and size of it. Magnetic Resonance Imaging (MRI) is most suitable way to do so. Hence there is a need to build such system which will automatically classify the brain tumour type based on input MR images only. The objective of the proposed system is to classify the brain tumour images into three sub-types: Meningioma, Glioma and Pituitary using convolutional neural network (CNN) and Support vector machine (SVM). Images from the dataset are downsized to reduce computation and some salt noise is added to make model robust and increase the dataset. The performance comparison is done on Google Colab and tensorflow platform in python language. |
7,354 | Please write an abstract with title: A separation principle for non-UCO systems: the jet engine stall and surge example, and key words: Jet engines, Surges, Control systems, Output feedback, Pressure control, State feedback, Compressors, Pressure measurement, Mathematical model, Weight control. Abstract: The problem of controlling surge and stall in jet engine compressors is of fundamental importance in preventing damage and lengthening the life of these components. In this theoretical study, we illustrate the application of a novel output feedback control technique to the Moore-Greitzer mathematical model (1986) for these two instabilities assuming that the plenum pressure rise is measurable. This problem is particularly challenging since the system is not uniformly completely observable and, hence, none of the output feedback control techniques found in the literature can be applied to recover the performance of a full state feedback controller. |
7,355 | Please write an abstract with title: Research on online course teaching quality evaluation index system in Colleges and Universities, and key words: Deep learning, Analytical models, Information science, Distance learning, Computational modeling, Education, Rough sets. Abstract: At present, colleges and universities evaluate courses in different ways, mainly reflected in the differences of schools, majors and regions. They use different indicators to evaluate teaching quality and the weight of differences. This article introduces the problems existing in the current online teaching quality evaluation, such as unscientific evaluation index weight and imperfect evaluation system, this paper preliminarily determines the weight index by using the analytic hierarchy process, and redistributes the weight index by using the fuzzy quotient space and rough set theory. Finally, a complete set of online course quality evaluation index system is constructed, and a specific example is used to verify the correctness of this method. |
7,356 | Please write an abstract with title: Combining ordered best-first search with branch and bound for exact BDD minimization, and key words: Binary decision diagrams, State-space methods, Data structures, Boolean functions, Artificial intelligence, Minimization methods, Hardware, Costs, Logic design, NP-complete problem. Abstract: Reduced-ordered binary decision diagrams (BDDs) are a data structure for efficient representation and manipulation of Boolean functions. They are frequently used in logic synthesis. The size of BDDs depends on a chosen variable ordering, i.e., the size may vary from linear to exponential, and the problem of improving the variable ordering is known to be NP-complete. In this paper, a new exact BDD minimization algorithm called A/sup stute/ is presented. Here, ordered best-first search, i.e., the A/sup */ algorithm, is combined with a classical branch-and-bound (B&B) algorithm. A/sup */ operates on a state space large parts of which are pruned by a best-first strategy expanding only the most promising states. Combining A/sup */ with B&B allows to avoid unnecessary computations and to save memory. Experimental results demonstrate the efficiency of our approach. |
7,357 | Please write an abstract with title: AutoPhoto: Aesthetic Photo Capture using Reinforcement Learning, and key words: Photography, Measurement, Codes, Navigation, Pipelines, Reinforcement learning, Autonomous agents. Abstract: The process of capturing a well-composed photo is difficult and it takes years of experience to master. We propose a novel pipeline for an autonomous agent to automatically capture an aesthetic photograph by navigating within a local region in a scene. Instead of classical optimization over heuristics such as the rule-of-thirds, we adopt a data-driven aesthetics estimator to assess photo quality. A reinforcement learning framework is used to optimize the model with respect to the learned aesthetics metric. We train our model in simulation with indoor scenes, and we demonstrate that our system can capture aesthetic photos in both simulation and real world environments on a ground robot. To our knowledge, this is the first system that can automatically explore an environment to capture an aesthetic photo with respect to a learned aesthetic estimator. Source code is at https://github.com/HadiZayer/AutoPhoto |
7,358 | Please write an abstract with title: A Switched System Approach Against Time-Delay Attacks in Cyber- Physical Systems, and key words: Delays, Control systems, Switches, Actuators, Switched systems, Uncertainty, Communication channels. Abstract: This paper investigates the modeling and stabilization problem for cyber-physical systems (CPSs) under time-delay attacks. First of all, the attack-induced delays are divided into multiple equilong subintervals and each subinterval is separated into a nominal part and an uncertain part. Then, the system is considered to dwell in different subsystems when the attack-induced delays fall into different subintervals. In this way, the CPS is modeled as a discrete-time switched system with norm-bounded uncertainties. Moreover, the mode-dependent controller is designed to defend the time-delay attacks and guarantee the exponential stability of the closed-loop CPS, which is switched according to the attack-induced delays and implemented combined with the packet-based control strategy. Finally, the experiments of a networked inverted pendulum control system are given to demonstrate the effectiveness of the proposed method. |
7,359 | Please write an abstract with title: A Structured Document Model for Authoring Video-Based Hypermedia, and key words: Navigation, XML, Multimedia systems, Australia, Search engines, Prototypes, Information technology, Image segmentation, Layout, HTML. Abstract: This paper describes a new method for authoring video-based hypermedia. It defines an XML-based (Extensible Markup Language) data modeling language called HyperVideo Authoring Language (HyVAL) for constructing structured documents in which the composition of internal video objects (segments, scenes, shots, frames and visual objects in frames) and external media objects (text, audio, images, html pages, etc.) is specified. The model allows an author to interactively specify various internal objects and relationship among internal and external objects. Through the language, a flexible presentation of video-based hypermedia is achieved and comprehensive viewer interactions with video objects are carried out. The experiment of structuring video-based hypermedia using HyVAL in our authoring and presentation environment is also described in this paper. |
7,360 | Please write an abstract with title: Game Against Nature Based Control of an Intelligent Wheelchair with Adaptation to Pedestrians' Behaviour, and key words: Space vehicles, Adaptation models, Uncertainty, Navigation, Wheelchairs, Games, Predictive models. Abstract: This paper addresses the problem of synthesis of the control law for intelligent wheelchair navigation assistant, intended to support the navigation in dynamic and populated areas. The method presented in this paper uses a deterministic, model-based prediction strategy to generate the wheelchair motion. The motion has the feature that is acceptable by the patient being transported on the wheelchair. Using the long-term pedestrians motion prediction the minimal collision risk control strategy is applied. While concerning the wheelchair navigation and its environmental interactions, an issue arises which is related to the pedestrians' empathy towards a disabled person being carried by the wheelchair. In this work we propose to use this phenomena for designing adaptive, driving strategy of the intelligent wheelchair. An intelligent motion controller proposed in this paper, generates collision free trajectory based on safe distance policy and evaluation of the environmental response. By comparing the predicted pedestrians behaviour to the real one, the system adapts control strategy coming from game against nature formalism and Hurwicz criterion based solution. The method performance was evaluated in a simulated environment. Relevant simulation scenarios are presented and discussed. |
7,361 | Please write an abstract with title: An Artificial Intelligence Framework for Estimating the Cost and Duration of Autonomous Electric Vehicle Maintenance, and key words: Vibrations, Training, Histograms, Uncertainty, Transportation, Vehicle crash testing, Delays. Abstract: Transportation, healthcare, manufacturing, office automation, and industrial automation all rely heavily on AI. Automating industrial physical systems necessitates the use of artificial / computational intelligence techniques. Adaptive Neural Networks, Machine Learning, and Deep Learning algorithms are used to identify and predict images based on the learning data. One of the most important goals is to find a low-cost replacement for the current methods. Misfire is a primary focus of the current research, which makes extensive use of the engine block's vibration signature. Fuel consumption-related characteristics such as air filter choking, gear knock, excessive engine speed, and low tyre pressure might be monitored using the same sensor data. In addition to detecting two-cylinder misfires simultaneously, the model's performance was assessed at various speeds and under load. For the vehicle management system to be created over the existing misfire detection model, all these model additions must perform consistently. Engine misfire detection with simultaneous misfire cannot be reliably detected using histogram characteristics in any format. An axial crash test simulation can be completed in 270 times less time using an artificial intelligence framework, but accuracy is sacrificed in the process. The framework's training time could be decreased from 111 hours to 37 minutes for a single sample or 3 hours for an ensemble of models, but accuracy would be sacrificed in the process. |
7,362 | Please write an abstract with title: An Efficient Intrusion Detection Model Based on Recurrent Neural Network, and key words: Deep learning, Support vector machines, Recurrent neural networks, Intrusion detection, Telecommunication traffic, Feature extraction, Numerical models. Abstract: Intrusion detection has proven to be an efficient strategy of information security since it can identify unknown attacks from network traffic. The existing method to detect network anomalies is often based on classic machine learning models like KNN, SVM, and others. Even though these techniques can provide some impressive results, they have a poor level of accuracy and rely primarily on manual system design is required in feature extraction which is no longer relevant in the big data era. A deep learning-based intrusion detection methodology is suggested in this method to address the issues of low accuracy and feature extraction. The recurrent neural network is used in this approach with three steps in preprocessing such as data numerical conversion, data normalization, and data balancing. It can efficiently represent network traffic flow and enhance the capacity to identify anomalies. The suggested model is put to the test using a publicly available benchmark dataset, and the findings show that it outperforms alternative comparison approaches. The result analysis of the proposed method shows that the average accuracy is 99.56%, average TPR is 99.55%, average TNR is 99.32%. |
7,363 | Please write an abstract with title: Legendre distribution for radiation pattern, and key words: Polynomials, Phased arrays, Chebyshev approximation, Equations, Laboratories, Electromagnetic fields, Current distribution. Abstract: The electromagnetic field from a group of radiators depends upon amplitude and phase distribution of the source. The distributions, which are of considerable interest in the mathematical theory of linear arrays, are the Chebyshev, uniform, triangular, and binomial. The radiation patterns of these distributions are highly directive. The Legendre distribution is considered |
7,364 | Please write an abstract with title: Investigation of the Fiber-Forming Properties from Ternary Solutions Containing PVA and Nutraceptics Additives on Electrospinning Process, and key words: Proteins, Additives, Power transmission, Voltage, Optical fiber communication, Skin, Polymers. Abstract: The article defines the optimal electrospinning process conditions of vertical power transmission for a solution with a triple composition of polyvinyl alcohol (PVA) polymer, antiseptic additives such as chlorhexidine gluconate (CHG), and natural protein (Sericin) as a regenerative natural product. The average diameters of the fibers obtained under optimal conditions, as well as the area covered by them and the number of defects, are calculated. The increased number of spindles observed is due to the addition of sericin and its incomplete conversion from globular to linear form of the protein macromolecule during the electrospinning process. When the distance between the nozzle and the collector is increased while the voltage remains constant, the nozzle diameter must be changed. |
7,365 | Please write an abstract with title: A New Network shortest path algorithm via Neutrosophic support digraph, and key words: Fuzzy sets, Electron traps, Neural networks, Decision making, Information and communication technology, Geographic information systems, Business. Abstract: In the literature, there have been several studies and introductions of fuzzy set extension and generalisation. A extension of the intuitionistic fuzzy set and fuzzy graph is the neutrosophic support digraph. The neutrosophic support graph is referred to as neutrosophic support digraph in this study since several fundamental operations are redefined (in short NSDG). NSDG is discussed in terms of mathematical operations and relationships. We also developed a scoring function-based approach to solving the shortest route issue. |
7,366 | Please write an abstract with title: Normalization of ambient background intensity in high-resolution sonar imagery and its impact on mine detection and classification, and key words: Sonar detection, Systems engineering and theory, Sea measurements, Reflectivity, Lighting, Sea floor, Frequency, Bandwidth, Image segmentation. Abstract: In high-resolution sonar imagery, large variations in the intensity of the ambient background are caused by variations in sea bottom reflectance and irregular illumination of the sea floor caused by sonar platform motion. These variations in the background are often difficult to reliably distinguish from regions of actual target highlight and shadow, especially when the quality of the target signature is fair to poor. Contributing to this problem is the fact that the spatial frequencies of the varying background are often in the same spatial bandwidth as the targets. Consequently, image-processing methods that attempt to segment image regions, associated with target highlight (or shadow), are often fooled by bright (or dark) target-size patches of background. This typically results in an increase of the number of false alarms. This paper describes several new image normalization methods that attempt to remove the variations of the ambient bottom while minimizing the distortion of the target signature. Results are presented that show the impact of the image normalization on reducing false alarms and preserving a high probability of mine detection and classification. |
7,367 | Please write an abstract with title: Intelligent HealthCare System using Raspberry Pi, and key words: Technological innovation, Protocols, Hospitals, Databases, Real-time systems, Mobile handsets, Mobile applications. Abstract: The Internet of Things (IoT) is a trendy topic having social, economic, and technological consequences. It’s built using a protocol that makes it easier to engage and communicate with one another and with users. Healthcare is an important part of the Internet of Things because it reduces obstacles that patients and clinicians experience. By boosting the usefulness of a patient’s important information, the suggested solution delivers a new healthcare system that is scalable and flexible. The suggested solution gathers essential data from existing hospital-grade equipment in a portable container that can wirelessly communicate with database, which can then be monitored on any mobile or internet-connected device. To keep the kit modest, an Arduino is utilized, and the data is collected and processed by a Raspberry Pi before being stored in a Firebase database. An android application has been developed to display the result of patient. In this research, we provide a new and intelligent healthcare system based on modern technologies like the Internet of Things (IoT). This technology is smart enough to sense and process a patient’s data using a medical decision support system. This device offers a low-cost solution for people who live in remote areas; they can use it to detect if they have a serious health problem and seek treatment from nearby hospitals. |
7,368 | Please write an abstract with title: Platoon-based Cooperative Intersection Management Strategies, and key words: Throughput, Delays, Roads, Real-time systems, Junctions, Scheduling, Aerospace electronics. Abstract: Intelligent transportation systems and the concept of cooperative autonomous vehicles has emerged as an efficient solution for enhancing the mobility of mixed traffic and counteracting the ever-increasing traffic congestion. Since the bottleneck of traffic flow and the most accident-prone areas are road intersections, this paper discusses cooperative platoon based scheduling strategies for managing traffic at road intersections. In this paper, proximity based cooperative traffic control strategy is implemented which prioritizes platoons based on their proximity to the intersection. It is a decentralized approach where the decisions are based on real-time traffic data obtained from surrounding platoons via wireless communication. The objective is to reduce the halt time of vehicles at intersections. The proposed decentralized strategy is presented against two state-of-the-art cooperative strategies. Simulation results show that the proposed decentralized strategy improves traffic throughput in terms of distance traveled by vehicles. |
7,369 | Please write an abstract with title: Automated Code Transformations: Dealing with the Aftermath, and key words: Industries, Codes, Costs, Quality assurance, System integration, Aging, Maintenance engineering. Abstract: Dealing with legacy systems has been a challenge for the industry for decades. The pressure to efficiently modernise legacy assets to meet new business needs and minimise associated risks is increasing. Automated code transformation, which is associated with serious (long-known) risks, is a high priority in the industrial environment due to the cost structure, the effort required and the supposed time savings. However, little has been published about the long-term effects of successful migrations. This paper looks at three different cases of automated code transformation at different stages of their lifecycle, highlights the lessons learned and derives a number of recommendations that should be useful for planning and executing future transformations. |
7,370 | Please write an abstract with title: Electron and hole mobility enhancement in strained SOI by wafer bonding, and key words: Silicon, Germanium alloys, Silicon alloys, Semiconductor materials, Silicon on insulator technology, Wafer bonding, Charge carrier mobility, CMOS integrated circuits, MOSFETs. Abstract: N- and p-MOSFETs have been fabricated in strained Si-on-SiGe-on-insulator (SSOI) with high (15-25%) Ge content. Wafer bonding and H-induced layer transfer techniques enabled the fabrication of the high Ge content SiGe-on-insulator (SGOI) substrates. Mobility enhancement of 50% for electrons (with 15% Ge) and 15-20% for holes (with 20-25% Ge) has been demonstrated in SSOI MOSFETs. These mobility enhancements are commensurate with those reported for FETs fabricated on strained silicon on bulk SiGe substrates. |
7,371 | Please write an abstract with title: High Symbol-Rate Signal Optimization for Long-Haul Transmission Systems over 1-Tbps/λ Net-Data Rate, and key words: Europe, Bandwidth, Transceivers, Optical fiber communication, Optical noise, Optical modulation, Optimization. Abstract: We discuss the theoretical and practical aspects of high symbol-rate signal optimization techniques for realizing a >1-Tbps/λ long-haul transmission system. We also review the key technologies for transmitting the high symbol-rate signal such as modulation format design, bandwidth extension techniques, and equalization schemes. |
7,372 | Please write an abstract with title: An Improved ResNet Algorithm Based On CBAM, and key words: Deep learning, Adaptation models, Image recognition, Target recognition, Neural networks, Training data, Interference. Abstract: Flower recognition has important application value in the field of flower cultivation and planting. As a kind of fine-grained image recognition, the traditional flower recognition has the problem of low recognition accuracy. In order to solve these problems, this paper proposes a neural network algorithm of ResNet structure that integrates CBAM mechanism, and adds residual blocks of attention modules to the second layer to the fifth layer of the ResNet structure. Finally, the results are output through adaptive average pooling and full connection layer. Experimental results show that the recognition accuracy of the model is close to 98% even when the recognition is difficult and there are few training data. Compared with the traditional deep learning model, the model proposed in this paper significantly improves the recognition accuracy. |
7,373 | Please write an abstract with title: Detection of faces in a color natural scene using skin color classification and template matching, and key words: Face detection, Layout, Skin, Humans, Classification algorithms, Filters, Facial features, Eyes, Mouth, Shape. Abstract: In this paper, an efficient algorithm for the detection of human faces in a color nature scene is proposed. The proposed algorithm consists of two sections. The first section is the segmentation of skin color regions using color information. Large data of chrominance like skin pixels is collected and analyzed in a training process to study its distributions. Then a binary color map is obtained by applying the skin/non-skin color classification algorithm. Thereafter, we use a boost filter algorithm to generate the facial features (eyes, mouth), then are merged with the obtained color map. The second section is to perform face verification by aligning a model of faces representing a front view face in a template-matching process. The fitness is calculated between the model and the candidate face regions to verify the elliptical shape of face regions. 50 images are used to examine the algorithm performance, and experimental results demonstrate that our algorithm can deal with different sizes, and different lighting conditions problems. A comparison between our algorithm and a well known related algorithm is demonstrated. The experimental results reveal that the proposed algorithm gives better results than the traditional algorithm in terms of accuracy, and time consumption |
7,374 | Please write an abstract with title: Early Blindness Detection Based on Retinal Images Using Ensemble Learning, and key words: diabetic retinopathy, retinal image processing, image augmentation, tone mapping, histogram, feature extraction, ensemble learning, APTOS 2019 blindness detection. Abstract: Diabetic retinopathy (DR) is the primary cause of vision loss among grown-up people around the world. In four out of five cases having diabetes for a prolonged period leads to DR. If detected early, more than 90% of the new DR occurrences can be prevented from turning into blindness through proper treatment. Despite having multiple treatment procedures available that are well-capable to deal with DR, the negligence and failure of early detection cost most of the DR patients their precious eyesight. The recent developments in the field of Digital Image Processing (DIP) and Machine Learning (ML) have paved the way to use machines in this regard. The contemporary technologies allow us to develop devices capable of automatically detecting the condition of a person’s eyes based on their retinal images. However, in practice, several factors hinder the quality of the captured images and impede the detection outcome. In this study, a novel early blind detection method has been proposed based on the color information extracted from retinal images using an ensemble learning algorithm. The method has been tested on a set of retinal images collected from people living in the rural areas of South Asia, which resulted in a 91% classification accuracy. |
7,375 | Please write an abstract with title: Identifying Influential Spreaders in Social Networks Through Discrete Moth-Flame Optimization, and key words: Optimization, Social networking (online), Computational modeling, Search problems, Heuristic algorithms, Estimation, Cost accounting. Abstract: Influence maximization in a social network refers to the selection of node sets that support the fastest and broadest propagation of information under a chosen transmission model. The efficient identification of such influence-maximizing groups is an active area of research with diverse practical relevance. Greedy-based methods can provide solutions of reliable accuracy, but the computational cost of the required Monte Carlo simulations renders them infeasible for large networks. Meanwhile, although network structure-based centrality methods can be efficient, they typically achieve poor recognition accuracy. Here, we establish an effective influence assessment model based both on the total valuation and variance in valuation of neighbor nodes, motivated by the possibility of unreliable communication channels. We then develop a discrete moth-flame optimization method to search for influence-maximizing node sets, using a local crossover and mutation evolution scheme atop the canonical moth position updates. To accelerate convergence, a search area selection scheme derived from a degree-based heuristic is used. The experimental results on five real-world social networks, comparing our proposed method against several alternatives in the current literature, indicates our approach to be effective and robust in tackling the influence maximization problem. |
7,376 | Please write an abstract with title: A Conceptual Framework for Designing Mobile Augmented Reality Self-Directed Learning Practical Module on Direct-On-Line Motor Control, and key words: Wiring, Motor drives, Automation, Induction motors, Pandemics, Education, Mobile applications. Abstract: The pandemic of SARS-COVID-19 has given a major impact on many educational institutions. In this situation, Teaching and Learning (T&L) become an issue, especially for the practical learning session that requires certain teaching aid using the latest technology. Currently, T&L was delivered through an online medium. Direct On-Line (DOL) starter in automation is a method of starting a 3-phase induction motor that is connected directly across its 3-phase supply. Its starter applies the full line voltage to the motor terminals. However, during this pandemic, the lab session for doing the wiring and testing for DOL motor control is limited to a demonstration by the lecturer via video, and students will do the wiring on paper or using the software. Mobile learning can be an alternative learning tool for this group of students. Therefore, this paper aims to propose a conceptual framework for designing a mobile Augmented Reality (AR) Self-Directed Learning (SDL) practical module on DOL motor control for subjects related to industrial automation. The framework consists of an SDL, a motivational Flow Theory (engagement), User Experience Design (UX-D) using an AR environment to learn the practical part of DOL motor control. |
7,377 | Please write an abstract with title: Comparing Power Scattered by RIS with Natural Scatter around Urban Corners, and key words: Wireless communication, Phased arrays, Power measurement, Surface waves, Buildings, Scattering, Phase control. Abstract: Reflective Intelligent Surfaces (RIS) are considered promising in improving coverage in Non-Line of sight (NLOS) wireless links, especially at mm wave bands. Coverage provided by RIS is here compared to coverage from such ambient propagation mechanisms as scattering from street poles, rough building walls and corner diffraction. It is found that such background scatter provides signal levels around an urban street corner comparable to that of an ideal 0.3m x 0.3 m RIS at 28 GHz. Larger area RIS is thus required to deliver substantial gain in such a scenario. |
7,378 | Please write an abstract with title: Facial Expression Recognition for OoD Generation Using Risk Extrapolation, and key words: Training, Computers, Extrapolation, Emotion recognition, Cloud computing, Image resolution, Face recognition. Abstract: Humans express emotions through facial expressions. It's easy for humans to recognize these emotions, but it's a very challenging task for computers. Every face image will be different because of the differences in brightness, contrast, resolution, angle, etc. when taking an image. which is why Out-of-distribution (OoD)Generalizing for facial recognition expression is very difficult. In pursuit of strong OoD generalization, We introduce the principle of Risk Extrapolation (REx) into the field of face recognition. The robustness of affine combination of training environments is enhanced by making each training risk equal. In this paper, we identified seven basic facial expressions and improve their adaptability based on risk extrapolation from multiple datasets. |
7,379 | Please write an abstract with title: DLEP: A Deep Learning Model for Earthquake Prediction, and key words: Earthquakes, Feature extraction, Machine learning, Predictive models, Electric shock, Geology, Convolution. Abstract: Earthquakes are one of the most costly natural disasters facing human beings, which happens without an explicit warning, therefore earthquake prediction becomes a very important and challenging task for humanity. Although many existing methods attempt to address this task, most of them use either seismic indicators (explicit features) designed by geologists, or feature vectors (implicit features) extracted by deep learning methods, to characterize an earthquake for earthquake prediction. The problem of combining these two kind of features to improve final earthquake prediction performance remains pretty much open. To this end, we propose a deep learning model named DLEP to effectively fuse the explicit and implicit features for accurate earthquake prediction. In DLEP, we adopt eight precursory pattern-based indicators as the explicit features, and use a convolutional neural network (CNN) to extract implicit features. Then, an attention-based strategy is suggested to fuse these two kinds of features well. In addition, a dynamic loss function is designed to deal with the category imbalance of seismic data. Finally, experimental results on eight datasets from different regions demonstrate the effectiveness of the proposed DLEP for earthquake prediction comparing to several state-of-the-art baselines. |
7,380 | Please write an abstract with title: Millimeter-wave integrated circuits, and key words: Millimeter wave integrated circuits, Millimeter wave technology, FETs, Optical receivers, Microwave devices, Optical waveguides, Coplanar transmission lines, Distributed parameter circuits, Diodes, Oscillators. Abstract: Summary form only given. The size of the millimeter wave (mmW) market has not yet lived up to predictions. Consequently, companies have been unwilling t o invest the large sums required to solve formidable technical problems. Now, one can see a huge potential for local data and other communications, miniature radars for autos, trains etc., radiometric seekers, and even smart bullets as real possibilities. |
7,381 | Please write an abstract with title: Design of High-Voltage Power Transmission Insulators Based on Ultrasonic Technology, and key words: Insulators, Acoustics, High-voltage techniques, Ceramics, Power transmission, Power supplies, Voltage. Abstract: To solve the power supply problem of high voltage equipment in electric power systems, this article proposes an innovative ultrasonic power transmission (UPT) insulator system with high-voltage insulation and power transfer capabilities. The design scheme of an UPT insulator system, which can achieve an insulation distance of a few meters, is introduced in detail. System characteristics and energy loss are analyzed using different insulation transmission materials based on the equivalent circuit model of an UPT system, and a circuit design method is introduced. Furthermore, the main causes of energy loss are analyzed by simulation, and the structure of an UPT insulator system is optimized to improve transmission efficiency. Finally, a prototype of the UPT insulator with a maximum transmission efficiency of 57.28% and an output power of 72.62 W is constructed. The total length of the insulator is 1 m, which ensures that it can withstand a dc voltage of 50 kV. In addition, the insulation distance of the proposed UPT insulator design can be further increased without impacting the system performance. |
7,382 | Please write an abstract with title: Commercial Micro Computer Chips for Integrated Phased Array Control, and key words: Phased arrays, Microcomputers, Antenna arrays, Radar antennas, Beam steering, Concurrent computing, Phase shifters, Equations, Costs, Application software. Abstract: Low cost commercial microcomputers, (currently used in many diverse applications, e.g. point-of-sale terminals, desk top computers, check processors, etc.), despite their relatively low computational speed, provide the opportunity for computing beam steering and shaping phase shifts for large phased-array antennas at high beam switching rates through the use of federated multi-computer techniques. |
7,383 | Please write an abstract with title: Inter-data commonality detection for spectrum monitoring in wireless sensor networks, and key words: Monitoring, Sensors, Logic gates, Wireless sensor networks, Greedy algorithms, Signal processing algorithms, Task analysis. Abstract: Cooperative spectrum monitoring with multiple sensors has been deemed as an efficient mechanism for improving the monitoring accuracy and enlarging the monitoring area in wireless sensor networks. However, there exists redundancy among the spectrum data collected by a sensor node within a data collection period, which may reduce the data uploading efficiency. In this paper, we investigate the inter-data commonality detection which describes how much two data have in common. We define common segment set and divide it into six categories firstly, then a method to measure a common segment set is conducted by extracting commonality between two files. Moreover, the existing algorithms fail in finding a good common segment set, so Common Data Measurement (CDM) algorithm that can identify a good common segment set based on inter-data commonality detection is proposed. Theoretical analysis proves that CDM algorithm achieves a good measurement for the commonality between two strings. In addition, we conduct an synthetic dataset which are produced randomly. Numerical results shows that CDM algorithm can get better performance in measuring commonality between two binary files compared with Greedy-String-Tiling (GST) algorithm and simple greedy algorithm. |
7,384 | Please write an abstract with title: Microseismic First-Arrival Picking Using Fine-Tuning Feature Pyramid Networks, and key words: Data models, Predictive models, Noise measurement, Numerical models, Computational modeling, Training data, Feature extraction. Abstract: Microseismic event picking is one of the key steps in seismic processing and imaging. Manually picking is a widely used way to pick the microseismic events, which is time-consuming. The standard short-term average/long-term average (STA/LTA) is a traditional method to pick the microseismic first arrivals, which would lead to inaccurate first-arrival picks in case of low signal-to-noise ratio (SNR). We developed a workflow to automatically pick the microseismic first arrivals by using the feature pyramid networks (FPNs). To train the proposed model, we first randomly select part of the microseismic traces and manually pick the time index of the first arrivals. Next, we segment every selected trace into two parts based on the time index of the manual picking and then assign each part a label. Afterward, we train the proposed fine-tuning FPN model by using the training data and the corresponding labels. It should be noticed that we proposed a loss function, named the point-aware loss, for solving the microseismic first-arrival picking issue. Finally, we predict the microseismic first arrivals by using the well-trained fine-tuning FPN model. The numerical examples demonstrate that our proposed model successfully identifies the microseismic first arrivals. The microseismic first arrivals predicted by using our proposed model are more robust and more accurate than those obtained by using the STA/LTA and the encoder–decoder network. |
7,385 | Please write an abstract with title: A Link Quality Estimation Method for Wireless Sensor Networks Based on the Ladder Network, and key words: Wireless communication, Fading channels, Wireless sensor networks, Correlation, Conferences, Estimation, Interference. Abstract: Wireless Sensor Networks are affected by multipath fading, noise, and interference in the deployment environment, which makes wireless communication unreliable. Accurate and effective evaluation of communication link quality is helpful to assist the design of high-level routing protocol, ensure network throughput, and reduce retransmission. In this paper, a link quality estimation method based on ladder network is proposed: PAM(partitioning around medoids) algorithm is used to divide the link quality Grade, which as a basis for measuring the quality of the link; To improve the robustness and correlation of link features, ladder network is used to build link quality estimator to evaluate link quality. Data are collected in different interference scenarios. In the experiment, compared with other methods, the proposed link quality estimator has better precision and fl-score. |
7,386 | Please write an abstract with title: Comparative Analysis of Different Symmetric Encryption Techniques Based on Computation Time, and key words: Encryption, Security, Cloud computing, Fish, Encoding, Decoding, Time complexity. Abstract: Lately the trend of the internet is taking a front seat for different applications. Organizations are collecting and processing and then sharing the data using the internet. Sharing using public network will invite various security lapses in the data. Security will remain the maj or thrust in the area for providing enough level of security for the data. Encryption is the best way to provide security for the data. There are two different types of approaches for ensuring data security. These techniques are symmetric and asymmetric. The symmetric technique includes different approaches with variation in the time and space complexity. In this research paper five different techniques of the symmetric approaches are compared for three different length strings. AES is the best performing in all the three cases. The time comparison for the AES with different techniques is comparatively better than the other four techniques like IDEA, RC6, Two Fish, MARS. |
7,387 | Please write an abstract with title: Glaucoma Detection: Joint Segmentation and Classification Framework via Deep Ensemble Network, and key words: Feature extraction, Image segmentation, Training, Optical imaging, Decoding, Neural networks, Robots. Abstract: Clinical research shows that glaucoma is primarily caused by pathological changes in the optic nerve structure, which may bring about irreversible damage of sight. In relevant literature research, the cup-to-disc ratio (CDR) is mainly used as an important indicator for glaucoma detection, which needs to segment optic disc (OD) and optic cup (OC) region clearly and accurately. However, due to the low contrast image of boundary, the segmentation of OD and OC is still a challenging problem. In this paper, a novel hybrid model based on the ensemble random-forest deep-neural-network (RF-DNN) is proposed for OD and OC segmentation, which can calculate more accurately for glaucoma detection. At the same time, the advantages of DNN and ensemble RF are combined to carry out the corresponding feature extraction and classification, which employs the winner-takes-all strategically to the segmentation and classification for glaucoma detection. Finally, the experiment result shows that the proposed method has reached the best evaluation level in terms of OD and OC segmentation results on ORIGA dataset and SCES dataset, which achieves highest diagnosis accuracy with AUC of 0.96 and 0.98 on ORIGA dataset and SCES dataset, respectively. |
7,388 | Please write an abstract with title: Defining a Use Case for the ADMS Test Bed: Fault Location, Isolation, and Service Restoration with Distributed Energy Resources, and key words: Electric potential, Renewable energy sources, Fault location, Power industry, Distributed power generation, Smart grids, Reliability. Abstract: Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. After experiments are completed, results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid. |
7,389 | Please write an abstract with title: Research on the Performance of Sound Absorption Coating Based on Piezoelectric Shunt Damping, and key words: Damping, Resistance, Resistors, Inductance, Absorption, Piezoelectric materials, Piezoelectric effect. Abstract: The traditional sound-absorbing structure converts sound energy into heat energy through internal friction of the damping material to be absorbed in order to achieve the purpose of reducing sound energy. This paper proposes a piezoelectric shunt damping sound absorption control scheme based on the positive piezoelectric effect of piezoelectric materials. The external sound is connected to the composite material formed by piezoelectric ceramics and rubber by an external circuit system formed by resistors, inductances, and capacitors. It can be converted into electric energy, and the sound wave energy is consumed by resistance heating. This solution can effectively improve the low-frequency sound absorption performance, thereby realizing wide-band reflected sound control. |
7,390 | Please write an abstract with title: Four-Antenna Analog Beamformer Prototype with Automatic Phase Control, and key words: Beamforming, prototype, antenna array, automatic control, phase. Abstract: Beamforming techniques, which steer the radiation pattern of an antenna array according to the needs of the communication system, have had a renewed interest in recent years due to their potential application in nest-generation wireless networks. In tbis paper, we present an analog beamforming prototype with automatic phase controL Current literatore in the subject is Umlted to theoretical studies thst assume Ideal RF phase shifters, and do not consider relewnt implementation parameters such as settling time, steady-state error, or system nonlinearities. Our prototype performs a classic PID control over the phase shifters, which are always analyzed in open loop in current literature, providing a novel approach. This prototype is expected to contribute to the implementation of future hybrid beamforming systems (combining digital processing) that bave only been theoretically analyzed so far. In addition, the prototype is a didactic example of the integration nf control systems, communication systems, signal processing, and antenna theory. |
7,391 | Please write an abstract with title: High-sensitivity flexible sensor based on silver nanowire aerogel, and key words: Silver, Sensitivity, Composite materials, Conductivity, Robot sensing systems, Stability analysis, Sensors. Abstract: Simulating various human perceptions through flexible electronic sensors is the key to the development of artificial intelligence and biomimetic robots. In this paper, a novel composite material of Silver nanowire aerogel(AgNWA) and conventional flexible polymer, such as PDMS, PI or other flexible polymers, is proposed to fabricate flexible sensors. The AgNWA used in this paper is a three-dimensional porous material self-assembled from silver nanowire, which combines the ultra-high conductivity of silver and the ultra-low density of aerogel materials as well as the flexibility. Hence, the conductivity of AgNWA would change immediately even a minor pressure applied. Based on this property, we fabricated flexible AgNWA/PDMS elaster and applied it to the field of flexible sensing. The AgNWA/PDMS elaster has shown excellent sensitivity to contact pressure, which can detect the stress in the range of 6kPa-1MPa. In addition, the resistance change rate of this composite material has a linear relationship with the stress received, so this composite material can sense the magnitude of the contact pressure. Furthermore, this composite material has good stability, and the minimum strain fatigue failure number is not less than 5000 times, maintaining surface integrity and structural flexibility. Therefore, the AgNWA/PDMS elaster has excellent sensitivity and stability, which provides a new way to realize flexible sensing. |
7,392 | Please write an abstract with title: Hybrid Connected Unified Power Quality Conditioner Integrating Distributed Generation With Reduced Power Capacity and Enhanced Conversion Efficiency, and key words: DC-DC power converters, Power quality, Topology, Load flow, Hybrid power systems, Distributed power generation, Voltage control. Abstract: In this article, a hybrid connected unified power quality conditioner integrating distributed generation (HCUPQC-DG) is proposed. Two dc ports are created at the dc link of the HCUPQC-DG, in which one low-voltage (LV) dc port is directly connected to distributed generation (DG), and the other high-voltage (HV) dc port is indirectly connected to DG through the front-end dc-dc converter. With the hybrid connected configuration, the HV is designed to ensure the dc-ac voltage conversion capability, whereas the LV, i.e., the voltage of DG, can be relatively low and vary in a wide range. Besides, most active power can be directly transferred from DG to the ac load or grid through the direct power flow path. Hence, the conversion efficiency is enhanced, and the power capacity of the front-end dc-dc converter is significantly reduced. The operating principle and the control and modulation strategies of the proposed HCUPQC-DG are discussed. Moreover, the power flow through the HCUPQC-DG is analyzed in detail to understand the system operation. Experimental results with a 3-kVA prototype are provided to verify the feasibility and effectiveness of the proposed HCUPQC-DG. |
7,393 | Please write an abstract with title: An effective method of color image recognition, and key words: Color, Image recognition, Quaternions, Matrix decomposition, Feature extraction, Pixel, Singular value decomposition, Radio access networks, Computer science, Mathematics. Abstract: An effective method of color image recognition is proposed in this paper. The singular value (SV) feature vector is firstly extracted as algebraic feature of color image; then the characteristic matrix of image is presented, which is made up of the SV feature vector of image. And then using the similarity of the characteristic matrices, the method for recognition is established. The recognition rate is satisfactory from the experiment. |
7,394 | Please write an abstract with title: A 3 /spl mu/m NMOS high-performance LPC speech synthesizer chip, and key words: MOS devices, Linear predictive coding, Speech synthesis, Synthesizers, Microcomputers, Vocabulary, Read only memory, Digital filters, Speech processing, Integrated circuit technology. Abstract: A high performance speech processing integrated circuit (SPIC) based on linear predictive coding (LPC) techniques is presented. Both system and technological aspects of the SPCI design are covered in detail. The SPIC synthesizer chip will normally be used in a three-chip minimum system configuration including the synthesizer, a microcomputer, and an external vocabulary ROM. The speech quality can be tailored to the user's requirements by varying the bit rate between the vocabulary ROM and the microcomputer from 1.1 to 8.5 kbit/s. Among the specific features of the SPIC are pitch synchronous synthesis, speech parameters interpolation capability, silence, and power-down mode. Moreover, the digital filter output is interpolated at a high sampling rate (32 kHz) to avoid the necessity for off-chip filtering. An 8-bit PCM output (A law) and a 16-bit linear-coded output are provided. The SPIC can be delivered in two different bonding configurations either for small system application (three-chip system) or for larger system configuration. |
7,395 | Please write an abstract with title: Ka-band MMIC LNA Design, and key words: Noise figure, Microstrip, Low-noise amplifiers, Gain, Circuit stability, Integrated circuit modeling, Stability analysis. Abstract: In order to better adapt to the requirements of smaller noise and better performance in low-noise amplifiers in radio communications,this article simulates and designs a 35GHz broadband monolithic microwave integrated circuit (MMIC) low noise amplifier,by adopting InGaAs pseudo-crystal high electron mobility transistor (pHEMT) process model. The circuit uses a three-stage cascaded dual power supply structure. The front-stage amplifier circuit optimizes the noise figure while ensuring a good input and output standing wave ratio. The last two stages provide maximum gain matching, which guarantees the good noise figure, gain flatness and VSWR of the overall amplifier.In addition, the source negative feedback inductance and bias network circuit of each stage are optimized to achieve a broadband output and high gain under low noise. The simulation design shows that under the working conditions of gate and drain bias voltages of -0.5V and 3V, and current of 90mA respectively, the amplifier has a minimum noise figure of less than 2dB and a maximum gain of more than 20dB in the 25-45GHz band. At 35GHz, it has a minimum noise figure of 1.702dB, a maximum gain of 24.594dB, an input standing wave ratio of 2.236 and an output standing wave ratio of 1.122.The designed low-noise amplifier can be implemented in a broadband millimeter wave transceiver system. |
7,396 | Please write an abstract with title: A new solution for inverse kinematics of manipulator based on neural network, and key words: Neural networks, Manipulators, Fuzzy systems, Motion control, Equations, Jacobian matrices, Computational modeling, Robot kinematics, Angular velocity control, Angular velocity. Abstract: This paper deals with the inverse kinematics problem of manipulator. Based on ANFIS (adaptive neural fuzzy inference system) neural network, the inverse kinematics solution of manipulator is set up. Simulation results indicate that this method has the advantage of faster learning rate, higher identifying precision and better real-time ability. Therefore, a new way for solving the inverse kinematics of manipulator is provided. |
7,397 | Please write an abstract with title: Laser Spectroscopy for Marine Biofouling Analysis, and key words: Spectroscopy, Databases, Oceans, Sea measurements, Measurement by laser beam, Substrates, Monitoring. Abstract: In the present study, femtosecond Laser Induced Breakdown Spectroscopy LIBS technique has been used to investigate the growth of biofouling on Fiber Reinforced Plastic (FRP) panels submerged in the Indian Ocean for various stages of growth. The coupons were suspended in the Indian Ocean at a depth of 1m at a distance of 480 m from the shoreline. The panels were recovered from the sea at regular intervals of 5, 10, 15 and 20 days. Growth of fouling panels were monitored and related with contact angle measurements. Elemental characterization conducted with Femtosecond LIBS indicated the presence of the elements Al, Ca, N, Ba, and Na. The study would help in creating a database for marine biofouling. |
7,398 | Please write an abstract with title: Analysis of Electric Vehicle Load Storage Resource Potential Based on R-ANN Activity Behavior Model, and key words: Space vehicles, Electric potential, System integration, Predictive models, Electric vehicles, Data models, Load modeling. Abstract: Electric vehicles have extensive and flexible energy dispatch potential. The difference in user behavior results in different temporal and spatial distribution characteristics of electric vehicle charging demand. In order to be able to quickly and accurately calculate the charging power of large-scale electric vehicles and the potential of the storage resources it can provide, it is necessary to explore the temporal and spatial characteristics and laws. Analyze the travel time and space data of electric vehicles, and get the probability distribution of travel start and end time. A new neural network (R-ANN) prediction model based on a space-time activity, the use of rough set theory, activity data to predict the behavior of the electric vehicle travel mileage by historical time and launch the required charging time can solve the time and mileage do not match Under the circumstances, the probability model is used to calculate the charging power of a single vehicle to realize the quantitative calculation of the storage capacity of electric vehicle clusters. Finally, the simulation obtains the charging law of large-scale automobile clusters, and predicts the potential of electric vehicle storage resources at different times of the day through calculation examples. |
7,399 | Please write an abstract with title: Can Selfless Learning improve accuracy of a single classification task?, and key words: Training, Computer vision, Conferences, Neurons, Task analysis. Abstract: The human brain has billions of neurons. However, we perform tasks using only a few concurrently active neurons. Moreover, an activated neuron inhibits the activity of its neighbors. Selfless Learning exploits these neurobiological principles to solve the problem of catastrophic forgetting in continual learning. In this paper, we ask a basic question: can the selfless learning idea be used to improve the accuracy of deep convolutional networks on a single classification task? To achieve this goal, we introduce two regularizers and formulate a curriculum learning-esque strategy to effectively enforce these regularizers on a network. This has resulted in significant gains over vanilla cross-entropy training. Moreover, we have shown that our method can be used in conjunction with other popular learning paradigms like curriculum learning. |
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