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14,400 | Please write an abstract with title: Time-delay phase shifter controlled by piezoelectric transducer on coplanar waveguide, and key words: Phase shifters, Piezoelectric transducers, Coplanar waveguides, Microstrip, Positron emission tomography, Electromagnetic waveguides, Dielectric constant, Electromagnetic fields, Phased arrays, Wideband. Abstract: A time-delay phase shifter controlled by piezoelectric transducer (PET) is realized on a coplanar waveguide (CPW). The effective dielectric constant, propagation constant, etc., of the CPW are varied by the perturbation controlled by a PET. Compared to the perturbation on a microstrip line, published previously, the new CPW device provides 50% more phase shift. |
14,401 | Please write an abstract with title: TCP Capacity Utilization In Next Generation Passive Optical Network During Degradation Attack, and key words: Degradation, Resistance, Protocols, Heuristic algorithms, Throughput, Optical network units, Passive optical networks. Abstract: The next-generation gigabit passive optical network (NG-PON) is a promising expansion and growth solution for access networks. NG-PON aims to connect more people as the fiber-to-the-home (FTTH) concept is implemented. However, immediate attention is required due to threats to its security infrastructure, such as degradation attacks in the presence of transmission protocol (TCP) traffic environments. Throughout the attack, TCP congestion management is activated to manage collisions. This research investigates the relationship between TCP response in the transport layer while enduring attack in the MAC layer. Two types of TCP were evaluated for resistance to the attack. New Reno TCP reduced link consumption by 54%, whereas high-speed TCP (HSTCP) only reduced it by 37%. The capability of TCP's congestion window to regain quickly in HSTCP demonstrates that TCP flavor contributes to sustaining network performance under attack. |
14,402 | Please write an abstract with title: Settling Time of Current-Tunable Probabilistic Bit's Distribution, and key words: Magnetic tunneling, Magnetization, Probability distribution, Tuning, Probabilistic computing, Spintronics, Saturation magnetization. Abstract: Probabilistic bits (p-bits) based on magnetic tunnel junctions are of recent interest in probabilistic and neuromorphic computing architectures based on their small size, high operating speeds, and truly stochastic nature. In practical systems, the output probability of the bit can be tuned by an applied current, which is generally characterized by a quasi-static tuning curve. In this letter, we instead focus on the finite time it takes the p-bit's probabilistic distribution to respond to an applied bias current. We find that this settling time is in the range of hundreds of picoseconds for a typical junction, and is highly dependent on various parameters, including the device size, material properties, and magnitude of the applied current. These results provide a baseline understanding of the dynamic properties of a nanomagnetic p-bit's probability distribution, which is helpful for p-bit-related system architecture discussions. |
14,403 | Please write an abstract with title: Connected word recognizer on a multiprocessor system, and key words: Multiprocessing systems, Speech recognition, Pattern recognition, Vocabulary, Hardware, Partitioning algorithms, Instruments, Computer architecture, Digital signal processing, Computer interfaces. Abstract: Speech recognition algorithms employing a similarity measure between the input speech utterance and the stored reference patterns to determine recognition of a word/sentence are computationally intensive. The instantaneous vocabulary size that can be handled in real-time is relatively small. This limitation can be alleviated by either using multiple programmable processors or by using special purpose hardware to handle the computation-intensive tasks. In a research environment the former approach is preferred, because improvements to the algorithm can rapidly be incorporated and their effects studied in real-time. Texas Instruments has developed a multiple-processor architecture based on the TMS32020 DSP, called Odyssey, that interfaces with Explorer, a symbolic computer. This paper addresses the issues involved in partitioning and allocating tasks in a multiple-processor environment to maximise throughput, and discusses the implementation of a grammar-driven speaker-dependent connected-word recognizer (GDCWR) as an example application that uses the power of multiple processors. |
14,404 | Please write an abstract with title: Gain-switching characteristics and fast transient response of three-terminal size-effect modulation laser, and key words: Transient response, Optical modulation, Light sources, Semiconductor lasers, Pulse modulation, Stimulated emission, Charge carrier processes, Gallium arsenide, Optical fiber communication, Quantum well lasers. Abstract: Gain-switching characteristics of the proposed size-effect modulation light sources are investigated. For realizing the laser operation, the consideration of the screening effect on the applied electric fields due to the high concentration of carriers is indispensable. In this respect, we propose a separate-confinement-hetero-multiple-quantum-well (SCH-MQW) structure as the most suitable one for gain switching. The key point of the structure is the sufficiently high heterobarriers at the clad-barrier interfaces to prevent carrier leakage. The examinations of the transient response clarify that they are principally photon-lifetime limited. Employing the three-terminal character of the proposed laser, the fast pulse modulation up to 12 Gbits/s, which is almost free from the relaxation oscillations and the pattern effects, is predicted. |
14,405 | Please write an abstract with title: DDOS Attack Identification using Machine Learning Techniques, and key words: Fault tolerance, Machine learning algorithms, Limiting, Neural networks, Memory management, Fault tolerant systems, Feature extraction. Abstract: One of the major problems that the world faces today is cyber attacks. Denial of Service attacks have been one of most frequent attacks. Some of the mitigating techniques are whitelisting / blacklisting IP addresses, rate limiting etc. The major goal of any DoS attack is to bring down the reputation of the victim organisation. So, instead of facing the issues after the attack, it is always advisable to develop a smart detection system to detect and prevent DoS attacks. While there are many ways to detect DoS attacks, applying machine learning techniques to detect and prevent the attacks turns out to be a promising one. Since there is a lot of data available about DoS attacks, machine learning algorithms can detect patterns of these DoS attacks and thus apply these patterns to new requests and classify them as malicious or benign requests. We consider the CICIDS2017 dataset. The dataset has data related to requests of 7 days of a week. Among those, Wednesday's dataset contains records related to types of DoS attacks. Even though techniques like AdaBoost, XGBoost and neural networks can be applied, random forest gives great performance. |
14,406 | Please write an abstract with title: High-temperature dielectric measurements of high-purity alumina ceramics, and key words: Dielectric measurement, Ceramics, Postal services, Microwave measurement, Microwave technology, Dielectric constant. Abstract: The speed of high-power (≥100 W) microwave sintering of ceramics from the ‘green’ state to the high-fired condition depends on the loss factor Ktan(δ). Free-space, W-band data at low power (≤0.1 mW) is presented on the complex dielectric constant of high-purity alumina (in air) in these two states – as achieved via conventional processing – for RT ≤ T ≤ 1700°C. |
14,407 | Please write an abstract with title: A 120 GHz Wideband CMOS I/Q Transmitter for Short-Range Wireless Device-to-Device Communication, and key words: Wireless communication, Microwave measurement, Transmitters, Device-to-device communication, Calibration, Wideband, Gain. Abstract: In this paper, we present a 120 GHz CMOS I/Q transmitter for short-range wireless device-to-device communication. Targeting 16-QAM communication at a transmission distance of 10 cm, an I/Q transmitter with an injection-locked frequency tripler chain (ILFT) having a data transfer rate of tens of Gbps is designed. To minimize the image-rejection ratio (IMRR) and enhance the EVM performance, the I/Q gain and phase calibration circuits are also integrated in the ILFT. In the simulation, our proposed transmitter exhibits wideband characteristics over 25 GHz and 14.7 dB conversion gain. From the I/Q calibration, the transmitter shows a high IMRR over 50 dBc. |
14,408 | Please write an abstract with title: Identification of Endometrial Cancer in Myometrium using RNN and SVM Algorithms for Accuracy and Sensitivity improvement, and key words: Support vector machines, Sensitivity, Recurrent neural networks, Statistical analysis, Software algorithms, Predictive models, Prediction algorithms. Abstract: The objective of this work is to compare the Recurrent Neural Network (RNN) algorithm and Support Vector Machine (SVM) algorithm in the identification of endometrial cancer based on its accuracy and sensitivity measurements. Materials and Methods: The endometrial cancer dataset, obtained from the National Institute of Endometrial Cancer Diseases (NIECE), contains 768 patient health records that were used to train (80 %) and test (20 %) the predictive model in MATLAB and the statistical analysis is done using SPSS software. For this research work 768 images were used with the pixel size of 3048×2048 and these images are taken from the pap smear slide dataset. The RNN algorithm is used and compared with the SVM algorithm. The sample size is estimated for two groups (RNN & SVM) with G-power of 80 % and 0.05 Type I/II Error rate (Alpha). Results: The predictive model using RNN algorithm shows a higher accuracy of 93.90 ± 0.3160 and sensitivity of 91.0400 ± 1.07207 followed by the significance value of 0.002 than SVM algorithm with accuracy of 88.10 ± 0.9940 and sensitivity of 86.1700 ± 1.36793 with the significance value of 0.000 using 2-tailed test in SPSS. Conclusion: Based on the outcome of the proposed work RNN classifier shows significantly better performance than the SVM classifier in the innovative detection of endometrial cancer. |
14,409 | Please write an abstract with title: Differential device for the determination of magnetic permeability or electric resistivity inside massive cylindrical samples, and key words: Permeability, Electric resistance, Coils, Steel, Equations, Magnetic properties, Physics, Coupling circuits, Circuit testing, Magnetic hysteresis. Abstract: A differential device for the determination of magnetic permeability or electric resistivity of the ferromagnetic cylindrical samples was realized. Our method, which takes into account a simple model of hysteresis, leads to encouraging results. |
14,410 | Please write an abstract with title: Predictions of Network Attacks in Collaborative Environment, and key words: Correlation, Intrusion detection, Collaboration, Organizations, Data processing, Data mining, Security. Abstract: This paper is a digest of the thesis on predicting cyber attacks in a collaborative environment. While previous works mostly focused on predicting attacks as seen from a single observation point, we proposed taking advantage of collaboration and exchange of intrusion detection alerts among organizations and networks. Thus, we can observe the cyber attack on a large scale and predict the next action of an adversary and its target. The thesis follows the three levels of cyber situational awareness: perception, comprehension, and projection. In the perception phase, we discuss the improvements of intrusion detection systems that allow for sharing intrusion detection alerts and their correlation. In the comprehension phase, we employed data mining to discover frequent attack patterns. In the projection phase, we present the analytical framework for the predictive analysis of the alerts backed by data mining and contemporary data processing approaches. The results are shown from experimental evaluation in the security alert sharing platform SABU, where real-world alerts from Czech academic and commercial networks are shared. The thesis is accompanied by the implementation of the analytical framework and a dataset that provides a baseline for future work. |
14,411 | Please write an abstract with title: Natural human animation via learning with dynamic manipulability, and key words: Humans, Animation, Leg, Joints, Computational efficiency, Kinematics, Path planning, Skeleton, Learning systems, Character generation. Abstract: We propose a method for creating human movements by imposing positional constraints of end-effectors at multiple key-frame. We introduce hierarchical reinforcement learning for efficiently searching postures at each key-frame among the huge number of possible candidates. The mechanical structures of virtual characters are also hierarchically decomposed so as to suit the learning mechanism, and each hierarchy prepares templates of discretely sampled postures for narrowing down the searching space. Our method automatically generates complicated sequential movements so that the resulting motions optimize dynamic manipulability for enhancing naturalness of realistic human behaviors. |
14,412 | Please write an abstract with title: Analysis of oscillator amplitude control, and its application to automatic tuning of quality factor for active LC filters, and key words: Oscillators, Automatic control, Tuning, Q factor, Active filters, Resonator filters, Resonant frequency, Spirals, Active inductors, Steady-state. Abstract: This paper presents an analytical solution to the amplitude control of the Q-enhanced LC resonator. It is shown that due to the nonlinearity of the active devices, effective amplitude control is realizable by a conventional magnitude-locked-loop, and that it is applicable to the automatic quality factor tuning of active LC filters. The effects of the weak nonlinearity magnitude and the amplitude used in the reference resonator on the achieved Q of filter resonator(s) is discussed. The results are verified by simulations and breadboard experiments. |
14,413 | Please write an abstract with title: Block-Gaussian-Mixture Priors for Hyperspectral Denoising and Inpainting, and key words: Noise reduction, Noise measurement, Gaussian mixture model, Feature extraction, Data mining, Transforms. Abstract: This article proposes a denoiser for hyperspectral (HS) images that consider, not only spatial features, but also spectral features. The method starts by projecting the noisy (observed) HS data onto a lower dimensional subspace and then learns a Gaussian mixture model (GMM) from 3-D patches or blocks extracted from the projected data cube. Afterward, the minimum mean squared error (MMSE) estimates of the blocks are obtained in closed form and returned to their original positions. Experiments show that the proposed algorithm is able to outperform other state-of-the-art methods under Gaussian and Poissonian noise and to reconstruct high-quality images in the presence of stripes. |
14,414 | Please write an abstract with title: Watermark based Image Authentication using Integer Wavelet Transform, and key words: Industries, Codes, PSNR, Wavelet domain, Satellites, Telemedicine, Authentication. Abstract: Digital watermarking has immense importance in protection of copyright as well as authentication. In this work, a watermarking process utilising S transform is proposed with Haar wavelet that generate only integer coefficients. Initially, the forward transform of cover image generates four coefficient bands – HH, HL, LH and LL. The HH sub-band location map is randomized and watermark image is embedded using least significant bits (LSB) substitution of the coefficient. Additionally 256 bit SHA hash code of the watermark image is generated for authentication and embedded in the HL sub-band in a similar fashion. During extraction, watermark is extracted and SHA256 hash code is computed again. This new hash code is compared with extracted hash code for authenticity. The average PSNR (Peak Signal to Noise Ratio) observed for SIPI dataset is 65 dB and 59 dB with 8192 bit and 32768 bit watermark respectively with embedding rate of 2 bits per pixel. The results of the proposed merthod are checked against existing methods and it has been found superior in many cases. |
14,415 | Please write an abstract with title: Ultra low loss and long length photonic crystal fiber, and key words: Optical fiber losses, Photonic crystal fibers, Optical losses, Optical attenuators, Optical fibers, Absorption, Optical scattering, Optical fiber communication, Optical device fabrication, Propagation losses. Abstract: Photonic crystal fiber is a promising candidate for future transmission media due to its unobtainable features in a conventional single-mode fiber. We discuss some important problems to realize a PCF for transmission purpose. |
14,416 | Please write an abstract with title: Measurement-to-track cost assignment computation when tracking with the IMM estimator, and key words: Computational efficiency, Radar tracking, Costs, Acceleration, State estimation, Monte Carlo methods, Gravity, Target tracking, Covariance matrix, Registers. Abstract: In the multi-target tracking problem, the association of measurements to tracks is typically conducted using an m times n cost matrix, where there are m tracks and n measurements. Each element of this cost matrix is computed based on some measure of the statistical distance between the estimated track state and the measurement. A common approach is to calculate a negative log-likelihood value that includes the uncertainty of the estimate and measurement. When tracking with an interacting multiple model (IMM) estimator, multiple mode likelihood values are possible for each measurement/track pair. Computing the cost assignment matrix given these likelihoods is a critical design issue. This paper compares two approaches for computing the cost assignment matrix. The first computes the likelihood with the mode that maximizes the likelihood for each given measurement. An alternate approach evaluates the pure likelihood of the Gaussian mixture. To focus on data association, we assume that the objects are perfectly resolved. The impact of imperfect object resolution is reserved for future work |
14,417 | Please write an abstract with title: Implementation of a phase tuner for exchange of electrical energy, and key words: Tuner, phase, PLL, synchrony, DSP, grid. Abstract: Applications of local systems for power generation connected to the utility power grid require tuning between the phase grid voltage and the voltage synthesized by the converter. The most widely accepted solution to provide tuning between time-varying signals is the use of a Phase-Locked Loop (PLL) system. The implementation of a phase tuner based on a PLL embedded in a digital signal processor (DSP) is presented, this tuning technique is aimed to assist DC-AC inverters of a single phase system of local energy generation for create a sine wave in concordance with the grid. In many cases, the reference signal obtained from the grid voltage is contaminated by harmonics, for this reason, a series of tests are presented in order to demonstrate the robustness of this tuning technique. |
14,418 | Please write an abstract with title: Disaster Management System using Wireless Sensor Network: A Review, and key words: Wireless sensor networks, Technological innovation, Protocols, Computer architecture, Alarm systems, Tsunami, Prediction algorithms. Abstract: Due to the changes in the environment natural catastrophe is increasing day by day. Any hazardous incident can happen at any time, with that effect lot of people loss their life, property. These calamities can be of any type weather it can be natural or human induced cause mass devastation. Wireless Sensor Network (WSN) is very realistic and demandable technology from past few years which can be supportive in monitoring and managing disaster. In this paper, we are describing the WSN architecture and how it works. Another is the types of disaster and the sensors which are used to compute their intensity. After that, a survey is done on the literature in which the issues, technologies and protocols used and their solutions are explained. An architecture of early warning system for disaster detection in WSN is elucidated which can be helpful in detecting, alerting and rescuing operation. |
14,419 | Please write an abstract with title: Characteristic of the cold cathode with secondary electron emission, and key words: Electron emission, Insulation, Voltage, Electron beams, Electron sources, Energy consumption, Delay effects, Radiofrequency amplifiers, Cathode ray tubes, Flat panel displays. Abstract: In the electron beam device, the cathode provides electrons with the initial energy. According to its emission mechanism, the electron source includes thermal cathode, cold cathodes, etc. With the cold cathode, the power consumption of the cathode is decreased. The delay time of the electron emission after the applying of voltage is very small in a device with a cold cathode. However, the perpendicular energy distribution of the electrons emitted from the cold cathode is a little larger than that of the thermionic cathode. An additional focusing structure has to be designed if the cold cathode is applied in the RF amplifier. In cathode ray tube and the field emission display panel, the electron current emitted from the cathode has to be modulated. Because of the high electric field in front of the cold cathode, the swing of the voltage for the current modulation is a little high. In this paper, an insulator tunnel is adopted in a cold cathode. When the primary electron bombarded on the surface of the insulator tunnel, the secondary electrons are generated. This paper studies the characteristic of the cold cathode with the secondary electron emission. The structure of the insulator tunnel is designed. As results, the perpendicular energy distribution of the electrons has been decreased effectively. Because the initial energy of the secondary electron is often smaller than that of the primary electron, the driving voltage for the current modulation is also decreased after the introduction of the insulator tunnel. |
14,420 | Please write an abstract with title: Conjugate Cyclic Feature Detection in the Presence of LEO-Satellite Doppler Effects, and key words: Time-frequency analysis, Satellite antennas, Satellites, Transmitting antennas, Receiving antennas, Feature extraction, Performance analysis. Abstract: The problem of detecting conjugate cyclic features (CCFs) despite time-varying carrier frequency offsets is considered. The novelty of this paper is a model for the conjugate cyclic autocorrelation function (CCAF) of the receive signal when transmitting a cyclostationary signal through a Doppler-rate channel. Moreover, a matched filter (MF) for recovering the energy of the transmitted-signal CCAF is derived. When the Doppler rate is unknown a-priori, the MF can be used in a loop to yield Doppler-shift and Doppler-rate estimates, which facilitates further tasks such as demodulation. Performance advantages over brute-force time-domain de-chirping are demonstrated. While this work is applicable to all channels with rapidly moving receive and transmit antennas, the performance is evaluated on real-world and simulated low-earth orbit satellite data. |
14,421 | Please write an abstract with title: Harmonic and reactive power compensation of high power cycloconverter induction motor drives by using decoupled inverters, and key words: Power system harmonics, Reactive power, Induction motor drives, Automatic voltage control, Power harmonic filters, Pulse width modulation inverters, Passive filters, Australia, Frequency, Power system modeling. Abstract: This paper examines a combined system with two converters for the harmonic and reactive power compensation (active conditioning) of high power cycloconverter drives. Compensation of harmonic and interharmonic components is achieved by a low rating fast transistor inverter and compensation for fundamental reactive current is achieved by a fundamental switched multilevel thyristor inverter. A full dynamic model of a cycloconverter drive and conditioning system is developed in a power electronic simulator. The system performance obtained in the simulations shows better performance than hybrid filter methods. |
14,422 | Please write an abstract with title: Stock Price Prediction Using Sentiment Analysis, and key words: Measurement, Sentiment analysis, Analytical models, Conferences, Bit error rate, Predictive models, Data models. Abstract: We investigate the influence of financial news headline sentiment on the predictability of stock prices using Long Term Short Term Memory (LSTM) networks. The investigation is performed on intraday data with specific lag-times between published article headlines and realised stock prices. FinBERT, a natural language processing model which is fine-tuned specifically for financial news is used to perform sentiment analysis on the company related news headlines. Two base models, one with only historical stock price data as inputs and the other with both historical stock price data and sentiment data from the original BERT model is tested. An alternative model with have both historical stock price data and sentiment data from the fine tuned FinBERT model as additional features. A comparison is performed on both the base and alternative models using Root Mean Square Error (RMSE) and mean absolute error (MAE) as performance metrics. The results suggest that the use of news headline sentiment features from FinBERT significantly improve the predictive performance of LSTM networks in intraday stock price prediction. FinBERT features are also found to outperform features based BERT model trained on a general corpus, illustrating the positive effect of domain specific fine tuning for Large Language models. |
14,423 | Please write an abstract with title: Lattice Boltzmann simulations: flow-through PCR, and key words: Lattice Boltzmann methods, Microfluidics, Biosensors, Numerical simulation, Temperature, Navier-Stokes equations, Computational fluid dynamics, Detectors, Biological system modeling, Analytical models. Abstract: This paper describes the lattice Boltzmann, numerical simulations used to evaluate a conduction-based PCR device (U. Texas) for uniformity of the micro channel temperature profile and its velocity field distribution. For comparison purposes, numerical simulations were also performed using conventional PCR configurations. The results show that simulations in two-dimensions demonstrate adequate performance of both the conventional and the heat conduction-based PCR systems. However, three-dimensional results indicate that nearly uniform wall temperatures (top, bottom and sides) are required to obtain uniform temperature fields in the PCR micro channels. |
14,424 | Please write an abstract with title: Modular Multilevel Converter with Simplified Nearest Level Control (NLC) Strategy for Voltage Balancing Perspective, and key words: Multilevel converters, Switching frequency, Pulse width modulation, Logic gates, Voltage control, Level control, Sorting. Abstract: Modularity, low losses, scalability as well as low filtering requirements make the Modular Multilevel Converter (MMC) a best solution besides HVDC implementations. But still the key concern associated with the implementation has been the voltage balancing of capacitors of about their sub - modules (SMs). Even though the MMC does have an attractive configuration with such a variety of notable features, a sophisticated control method is designed for desirable process. Pulse-width modulation (PWM) control strategy of various combinations, such as phase and level-shifted carriers, has been the most popular MMC deployment. However, the difficult positioning of a significant number of SMs as well as a high switching frequency seems to be constraints of PWM techniques. Even so, Nearest Level Control (NLC) provides a lower switching frequency and easier implementation. Due to its flexibility as well as easy implementation, NLC has become the most famous having to balance methodology for MMC SMs. The research article provides an insight that the use of NLC for 5 levels of MMC, where neither individual sub-module status has been required at the gate pulse generation stage. SM Identification is done upon sorting of sub-modules and the logic of a gate voltage level switching could be assessed. Throughout this article the MATLAB simulation has been conducted out on 5 levels of MMC with simplified NLC and the control strategy of PWM. Just on basis of the results obtained, a comparative evaluation between two techniques was carried out. |
14,425 | Please write an abstract with title: Autoencoder ensembles for network intrusion detection, and key words: Training, Adaptation models, Network intrusion detection, Machine learning, Feature extraction, Communications technology, Classification algorithms. Abstract: Machine learning methods have been widely used in the field of intrusion detection. However, most methods require labeled data sets, and the overhead is very high. Network data is often high-dimensional and has the problem of data imbalance, which makes many techniques unable to adapt to the real network environment. In this paper, we propose a network intrusion detection model based on autoencoder ensembles. This model uses a recursive feature addition algorithm to select the optimal subset of features, which can significantly reduce the training time of classifiers, and improve the performance of intrusion detection system. After feature selection, the feature subset is grouped, and then each group is mapped to an autoencoder. Multiple such autoencoders ensembles form the detection model. Only normal samples are used for training. The detection model is unsupervised, which improves the efficiency of detecting known and unknown attacks. The experimental results show that feature selection can effectively reduce training and detection time. Our model has high detection accuracy and strong adaptability. |
14,426 | Please write an abstract with title: Performance evaluation of LDPC codes in the presence of colored noise, and key words: Parity check codes, Colored noise, AWGN, Gaussian noise, Additive white noise, Signal to noise ratio, Bit error rate, Communication standards, Ethernet networks, Error correction codes. Abstract: The class of low density parity check (LDPC) codes includes the most powerful capacity-approaching codes reported to date. As a result, LDPC codes have been considered for application in new communication standards such as 10GBASE-T Ethernet. However, the successful use of LDPC codes for such applications requires a better understanding of the effects of signal impairments on their error correction capabilities. In this paper, the performance of various LDPC codes in the presence of additive colored Gaussian noise (ACGN) is evaluated and compared with the effects of conventional additive white Gaussian noise (AWGN). The simulation results provide insight into the performance of LDPC codes in real systems in which the noise components can indeed be correlated. In particular, our results show that at the same signal-to-noise ratio (SNR), ACGN is more detrimental to the bit error rate (BER) performance than AWGN. |
14,427 | Please write an abstract with title: Weighted Support Tensor Machines for Human Activity Recognition with Smartphone Sensors, and key words: Tensors, Activity recognition, Sensors, Support vector machines, Feature extraction, Sensor phenomena and characterization, Videos. Abstract: Along with the development of the Industrial Internet of Things, human activity recognition (HAR) has received widespread attention in many fields. Support Vector Machine (SVM), is widely used by researchers for human activity recognition. However, the inherent difference of signal properties from different sensors and various orientations is potentially lost when using the vector-based SVM for human activity recognition. What's more, the outlier sensitivity problem of the standard SVM reduces the accuracy of human activity recognition. To tackle this problem, we present a tensor-based feature representation model and a weighted support tensor machine (WSTM) for human activity recognition. Specifically, tensor-based representations are first used to model features from different sensors and various orientations to retain the latent relationship. In addition, the weighted support tensor machine is proposed to classify the human activities in tensor space while avoiding the outlier sensitivity problem. Experimental results demonstrate the proposed WSTM algorithm. |
14,428 | Please write an abstract with title: Vehicle trajectory prediction works, but not everywhere, and key words: Tracking, Navigation, Computational modeling, Roads, Machine vision, Urban areas, Predictive models. Abstract: Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the industry and research communities have acknowledged the need for such a pillar by providing public benchmarks. While state-of-the-art methods are impressive, i.e., they have no off-road prediction, their generalization to cities outside of the benchmark remains unexplored. In this work, we show that those methods do not generalize to new scenes. We present a method that automatically generates realistic scenes causing state-of-the-art models to go off-road. We frame the problem through the lens of adversarial scene generation. The method is a simple yet effective generative model based on atomic scene generation functions along with physical constraints. Our experiments show that more than 60% of existing scenes from the current benchmarks can be modified in a way to make prediction methods fail (i.e., predicting off-road). We further show that the generated scenes (i) are realistic since they do exist in the real world, and (ii) can be used to make existing models more robust, yielding 30-40% reductions in the off-road rate. The code is available online: https://s-attack.github.io/. |
14,429 | Please write an abstract with title: Short-term photovoltaic power generation prediction model based on fuzzy clustering-Elman neural network, and key words: Predictive models, Photovoltaic systems, Neural networks, Clustering algorithms, Prediction algorithms, Forestry, Forecasting. Abstract: Photovoltaic power generation forecasting is the basis of safe and stable operation in power grids. This paper proposes a short-term photovoltaic power generation prediction model based on Isolation Forest, Fuzzy C Means and Elman. Firstly, similar daily datas are selected according to the forecast date and classified according to the weather. Secondly, the abnormal parts in the Isolation Forest cleaning training samples are adopted. Thirdly, Fuzzy C Means clustering method is used to cluster the meteorological data of similar and the forecasting days. Finally, combined with the Elman neural network algorithm, a fuzzy clustering-Elman neural network prediction model with isolated forest data cleaning is formed. The experimental simulation is carried out according to the actual measured data of a certain city in Anhui Province. The prediction results are respectively compared with the traditional Elman and BP model. It is demonstrated that higher prediction accuracy can be obtained. |
14,430 | Please write an abstract with title: On transform-domain decoding of generalized Gabidulin codes : Dedicated to the memory of Ernst M. Gabidulin (1937–2021), and key words: Codes, Redundancy, Transforms, Shift registers, Control systems, Decoding. Abstract: The class of maximum rank distance generalized Gabidulin codes, suggested by Kshevetskiy and Gabidulin in 2005, extends the class of Gabidulin codes. For generalized Gabidulin codes we propose an efficient decoding algorithm based on the skew transform and the skew shift register synthesis. |
14,431 | Please write an abstract with title: Independent WCRT analysis for the Best-Effort class BE in Ethernet AVB, and key words: Conferences, Ethernet, Quality of service, Bandwidth, Real-time systems, Production facilities, Time factors. Abstract: Existing papers on worst-case response time analysis for individual classes in Ethernet AVB typically focus on classes under credit-based shaping (CBS). There also exist industrial applications that use the Best-Effort class BE for non-hard real-time traffic with a minimum quality-of-service (QoS) require-ment, however. In this paper, we therefore present a conjecture for worst-case response time analysis for that class BE, stating that the existing analysis based on eligible intervals can be equally well applied to a single (highest-priority) stream without CBS, by simply assuming the remaining bandwidth to be available to that stream. The conjecture is illustrated using a figure. |
14,432 | Please write an abstract with title: Preferences for Single-Turn vs. Multiturn Voice Dialogs in Automotive Use Cases—Results of an Interactive User Survey in Germany, and key words: Oral communication, Automotive engineering, Task analysis, Man-machine systems, Chatbots, Virtual assistants, Speech recognition. Abstract: Voice assistants have manifested their existence in the vehicle over the last decade. Further technological developments in the area of voice recognition and interactions with users open up the opportunity for new customer-centric user scenarios. In the following work, eight dialog use cases and two different interaction types were examined in detail. The focus of this work is to answer the research question to which extent do users prefer task-oriented multi-turn dialogs over the question-and-answer single-turn dialogs in certain driving situations. Employing a three-step online survey in 2020, participants were asked about their preferences for the assistant’s interaction type, use case as well as the perceived usefulness and pleasantness. The authors found that users preferred multi-turn conversations over single-turn conversations for all defined use case scenarios. As further challenges for the future development of voice assistants in the automotive context, the changed driving situation due to e.g. progress in autonomous driving and the focus on an integration of the voice modality as a direct function should be considered. |
14,433 | Please write an abstract with title: Flow Data Task Scheduling Model of RTOS Based on Multicore Operation System, and key words: Multicore processing, Operating systems, Conferences, Data processing, Real-time systems, Data models, Task analysis. Abstract: In this paper, the model contain with real-time streaming task package, an operating system buffer space and a system scheduling mechanism for RTOS system has been shown. The presented model is design to process real-time streaming task and results is verified by comparable operating system. Our results show that this model fit the structure of real-time streaming task package to improve the efficiency of flow data processing. |
14,434 | Please write an abstract with title: Scoping and concept design of a WEC for autonomous power, and key words: Performance evaluation, Oceans, Sea measurements, Hydrodynamics, Solids, Mathematical models, Sensors. Abstract: This paper reports results from an ongoing investigation on potential ways to utilize small wave energy devices that can be transported in, and deployed from, torpedo tubes. The devices are designed to perform designated ocean measurement operations and thus need to convert enough energy to power onboard sensors, while storing any excess energy to support vehicle recharging operations. Examined in this paper is a traditional tubular oscillating water column device, and particular interest here is in designs that lead to optimization of power converted from shorter wind sea waves. A two step design procedure is investigated here, wherein a more approximate two-degree-of-freedom model is first used to identify relative dimensions (of device elements) that optimize power conversion from relative oscillations between the device elements. A more rigorous mathematical model based on the hydrodynamics of oscillating pressure distributions within solid oscillators is then used to provide the hydrodynamic coefficients, forces, and flow rates for the device. These results provide a quick but rigorous way to estimate the energy conversion performance of the device in various wave climates, while enabling more accurate design of the power takeoff and energy storage systems. |
14,435 | Please write an abstract with title: A speech processor providing fricative and low-frequency periodicity information for single channel cochlear prosthesis, and key words: Speech processing, Prosthetics, Low-frequency noise, Hafnium, Acoustic noise, Band pass filters, Envelope detectors, Electrical stimulation, Signal mapping, Delay. Abstract: Single channel cochlear prostheses have been shown to be effective as aids to lipreading. Due to the small range of the pulse repetition rate available for electrical stimulation, these devices usually do not provide clues regarding certain fricative sounds characterized by high-frequency noise bursts. A speech processor for presenting the information corresponding to these noise bursts along with the low-frequency periodicity (voicing and intonation) information has been developed and tested on two patients. Results indicate that the high-frequency fricative noise burst information can be presented without any adverse effect on the reception of voicing and place information. |
14,436 | Please write an abstract with title: Application of fuzzy logic for improved software project management estimations, and key words: Application software, Fuzzy logic, Project management, Delay estimation, Cost function, Resource management, ANSI standards, Uncertainty, Parameter estimation, Availability. Abstract: Project management (PM) is the application of knowledge, skills, tools and techniques to project activities in order to meet project requirements. The success of any project relies heavily on the initial estimation of all project parameters. Fuzzy logic is a soft-computing technique used to effectively solve uncertainties due to imprecise inputs to generate linguistic or quantitative outputs. This paper investigates the application of fuzzy logic as a feasible technique for improved estimation accuracy to all the tasks within the project management knowledge areas to ensure higher software project success rates. |
14,437 | Please write an abstract with title: A New Feature Selection Approach and Classification Technique for Current Intrusion Detection System, and key words: Computers, Computer science, Intrusion detection, Machine learning, Feature extraction, Computer networks, Internet of Things. Abstract: These days, various devices including computers, smartphones, internet of things (IoT), and cloud services are using computer networks for data communications. As the computer network is being used extensively, it becomes the target of many attacks. It can be different attacks such as denial of service attack (DoS), remote to user attack (R2L), user to remote attack (U2R), and probing attack. To protect communication networks from network-based attacks, intrusion detection systems (IDSs) have been proposed in many studies. However, today IDSs are not good enough to detect new attack types in the communication networks. To increase the efficiency of the current IDSs, a subset of features needs to be obtained before performing the machine learning classifiers. In this study, a new feature selection method is proposed for current IDSs. In addition, the proposed method is combined with machine learning classifiers and tested on KDD ’99 dataset and %99.81 accuracy rate was obtained. The obtained performance is pretty high to separate network attacks from the normal traffic. |
14,438 | Please write an abstract with title: BER performance analysis of a direct conversion receiver, and key words: Bit error rate, Performance analysis, Receivers, Baseband, Costs, Fading, Production, Radio frequency, Signal to noise ratio, Error analysis. Abstract: Direct conversion receivers are increasingly popular for use in mobile terminals. This is due to advantages over other architectures such as heterodyne receivers in terms of cost, electrical current, and physical size. However, a direct conversion receiver often generates a DC-offset that has to be taken care of either by suppressing the DC-offset in the radio-frequency part of the receiver, or by taking care of it during baseband processing. A theoretical analysis of the bit error rate (BER) performance in a direct conversion receiver with different levels of DC-offset suppression is presented. Explicit results are presented on how the BER depends on the signal-to-noise ratio (SNR), the signal-to-DC-level, and the choice of pilot symbols both with M-QAM and M-PSK in a slow, flat Rayleigh fading channel. A design rule, which applies to the design of DC-compensation in direct conversion receivers, is also presented. |
14,439 | Please write an abstract with title: InAs/AlGaSb heterostructure stress sensor for MEMS/NEMS applications, and key words: Stress, Micromechanical devices, Nanoelectromechanical systems, Nanoscale devices, Actuators, Mechanical sensors, Sensor phenomena and characterization, Sensor systems and applications, Signal processing, Medical diagnosis. Abstract: Semiconductor micro- and nano-electromechanical systems (MEMS/NEMS) have the potential to bring about a revolution in the application of semiconductor fine-structure devices, such as high-resolution actuators and sensors, high-frequency signal processing components, and medical diagnostic devices. In addition, when device size reaches the nanometer scale and the characteristic frequency becomes sufficiently high to quantize the freedom of mechanical motion, novel quantum mechanical functions can be introduced. Compared with the commonly used materials systems, such as Si/SiO/sub 2/ and GaAs/AlGaAs-based heterostructures, InAs-based structures have the advantage that the surface Fermi level pinning in the conduction band makes it possible to fabricate much smaller conductive structures than other semiconductors. We have successfully fabricated a novel piezoresistive stress sensor with a surface InAs conductive layer of nanometer-scale thickness based on MBE-grown InAs/AlGaSb heterostructures. The size of this self-sensing device can be reduced to a nanometer scale and it is expected to be a key component in future MEMS/NEMS applications. |
14,440 | Please write an abstract with title: GHz modulation of carbon nanotube cathodes for microwave amplifiers, and key words: Carbon nanotubes, Cathodes, Microwave amplifiers, Pulse amplifiers, Pulse modulation, Optical modulation, Electron beams, Frequency, Microwave generation, Costs. Abstract: Cold cathodes based on carbon nanotubes (CNs) allow to produce a pulsed/directly modulated electron beam. Using an array of vertically aligned CNs that exhibit an aspect ratio of around 200, we demonstrated the modulation of a 1.5 A/cm/sup 2/ beam at 1.5 GHz frequency. Such CN cathodes are very promising for their use in a new generation of compact and low cost microwave amplifiers that operates between 30 and 100 GHz. |
14,441 | Please write an abstract with title: Methodology for the Assessment of Complexity in Corporate Value Networks, and key words: Complexity theory, Companies, Biological system modeling, Collaboration, Context modeling, Visualization, Computational modeling. Abstract: Nowadays, companies are forming corporate value networks to meet the increasing demands of customers and to implement new business models for the generation of new revenue streams. Nevertheless, managing a larger number of partnerships can often be challenging for companies. In this context, methods are required to manage network complexity. The literature neglects the holistic assessment of complexity in corporate value networks. In this paper, a methodology to assess complexity in corporate value networks within the mechanical and plant engineering industry is proposed. Various complexity drivers contributing to overall network complexity have been identified from the scientific literature and quantified using a verbalized ordinal scale. Different complexity dimensions are operationalized and visualized by the means of complexity vectors, which consist of the assessed complexity drivers. The proposed methodology enables the user to derive holistic measures in order to deal with complexity in corporate value networks. |
14,442 | Please write an abstract with title: An efficient method for fuzzy identification of regulatory events in gene expression time series data, and key words: Gene expression, Data mining, Genetics, Bioinformatics, Data analysis, Genomics, Intelligent networks, Time series analysis, Reverse engineering, Testing. Abstract: The increase in the number of time-series gene expression experiments drives an increase in the development of analysis methods that aim to reverse engineer genetic regulatory networks. Methods have previously been developed that test all combinations of gene interactions in a gene expression time-series dataset for those that closely fit a model of gene regulation. We describe an efficient method for reducing the computational cost of this approach by pruning the search space of candidates least likely to fit a regulatory model. Our approach represents changes in expression levels as directional slope information and discards combinations whose slope relationships are most likely outside the scope of the given model of regulatory relationships. We demonstrate a 70% reduction in the computational time required to process three S. cerevisiae microarray time-series datasets. |
14,443 | Please write an abstract with title: Digital Modeling in Railway Infrastructure and Rolling Stock Objects at all Stages Life Cycle: Features, and key words: Rail transportation, Solid modeling, Biological system modeling, Automation, Buildings, Standards, Data models. Abstract: Digital modelling has become used in complex engineering structures design. However, the digital modelling application is much wider than a simple design. This technology can be applied at all stages of the technical object's life cycle. The authors focus on the possibilities of digital modelling in the use at all the life cycle stages of infrastructure facilities and rolling stock in railway transport. A conceptual model is presented, and the main advantages of using the described technology at all life cycle stages of technical objects are noted. Separately, the need for the use of digital modelling technologies in the field of train control systems and railway automation is noted. |
14,444 | Please write an abstract with title: Self-injection-locked Brillouin laser with high-Q fiber ring cavity, and key words: Power system measurements, Semiconductor lasers, Power lasers, Scattering, Distributed feedback devices, Laser feedback, Lasers and electrooptics. Abstract: A simple Brillouin fiber laser pumped from a self-injection locked distributed feedback (DFB) laser diode delivers radiation with the Lorentzian linewidth of ~75 Hz and phase noise power density less than –100dBc/Hz (>30 kHz). |
14,445 | Please write an abstract with title: An Improved Lyapunov Stability Test for Linear Time-Delay Systems, and key words: Delays, Lyapunov methods, Symmetric matrices, Stability criteria, Linear systems, Delay systems, Control theory. Abstract: This paper presents an improved necessary and sufficient condition of exponential stability for LTI delay systems. By this criterion, the stability analysis of any system of the class can be reduced to verification of the positive definiteness of a special matrix (which is based on the delay Lyapunov matrix). The dimension of the matrix depends on the parameters of the system, and the goal of this paper is to make it smaller. We applied a new technique, and reduced the dimension by about half. |
14,446 | Please write an abstract with title: Effect of curing condition of adhesion strength and ACA flip-chip contact resistance, and key words: Curing, Contact resistance, Temperature, Conductive adhesives, Bonding, Scanning electron microscopy, Conducting materials, Manufacturing, Cost function, Anisotropic magnetoresistance. Abstract: There has been steadily increasing interest in using electrically conductive adhesives as interconnecting materials in electronics manufacturing. Simple processing, low processing temperature and fine pitch capability are the major advantages of conducting adhesive technology. A new and innovative connection technology geared towards achieving increased functionality at a lower total system cost is anisotropic conductive adhesive (ACA) interconnection. ACAs provide electrical as well as mechanical interconnections for fine pitch applications when used for flip chip assembly. In the other hand, this new technology still has reliability limitation. One major concern is the poor adhesion strength of adhesive interface, another is the contact resistance shift. The mechanism of adhesion interface and contact resistance shift during elevated temperature and humidity aging had been discussed in previous study. The ultimate goal of this work is to develop conductive adhesive with stable contact resistance and desirable interface adhesion strength. The purpose of this study is to investigate optimum curing degree and curing temperature to achieve the best performance of ACA. The curing reaction of a conductive adhesive was studied with a differential scanning calorimeter (DSC) under isothermal condition and temperature scanning. Adhesion strength was measured by 90 degrees peel test and contact resistance was also studied as a function of curing degree and curing temperature. Microstructural investigations of the fracture surfaces were studied by scanning electron microscopy (SEM). It was shown that the electrical and mechanical performance is dependent on curing conditions. By comparing the dynamic DSC results of the conductive adhesive with different bonding condition, it can be seen that it is not fully correct that high temperature cured sample have higher adhesion strength than low temperature cured sample, peel strength increase proportion with the increase of bonding temperature up to 120/spl deg/C and then decrease when the bonding temperature was above 120/spl deg/C. Contact resistance was found to be strongly dependent on the curing degree, but also revealed no related with curing temperature. In this case, the optimum temperature for bonding with ACA was concluded to be at 120/spl deg/C. |
14,447 | Please write an abstract with title: A Data-Centric Approach to Taming the Message Dissemination in the Internet of Vehicles, and key words: Authentication, Transportation, Vehicular ad hoc networks, Cryptography, Protocols. Abstract: The Internet of Vehicles (IoV) aims to establish a network of autonomous and connected vehicles that communicate with one another and with road-side units (RSUs) and a central trust authority (TA). Messages must be efficiently and securely disseminated to conserve resources and preserve network security. Currently, there is much research on the security schemes and methods of disseminating messages. Furthermore, there is a deficiency of information regarding resource optimization. This paper takes an interdisciplinary approach by merging both cybersecurity and data science to optimize and secure the network. The proposed method applies Prim's algorithm to an existing vehicular security scheme, Privacy-Preserving Dual Authentication Scheme (PPDAS), to further network efficiency in terms of time consumption. When a dual authentication security scheme is in place, the time taken for message dissemination follows a quadratic growth; applying Prim's algorithm to the security scheme reduces the time to disseminate messages to a linear growth. The number of messages sent was decreased by a magnitude of up to 44.57. Contemporary security schemes are compared with PPDAS to justify the overhead consumption. The usage of network resources, such as time, is reduced, which substantially enhances the performance of the vehicular network and allows for the scalability of the IoV. |
14,448 | Please write an abstract with title: Drop impact test - mechanics & physics of failure, and key words: Testing, Physics, Solid modeling, Stress, Finite element methods, Failure analysis, Performance analysis, Packaging, Assembly, Parametric study. Abstract: This paper deals with the mechanics and physics of board-level drop test with the intention of providing the fundamental understanding required to design and analyse the results of a drop test. Three finite element analyses were performed to understand the physics of failure in board-level drop impact: (i) velocity impact of a PCB - modeled as a beam; (ii) velocity impact of a PCB with centrally mounted package - modeled as a beam; (iii) velocity impact of a drop assembly - solid elements with submodeling. Parametric studies have been performed on the solid model for a number design variables: drop height, fall plate thickness, PCB length, PCB thickness, solder bump height, solder bump size, solder bump number, and impact cone diameter. Differential flexing as well as inertia has been identified as the key failure drivers. In both cases, the transverse stress, S33, is the most critical stress component. Geometrical stress concentration and intermetallics of the interconnection are critical in the impact strength of interconnection. |
14,449 | Please write an abstract with title: Algorithm of Tunning Heating Source Thermophysical Parameters in Smart Home, and key words: Heating systems, Micromechanical devices, Temperature distribution, Heuristic algorithms, Time series analysis, Pipelines, Smart homes. Abstract: A development of the efficient smart home energy management systems requires understanding of the heating behavior. Part and parcel of this process is thermal parameters of heating sources which define the effectiveness of energy usage. In this paper we introduce a novel approach for the estimation of thermophysical parameters of heating elements. Based on the formulation of dynamic heat transfer problem we present a model that describes the heating process in a building with multiple heating sources. Within this model we propose an algorithm of determination the effective thermophysical parameters, where historical temperature and aggregated energy data are used in order to estimate unknown parameters. Also we present the algorithms for data preparation and renormalization. The latter means a transition from integral building parameter of heating sources to separate parameters corresponding to particular room heating element. Due to occurred errors during the computation, the presence of some incorrect values in provided time series and the ambiguity of calculation scenarios, the resulting parameters can be tuned to achieve greater accuracy. To do that, we propose an approach which involves the multivariate minimization of loss function using the genetic algorithm. The whole algorithmic pipeline is discussed in this report. |
14,450 | Please write an abstract with title: Multi-Modal Aesthetic Assessment for Mobile Gaming Image, and key words: Training, Measurement, Industries, Correlation, Image resolution, Training data, Games. Abstract: With the proliferation of various gaming technology, services, game styles, and platforms, multi-dimensional aesthetic assessment of the gaming contents is becoming more and more important for the gaming industry. Depending on the diverse needs of diversified game players, game designers, graphical developers, etc. in particular conditions, multi-modal aesthetic assessment is required to consider different aesthetic dimensions/perspectives. Since there are different underlying relationships between different aesthetic dimensions, e.g., between the ‘Colorfulness’ and ‘Color Harmony’, it could be advantageous to leverage effective information attached in multiple relevant dimensions. To this end, we solve this problem via multi-task learning. Our inclination is to seek and learn the correlations between different aesthetic relevant dimensions to further boost the generalization performance in predicting all the aesthetic dimensions. Therefore, the ‘bottleneck’ of obtaining good predictions with limited labeled data for one individual dimension could be unplugged by harnessing complementary sources of other dimensions, i.e., augment the training data indirectly by sharing training information across dimensions. According to experimental results, the proposed model outperforms state-of-the-art aesthetic metrics significantly in predicting four gaming aesthetic dimensions. |
14,451 | Please write an abstract with title: Fourier Phase Retrieval with Side Information Using Generative Prior, and key words: Generators, Image reconstruction, Phase measurement, Mathematical model, Minimization, Noise measurement, Optimization. Abstract: Classical methods for phase retrieval rely on prior knowledge about the support and positivity of the images. In recent years, sparse, low-rank, and generative models with spectral initialization have been proposed for various phase retrieval problems. Despite the progress, phase retrieval with structured measurements, still remains a challenging problem. In particular, Fourier phase retrieval is sensitive to the initialization and comes with inherent ambiguities about shift and flip on images. In this paper, we propose to use additional side information about the signal to initialize and regularize the phase retrieval problem. In particular, we assume that a part of the signal is known. We use the known part to initialize the estimate and incorporate the support knowledge as an additional constraint while solving the phase retrieval problem. We empirically demonstrate that our proposed method provides significant improvement over Fourier phase retrieval without side information. |
14,452 | Please write an abstract with title: Functionally Graded Multilayered Soil Models, an Alternative to Modeling the Soil Electrical Resistivity for Computing the Grounding Resistance, and key words: Conductivity, Mathematical model, Soil, Resistance, Electric potential, Grounding, Nonhomogeneous media. Abstract: Alternative models of the electrical resistivity of the soil to the well-known constant piecewise multilayer model are presented in this paper. By their special features, the proposed models lead to reasonably simple semi-analytical expressions for the electric potential. The parameters associated with these models are obtained from apparent resistivity measurements using an optimization procedure. The proposed models allow obtaining a continuous piecewise resistivity profile as a function of depth from the soil surface. From the full definition of the models, the grounding resistance of several electrodes is calculated and compared with that obtained from the classic multilayer model. Finally some application examples including data from field measurements are considered in this paper. |
14,453 | Please write an abstract with title: Peer Selection in Device-to-Device Communication Based on Multi-Attribute Decision Making, and key words: Device-to-device communication, Performance evaluation, Delays, Interference, Signal to noise ratio, Throughput. Abstract: The massive number of peers in network with the mobility of peers rises the challenges of finding the best peer to establish a Device-to-Device (D2D) connection. This paper aims to evaluate the performance of the peer selection mechanism where the peer selection mechanism is proposed using a multi-attribute decision-making technique, based on Analytic Hierarchy Process (AHP) and Hierarchical Adaptive Weighting (HAW) algorithms. It attempts to find and select the best peer to establish D2D communication when the user is moving among different cells in the network. The performance of the proposed mechanism showed better performance based on the attribute weights. |
14,454 | Please write an abstract with title: Cooperative Estimation of Local Atmospheric Delay in Precise Point Positioning with GNSS, and key words: Global navigation satellite system, Filtering, Estimation, Collaboration, Delays, Distributed algorithms, Standards. Abstract: In standard PPP GNSS, residual atmospheric delay (RAD) is estimated independently at each agent by filtering through time, resulting in estimation periods that are too long for vehicular applications. This paper explores cooperative estimation of local vertical RAD within a network of interacting agents. After formulating the problem, the paper formulates and compares: the individual solution when there is no inter-agent interactions, the centralized solution when all agents interact with a central node, and four distributed algorithms (i.e., information-weighted consensus (IWC), covariance intersection (CI), Inverse covariance intersection (ICI), and ellipsoidal intersection (EI)). The role of information shared between agents (i.e., cross-correlation) is specifically considered. The article shows that the distributed methods estimate the common RAD faster than independent agents. This increased accuracy enables faster and more accurate estimation of the unique portion of each agent's state (e.g., horizontal position). |
14,455 | Please write an abstract with title: DBRG: Description-Based Non-Quality Requirements Generator, and key words: Dictionaries, Conferences, Tools, Generators, Large-scale systems, Complexity theory, Requirements engineering. Abstract: Requirements quality checking is a key process in requirements engineering. For complex and large scale systems, it is recommended to use automated requirements quality checking tools because of the size and complexity of requirements. However, such tools are typically evaluated on a small set of manually curated requirements. This limitation affects the comprehensiveness and reliability of the evaluation and leaves several possible quality issues undetected. In this paper, we de-scribe a novel quality-checking-oriented synthesised requirements generator. We provide an input description language so that several quality checking issues and scenarios can be defined. The generator utilises an input dictionary of nouns and verb frames, and generates requirements sentences complying to a user-defined description of a quality affected requirement. |
14,456 | Please write an abstract with title: Robot-on-Chip: Computing on a Single Chip for an Autonomous Robot, and key words: Architecture, Buildings, Signal processing algorithms, Computer architecture, Robot sensing systems, Sensor systems, Sensors. Abstract: The interest in autonomous robots is growing due to diverse usability. Autonomous robots are equipped with various sensors for stable operation. As the sensor data increases, the system for sensor signal processing and actuators controlling is complicated. In this paper, we propose the robot-on-chip (RoC) which processes all functions for an autonomous robot on a single chip mounted on a robot. In order to realize the RoC, we designed an autonomous robot with a lightweight algorithm and a hardware-friendly architecture. We demonstrated the feasibility of the RoC that the robot moves successfully without bumping into people in a building by recognizing the environment. |
14,457 | Please write an abstract with title: End-to-End Speaker Verification via Curriculum Bipartite Ranking Weighted Binary Cross-Entropy, and key words: Training, Measurement, Feature extraction, Calibration, Training data, Speech processing, Roads. Abstract: End-to-end speaker verification achieves the verification through estimating directly the similarity score between a pair of utterances, which is formulated as a binary (i.e., target versus non-target) classification problem. Unlike the stage-wise method, an end-to-end verification approach optimizes the evaluation metrics directly and its output layer is parameter-free, which can save great computing and memory resources. However, it faces two important difficulties. The first one is how to deal with severely imbalanced trials, i.e., the number of target trials is much smaller than that of nontarget trials, and the other is about how to handle easy trials that do not help improve the model in training. To circumvent these two issues, we propose in this paper a binary cross-entropy (BCE) type of loss function and present a method to train the deep neural network (DNN) models based on the proposed loss function for end-to-end speaker verification. The training process employs a bipartite ranking method to deal with the trial imbalance problem and a curriculum learning method to help improve both the training stability and performance of the model by selecting non-target trials from easy to hard ones gradually along the convergence process. Since the training process employs bipartite ranking and curriculum learning and the loss function is of the generalized BCE form, we name the new approach curriculum bipartite ranking weighted binary cross-entropy (CBRW-BCE). Experimental results show that the model trained with CBRW-BCE not only achieves the state-of-the-art performance but is also well calibrated. |
14,458 | Please write an abstract with title: Capital System vs. Information and Communications Technology: A Perspective of Civilization Development, and key words: Geography, Information and communication technology, History. Abstract: Information Civilization is the newest achievement of human civilization, which is characterized by information and communications technology. It is a transcendent development of the human civilization which dominated by the capital system. Information Civilization goes beyond the alienation, polarization and monetization in the capital system. It is widely opened a better social conditions and environments for society development and human civilization. Information Civilization has also increased the communication platform and integrate opportunity for other human civilizations. The capital system is based on commodity exchange, it, s a civilization that taking one-way communication as its development mode. Information Civilization is a civilization that is different from capital system, it is supported by information and communications technology. It provides a lot of new ways and opportunities for other human civilizations which are different from capital system. Information Civilization could enlarge the human boundaries of geography, country, nationality, language, custom and religion in many many ways. In the future Information Civilization, the non-capital system civilization, such as Chinese civilization and other traditional human civilizations with long history, is going to be integrated into the global civilization system with the help of information and communications technology. Furthermore, the non-capital system civilization is also going to enrich human civilization and lead human society to go happier, better and higher. |
14,459 | Please write an abstract with title: Transient response of single-phase photovoltaic inverters to step changes in supply voltage distortion, and key words: Photovoltaic systems, Transient response, Time-frequency analysis, Systematics, Voltage, Harmonic analysis, Distortion. Abstract: This paper presents an experimental study on the transient response of three commercially available photovoltaic (PV) inverters on step changes in the supply voltage distortion. Step changes of individual harmonics are applied to three different PV inverters varying in order, amplitude and phase angle. Moreover, different times of switching in terms of the fundamental frequency, i.e. points on wave, are considered. From the laboratory results presented, it can be seen that the inverters behave very different. To quantify the dynamic response characteristics, three parameters of interest are defined and evaluated: the overshoot of the grid-side current, the settling time and the eigenfrequencies of the transient response. The dependencies of these parameters on the above mentioned impact factors are analyzed, which can be used e.g. to develop dynamic models of PV inverters. The paper demonstrates the importance for assessing the transient response (dynamic behavior) of PV inverters and the individuality of their behavior, which requires inverter-make dependent models for grid-studies. A single model covering different makes of inverters is insufficient. |
14,460 | Please write an abstract with title: Carrier-envelope-phase-controlled optical poling, and key words: Optical harmonic generation, Nonlinear optics, Stimulated emission, Ultrafast optics, Optical control, Optical filters, Optical feedback, Optical pulse generation, Control systems, Frequency. Abstract: The efficiency of optical poling process is controlled by the self-stabilized carrier-envelope phase of the idler output from our noncollinear optical parametric amplifier system. |
14,461 | Please write an abstract with title: More treasured texts [educational textbooks], and key words: Books, Radar, Electrical engineering, Maxwell equations, Missiles, Mathematics, Circuit analysis, Cathode ray tubes, Educational technology, Vectors. Abstract: In this article, the author describes how the years after World War II saw the best textbooks renew an emphasis on theory and strive to educate students in the new fields of solid-state electronics and computers. |
14,462 | Please write an abstract with title: Robust Image-Based Adaptive Fuzzy Controller for Guarantee Field of View with Uncertain Dynamics, and key words: Visual servoing, fuzzy neural networks, field of view constraints, asymmetric barrier Lyapunov function. Abstract: Visual servoing technology has widely been employed in manufacturing because it is a flexible, realizability, and low-cost way to improve the intelligence of the industry robot. Nevertheless, a worrisome and overlooked issue is that the loss of visual features in the camera's field of view may lead to the failures of the visual servoing tasks. This article addresses the visual features escaping problem, by implementing an asymmetric barrier Lyapunov function with a field of view constraint controller. The asymmetric barrier Lyapunov function defines a tightly specified range for the feature coordinate errors and ensures the transient response of the tracking error as well as enables arbitrary tracking accuracy. It is worth noting that the asymmetric barrier Lyapunov function directly handles the visual-robot coupled dynamics while guaranteeing system stabilities. Besides, to accommodate the uncertain dynamics derived from a high-dimensional coupled system, an adaptive controller is proposed utilizing fuzzy neural networks with computational efficiency and few training parameters to enhance the control performance. Finally, the effectiveness of the proposed control strategy has been demonstrated through both theoretical analysis and experimental verification. |
14,463 | Please write an abstract with title: Robust ISAR Target Recognition Based on ADRISAR-Net, and key words: Feature extraction, Strain, Target recognition, Generators, Convolution, Deformable models, Standards. Abstract: Due to the inherent unknown image deformation among the training and test samples, performance of the deep convolutional neural network (CNN) will be degraded for Inverse Synthetic Aperture Radar (ISAR) automatic target recognition. Meanwhile, traditional CNN only captures the local spatial information due to small receptive fields, thus, neglects the global information useful for recognition. To tackle these issues, this article proposes the attention-augmented deformation robust ISAR image recognition network, dubbed as ADRISAR-Net. The model adopts the inverse compositional spatial transformer for automatic image deformation adjustment, and performs joint local and global feature extractions by the attention-augmented CNN. Finally, the softmax classifier outputs the recognition results. The proposed ADRISAR-Net is end-to-end trainable, and achieves higher recognition accuracy for the four-satellite and three-airplane ISAR image data sets generated by electromagnetic computing. |
14,464 | Please write an abstract with title: Intelligent detection method of rope shape abnormality of cold source interception network based on yolov5 and twin network, and key words: Knowledge engineering, Deep learning, Shape, Target recognition, Morphology, Robustness, Safety. Abstract: The safety of water intakes is very important to nuclear power plants. The use of interception nets to intercept marine life is related to the safety of water intakes. This method is based on deep learning technology to detect the abnormal state of the cold source interception network. Judge whether the interception net is abnormal by comparing the historical morphology of the interception net rope, and send an abnormal warning message when an abnormality occurs to remind the management personnel to deal with and repair it in time. This method is based on independent research and development of various deep learning networks such as yolov5 and twin networks. The test results show that the recognition recall rate for abnormal changes in the shape of the interception network is more than 95%. |
14,465 | Please write an abstract with title: Forming Software Development Team: Machine-Learning Approach, and key words: Stochastic processes, Software, Outsourcing, Planning, Task analysis, Sustainable development, Intelligent systems. Abstract: Software development team formation is a task done by skilled persons who have enough experience in mapping crew members to project tasks. Choosing software development team members according to their experience and within the amount of available budget/time is a vital task. However, the availability of a tool to suggest the best team members to the different tasks in some projects will definitely help project managers in their selections. This work is related to suggesting the most suitable skilled software development professionals to projects tasks based on some machine learning technique (Random Forest Classifier). The project manager just feeds the tool with the required tasks, and the latter suggests a ranked list of the most suitable professionals that fit each task which reflects positively on the team formation process. The experimental results conducted at the end of the work reflect the improvement of software development team formation gained comparable with the ordinary, self-experience-based one. |
14,466 | Please write an abstract with title: SASLN: Signals Augmented Self-Taught Learning Networks for Mechanical Fault Diagnosis Under Small Sample Condition, and key words: Fault diagnosis, Generators, Training, Generative adversarial networks, Data models, Wind turbines, Robustness. Abstract: The implementation of condition monitoring and fault diagnosis is of special importance for ensuring wind turbine (WT) operation safely and stably. In practice, however, the fault data of WT are limited, which makes it hard to identify faults of WT accurately using the existing intelligent diagnosis methods. To address this, signals augmented self-taught learning network (SASLN) is proposed for the fault diagnosis of the generator, which is one of the most important parts in WT. In SASLN, fault signal samples are generated by the Wasserstein distance guided generative adversarial networks to expand the limited training data set. The sufficient generated signal samples are used to pretrain the self-taught learning network (SLN) to enhance the generalization ability of SLN. Then, the weights of SLN are fine-tuned using a small number of real signal samples for accurate fault classification. The effectiveness of SASLN is verified by two bearing vibration data sets. The results show that SASLN can achieve fairly high fault classification accuracy using small training samples. Besides, SASLN has good robustness in noisy working environment and can also identify faults even in variable loads and variable rotating speeds cases, which makes it meaningful for decreasing the running costs and improving the maintenance management of WT. |
14,467 | Please write an abstract with title: Joint Information and Energy Transfer of SWIPT-Enabled Mobile Users in Wireless Networks, and key words: Interference, 6G mobile communication, Switches, RF signals, Correlation, Wireless sensor networks, Geometry. Abstract: Extremely high reliability and energy efficiency are crucial in sixth generation (6G) mobile networks to accommodate the diverse range of end-user devices in the era of the Internet of Everything. The concept of simultaneous wireless information and power transfer (SWIPT) has been emerged as a promising solution to boost the reliability of wireless communication systems through prolonging the battery lifetime by harvesting energy from the received radio-frequency signals. In this paper, we propose a low complexity threshold-based pair switching (TbPS) technique for SWIPT in the context of large-scale cellular networks, where the multiple-antenna mobile users (MUs) employ maximum ratio combining technique and adopt the random waypoint model. Under the TbPS technique, a subset of MU’s antennas is allocated for information decoding (ID), only when their post-combiner signal-to-interference ratio, exceeds a certain threshold, while the remaining antennas are allocated for energy harvesting (EH). Contrary to traditional approaches which assume the existence of either uncorrelated or fully correlated interference, our proposed technique takes into consideration the interference correlation between nearby antennas. In order to further alleviate the inter-cell interference and energy consumption, we propose a traffic load-based sleeping (TLbS) technique in the context of finite-area network deployments, where lightly-loaded cells switch into sleep mode. By leveraging tools from stochastic geometry, we derive analytical expressions for the ID, EH as well as joint ID and EH success probability of MUs based on the proposed techniques. Our results demonstrate the optimal parameters (i.e., antenna selection and traffic load threshold) of our proposed techniques, that maximize the joint ID and EH success probability. Finally, it is shown that, by properly selecting the threshold values, both the proposed TbPS scheme and TLbS mechanism outperform the conventional techniques in terms of the SWIPT capability of the MUs. |
14,468 | Please write an abstract with title: Development of highly stabilized & high precision power supply for KCCH cyclotron magnet, and key words: Power supplies, Cyclotrons, Cancer, Hospitals, Stability, Thyristors, Inductors, Passive filters, MOSFETs, Regulators. Abstract: 110 V/600 A, highly stabilized power supply have been installed at the Korea Cancer Center Hospital (KCCH) in Seoul, to energize water-cooled, resistive, high field research magnet for cyclotron. The power supply achieves a long term current stability of 20 ppm over one hour period with a short term ripple and noise variation of <20 ppm over a time period of one cycle. Power supply consists of a three-winding transformer, 12-pulse thyristor converter with interphase reactor, and a passive filter and a pass bank MOSFETs regulator. Various test results taken during the commissioning phase with a 70 kW resistive load and results taken with the research magnet for cyclotron are shown. This paper presents the detailed design of the power supply components. Problems with the power supply design and solutions are also presented. Some suggestions on how to improve the performance of these supplies are outlined. |
14,469 | Please write an abstract with title: Capacitance extraction of high-density 3D interconnects using finite element method, and key words: Capacitance, Finite element methods, Integrated circuit interconnections, Boundary conditions, Integral equations, Dielectrics, Parameter extraction, Very large scale integration, Concurrent computing, Frequency. Abstract: In this paper, the element-by-element technique in conjunction with preconditioned conjugate gradient (PCG) solver is adopted for fast parameter extraction of multi-layer and multi-conductor interconnects in VLSI circuit. In order to partially implement parallel computation, the proposed technique takes advantage of Fortran 95 in the array manipulation, and the efficiency of this technique is verified by numerical examples. Compared to some reference solutions, both the memory requirement and the CPU time are significantly reduced while maintaining a relatively high accuracy. |
14,470 | Please write an abstract with title: An execution-time estimation model for heterogeneous clusters, and key words: Application software, Matrix decomposition, Knowledge engineering, Degradation, Time measurement, Computer applications, Concurrent computing, Distributed computing, Acceleration, Distributed processing. Abstract: Summary form only given. Heterogeneous clusters are flexible and cost-effective, but entail intrinsic difficulties in optimization. Although it is simple to invoke multiple processes on fast processing elements (PEs) to alleviate load imbalance, the optimum process allocation is not so obvious. Communication time is another problem. It is sometimes better to exclude slow PEs to avoid performance degradation, but it is generally difficult to find the optimal PE configuration. In this study, the execution time is first modeled from the measurement results of various configurations. Then, the derived model is used to estimate the optimal PE configuration and process allocation. We implemented the models from HPL (high performance linpack benchmark) of N = 400-6400, and estimated the optimal configuration for N = 3200-9600. The execution time of the estimated optimal configuration was 0%-3.6% longer than the actual optimal configuration. The models derived from N = 1600-6400 were also constructed, and their errors were 0%-4.3%for N = 1600-9600. |
14,471 | Please write an abstract with title: A Service-Oriented Digital Twins Framework for Smart Grid Management, and key words: Microservice architectures, Intrusion detection, Reliability engineering, Real-time systems, Software, Smart grids, Digital twins. Abstract: Cyber-Physical Systems (CPS) are infrastructures with capabilities of perception, networking, and computation. They consist of physical and virtual components that interact with their environment. Their main goal is to monitor the physical system in real-time to have its behavior under control. Some of these infrastructures require well-defined security measures due to their critical processing capabilities. Digital Twins are defined as virtual structures emulating the physical components in various systems. They enable the deployment of isolated simulation environments to test changes and specify the security issues of a CPS. One of the main applications of CPS is smart grids. Microservices allow us to create fine-grained operations on automation systems. Using small, well-defined, modular processes, we can observe the states of smart grid infrastructure in many stages. In this work, we aim to design a framework that can create a reliable environment for smart grids compliant with existing industrial standards. We propose a service-oriented digital twins framework consisting of entities such as power meters, data aggregators, and system parameters for providing a scalable and highly available platform for complex energy systems. |
14,472 | Please write an abstract with title: A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions, and key words: Sleep, Vehicles, Fatigue, Feature extraction, Roads, Hidden Markov models, Faces. Abstract: Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1–9 or a binary decision as alert (defined as KSS 1–6) or sleepy (defined as KSS 7–9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached. |
14,473 | Please write an abstract with title: Modeling of complex automation systems using colored State Charts, and key words: Object oriented modeling, Unified modeling language, Power system modeling, Petri nets, Real time systems, Computer architecture, Design automation, Power engineering and energy, Formal verification, Usability. Abstract: The design of complex distributed automation systems often presents great challenges due to the size and number of components which have to work in parallel to one another in real time. This paper discusses some of the problems of designing such systems. The use of colored dynamic state diagrams for the modeling of complex real-time systems is suggested as a possible solution. This type of diagram is based on State Charts, the well-known and generally applied description technique included as one variation in the unified modeling language. Colored State Charts harness two techniques: the modelling technique well accepted by engineers, and high level Petri nets with their outstanding powers of description. By coloring State Charts, the behaviour of several objects or processes can be modelled simultaneously in a single figure. The colored state diagrams contain a variety of resources to facilitate clear and unequivocal representation of the composition of a number of simple state diagrams. They also have additional mechanisms for mapping the dependencies and relationships between individual objects. Via transformation into colored Petri nets, they make formal verification possible. Their usability is shown in a modelled reference example. |
14,474 | Please write an abstract with title: Robust pitch estimation using an event based adaptive Gaussian derivative filter, and key words: Robustness, Signal to noise ratio, Iterative algorithms, Adaptive filters, Speech processing, Working environment noise, Detection algorithms, Iterative methods, Smoothing methods, Detectors. Abstract: In the development of practical speech processing algorithms, the ability to automatically and accurately determine the pitch period in noisy environments remains a fundamental obstacle. In this paper, we propose a new pitch detection algorithm based on an iterative adaptive smoothing approach using a Gaussian derivative filter which is the sum of a zeroth and second order Hermite function. We refer to this new algorithm as the adaptive Gaussian derivative filter (AGDF). The AGDF pitch detector works under varying noise conditions, with variable pitch periods and for different speakers. We compare the performance of the AGDF method to the approach based on the dyadic wavelet transform (DyWT) and the pitch prediction (PP) formulation for speech subjected to different noise conditions and signal to noise ratios (SNR). The results show that the AGDF is slightly better than the DyWT pitch detection scheme and significantly outperforms the PP approach. |
14,475 | Please write an abstract with title: Designing Protograph-Based Quasi-Cyclic Spatially Coupled LDPC Codes With Large Girth, and key words: Couplings, Matrix decomposition, Iterative decoding, Block codes, Decoding, Systematics. Abstract: Spatially coupled (SC) low-density parity-check (LDPC) codes can achieve capacity approaching performance with low message recovery latency when using sliding window (SW) decoding. An SC-LDPC code constructed from a protograph can be generated by first coupling a chain of block protographs and then lifting the coupled protograph using permutation matrices. In this paper, we introduce a systematic design to eliminate 4-cycles in a coupled protograph. Further using a quasi-cyclic (QC) lifting, we introduce a procedure for constructing QC-SC-LDPC codes of girth at least eight. This can be interpreted as a multi-stage graph lifting process that yields a greater flexibility in designing QC-SC-LDPC codes with a large girth than previous approaches. Simulation results show the design leads to improved decoding performance, particularly in the error floor, compared to random constructions. Finally, we determine the minimum coupling width required to eliminate 4-cycles in a coupled protograph. |
14,476 | Please write an abstract with title: Modeling fading properties for mobile satellite link channels using Markov model approaches, and key words: Fading, Hidden Markov models, Predictive models, Rayleigh channels, Quadrature phase shift keying, Artificial satellites, Attenuation, Stochastic processes, Statistics, Error probability. Abstract: In this paper, the fading properties of satellite-to-earth propagation channels are predicted using different Markov models. The proposed methods are validated and evaluated using mobile satellite link measurements data at typical mobile user environments. Compared with multi-states Markov models and traditional hidden Markov model, a better match between simulated and measured data shows that the non-stationary hidden Markov model predicts most satisfactorily the first and second order statistics of propagation properties. Besides, the proposed Markov models can be applied to evaluate the performance of error probability using coherent QPSK modulation schemes. This simple and efficient method extends the applicability of the Markov model approach in propagation channel modeling for satellite mobile communication services. |
14,477 | Please write an abstract with title: Research on the Evaluation Technology of Network Audiovisual APP Services, and key words: Network Audiovisual APP, Service Security, Au-diovisual Service Common Security Vulnerabilities, Audiovisual Service Permissions. Abstract: This paper presented measurement methods for audiovisual service security and compliance evaluation in or-der to meet the requirements of network audiovisual service management. In the paper, we introduce the detailed techni-cal requirements for audiovisual service evaluation, as well as suggestions for risk grading and permission for audiovisual services. At the same time, we introduce the architecture and functions of the audio-visual service testing system developed by the project team, and provide the evaluation of APP services based on this testing system. The results show that the system can identify security issues in audiovisual app services and provide modification suggestions. These research results provide technical support for the dissemination security of network audiovisual apps. |
14,478 | Please write an abstract with title: A Benders Decomposition Based Algorithm for Steady-State Dispatch Problem in an Integrated Electricity-Gas System, and key words: Steady-state, Natural gas, Wind farms, Hybrid power systems, Piecewise linear techniques. Abstract: Optimally operating an integrated electricity-gas system (IEGS) is significant for the energy sector. However, the IEGS operation model's nonconvexity makes it challenging to solve the optimal dispatch problem in the IEGS. This letter proposes a new Benders decomposition-based (IBD) algorithm catering to a commonly used steady-state dispatch model of the IEGS. This IBD algorithm leverages a refined decomposition structure where the subproblems are linear and ready to be solved in parallel. We analytically compare our IBD algorithm with an existing Benders decomposition algorithm and a typical piecewise linearization method. Case studies have substantiated the higher computational efficiency of our IBD algorithm. |
14,479 | Please write an abstract with title: Multimodal Proximity and Visuotactile Sensing With a Selectively Transmissive Soft Membrane, and key words: Pressure sensors, Fabrication, Machine vision, Robot vision systems, Soft robotics, Robot sensing systems, Cameras. Abstract: The most common sensing modalities found in a robot perception system are vision and touch, which together can provide global and highly localized data for manipulation. However, these sensing modalities often fail to adequately capture the behavior of target objects during the critical moments as they transition out of static, controlled contact with an end-effector to dynamic and uncontrolled motion. In this work, we present a novel multimodal visuotactile sensor that provides simultaneous visuotactile and proximity depth data. The sensor integrates an RGB camera and air pressure sensor to sense touch with an infrared time-of-flight (ToF) camera to sense proximity by leveraging a selectively transmissive soft membrane to enable the dual sensing modalities. We present the mechanical design, fabrication techniques, algorithm implementations, and evaluation of the sensor's tactile and proximity modalities. The sensor is demonstrated in three open-loop robotic tasks: approaching and contacting an object, catching, and throwing. The fusion of tactile and proximity data could be used to capture key information about a target object's transition behavior for sensor-based control in dynamic manipulation. |
14,480 | Please write an abstract with title: RAS2P: Remote Attestation via Self-Measurement for SGX-based Platforms, and key words: Performance evaluation, Runtime environment, Codes, Protocols, Authentication, Malware, Time measurement. Abstract: Remote Attestation (RA) is a security service by which a Verifier (Vrf) can verify the platform state of a remote Prover (Prv). However, in most existing RA schemes, the Prv might be vulnerable to denial of service (DoS) attacks due to the interactive challenge-response methodology while there is no authentication about the challenge. Worse, many schemes cannot effectively detect mobile malware that can be inactive during the on-demand attestation launched by the Vrf. In this paper, we propose a self-measurement RA for SGX-based platforms, which can effectively mitigate DoS attacks and defend against mobile malware. To this end, a two-way identity authentication is first enforced between the Prv and Vrf with the help of a blockchain system, in which a shared session key is also generated. Secondly, trigger conditions of measurements on the Prv’s side are time points generated by the Prv self instead of Vrf’s requests. The Vrf can retrieve multiple self-measurement results during one execution of the protocol to monitor the Prv’s platform over a period of time continuously, which can detect mobile malware effectively. Our scheme utilizes SGX to provide the runtime protection for sensitive information such as session key, self-measurement code, time points of self-measurements, and self-measurement results, making a higher security guarantee. In addition, the session key, time points of self-measurements, and self-measurement code can be changed or upgraded, making our scheme more flexible and scalable. The simulation implementation and results show that our scheme is feasible and practical. |
14,481 | Please write an abstract with title: 3D Reconstruction using HDR-based SLAM, and key words: Three-dimensional displays, Cameras, Simultaneous localization and mapping, Image reconstruction, Image color analysis, Pipelines, Visualization. Abstract: 3D reconstruction is the key technology to emerging technologies such as smart robotics, VR/AR/XR and autonomous driving. To enhance the robustness of our proposed 3D reconstruction system, the HDR-based SLAM is adopted in the camera pose estimation step to improve the qualitative result of geometric reconstruction. The proposed HDR-based SLAM uses the pre-calibrated inverse camera response function (CRF) to map a single RGB image into a radiance map. To exclude the influence of exposure time, normalized radiance maps independent of exposure time are used during tracking. Since ORB feature matching is the basic element of tracking and mapping in our system, the ORB descriptor patch is re-trained especially for normalized radiance maps. Experimental results have shown good performance of our system under challenging low-light environment, which helps expand the applicability of 3D reconstruction system. |
14,482 | Please write an abstract with title: Threshold method to reduce PAPR in wavelet based multicarrier modulation systems, and key words: Peak to average power ratio, Multiresolution analysis, Discrete wavelet transforms, Equations, Wavelet packets, Filters, Baseband, Mirrors, Mobile communication, Intserv networks. Abstract: A novel peak to average power ratio (PAPR) reduction method, threshold method, for wavelet based multicarrier modulation (WMCM) systems is proposed and presented in this paper. Theory analysis and simulation results both prove that our proposed PAPR reduction method to be a feasible and efficient one for multicarrier modulation system (MCM) |
14,483 | Please write an abstract with title: Time Multiplexing via Circuit Folding, and key words: Combinational circuits, Pins, Clocks, Logic gates, Field programmable gate arrays, Time division multiplexing. Abstract: Time multiplexing is an important technique to overcome the bandwidth bottleneck of limited input-output pins in FPGAs. Most prior work tackles the problem from a physical design standpoint to minimize the number of cut nets or Time Division Multiplexing (TDM) ratio through circuit partitioning or routing. In this work, we formulate a new orthogonal approach at the logic level to achieve time multiplexing through structural and functional circuit folding. The new formulation provides a smooth trade-off between bandwidth and throughput. Experiments show the effectiveness of the structural method and improved optimality of the functional method on look-up-table and flip-flop usage. |
14,484 | Please write an abstract with title: Weighted Shallow-Deep Feature Fusion Network for Pansharpening, and key words: Visualization, Adaptive systems, Fuses, Geoscience and remote sensing, Pansharpening, Feature extraction, Convolutional neural networks. Abstract: In this paper, we propose a novel weighted shallow-deep feature fusion convolutional neural network (WSDFNet) for the task of multispectral image pansharpening. This network could effectively overcome the drawback of the common identity skip connection (ISC), and propagate shallow features scaled by a novel adaptive skip weighter (ASW) to deeper layers. By the technique, it could favor the feature fusion in different network depths adequately, as well as yield a promising outcome. Experimental results on reduced- and full-resolution WorldView-3 dataset demonstrate the superiority of the WSDFNet compared with recent state-of-the-art (SOTA) pansharpening approaches. Moreover, WSDFNet is also verified as a lightweight network. |
14,485 | Please write an abstract with title: Back-Guard: Wireless Backscattering based User Activity Recognition and Identification with Parallel Attention Model, and key words: Backscatter, Wireless communication, Wireless sensor networks, Activity recognition, Motion segmentation, Communication system security. Abstract: With the rapid advance of smart home and office systems, it becomes possible to provide a fine-grained user activity tracking service accurately recognizing user activities and identities in a seamless and non-invasive manner. Such a system can find applications in various domains, such as elder safeguard, customized services, and simply personal activity diary. Recently, several radio frequency (RF) based sensing systems were proposed for human sensing, most of which focus on limited scenarios and suffer from interference caused by other users or wireless devices. To tackle this challenge, we propose Back-Guard, which achieves accurate and non-intrusive user activity recognition and then user identification through battery-free wireless backscattering. Back-Guard carefully examines the backscatter spectrogram data and extracts high-level features from both spatial and temporal domains that can characterize the user behaviors. Leveraging the parallel attention based deep learning models, our system can discriminate different motions and users accurately and robustly in various situations. We implement a prototype system and collect data in actual scenarios from 25 users for over 2 months. Extensive experiments demonstrate the promising performance of our system. In particular, Back-Guard achieves 93.4% activity recognition accuracy and 91.5% user identification accuracy, respectively. Our experiments also demonstrate little accuracy reduction when multiple users are separated, e.g., by around 2 meters. |
14,486 | Please write an abstract with title: Server-based scheduling of the CAN bus, and key words: Processor scheduling, Bandwidth, Automotive engineering, Timing, Real time systems, Communication system traffic, Broadcasting, Computer science, Application software, Design optimization. Abstract: In this paper we present a new share-driven server-based method for scheduling messages sent over the controller area network (CAN). Share-driven methods are useful in many applications, since they provide both fairness and bandwidth isolation among the users of the resource. Our method is the first share-driven scheduling method proposed for CAN. Our server-based scheduling is based on earliest deadline first (EDF), which allows higher utilization of the network than using CAN's native fixed-priority scheduling approach. We use simulation to show the performance and properties of server-based scheduling for CAN. The simulation results show that the bandwidth isolation property is kept, and they show that our method provides a quality-of-service (QoS), where virtually all messages are delivered within a specified time. |
14,487 | Please write an abstract with title: Brain Tissue Segmentation via Deep Convolutional Neural Networks, and key words: Training, Brain, Three-dimensional displays, Pipelines, Software, Windows, Convolutional neural networks. Abstract: Deep convolutional neural networks were used to successfully segment several important neural tissue classes in MRI brain images, and approaches for integrating prior information into the networks to increase their performance on this task were investigated. Regrettably, only the first of them is addressed in this paper. To make the implementation of nonstandard architectures, which was expected to be required for the second goal, it was determined to provide a framework for defining and training networks by only using fundamental components. While this was an educational experience, the amount of progress accomplished was far less than if a conventional network package had been utilized instead. The requirement to deal with all of the lowest level aspects of network construction, from initialization schemes to adaptive learning rates and all the other components of the optimizer pipeline has left no time for utilizing this infrastructure to do something which has not been accomplished by the existing frameworks, and of course in all other respects it is far more limited than they are. It would in-stead be focused on a clear and detailed analysis of the full pipeline, which is required to build a network for solving the first problem. Despite several difficulties tracking down bugs in the optimizer, GPU memory allocation, and the last-minute accidental deletion of a large portion of the experimental results, the software implementation made available at: achieves DICE results of 0:8, which, while not class leading, would still place well in many benchmarks. |
14,488 | Please write an abstract with title: GMM-based Document Clustering of Knowledge Graph Embeddings, and key words: Knowledge engineering, Dimensionality reduction, Deep learning, Semantics, Natural languages, Clustering algorithms, Reinforcement learning. Abstract: Digital technology and World Wide Web have re-sulted in a growth in the number of digital documents. The ma-jority of the data is unstructured, and extracting information into a structured machine-readable format remains a difficult under-taking. Clustering, which automatically categorizes information into meaningful groupings, is one of the most important activ-ities. Several information extraction and information gathering applications use document clustering. Document clustering is an unsupervised method for dividing a big corpus of documents into smaller, meaningful, identifiable, and verifiable sub-groups. But capturing the semantics of the documents is still an open problem. A knowledge graph can represent the relationships between the entities in the document collection. But a knowledge graph gets extremely dense and high-dimensional as the amount of data increases, requiring significant processing resources. We aim to explore this problem by using Knowledge Graph Embedding (KGE), which maps the high-dimensional representation into a compute-efficient low-dimensional embedded representation and then cluster these embeddings using the Gaussian Mixture Model (GMM)-based clustering technique. Dimensionality reduction of the embeddings has been done using t-SNE. We have found that the silhouette coefficient has improved considerably for t-SNE based GMM clustering as compared to Kmeans clustering alone. |
14,489 | Please write an abstract with title: Early detection of masses in digitized mammograms using texture features and neuro-fuzzy model, and key words: Breast tissue, Image edge detection, Image segmentation, Mammography, Breast cancer, Cancer detection, Lesions, Histograms, Feature extraction, Neoplasms. Abstract: A neuro-fuzzy model for fast detection of candidate circumscribed masses in digitized mammograms is presented. The breast tissue is scanned using variable window size, for each sub-image co-occurrence matrices in different orientations (/spl theta/=0/spl deg/, 45/spl deg/, 90/spl deg/ and 135/spl deg/) are calculated and texture features are estimated for each co-occurrence matrix, then the features are used to train neuro-fuzzy models. The classification results reach 100% for abnormal cases and 80% for normal ones. |
14,490 | Please write an abstract with title: Research on the Factors Influencing the Intention to Use Intelligent Teaching Tools under the Integrated Model, and key words: Technology acceptance model, Education, Tools, Market research, Internet, Information technology, Robots. Abstract: Under the trend of information teaching on the mobile Internet, intelligent teaching tools promote the effectiveness of intelligent teaching tools in teaching design and teaching interaction, and enrich the diversification of classroom teaching. Optimize the depth of teaching interaction and the accuracy of classroom effective evaluation and feedback. This study constructs an integrated technology acceptance model based on six dimensions: performance expectation, information technology level, improvement of academic performance, technology satisfaction teaching-task adaptation, and external factors (school, society, teachers) to explore the influencing factors of teacher' intention to use intelligent teaching tool. The results show that the six dimensions indicators of the model have a significant positive impact on the use intention. The research results play a positive role in guiding teachers to make effective use of teaching tools to carry out teaching. |
14,491 | Please write an abstract with title: Revive Family Photo Albums through a Collaborative Environment Exploiting the HoloLens 2, and key words: Social networking (online), Collaboration, Human factors, Social factors, Digital photography, Artificial intelligence, Augmented reality. Abstract: While human culture evolves, human heritage remains frozen in time, engraved in material culture as a testament to the past. Among such materials, pictures amount to a prominent example, as they yield information and clues about what happened in the past. In fact, pictures from the past represent a unique chance to revive old memories about affections, relatives, friends, special events etc. During all of the 20th century people printed and collected pictures in photo albums, namely family albums. Even if this phenomenon is not as popular as before, due to the advent of digital photography and the spread of social media, such kind of photos are still of interest, for all those who like to look back and discover their families’ pasts. At the time of social distancing, such photo albums may represent a link between people who are forced to stay away from each other and a distraction from worries and fears. For this reason, we here propose an augmented reality application, as a digital application that may bring people together and support the exploration of the content of photo albums with the aid of artificial intelligence paradigms. |
14,492 | Please write an abstract with title: RIS-Aided Multiple User Interference Mitigation via Fast Successive Upper-Bound Minimization Method, and key words: Interference, Transmitters, Receivers, Cost function, Linear programming, Genetic algorithms, Computational efficiency. Abstract: Reconfigurable intelligent surfaces (RIS) aided multiple user interference mitigation with constant modulus constraint (CMC) is a key issue in the future 6G communication systems. Usually, the existing methods solve this problem either by relaxing the CMC with performance degrading or by relaxing the cost function with huge computational cost. To achieve a good trade-off between the performance and the complexity, a Fast Successive Upper-bound Minimization (FSUM) method is proposed. In the proposed method, the problem is first reformulated as a penalty quadratic function with CMC. Then, by efficiently finding the surrogate function, a FSUM algorithm is derived to obtain the solution. Compared with the existing methods, the proposed method can achieve 0.4 bits/Hz/s average sum-achievable rate gain enhancement. |
14,493 | Please write an abstract with title: Low threshold current operation of membrane DR laser on Si with buried-ridge waveguide and ACPM grating for On-chip Optical Interconnection, and key words: Optical interconnections, Semiconductor lasers, Waveguide lasers, Threshold current, Silicon, System-on-chip, Semiconductor waveguides. Abstract: To reduce energy consumption of GaInAsP membrane laser on Si, we introduced BRW (buried-ridge-waveguide) structure and ACPM (Asymmetric Corrugation Pitch Modulation) grating to enhance the optical confinement to active region. Low threshold current of 0.16 mA and SMSR of 45dB were obtained by fabricating membrane DR laser with these structures. |
14,494 | Please write an abstract with title: Part Mutual Information Based Quality-related Component Analysis for Fault Detection, and key words: Monitoring, Mutual information, Fault detection, Real-time systems, Probability distribution, Input variables, Matrix decomposition. Abstract: In this paper, a novel part mutual information based quality-related component analysis (PMIQCA) method is presented to detect quality-related faults and reduce the interference alarms. The low-dimensional subspace of process variables can be found, which reflects real-time changes in quality. The detection rates of quality-unrelated faults can be reduced while the detection rates of faults that are related to quality are increased. The basic idea is to select the most relevant process variables and principal components (PCs) with the maximal part mutual information (PMI) for each iteration, so as to build a more accurate supervisory relations between process variables and quality. Afterwards, two appropriate statistics are established for quality-related fault detection. Finally, the Tennessee Eastman Process (TEP) is carried out to demonstrate the effectiveness of PMIQCA. |
14,495 | Please write an abstract with title: Human Factors Associated with Self-reported Aberrant Behavior-A Study of Different Indian Autorickshaw Driver Age Group, and key words: Visualization, Roads, Measurement uncertainty, Education, Psychology, Human factors, Maintenance engineering. Abstract: Driving is a complicated task that demands a high level of concentration for processing information and reacting to the road environment. Therefore, Human factors play an important role during driving task performance. The objective of this study is to investigate the human factors that impact driving behavior in different age groups of autorickshaw drivers in India. These factors are mainly associated with cognitive or psychological factors and personal characteristics. This study was conducted in the Mumbai, Maharashtra region with a total of 96 male autorickshaw drivers of two different age groups. A conventional neuropsychological battery was utilized to assess the cognitive ability of the drivers including simple reaction time, concentration, short-term memory, visual acuity, and matrix reasoning. A driving behavior questionnaire (DBQ) was developed and applied to measure the violation and errors done by the autorickshaw drivers. To identify the traffic knowledge of the drivers 10 traffic sign-related photographs were shown to the drivers to know their awareness about traffic signs and rules. Finding from the result shows that the simpler reaction time, visual acuity, and short-term memory are significantly correlated with the DBQ score. Lack of education and traffic knowledge was found among both groups of drivers but in the young age group, the DBQ score was found higher in comparison with the old drivers due to increased violation and error scores. |
14,496 | Please write an abstract with title: The Potential of LLC Resonant Converters Equipped With Split Resonant Capacitors: From Three-Phase to Fractal Structures, and key words: Network topology, Capacitors, Resonant frequency, RLC circuits, Resonant converters, Voltage, Fractals. Abstract: This paper extends the application range of a high efficiency and high power density dc-dc converter, a three-phase LLC resonant converter equipped with split resonant capacitors. The circuit topology features its resonant capacitor network. One resonant capacitor is connected to the dc input terminal, and the other is interconnected to the other phases, enabling natural current balancing and phase shedding. This paper develops three extended topologies based on the three-phase LLC resonant converter. A voltage-doubler rectifier for a higher output voltage range reduces the output voltage ripple without compromising the single-phase operation capability. Tuning the split ratio for a higher output current range reduces the currents in operation around the resonant frequency. An auxiliary switch for a wide input voltage range reduces the currents in operation below the resonant frequency. Furthermore, this paper introduces a new structure to connect multiple LLC resonant converters for a wide power range by expanding the capacitor network. A 4-kW experimental prototype based on the structure achieves a high efficiency over 99% from 5% to full load even with Si MOSFETs. |
14,497 | Please write an abstract with title: Dynamical Frequency Displacement Scheme for Fault-tolerant LLC Topology, and key words: Topology, Power supplies, Magnetic resonance, HEMTs, Gallium nitride, Mathematical model. Abstract: Gallium-nitride high-electron-mobility transistor (GaN HEMT) is a promising candidate for implementing next-generation power converter owing to wide semiconductor bandgap with excellent Johnson's figure of merit [1]. GaN HEMT has matured noticeably over the past decade and opened up the avenue to performance revolution in a wide variety of applications, ranging from active electronically scanned array (AESA) radar systems [2] to ultra-eco-friendly power converter [3]. In this work, a GaN & Silicon hybrid fault-tolerant LLC topology complemented by a deep-learning-based migration control (DLM) and a computation-free migration control (CFM) are introduced. This combination allows one to leverage the intrinsic fault-recovery mechanism of the proposed topology and empower the converter to recuperate from a failing system, an analog to N+1 redundancy power system at a fraction of the cost and reduced point-of-failure. |
14,498 | Please write an abstract with title: In-Situ Joint Light and Medium Estimation for Underwater Color Restoration, and key words: Sea surface, Parameter estimation, Image color analysis, Endoscopes, Estimation, Scattering, Ray tracing. Abstract: The majority of Earth’s surface is situated in the deep sea and thus remains deprived of natural light. Such adverse underwater environments have to be explored with powerful camera-light systems. In order to restore the colors in images taken by such systems, we need to jointly estimate physically-meaningful optical parameters of the light as well as the water column. We thus propose an integrated in-situ estimation approach and a complementary surface texture recovery strategy, which also removes shadows as a by-product. As we operate in a scattering medium under inhomogeneous lighting conditions, the volumetric effects are difficult to capture in closed-form solutions. Hence, we leverage the latest progress in Monte Carlo-based differentiable ray tracing that becomes tractable through recent GPU RTX-hardware acceleration. Evaluations on synthetic data and in a water tank show that we can estimate physically meaningful parameters, which enables color restoration. The approaches could also be employed to other camera-light systems (AUV, robot, car, endoscope) operating either in the dark, in fog – or – underwater. |
14,499 | Please write an abstract with title: An Event-Based System for Low-Power ECG QRS Complex Detection, and key words: Electrocardiography, Interpolation, Approximation algorithms, Software algorithms, Wearable computers, Hardware, Energy consumption. Abstract: One of the greatest challenges in the design of modern wearable devices is energy efficiency. While data processing and communication have received a lot of attention from the industry and academia, leading to highly efficient microcontrollers and transmission devices, sensor data acquisition in medical devices is still based on a conservative paradigm that requires regular sampling at the Nyquist rate of the target signal. This requirement is usually excessive for sparse and highly non-stationary signals, leading to data overload and a waste of resources in the full processing pipeline. In this work, we propose a new system to create event-based heart-rate analysis devices, including a novel algorithm for QRS detection that is able to process electrocardiogram signals acquired irregularly and much below the theoretically-required Nyquist rate. This technique allows us to drastically reduce the average sampling frequency of the signal and, hence, the energy needed to process it and extract the relevant information. We implemented both the proposed event-based algorithm and a state-of-the-art version based on regular Nyquist rate based sampling on an ultra-low power hardware platform, and the experimental results show that the event-based version reduces the energy consumption in runtime up to 15.6 times, while the detection performance is maintained at an average F1 score of 99.5%. |
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