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14,300 | Please write an abstract with title: Automated creation of parallel Bible corpora with cross-lingual semantic concordance, and key words: Computer science, Annotations, Semantics, Quality control. Abstract: Here we present a novel approach for automated creation of parallel New Testament corpora with cross-lingual semantic concordance based on Strong’s numbers. As scientific editions and translations of Bible texts are often not free to use for scientific purposes and are rarely free to use, and due to the fact that the annotation, curation and quality control of alignments between these texts are quite expensive, there is a lack of available Biblical resources for scholars. We present two approaches to tackle the problem, a dictionary-based approach and a Conditional Random Field (CRF) model and a detailed evaluation on annotated and non-annotated translations. We discuss a proof-of-concept based on English and German New Testament translations. The results presented in this paper are novel and according to our knowledge unique. They present promising performance, although further research is necessary. |
14,301 | Please write an abstract with title: Low-Light Image Restoration With Short- and Long-Exposure Raw Pairs, and key words: Imaging, Image color analysis, Colored noise, Task analysis, Pipelines, Noise reduction, Mobile handsets. Abstract: Low-light imaging with handheld mobile devices is a challenging issue. Limited by the existing models and training data, most existing methods cannot be effectively applied in real scenarios. In this paper, we propose a new low-light image restoration method by using the complementary information of short- and long-exposure images. We first propose a novel data generation method to synthesize realistic short- and long-exposure raw images by simulating the imaging pipeline in low-light environment. Then, we design a new long-short-exposure fusion network (LSFNet) to deal with the problems of low-light image fusion, including high noise, motion blur, color distortion and misalignment. The proposed LSFNet takes pairs of short- and long-exposure raw images as input, and outputs a clear RGB image. Using our data generation method and the proposed LSFNet, we can recover the details and color of the original scene, and improve the low-light image quality effectively. Experiments demonstrate that our method can outperform the state-of-the-art methods. |
14,302 | Please write an abstract with title: Variable structure systems with sliding modes, and key words: Variable structure systems, Regulators, Switches, State feedback, Eigenvalues and eigenfunctions, Control systems, Logic design, Laboratories, Asymptotic stability. Abstract: Variable structure systems consist of a set of continuous subsystems together with suitable switching logic. Advantageous properties result from changing structures according to this switching logic. Design and analysis for this class of systems are surveyed in this paper. |
14,303 | Please write an abstract with title: Detection Performance and Energy Efficiency of Sequential Detection in a Sensor Network, and key words: Energy efficiency, Intelligent networks, Sensor fusion, Event detection, Wireless sensor networks, Data communication, Sequential analysis, Educational institutions, Sensor systems, Laboratories. Abstract: Wireless sensor networks with event detection mechanisms are considered. Based on a simplified sensor network model, a distributed sequential detection scheme is proposed and investigated. Optimal sequential decision rule is derived and its detection performance is compared with that of the non-sequential detection. Our results show that on average the sequential detection requires fewer measurements than the non-sequential detection to achieve the same detection accuracy. Furthermore, energy efficiency of the two schemes is compared, and distinctive performance for different values of system parameters is observed. |
14,304 | Please write an abstract with title: Calculating the Minimum Number of Iterative Stages in a Wide-Band Amplifier, and key words: Broadband amplifiers, Bandwidth, Voltage, Circuits, Equations, Iterative methods, Electron tubes, Councils, Polynomials. Abstract: This correspondence reports a method of calculating the minimum number of iterative stages required to satisfy a given gain and bandwidth specification. The method can be applied to transistor or vacuum tube video amplifiers so long as the individual stage gain-bandwidth product is constant. |
14,305 | Please write an abstract with title: The performance of the GPSC/MSGC hybrid detector with argon-xenon gas mixtures, and key words: Solid scintillation detectors, Energy resolution, Xenon, Optical feedback, Argon, Spectroscopy, Scintillation counters, Microstrip, Signal processing, Electron optics. Abstract: The performance for X-ray spectrometry of Ar-Xe gas proportional scintillation counters using a CsI-coated microstrip plate in direct contact with the scintillation gas as a VUV photosensor is investigated for different argon-xenon mixtures. The GPSC/MSGC hybrid detectors filled with argon-xenon mixtures present superior performance when compared to those with pure argon and pure xenon-fillings. For these mixtures, the signal amplification due to the scintillation processes and the detector energy resolution may achieve values of 15-18 and 11-10%, respectively. Best energy resolutions can be achieved for mixtures with a broad range of xenon concentration, 20 to 70% Xe, being achieved for lower reduced electric fields in the scintillation region as the xenon concentration is reduced. As in pure argon or pure xenon gas-filling, the detector performance is limited by optical positive feedback resulting from additional scintillation produced in the electron avalanche processes around the MSP anodes. Best energy resolutions are achieved for positive feedback gains of about 1.1. |
14,306 | Please write an abstract with title: Design of Higher-Order Regulator System using Pole-Placement Technique, and key words: State feedback, Feedback loop, Regulators, Fluctuations, Simulation, SISO communication, Power systems. Abstract: This paper deals with designing of higher-order single-input, single-output (SISO) regulator system by the use of pole-placement technique. For linear control systems, pole-placement is a well-established design method. In classical control designing, only dominant poles are considered however recent pole-assignment technique specifies all closed-loop poles (CLP). In this approach, we assumed that the system is completely state controllable (CSC), the state variable can be measured and feedback is available and the control input is not constrained. State-space regulators are known by many of the engineers either they are more complicated to understand or modeling of a system to design a robust and stable feedback loop is needed. However, state-space regulators are used in number of plants. In this paper, we have taken higher order systems (more than 3rd order system). A regulator system is a system in which the reference input is zero always. The pole-placement (PP) method is used in the development of the regulator. Inverted pendulum (4th order), Tape drive control (5th order) and Aircraft control (6th order) system are taken as example. The intention of this paper is to design of state feedback control, determine state feedback gain matrix (Kp) to meet the requirement and plot response of each state variable. The response of state variables are following the zero input because it is a regulatory system. MATLAB has been used for implementation. |
14,307 | Please write an abstract with title: Effects of Droplet Volumes on Acoustothermal Heating in 128° YX LiNbO<inf>3</inf> Substrates, and key words: Heating systems, Temperature sensors, Temperature measurement, Proteins, Performance evaluation, Liquids, Lithium niobate. Abstract: Surface acoustic wave (SAW) devices can generate significant heat due to acoustic damping when liquid droplets are placed on them, and this heating (acoustothermal heating) can be used for microscale heating purposes. However, SAW devices are often used in biosensing applications where significant acoustothermal temperature rise can damage the proteins or the biomolecules and destroy the sensor performances. In this paper, we have performed thermal camera-based experiments to study the heating phenomena and how they can be controlled by varying droplet sizes. We found that the temperature rise linearly increases with increasing SAW power whereas it decreases with increasing droplet volume. Hence, a larger liquid volume and lower SAW power can be used in biosensors to avoid significant heating. |
14,308 | Please write an abstract with title: Risk assessment of credit field based on PSO-SVM, and key words: Support vector machines, Analytical models, Support vector machine classification, Predictive models, Prediction algorithms, Data models, Classification algorithms. Abstract: With the advent of the era of big data and the application of machine learning, user credit risk assessment in the credit process has gradually changed from traditional manual assessment to intelligent algorithm recognition. This paper proposes a support vector machine combination model based on particle swarm optimization and applies the model to user credit risk assessment. The paper first uses a support vector machine (SVM) with a radial basis function core (RBF core) as the core function as a verification algorithm, and then uses a particle swarm optimization algorithm (PSO) to optimize the parameters of the SVM, and establishes a particle swarm algorithm based Support vector machine combination model (PSO-SVM), finally compare the model with the original SVM, neural network, random forest, naive Bayes and other models on the UCI data set, and use Recall, Precision, Accuracy and F-score to evaluate Model performance. Empirical analysis proves that the model proposed in this paper has a good predictive classification effect. |
14,309 | Please write an abstract with title: CONTROL-CORE: A Framework for Simulation and Design of Closed-Loop Peripheral Neuromodulation Control Systems, and key words: Control systems, Computational modeling, Codes, Protocols, Closed loop systems, Ecosystems, Matlab, Neuromodulation. Abstract: Closed-loop Vagus Nerve Stimulation (VNS) based on physiological feedback signals is a promising approach to regulate organ functions and develop therapeutic devices. Designing closed-loop neurostimulation systems requires simulation environments and computing infrastructures that support i) modeling the physiological responses of organs under neuromodulation, also known as physiological models, and ii) the interaction between the physiological models and the neuromodulation control algorithms. However, existing simulation platforms do not support closed-loop VNS control systems modeling without extensive rewriting of computer code and manual deployment and configuration of programs. The CONTROL-CORE project aims to develop a flexible software platform for designing and implementing closed-loop VNS systems. This paper proposes the software architecture and the elements of the CONTROL-CORE platform that allow the interaction between a controller and a physiological model in feedback. CONTROL-CORE facilitates modular simulation and deployment of closed-loop peripheral neuromodulation control systems, spanning multiple organizations securely and concurrently. CONTROL-CORE allows simulations to run on different operating systems, be developed in various programming languages (such as Matlab, Python, C++, and Verilog), and be run locally, in containers, and in a distributed fashion. The CONTROL-CORE platform allows users to create tools and testbenches to facilitate sophisticated simulation experiments. We tested the CONTROL-CORE platform in the context of closed-loop control of cardiac physiological models, including pulsatile and nonpulsatile rat models. These were tested using various controllers such as Model Predictive Control and Long-Short-Term Memory based controllers. Our wide range of use cases and evaluations show the performance, flexibility, and usability of the CONTROL-CORE platform. |
14,310 | Please write an abstract with title: Total least squares approach for frequency estimation using linear prediction, and key words: Least squares approximation, Frequency estimation, Signal resolution, Signal to noise ratio, Matrix decomposition, Degradation, Least squares methods, Equations, Singular value decomposition, Noise reduction. Abstract: The resolution of the estimated closely spaced frequencies of the multiple sinusoids degrades as the signal-to-noise ratio (SNR) of the received signal becomes low. This resolution can be improved by using the total least squares (TLS) method in solving the linear prediction (LP) equation. This approach makes use of the singular value decomposition (SVD) of the augmented matrix for low rank approximation to reduce the noise effect from both the observation vector and the LP data matrix simultaneously. Comparison is made to the principle eigenvector (PE) method of Tufts and Kumaresan, both on theoretical and experimental grounds. The TLS algorithm exhibits superior performance over the PE method where low rank approximation is applied to the data matrix only. |
14,311 | Please write an abstract with title: N42.38-2022 - IEEE Standard for Spectroscopy-Based Radiation Portal Monitors Used for Homeland Security, and key words: IEEE N42.38TM, portal monitor, spectrometric, spectroscopy. Abstract: The performance requirements for spectroscopy-based radiation portal monitors are described in this standard. The requirements stated are based on portal monitors used in support of efforts associated with the U.S. Department of Homeland Security. The PDF of this standard is available at no cost compliments of the partnership with the Department of Homeland Security Domestic Nuclear Detection Office and the IEEE GET Program https://ieeexplore.ieee.org/browse/standards/get-program/page/series?id=83 |
14,312 | Please write an abstract with title: Performance Characterization of Equalization Techniques in MIMO System under Co-channel Interference and Spatial Correlation, and key words: MIMO communication, Cloud computing, Data science, Multiplexing, Maximum likelihood detection, Silicon carbide, Interference cancellation. Abstract: Advancements in mobile data communications require a very robust and reliable system. Future wireless systems requires high bit rate, low bit error rate, maximum transmission with very low power, lower bandwidth etc. The designed system should also be able to combat the effects of noise, co-channel interference (CCI), inter-symbol interference (ISI), spatial correlation and multipath fading effects. These effects deteriorate the performance of system significantly. MIMO system with more than one antenna at the transmitter and the receiver are used to combat all these impairments. Different detection techniques are applied at the receiver for the equalization and reduction of unwanted effects. In this paper, bit error rate (BER) of different equalization algorithms has been derived under the influence of ISI, CCI, and spatial correlation. Different Equalization techniques like ZF, MMSE, ZF-SIC, MMSE-SIC and ML. |
14,313 | Please write an abstract with title: Analysis of College Students' Creativity Consciousness Driven under the Background of Blockchain, and key words: Economics, Art, Machine learning, Cognition, Blockchains, Cultural differences, Creativity. Abstract: Taking the current situation of contemporary college students' creativity consciousness as the research subject and based on the concept of creativity driven, 648 college students were randomly sampled, a questionnaire survey was conducted by the Creativity Consciousness Scale and the data was statistically analyzed by SPSS13.0. It was found that college students' creativity consciousness was generally not high but they had strong creativity emotions and motivations. What has an impact on college students' creativity consciousness is demographic variables such as gender, major and grade. |
14,314 | Please write an abstract with title: A Combined Approach for Customer Profiling in Video on Demand Services Using Clustering and Association Rule Mining, and key words: Data mining, Customer relationship management, IPTV, Clustering algorithms, Tools, Video on demand. Abstract: The purpose of this paper is to propose a combined data mining approach for analyzing and profiling customers in video on demand (VoD) services. The proposed approach integrates clustering and association rule mining. For customer segmentation, the LRFMP model is employed alongside the k-means and Apriori algorithms to generate association rules between the identified customer groups and content genres. The applicability of the proposed approach is demonstrated on real-world data obtained from an Internet protocol television (IPTV) operator. In this way, four main customer groups are identified: “high consuming-valuable subscribers”,” less consuming subscribers”,” less consuming-loyal subscribers” and “disloyal subscribers”. In detail, for each group of customers, a different marketing strategy or action is proposed, mainly campaigns, special-day promotions, discounted materials, offering favorite content, etc. Further, genres preferred by these customer segments are extracted using the Apriori algorithm. The results obtained from this case study also show that the proposed approach provides an efficient tool to form different customer segments with specific content rental characteristics, and to generate useful association rules for these distinct groups. The proposed combined approach in this research would be beneficial for IPTV service providers to implement effective CRM and customer-based marketing strategies. |
14,315 | Please write an abstract with title: Computational Experimental Study on Social Organization Behavior Prediction Problems, and key words: Predictive models, Prediction algorithms, Organizations, Learning systems, Biological system modeling, Data mining, Data models. Abstract: With the development of mobile Internet, behavioral trajectories of human life are more and more recorded, which makes it possible to use computer technology to mine organizational behavior patterns. The mining of organizational behavior patterns based on social computing can not only prepare them in a targeted manner but also predict the consequences of possible measures. The organization behavior pattern mining has achieved a series of achievements in the fields of e-commerce and enterprise management. However, the problem of class imbalance and nonconsistent misclassification cost is common in the field of organizational behavior. For this problem, this article compares and analyzes the performance of the organizational behavior prediction model established by four typical cost-sensitive learning methods based on six classifiers, which provides a basis for the appropriate selection of cost-sensitive learning methods in different situations. Among them, the upsampling learning method is a better cost-sensitive learning method. However, there are some shortcomings in the upper sampling method. In order to avoid the possible overfitting problem of the social organization behavior prediction model established by the upper sampling method, this article proposes a new cost-sensitive learning method suitable for the mining of organizational behavior patterns. Based on the cost curve, this article proposes an effective personalized solution to the problem of class disequilibrium and nonconsistent misclassification cost in organizational behavior prediction modeling. |
14,316 | Please write an abstract with title: Guidance Through Surrogate: Toward a Generic Diagnostic Attack, and key words: Smoothing methods, Robustness, Training, Optimization, Behavioral sciences, Computational modeling, Perturbation methods. Abstract: Adversarial training (AT) is an effective approach to making deep neural networks robust against adversarial attacks. Recently, different AT defenses are proposed that not only maintain a high clean accuracy but also show significant robustness against popular and well-studied adversarial attacks, such as projected gradient descent (PGD). High adversarial robustness can also arise if an attack fails to find adversarial gradient directions, a phenomenon known as “gradient masking.” In this work, we analyze the effect of label smoothing on AT as one of the potential causes of gradient masking. We then develop a guided mechanism to avoid local minima during attack optimization, leading to a novel attack dubbed guided projected gradient attack (G-PGA). Our attack approach is based on a “match and deceive” loss that finds optimal adversarial directions through guidance from a surrogate model. Our modified attack does not require random restarts a large number of attack iterations or a search for optimal step size. Furthermore, our proposed G-PGA is generic, thus it can be combined with an ensemble attack strategy as we demonstrate in the case of auto-attack, leading to efficiency and convergence speed improvements. More than an effective attack, G-PGA can be used as a diagnostic tool to reveal elusive robustness due to gradient masking in adversarial defenses. |
14,317 | Please write an abstract with title: Performance Evaluation of Classifiers for Predicting Infection Cases of Dengue Virus Based on Clinical Diagnosis Criteria, and key words: Classification algorithms, Viruses (medical), Clinical diagnosis, Data mining, Prediction algorithms, Support vector machines, Diseases. Abstract: Dengue fever caused by dengue virus infection is a severe health threat that can lead to death. In the medical and health field, to classify data, data mining exploitation and classification methods have an essential role in predicting disease. Two main criteria are crucial to diagnosing dengue virus infection, namely the criteria clinical diagnosis and laboratory diagnosis. Dengue infection based on clinical signs and symptoms, as well as laboratory examinations, is made in three clinical diagnosis criteria, which consist of dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS). This study was conducted with the primary objective to test and evaluate eight different classification algorithms to find the best algorithm in terms of efficiency and effectiveness. Classification algorithm used to predict dengue virus infection cases into three classes of DF, DHF, and DSS based on the performance of accuracy, precision, and recall. The classification algorithm used in this comparison were Neural Networks (NN), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision Tree, Random Forest, Naïve Bayes, AdaBoost, and Logistic Regression. The dataset called DBDDKK was collected from the Division of Disease Prevention and Control in the Semarang City Health Office, Central Java, Indonesia. Impute missing values, selection relevant feature, and normalize feature conducted in the preprocessing stage resulted in 14,019 records with 16 attributes for each record. Then the data were split into 70% for training data and 30% for testing data. Cross-validation with the number of folds 10 is applied to validate the accuracy during the dataset training process. The result of the comparison shows that the NN algorithm has the best accuracy that was over other algorithms. |
14,318 | Please write an abstract with title: 3D Reconstruction from Outdoor Ultrasonic Image Using Variation Autoencoder, and key words: Three-dimensional displays, Ultrasonic variables measurement, Shape, Interference, Acoustics, Distance measurement, Doppler effect. Abstract: We introduce a 3D object reconstruction technique using an ultrasonic array sensor and a variational autoencoder (VAE) in a high-interference environment. As described in this paper, we first explain how to carry out beam forming and how to measure distances using ultrasonic waves. Next, we describe a method for experimentation with 3D object reconstruction and reconstruction techniques. Finally, using this method, results obtained by attaching an ultrasonic sensor to a utility pole and performing ultrasonic measurements are shown. The evaluation results indicate that 3D object reconstruction was performed on a stationary object outdoors. Results show the precision as 0.939, the recall as 0.868, and the F-value as 0.902, which are regarded as sufficient values for the use of ultrasonic waves. |
14,319 | Please write an abstract with title: Silicon-Based Stretchable Structure via Parylene Kirigami Interconnection, and key words: Silicon, Integrated circuit interconnections, Young's modulus, Fabrication, Three-dimensional displays, Analytical models, Substrates. Abstract: High-performance stretchable electronics are attracting great attention due to the mechanical adaptability, but are still limited to achieving highly-integrable, high density, high-performance stretchable silicon-based electronics. This paper proposed a Parylene Kirigami structure as a stretchable interconnection to connect silicon (Si) units in an array. The equivalent Young’s modulus and stretchability model of the Parylene Kirigami were developed and verified numerically and experimentally. As a preliminary demonstration, a Parylene Kirigami structure-based stretchable Si array (Parylene KiSS array) was successfully fabricated by the wafer-scale microelectromechanical systems (MEMS) process with a high Si areal coverage of 68.8 % and the stretchability of 31.0 ± 1.1%. The equivalent Young’s modulus of this Parylene KiSS array was 130.88 ± 6.75 MPa, which was estimated precisely by the proposed model and was around 1000 times smaller than that of the intrinsic silicon. This MEMS process compatible stretchable electronics strategy can integrate Si-based high-performance chiplets, sensors and actuators to realize high-performance stretchable microsystems. [2022-0157] |
14,320 | Please write an abstract with title: Ku-Band Electronically Tunable Monopulse Receiver, and key words: Tunable circuits and devices, Radar tracking, Dielectric loss measurement, Microstrip components, Gunn devices, Microwave oscillators, Impedance, Diodes, Radar antennas, Conducting materials. Abstract: Techniques employed for Ku-band hybrid integrated microstrip components are discussed along with their performance data. The final integration results in a complete monopulse receiver with its own electronically tunable Gunn oscillator in a total packaged volume of 2.1 in/sup 3/. Materials and their limitations are discussed. Electronically tunable Gunn oscillator performance at Ku band is demonstrated which leads finally to a brief discussion of the dynamic impedance properties of negative resistance diodes. |
14,321 | Please write an abstract with title: Using transformer parasitics for resonant converters - a review of the calculation of the stray capacitance of transformers, and key words: Resonance, Parasitic capacitance, Power transformer insulation, Capacitors, DC-DC power converters, Nonhomogeneous media, Differential equations, Voltage transformers, Power system modeling, Switching converters. Abstract: Parasitic capacitances of conventional transformers can be used as resonant elements in resonant DC-DC converters in order to reduce the overall system size. For predicting the values of the parasitic capacitors without building the transformer different approaches for calculating these capacitances are compared. A systematic summary of the known approaches is given and missing links between the different theories and missing equations are added. Furthermore, a new simple procedure for modelling parasitic capacitances which is based on the known approaches is proposed. The resulting equations are verified by measurements on four different high voltage transformers. |
14,322 | Please write an abstract with title: Recognizing and quantifying human movement patterns through haptic-based applications, and key words: Pattern recognition, Biometrics, Humans, Educational institutions, Layout, Fingerprint recognition, Facial features, Keyboards, Telephony, Fingers. Abstract: Biometrics has been introduced recently to identify people by their behavior and physiological features. It offers a wide application scope to detect fraud attempts in organizations, corporations, educational institutions, electronic resources and even crime scenes. The field of biometrics can be divided into two main classes according to features that humans are born with, such as fingerprints or facial features, or behavioral characteristics of humans, like a handwritten signature or voice (J. Ortega-Garcia et al., 2004). The work presented in this paper pursues the latter class, specifically how a person reacts to using daily devices or tools. The fact that we can exploit people's habits in handling devices to identity individuals was the hypothesis that motivated this work. Among the many examples of the potential use of this class of biometrics is the particular force applied to the keys in a keyboard. There is also the time interval between each keypad when dialing a telephone number. Another example that can be extracted from the latter would be the map described by the fingers in navigating through solving maze operation. Extracting these features by using a haptic-based application and defining the subsequent individual pattern is the objective of this research. A framework that identifies behavioral patterns through physical parameters such as direction, force, pressure and velocity has been built. The set up for the experimental work consisted of a multisensory tool, using the Reachin system (Reachin Technologies, User's Programmers Guide and API). |
14,323 | Please write an abstract with title: Designing Training Scenarios for Stressful Spaceflight Emergency Procedures, and key words: Stress, Task analysis, Training, NASA, Resilience, Reliability, Physiology. Abstract: Graduated stress exposure aims to alleviate the negative effects of stress on task performance during high-stress conditions. Skills are practiced in increasing stress conditions that approximate the operational environment. Practice continues until stress resilience and task proficiency are achieved. The use of virtual reality (VR) for inducing a stress response has increased in popularity in recent years. The ability to simulate operational tasks could create training based on graduated stress exposure. However, more research is needed to verify that stress levels can be effectively manipulated in the virtual environment during training, and that the VR training task accurately replicates the existing task procedure. The objective of this study was to investigate the creation of different VR stressor levels from existing emergency spaceflight procedures and validate three distinguishable stressor levels (i.e., low, medium, high). Experts in spaceflight procedures and the human stress response helped design a VR spaceflight environment and emergency fire task procedure. A within-subject experiment was conducted using the three stressor levels. Sixty-one healthy participants completed three trials in VR to locate and extinguish a fire on the International Space Station (VR-ISS). Self-assessment was implemented for each stressor level; NASA Task load index, Post Task Stress Reaction scale, Free stress scale, Positive and Negative Affect Scale, and Short Stress State Questionnaire were used for assessment. The results suggest that the stressors can induce different, distinguishable, levels of stress in trainees for use in graduated stress exposure training. |
14,324 | Please write an abstract with title: Analysis of load structures for current-mode logic, and key words: Electron devices, Laboratories, Logic devices, Silicon, Solid state circuits, Doping, Physics, Semiconductor devices, Logic circuits, Diodes. Abstract: Integrated circuit technology allows load characteristics to be shaped to the requirements of a circuit. Because it is possible to claim advantages for a variety of loads, a computer-aided analysis is used to relate the transient characteristics of a current-mode logic circuit to its static load line. A variety of load lines have been studied and an integrated diode-clamped-type load structure appears to offer the best static and dynamic characteristics. |
14,325 | Please write an abstract with title: Robust and nonfragile H/sup /spl infin// output feedback controller design for affine parameter uncertain systems, and key words: Robustness, Control systems, Output feedback, Uncertainty, Sufficient conditions, Control system synthesis, Optimal control, Performance analysis, Design methodology, Robust control. Abstract: In this paper, we provide the synthesis of nonfragile H/sup /spl infin// output feedback controllers which is also optimal with respect to a H/sup /spl infin//-norm performance index. The uncertainties are assumed to be polytopic, both in the controller gains and the system dynamics. The sufficient condition of controller existence, the design method of robust and nonfragile H/sup /spl infin// output feedback controller, and the region of controllers which satisfies nonfragility are presented. Also using some change of variables and Schur complements, the obtained sufficient condition can be rewritten as parameterized LMIs, that is, LMIs whose coefficients are functions of a parameter confined to a compact set. A numerical example is presented to demonstrate the efficiency of this method, and the obtained controller guarantees the asymptotic stability and disturbance attenuation of the closed loop system with respect to the uncertainties in the plant and the controller within a resulted polytopic region. |
14,326 | Please write an abstract with title: Micromagnetism in two dimensions, and key words: Couplings, Magnetic anisotropy, Perpendicular magnetic anisotropy, Magnetostatics, Equations, Saturation magnetization, Anisotropic magnetoresistance, Demagnetization, Transistors, Amorphous magnetic materials. Abstract: The two-dimensional approximation to the magnetostatic problem in solving the equilibrium equations of micromagnetism is reviewed. The ripple equation leads to the effective demagnetizing field, which can be determined by means of high sensitive susceptibility measurements. A method for characterizing the quality of ferromagnetic thin film samples by conventional susceptibility measurement is described. |
14,327 | Please write an abstract with title: Distributed Resilient Secondary Control for DC Microgrids Against Heterogeneous Communication Delays and DoS Attacks, and key words: Delays, Voltage control, Denial-of-service attack, Microgrids, Packet loss, Security, Transmission line matrix methods. Abstract: In this article, a cooperative resilient control method for dc microgrid (MG) is proposed to dispel the adverse influences of both communication delays and denial-of-service (DoS) attacks. To avoid that the sampling period is captured by intelligent attackers, a new time-varying sampling period, and an improved communication mechanism are first introduced under the sampling control framework. Based on the designed sampling period and communication mechanism, a resilient secondary controller is designed. It is theoretically shown that the developed method can achieve the goals of bus voltage restoration and current sharing even in the presence of both DoS attacks and heterogeneous communication delays. Finally, a dc MG test system is built in a controller-hardware-in-the-loop testing platform to illustrate and verify the effectiveness of our developed method against both communication delays and DoS attacks. |
14,328 | Please write an abstract with title: Assessing harmonic impedance by synchronously layered distortion waves based on wavelet, and key words: Impedance, Harmonic distortion, Power system harmonics, Wavelet transforms, Frequency, Sampling methods, Wavelet analysis, Fluctuations, Fourier transforms, Power system simulation. Abstract: In this paper, a method assessing harmonic impedance by synchronously classifying distortion waves is proposed, which is based on the distortion quantity method, a simple and effective means. However the method is based on the Fourier transform, which can just precisely analyze the signals whose cycle is integer times as broad as that of fundamental wave. With sampling windows widening, the variations of distorted signals in a fundamental period are weakened. Moreover, the higher harmonic order is, the lower distinguish ability, and, as a result, the assessment accuracy becomes bad. Considered its prominent localization both in time-domain and in frequency-domain, wavelet is used to the field of assessing harmonic impedance for the first time. |
14,329 | Please write an abstract with title: Efficient computation of the covariance sequence of an autoregressive process, and key words: Autoregressive processes, Filters, Lattices, Reflection, Signal processing algorithms, Equations, Spectral analysis, Time series analysis, Parameter estimation, Polynomials. Abstract: An efficient algorithm is presented for computing the covariance sequence of a multichannel autoregressive process represented by a set of reflection coefficients. The covariance sequence is shown to be the impulse response of a certain lattice filter related to the optimal predictor. |
14,330 | Please write an abstract with title: A Smart Research Framework for Local Undergraduate Colleges’ Health Literacy Survey Based on Distributed Data Collection System, and key words: Pediatrics, Social networking (online), Education, Distributed databases, Atmosphere, Data collection, Sampling methods. Abstract: Based on the distributed data collection system, this paper studies the intelligent research framework of the health literacy survey of local undergraduate colleges. This system uses convenience sampling method to select 289 college students who participated in public elective courses in a college and use a self-designed questionnaire to assess their health literacy level. And health education needs survey. Results The proportion of college students with health literacy was 7.27%, and the proportions of college students with basic knowledge and ideas, healthy lifestyles and behaviors, and basic skills literacy were 15.92%, 6.23%, and 68.17%, respectively. The overall health literacy level of college freshmen needs to be further improved, and their health the three dimensions of literacy are uneven. The basic medical literacy of college freshmen is relatively low. Colleges and universities should strengthen health education for freshmen undergraduates, and reform the form, method and evaluation system of health education. |
14,331 | Please write an abstract with title: Image Classification of Rice Leaf Diseases Using Random Forest Algorithm, and key words: Fungi, Image processing, Digital art, Media, Classification algorithms, Decision trees, Random forests. Abstract: The problem of rice diseases around the world make to damage and fall into a large number of rice. Caused by many of types, such as; fungi, Bakteri and Viruses. which are the main causes of rice disease affected to farmers. The classification of rice can be classified into several methods. In this research, image classification is used to classify the data set of rice leaf diseases, such as; Brown Spot Rice disease (BSR), Brown Spot Rice disease (BSR), Bacterial Leaf Blight disease (BLB), which is the rice leaf disease with severe outbreaks around Thailand. Moreover, image processing technology in the classification types of rice leaf disease, such as; Random forest classification algorithm, Decision tree classification algorithm, Gradient Boosting classification algorithm and Naïve-Baye classification algorithm, which is measured by the accuracy, precision and recall of each algorithms. The best result of performance in the image classification of rice leaf diseases is random forest algorithm equal to 69.44 percent. |
14,332 | Please write an abstract with title: Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis, and key words: Ontologies, Time series analysis, Roads, Emotion recognition, Affective computing, Interviews, Computational modeling. Abstract: One of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a Recording Ontology for Affective-related Datasets (ROAD) as a solution to this problem, by formally describing the datasets and unifying the terms used. The developed ontology allows information about the origin and meaning of the data to be modeled, i.e., time series, representing both emotional states and features derived from biosignals. Furthermore, the ROAD ontology is extensible and not application-oriented, thus it can be used to store data from a wide range of Affective Computing experiments. The ontology was validated by modeling data obtained from one experiment on AMIGOS dataset (A dataset for Multimodal research of affect, personality traits and mood on Individuals and GrOupS). The approach proposed in the paper can be used both by researchers who create new datasets or want to reuse existing ones, and for those who want to process data from experiments in a more automated way. |
14,333 | Please write an abstract with title: Information System for Monitoring and Analyzing the Technical Condition of Autonomous Vehicles, and key words: Space vehicles, Databases, Conferences, Software algorithms, Machine learning, Software, Forecasting. Abstract: The paper presents the results of the development of a module of an information system for monitoring and analyzing the technical condition of autonomous vehicles. A diagram of software use cases is created, a fragment of the main tables of the developed database for storing technical and operational information about vehicles is given. An algorithm for parsing data on the current location of the vehicle is proposed, a fragment of the created class diagram of the client application is given. |
14,334 | Please write an abstract with title: Recent progress in coherent lightwave neural systems, and key words: Neural networks, Optical computing, Associative memory, Frequency domain analysis, Informatics, Circuits, Hardware, Electromagnetic propagation, Optical propagation, Bandwidth. Abstract: Recent progress in the coherent lightwave neural networks is presented. The complex-valued neural network constructs a signal-phase-sensitive information space. When we Incorporate a carrier frequency in the complex-valued network, the network (coherent network) is sensitive also to the carrier frequency. The utilization of the carrier-frequency domain promises a vast and dense neural parallelism. We concentrate on the recent efforts and experimental results to realize a carrier-frequency-controllable behavior of the complex-valued neural networks. |
14,335 | Please write an abstract with title: Robust time-varying Kalman smoothers with uncertain noise variances, and key words: Estimation error, Upper bound, Uncertainty, Smoothing methods, Stochastic systems, Robustness, Mathematical models. Abstract: This paper addresses the design of robust Kalman smoothers for the time-varying system with uncertain noise variances. According to the minimax robust estimation principle, and the unbiased linear minimum variance (ULMV) optimal estimation rule, based on the worst-case conservative system with the conservative upper bounds of noise variances, two robust Kalman state smoothing algorithms are presented by the augmented and non-augmented state approaches, respectively. Their robustness is proved by the Lyapunov equation approach, and their robust accuracy relations are proved. A simulation example is given to verify the robustness and the correctness of the robust accuracy relations. |
14,336 | Please write an abstract with title: Monitoring of Vertical Land Motion at Tide Gauges Using Time-Series Sequential SBAS Technique, and key words: Sea measurements, Information and communication technology, Sea level, Motion measurement, Indexes, Tides, Spatial resolution. Abstract: Relative sea level changes from tide gauges requires various corrections including local vertical land motion due to natural and anthropogenic processes. This study aims to measure the vertical land motion at tide gauges in the Korean peninsula using StaMPS-SBAS time-series InSAR analysis. C-band Sentinel-1 A/B SAR data acquired during 2014/10 and 2020/05 for this study. We applied sequential pairs selection approach to optimize the amplitude dispersion index (ADI) and increase the PS pixel density. |
14,337 | Please write an abstract with title: A Coherent Integration Method for Moving Target Detection in a Parameter Jittering Radar System Based on Signum Coding, and key words: Radar, Radar cross-sections, Harmonic analysis, Time-frequency analysis, Radar countermeasures, Couplings, Transforms. Abstract: In this letter, we propose a novel long-time coherent integration detection method to detect an uncooperative moving target in a frequency and pulse repetition interval randomly jittering radar system based on signum coding (SC). In the proposed algorithm, an additional reference waveform is applied to eliminate the third-order harmonic influence induced by SC. Then, a generalized Keystone transform (GKT) is proposed to resolve the complex coupling among the range frequency, jittered carrier frequency, and nonuniformly sampled time. Simulation results are presented to validate the effectiveness and feasibility of the proposed method. |
14,338 | Please write an abstract with title: Self-Maintaining Overlay Data Structures for Autonomic Distributed Computing, and key words: Data structures, Distributed computing, Routing, Network topology, Mobile communication, Application software, Embedded computing, Encoding, Context awareness, Spread spectrum communication. Abstract: In our research, we developed a general framework to model and implement overlay data structures in dynamic network environments. Overlay data structures can be defined by means of a couple (C,P). The content C can be an arbitrary data structure representing the information carried on by the data structure. The propagation rule P determines how the overlay data structure should be distributed and propagated across the network. This includes determining the "scope" of the overlay (i.e. the distance at which it should be propagated and possibly the spatial direction of propagation) and how such propagation can be affected by the presence or the absence of other data structures in the system. In addition, the propagation rules can determine how the content should change while it is propagated. Overlay data structure are not necessarily distributed replicas: by assuming different values in different nodes, they can be effectively used to build a distributed overlay data structure expressing some kind of contextual information. In addition, we realized highly scalable, autonomic maintenance mechanisms to let the overlay data structures preserve its intended distribution (C,P) despite network contingencies |
14,339 | Please write an abstract with title: A Routing Scheme Using an Adaptive K-Harmonic Means Clustering for VANETs, and key words: Clustering algorithms, Routing protocols, Stability analysis, Euclidean distance, Maintenance engineering, Linear programming, Analytical models. Abstract: In this paper, we propose a routing protocol using an adaptive K-Harmonic Means (RPKHM) in order to improve the lifetime of links between vehicles and to increase the stability of the vehicular network. First, the number and initial positions of the centroids are determined using a mathematical model that takes into account the total number of vehicles and the network topology. Whereas, the clustering is done using a similarity value based on the Euclidean distance, the difference in speed and direction of the vehicles. Finally, the maintenance of the clusters and the selection of new cluster heads are based on a cost function, which takes into account the total size of the free buffer and expected transmission count (ETX). The simulation results show the efficiency of the proposed scheme in terms of Packet Delivery Ratio, average End-to-End Delay, and Throughput. |
14,340 | Please write an abstract with title: Time-resolved investigation of pulsed-DC magnetron reactive plasma, and key words: Bonding, Chemical vapor deposition, Optical films, Plasma measurements, Plasma density, Fluid flow, Annealing, Sputtering, Dielectric films, Dielectric breakdown. Abstract: Summary form only given, as follows. DC reactive sputter deposition of dielectric films can be greatly affected by arcing. Observations have indicated that arcing is due to breakdown of the dielectric (oxide) film, which grows on the surface of the metal target as a result of positive charge accumulation. The use of pulsed-DC power in the pulsing frequency range of 20-350 kHz has been employed to reduce or eliminate arcing. Using duty cycles, which could be varied between 50% and 90%, plasma dynamics were studied. The relationships between various deposition process parameters (power, pressure, pulsing frequency, duty cycle, etc.) were studied using time-resolved general electrical, Langmuir probe and optical emission measurement techniques and the results are discussed. |
14,341 | Please write an abstract with title: High resolution marking applications of fiber-lasers, and key words: Laser beams, Materials processing, Optical materials, Plastic films, Aluminum, Drilling, Glass, Fiber lasers, Laser modes, Power lasers. Abstract: Because of their simplicity, compactness and their very good beam quality fiber-lasers are dedicated very well for applications in the field of material processing or micro marking of different materials e.g. thin plastic films or anodized aluminium. For the material processing, e.g. the drilling of small holes in glass substrates we used a fiber laser with a output power of about 25 to 35 watts and a beam quality near to single mode. |
14,342 | Please write an abstract with title: AFM Tip Localization on Large Range Sample Using Particle Filter for MEMS Inspection, and key words: Particle filters, Micromechanical devices, Feature extraction, Robot sensing systems, Microscopy, Layout, Mathematical model. Abstract: Atomic force microscopy (AFM) is a powerful instrument that has the ability to characterize sample topography on nanoscale resolution. AFM is widely used in different fields, such as nanotechnology, semiconductor, Microelectromechanical Systems (MEMS), bioscience. In the case of obtaining 3D topography of a large range sample, we need to know the relative position of the AFM probe to the sample. The scanning range of an AFM generally is much smaller than the sample size. Therefore, it is hard to localize the AFM tip position without other auxiliary microscopes such as optical microscope. Moreover, the AFM scanned images on a MEMS sample typically involve only simple geometries with sparse features which usually leads to the difficulty of localization. Besides, the system uncertainties including piezoelectric scanner hysteresis, thermal drift, and coarse dual stage would affect positioning accuracy. In this paper, we propose an AFM tip localization method using particle filter referring to macro robot Simultaneous localization and mapping (SLAM). We take the AFM scanned image as the unique sensor and the sample layout as the map. The sensor model of the particle filter is based on a feature extraction algorithm. To verify the efficacy of the proposed methods, both simulations and experiments are conducted, and the proposed tip localization method is highly promising. |
14,343 | Please write an abstract with title: Vibration modes analysis by X-ray topography in quartz and langasite resonators, and key words: Surfaces, Electrodes, X-ray imaging, X-ray diffraction, Electric variables measurement, Frequency, Performance evaluation, Vibration measurement, Stress, Inductance. Abstract: This paper presents the results of the vibration modes measurements by X-ray topography in SC-cut quartz and Y-cut unpolished langasite resonators. A comparison of these results with X-ray diffraction topography images on AT-cut quartz resonators and Y-cut polished langasite resonators pointed out the behavior of mass-loading effect with plate orientation angle and with the surface state of the piezoelectric substrate. The results are compared with electrical measurements performed on the same resonators. 5 MHz Sawyer, plan parallel SC-cut quartz and Y-cut unpolished langasite resonators, with 14 mm plate diameter and various electrode thickness and diameters have been investigated on fundamental, third and fifth overtones. The study on SC-cut quartz resonators and unpolished Y-cut langasite resonators pointed out a good agreement with the results obtained on the same resonators by electrical measurements. The conclusion is that the SC-cut quartz resonator characteristics present a similarly harmonic dependence with those of the Y-cut langasite resonators thus revealing the stress-compensated feature of the Y-cut in langasite crystal. |
14,344 | Please write an abstract with title: Linkages Between Chinese Stock Price Index and Exchange Rates-An Evidence From the Belt and Road Initiative, and key words: Exchange rates, Indexes, Currencies, Stock markets, Correlation, Belts. Abstract: This paper selects the daily data of the exchange rates of Chinese Yuan (CNY) over the currencies of 14 countries along the Belt and Road, Shanghai composite index and Shenzhen composite index to study the influence of the Belt and Road Initiative on the linkages between exchange rates and Chinese stock index based on the flow-oriented model and the stock-oriented model. To reflect the fluctuations in daily data and reduce the central bank's interference with the exchange rate, two fuzzy techniques are used to process data, that is, the centroid based measure and the integral based measure. Then we judge the relationship between exchange rate and stock index through the Pearson correlation coefficient and the Granger causality test. Besides, we further compare the results and their differences by the classic crisp method and our two fuzzy techniques, which enable us to judge their correlation more accurately, and provide a reference for a wider application of the proposed fuzzy methods. We find that there is a correlation between exchange rate and stock index under certain conditions, and the Belt and Road initiative strengthens the relationship between the Chinese foreign exchange market and the stock market, more importantly, the fuzzy techniques are effective to judge this relation. |
14,345 | Please write an abstract with title: Similarity classifier based on modifications on Schweizer & Sklars equations, and key words: Equations. Abstract: In this article we have applied Schweizer & Sklars implication based measures with extension to generalized mean to classification task. We compare results to fuzzy similarity measure based classification and show that sometimes better results can be found by using these measures than fuzzy similarity measure. We also show that classification results are not so sensitive to p values with Schweizer & Sklars measures than when fuzzy similarity is used. Also investigation for correct mean values is carried out. |
14,346 | Please write an abstract with title: Finite element torque modeling for the design of a spherical motor, and key words: Finite element methods, Torque, Reluctance motors, Permanent magnet motors, Reluctance generators, Magnetic circuits, Predictive models, Electromechanical devices, Magnetic fields, Electromagnetic analysis. Abstract: This paper presents the method of modeling the torque generated by a variable reluctance spherical motor (VRSM) that presents some attractive possibilities by combining pitch, roll, and yaw motion in a single joint. Unlike prior works on the torque formulation of a VRSM, which were based on a lumped-parameter approach using equivalent magnetic circuits (widely used in developing force/torque models for electromechanical devices), this paper presents a distributed-parameter approach to predict the motor's magnetic field distribution for formulating the torque of a VRSM. A detailed three-dimensional finite-element (FE) analysis has been performed on a VRSM configuration that consists of both permanent magnet (PM) poles and air-cored electromagnets. The model obtained using FE methods offers more insight and an accurate representation of torque generated by a spherical motor. |
14,347 | Please write an abstract with title: Enantio-sensitive unidirectional light bending, and key words: Optical interferometry, Three-dimensional displays, Optical polarization, Stimulated emission, Magnetic resonance imaging, Bending, Media. Abstract: Structured light, which exhibits nontrivial intensity, phase, and polarization patterns in space, has key applications ranging from imaging and 3D micromanipulation to classical and quantum communication [1] . However, to date, its application to molecular chirality [2] has been limited by the weakness of magnetic interactions. Here we show how to lift this limitation by structuring light’s local chirality – a new type of chirality effective within the electric-dipole approximation [3] . We introduce and realize an enantio-sensitive interferometer for efficient chiral recognition without magnetic interactions, which can be seen as an enantio-sensitive version of Young’s double slit experiment. We show that if the distribution of light’s handedness breaks left-right symmetry, the interference of chiral and achiral parts of the molecular response leads to unidirectional bending of the emitted light, in opposite directions in media of opposite handedness. Our work introduces the concepts of polarization of chirality and chirality-polarized light, exposes the immense potential of sculpting light’s local chirality, and offers novel opportunities for efficient chiral discrimination, enantio-sensitive optical molecular fingerprinting and imaging on ultrafast time scales [4] . |
14,348 | Please write an abstract with title: Feedback-based Scheduling for Back-end Databases in Shared Dynamic Content Server Clusters, and key words: Dynamic scheduling, Databases, Delay, Resource management, Quality of service, Service oriented architecture, Web server, Feedback loop, Clustering algorithms, Sampling methods. Abstract: This paper introduces a self-configuring architecture for scaling the database tier of dynamic content web servers. We use a unified approach to load and fault management based on dynamic data replication and feedback-based scheduling. While replication provides scaling and high availability, feedback scheduling dynamically allocates tasks to commodity databases across workloads in response to peak loads or failure conditions thus providing quality of service. By augmenting the feedback loop with state awareness, we avoid oscillations in resource allocation. We investigate our transparent provisioning mechanisms in the database tier using the TPC-W e-commerce and the on-line auction Rubis benchmarks. We demonstrate that our techniques provide quality of service under load bursts and failure scenarios. |
14,349 | Please write an abstract with title: A 1.8-GHz LC VCO with 1.3-GHz tuning range and digital amplitude calibration, and key words: Voltage-controlled oscillators, Calibration, Phase noise, Wideband, CMOS process, Noise measurement, Phase measurement, Equations, Degradation, Instruments. Abstract: A 1.8-GHz LC VCO designed in a 0.18-/spl mu/m CMOS process achieves a very wide tuning range of 73% and measured phase noise of -123.5 dBc/Hz at a 600-kHz offset from a 1.8-GHz carrier while drawing 3.2 mA from a 1.5-V supply. The impacts of wideband operation on start-up constraints and phase noise are discussed. Tuning range is analyzed in terms of fundamental dimensionless design parameters yielding useful design equations. An amplitude calibration technique is used to stabilize performance across the wide band of operation. This amplitude control scheme not only consumes negligible power and area without degrading the phase noise, but also proves to be instrumental in sustaining the VCO performance in the upper end of the frequency range. |
14,350 | Please write an abstract with title: Spatial analysis phase fluctuating Bose-Einstein condensates, and key words: Fluctuations, Temperature, Clouds, Atomic measurements, Electronic mail, Coherence, Atomic beams, Atom lasers, Phase measurement, Length measurement. Abstract: The phase correlation properties of elongated BECs are studied in detail. It is shown that at finite temperature, the phase of the BEC is not uniform but undergoes statistical fluctuations. In particular, we observe BECs where the phase coherence length is smaller than the condensate size, i.e. so called quasicondensates. Recent interferometric measurement of the coherence length in the regime where strong phase fluctuations are present in the condensates is reported. The method is compared to complementary ways of measuring the coherence length. The possibility of a complete numerical phase reconstruction from time-of-flight images is evaluated. |
14,351 | Please write an abstract with title: Financial Distress Prediction: Principle Component Analysis and Artificial Neural Networks, and key words: Bankruptcy, Predictive models, Artificial neural networks, Modeling, Support vector machines, Companies, Training. Abstract: Financial distress prediction is vital in financial decision-making for industry practitioners, financial system users and policymakers. Most of the research work on bankruptcy prediction and credit scoring compare the prediction accuracy of a model on a specific dataset to other models applied on a different dataset. Those research work did not consider factors that affect the datasets. These factors include feature selection, the total number of instances, number of variables employed, training/testing ratio and they affect the accuracy of the model. Therefore, knowing these factors help in analyzing the models carefully before comparing the model's prediction accuracy. We proposed a hybrid model which combine principal component analysis (PCA) with neural network analysis ANN for bankruptcy prediction. The experimental set-up is conducted using a Polish companies bankruptcy dataset which is publicly online on the UCI database. The dataset was pass through different training and testing ratio. The experimental study shows that PCA-ANN with 32 principal components outperforms other models using cross-validation for the training and testing ratio. The aim is to confirm the model with the highest accuracy, and the best area under the ROC curve (AUC) base on the training/testing ratio. Hence, in this research work, we declared the best model based on the said dataset. We observed that the ROC curve (AUC) of PCA-ANN with 32 principal components convincingly outperformed other models in terms the training/testing ratio of 10 folds cross-validation. |
14,352 | Please write an abstract with title: Anatomical based FDG-PET reconstruction for the detection of hypometabolic regions in epilepsy, and key words: Epilepsy, Positron emission tomography, Reconstruction algorithms, Image segmentation, Sugar, Biochemistry, Hospitals, Image reconstruction, Signal to noise ratio, Iterative algorithms. Abstract: Positron emission tomography (PET) of the cerebral glucose metabolism has shown to be useful in the presurgical evaluation of patients with epilepsy. An iterative reconstruction algorithm is derived for the detection of subtle hypometabolic regions in FDG-PET images of the brain of epilepsy patients. Prior anatomical information, derived from MR data, and pathophysiological knowledge was included in the reconstruction algorithm. Results showed an improved signal-to-noise ratio and a reduction of bias. |
14,353 | Please write an abstract with title: Structural Damage Prediction from Earthquakes Using Deep Learning, and key words: Periodic structures, Monitoring, Two dimensional displays, Feature extraction, Data models, Computational modeling, Buildings. Abstract: Structures are susceptible to damages caused due to various calamities, including earthquakes. Structural health monitoring (SHM) system provides warnings of such damages and indicates the degradation of their life cycle. In this chapter, first database is created for G20+ model using SAP software. Accelerometer sensors are placed at each joint to detect vibration signals of an earthquake. This vibration signal acts as the raw data for signal processing and hybrid deep‐learning models. This chapter deals with three different approaches to achieve the classification results. The first approach deals with training 1D convolutional neural networks (CNNs) on the vibrational accelerometer data. The second approach deals with training long short‐term memories (LSTMs). The third approach involves 2D CNNs trained on the spectrograms of the vibrational data used for training in the previous approaches. Comparing the results, 1D CNNs outperformed all the other networks used in the chapter. |
14,354 | Please write an abstract with title: Dynamic models of a rotary double inverted pendulum system, and key words: Laboratories, DC motors, Equations. Abstract: This paper describes the dynamic models of a double rotary inverted pendulum, which has been developed for the laboratory experiments. Two different-length rigid pendulums are connected to a horizontally rotating disc which is attached directly to a DC motor. The derivation of the dynamical equations and the linearized model are described. Finally, the time responses of open-loop system are shown and compared with the experimental data to verify the model validity. |
14,355 | Please write an abstract with title: A Comparative Study of State-of-the-art Image Splicing Localization Methods Using Fully Convolutional Networks, and key words: Location awareness, Deep learning, Convolution, Splicing, Forensics, Digital images, Neural networks. Abstract: Image splicing forgery is one of the significant image manipulations. It is very difficult to find the location of forged portion in a spliced image. Nowadays, deep neural networks have been used to detect and localize image forgeries. In this paper, a brief survey and comparison on splicing localization of images using Fully Convolutional Network (FCN), a deep neural network is presented. |
14,356 | Please write an abstract with title: A TfidfVectorizer and SVM based sentiment analysis framework for text data corpus, and key words: Support vector machines, Sentiment analysis, Social networking (online), Annotations, Machine learning, Motion pictures, Real-time systems. Abstract: E-commerce and social networking sites are very much dependent on the available data which can be analyzed in real time to predict their future business strategies. However, analyzing huge amount of data manually is not possible in time context of business. Therefore, automated sentimental analysis, which can automatically determine the sentiments from the text data corpus plays an important role in today's world. Many sentimental analysis frameworks with state of the art results have been proposed in the literature. However, many of these frameworks have low accuracy on the textual data corpus contains emoticons and special texts. In addition, many of these frameworks are also energy and computation intensive with which puts limitation in their real time deployment. In this paper, we aim to address these issues by proposing a novel sentimental analysis framework based on Support Vector Machine (SVM). The proposed framework uses a novel technique to tokenize the text documents, wherein stop words, special characters, emoticons present in the text documents are eliminated. In addition, words with similar meanings and annotations are clubbed together into one type, using the concept of stemming. The pre-processed tokenized documents are then vectorized into n-gram integers vectors using the ‘TfidfVectorizer’ for use as input to the SVM based machine learning classifier model. Experimental results on the Amazon's electronics item review dataset and IMDB's movie review data corpus show that the proposed sentimental analysis framework achieves high performance compared to other similar frameworks proposed in the literature. |
14,357 | Please write an abstract with title: High Speed Sixty Four Bit Vedic Multiplier, and key words: Costs, Correlation, Fast Fourier transforms, Convolution, System performance, Mathematics, Delays. Abstract: Multiplication operation is the core of many techniques like convolution, correlation, fast fourier transform etc. Since multipliers are rather complex circuits and must typically operate at a high system clock rate, reducing the delay of a multiplier is an essential part of satisfying the overall design. Optimising multiplier (in terms of delay or area or power) will have a huge impact on system performance. One of the methods adopted to reduce delay is the use of Vedic Multiplier based on “Vedic Mathematics Sutras”. In this project “Urdhava - Tiryakbhayam” Sutra is used to perform multiplication and is simulated and implemented in Xilinx ISE Design 14.7 |
14,358 | Please write an abstract with title: Properties of WCAg and WCCu for vacuum contactors, and key words: Contactors, Circuit testing, Copper, Optical wavelength conversion, Tungsten, Interrupters, Composite materials, Grain size, Electrodes, Circuit breakers. Abstract: This paper compares the switching properties of WCAg and WCCu for vacuum contactors and studies the influence of material composition and grain size of the WC powder. Different materials are compared with respect to their breaking capability, the state of their contact surfaces after arcing, their erosion losses, and their chopping current. The experiments were carried out with a demountable vacuum chamber in a synthetic test circuit. For the switching capability tests, the contacts were stressed by arc currents up to 7 kA root-mean square (rms), and a transient recovery voltage of 23 kV peak. The chopping measurements were carried out at a test current of 45-A rms. For all materials investigated there was an adverse ranking between interruption capability on the one hand and chopping current on the other. Materials with a higher WC content showed lower chopping currents, but also lower interruption limits. A general explanation is that all factors keeping the arc stable down to lower currents in the case of chopping conditions, also favor re-establishment of the arc at current zero on high current stress. Furthermore, materials with lower interruption limits exhibit stronger cracks and spikes. |
14,359 | Please write an abstract with title: Machine-learning-assisted DDoS attack detection with P4 language, and key words: Computer crime, Feature extraction, Real-time systems, Prediction algorithms, Support vector machines, Protocols, Metadata. Abstract: While Software Defined Networking (SDN) provides well-known advantages in terms of network automation, flexibility and resources utilization, it has been observed that SDN controllers may represent critical points of failure for the entire network infrastructure, especially when they are targeted by malicious cyber attacks such as Distributed Denial of Service (DDoS). To address this issue, in this paper we exploit stateful data planes, as enabled by P4 programming language, where switches maintain persistent memory of handled packets to perform attack detection directly at the data plane, with only marginal involvement of the SDN controllers. As machine learning (ML) is recognized as primary anomaly detection methodology, we perform DDoS attack detection using a MLbased classification and compare different ML algorithms in terms of classification accuracy and train/test duration. Moreover, we combine ML and P4-enab1ed stateful data planes to design a real-time DDoS attack detection module, which we evaluate in terms of latency required for the detection. Three real-time scenarios are considered, where P4-enab1ed switches elaborate the received packets in different ways, namely, packet mirroring, header mirroring, and P4-metadata extraction. Numerical results show significant latency reduction when P4 is adopted. |
14,360 | Please write an abstract with title: System analysis of a multi-standard direct conversion wireless receiver, and key words: 1f noise, Circuit noise, Signal to noise ratio, Voltage, Nonlinear equations, Performance analysis, Phase distortion, Phase noise, Frequency, Very large scale integration. Abstract: Wireless devices with multi-mode function are gaining popularity, but existing multi-mode devices use separate chipsets, or separate receiver paths for different standards on the same chip. A multistandard receiver with a high level of hardware share between different standards is proposed. Measures to perform system analysis for the direct conversion architecture are analyzed and used in a Simulink model to extract design specifications for multi-standard receiver components. |
14,361 | Please write an abstract with title: Trainable Communication Systems: Concepts and Prototype, and key words: Receivers, Training, Optical transmitters, Communication systems, Iterative decoding, Optimization. Abstract: We consider a trainable point-to-point communication system, where both transmitter and receiver are implemented as neural networks (NNs), and demonstrate that training on the bit-wise mutual information (BMI) allows seamless integration with practical bit-metric decoding (BMD) receivers, as well as joint optimization of constellation shaping and labeling. Moreover, we present a fully differentiable neural iterative demapping and decoding (IDD) structure which achieves significant gains on additive white Gaussian noise (AWGN) channels using a standard 802.11n low-density parity-check (LDPC) code. The strength of this approach is that it can be applied to arbitrary channels without any modifications. Going one step further, we show that careful code design can lead to further performance improvements. Lastly, we show the viability of the proposed system through implementation on software-defined radios (SDRs) and training of the end-to-end system on the actual wireless channel. Experimental results reveal that the proposed method enables significant gains compared to conventional techniques. |
14,362 | Please write an abstract with title: Smart Contract-Based Access Control for the Vehicular Networks, and key words: Access control, Roads, Simulation, Smart contracts, Software, Blockchains, Telecommunications. Abstract: In Ad-hoc Networks (VANETs), vehicles exchange safety and road information in order to reduce the number of accidents on the road and get the best updated information to optimize their road path. However, the secure communications face big challenges in the VANETs. In a previous work, we have proposed a distributed trust management scheme based on the blockchain technology in order to provide a secure vehicle communication by checking the correctness of the message. For this purpose, the Blockchain facilitates the sharing of secure in-formation or messages among vehicles. However, vehicles cannot share the resources with other entities using only the blockchain and cannot manage to access control their resources. In order to provide an access control policies of the resources requested by the vehicle, we propose a distributed access control model for vehicles based on smart contracts and ABAC model to share the resources through miners. Then, we evaluate the execution time and the storage of the proposal. |
14,363 | Please write an abstract with title: Two-Stage Adaptive Constrained Particle Swarm Optimization Based on Bi-Objective Method, and key words: Optimization, Particle swarm optimization, Convergence, Sociology, Statistics, Linear programming, Heuristic algorithms. Abstract: For the sake of better balancing the relationship between diversity and convergence when handling constrained optimization problems, a two-stage adaptive constrained particle swarm optimization algorithm based on bi-objective method (TABC-PSO) is proposed. In accordance with different phases of the constraint process, the target-constraint space derived from the angle is partitioned adaptively, and simultaneously the global best particle is selected and the external archive set is safeguarded. In the first stage, the whole space is divided adaptively in term of the angular distribution of individual, and the feasible region is explored comprehensively. In the second stage, local regions are adaptively compartmentalized and in-depth exploitation is carried out. Primary and secondary external archive sets are established to maintain population diversity and accelerate convergence. The two phases are switched adaptively in light of the storage status of the two external archive sets. We evaluated TABC-PSO algorithm on the benchmark functions in CEC 2006 and CEC 2017. The experimental results show that TABC-PSO algorithm compared with other state-of-the-art algorithms can be superior to applied to test functions with different types of constraints and possesses a competitive search capability. |
14,364 | Please write an abstract with title: Study on IGBT super-audio frequency induction heating power supply, and key words: Insulated gate bipolar transistors, Frequency, Power supplies, Circuit topology, Power electronics, Rectifiers, Inverters, Protection, Circuit testing, Design methodology. Abstract: The topology of super-audio induction heating power supply that adopted the new type power electronic components IGBT was analyzed. Especially the parallel-connected circuit was introduced. The control of rectifier and the inverter were explained in detail. And the protection circuit was proposed. A novel method of startup was brought forward. At last through the test of the sample it was proved that the designed method is reasonable and the whole device is high efficiency. |
14,365 | Please write an abstract with title: Minimizing Age-of-Information of NVRAM-based Intermittent Systems, and key words: Energy consumption, Power demand, Embedded systems, Nonvolatile memory, Transmitters, Data integrity, Random access memory. Abstract: Due to the near-zero idle power consumption characteristic of non-volatile random access memory (NVRAM), NVRAM has gained popularity as a great alternative to volatile RAM on energy-constraint and tiny embedded systems that run on intermittent power. In particular, multi-level-cell (MLC) NVRAM can further reduce the energy consumption of data writes by alternating data write modes with different retention periods. Nevertheless, due to the unstable power supply of intermittent systems, data on NVRAM could become obsolete and result in distortion of reality as time goes by. As intermittent systems typically involve a large number of sensors and numerous transmitters to collect environmental data, data freshness is vital for accurate scientific study. To ensure the data freshness, this paper proposes a minimizing average system age-of-information (AoI) scheme, abbreviated as MASA scheme, for MLC-NVRAM-based intermittent systems. The proposed policy harmonizes data write modes according to data update intervals of sensors with the goal of minimizing AoI and energy consumption. The experimental results indicate that the proposed policy achieves a better average AoI than the existing schemes. |
14,366 | Please write an abstract with title: Evaluating IPv6 on Windows and Solaris, and key words: Testing, Time measurement, Ethernet networks, Protocols, Workstations, Monitoring, Extraterrestrial measurements, Scalability, Security, Web and internet services. Abstract: IPv6 might solve several of IPv4's shortcomings, but the longer headers and address space add overhead that affects a range of performance metrics for both TCP and UDP. We established a test bed to compare the two protocol stacks along a set of six performance metrics. We also compared two IPv6 implementations running on Windows 2000 and Solaris 8 using identical hardware and settings. We performed additional tests using different configurations, including a pair of commercial routers that support dual IPv4-IPv6 stacks. While the majority of those results are beyond this article's scope, some of our experiences with the routers raised points that we address here. |
14,367 | Please write an abstract with title: A Method of Equipment Disassembly Path Planning Based on Directed Constraint Graph Disassembly Sequence, and key words: Training, Visualization, Interference, Maintenance engineering, Reliability engineering, Path planning, Planning. Abstract: This paper proposes a method of equipment disassembly and assembly path planning based on directed constraint graphs. By establishing a model of disassembly and assembly sequence based on directed constraint graphs, an assembly constraint matrix interference table is generated, and a directed constraint graph is used to describe parts. Then, we can quickly solve the constraint degree of the parts, optimize and improve the disassembly and assembly path, solve the problem of inefficient planning of the virtual maintenance and disassembly path of the equipment, and program the virtual operation steps for detecting disassembly and assembly. The paper provides technical support for the development of virtual maintenance training system. |
14,368 | Please write an abstract with title: Inductive Parallel Learning for Multiple Classification Problems, and key words: Training, Neural networks, Transfer learning, Supervised learning, Fitting, Knowledge representation, Data models. Abstract: The default approach to the construction of pattern recognition models solving supervised learning problems is fitting the knowledge representation to the samples of a single problem, describing a single, static concept. In recent years, however, the transfer learning approach has been gaining popularity, consisting in training a model initially learned on a different, standard dataset to a specific problem. However, such solutions are mainly used for signal data, in applications typical of deep learning models. This paper proposes a new training procedure for tabular data, in which a serial ensemble of models based on neural networks is trained in parallel to recognize two different problems. In extensive experimental analysis, the approaches based on disjoint models, disjoint learning and - constituting the basic proposal of the work - inductive parallel learning of two problems were compared. The analysis carried out on synthetic and real-world problems shows that the proposed approach is a promising starting point for further research. |
14,369 | Please write an abstract with title: Text Classification Model Based on fastText, and key words: Text categorization, Classification algorithms, Training, Data models, Industries, Support vector machines, Machine learning algorithms. Abstract: Most text classification models based on traditional machine learning algorithms have problems such as curse of dimensionality and poor performance. In order to solve the above problems, this paper proposes a text classification model based on fastText. Our model explores the important information contained in the text through the feature engineering, and obtains the low-dimensional, continuous and high-quality text representation through the fastText algorithm. The experiment is based on Python to classify the text dataset of “user comment data emotional polarity judgment” in Baidu Dianshi platform. In the emotional polarity judgment task, the experimental results show that the precision, recall and F values of our model are superior to the model based on traditional machine learning algorithms and have excellent classification performance. |
14,370 | Please write an abstract with title: Feasibility of Bone Fracture Detection Using Microwave Imaging, and key words: Bones, Skin, Dielectrics, Phantoms, Microwave theory and techniques, Numerical models, Microwave imaging. Abstract: This paper studies the feasibility of Microwave Imaging (MWI) for detection of fractures in superficial bones like the tibia, using a simple and practical setup. First-responders could use it for fast preliminary diagnosis in emergency locations, where X-Rays are not available. It may prove valuable also for cases where X-ray are not recommended, e.g., length pregnant women or children. The method is inspired on the synthetic aperture radar technique. A single Vivaldi antenna is used to linearly scan the bone in the 8.3-11.1 GHz frequency range and collect the scattered fields. The system is operated in air, without the need for impractical impedance-matching immersion liquids. The image is reconstructed using a Kirchhoff migration algorithm. A Singular Value Decomposition (SVD) strategy is used to remove skin and background artifacts. To test this technique, a set of full-wave simulations and experiments were conducted on a multilayer phantom and on an ex-vivo animal bone. Results show that the system can detect and locate bone transverse fractures as small as 1 mm width and 13 mm deep, even when the bone is wrapped by 2 mm thick skin. |
14,371 | Please write an abstract with title: Spectral-Spatial Classification Of Hyperspectral Images With Multi-Level Cnn, and key words: Deep learning, Dimensionality reduction, Convolution, Computer architecture, Feature extraction, Convolutional neural networks, Kernel. Abstract: In recent years, deep learning methods have significantly increased the classification accuracy of remotely sensed images. However, most of the methods focus only on spectral information ignoring the spatial information, thus extracting only low-level features from a hyperspectral image. In this study, a multi-level 3-dimensiona1 convolutional neural network (3- D CNN) has been proposed. The 3-D CNN serves the purpose of including both spatial and spectral information. The multi-level architecture consists of varying kernel sizes to extract features at different levels. This helps in distinguishing classes from multiple spatial scales and aspect ratios. We have evaluated the performance of the proposed approach on four standard hyperspectral datasets to verify the generalisation ability. Compared with other state-of-the-art methods, an improvement of 2%–5% in overall accuracy and kappa coefficient has been observed. The effect of spatial window size on classification accuracy has been analysed as well in this study. Furthermore, in comparison with the former deep learning models, our approach is found to be less sensitive to the network parameters and achieves better accuracy even with lesser network depth. |
14,372 | Please write an abstract with title: Condition-based, diagnostic gas path reasoning for gas turbine engines, and key words: Turbines, Engines, Prognostics and health management, Maintenance, Condition monitoring, Force control, Aircraft propulsion, NASA, Observability, Automation. Abstract: This paper addresses the requirements and concept for a condition-based, diagnostic gas path reasoner algorithm for the aggregation, classification and prediction of gas path faults/anomalies in gas turbine engines. A more accurate maintenance recommendation is made based upon all available information about the state of the engine. We propose a scheme that gathers the results of different diagnostic methods and leverages the advantages of each one. Such a fusion scheme holds the promise to deliver a result that is at least as good as the best of the algorithms used, and potentially much better because of the leveraging of complementary information of the other diagnostic algorithms. There are many issues involved with gas path reasoning. We present an approach that tackles the problems and focuses in particular on the system issues involved in implementing an advanced, condition-based, diagnostic gas path reasoner. |
14,373 | Please write an abstract with title: Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks, and key words: Deep learning, Training, Visualization, Target tracking, Tracking, Training data, Benchmark testing. Abstract: The current deep learning based visual tracking approaches have been very successful by learning the target classification and/or estimation model from a large amount of supervised training data in offline mode. However, most of them can still fail in tracking objects due to some more challenging issues such as dense distractor objects, confusing background, motion blurs, and so on. Inspired by the human “visual tracking” capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual tracking, which successfully exploits both appearance and motion features for model update. Our TS-RCN can be integrated with existing deep learning based visual trackers. To further improve the tracking performance, we adopt a “wider” residual network ResNeXt as its feature extraction backbone. To the best of our knowledge, TS-RCN is the first end-to-end trainable two-stream visual tracking system, which makes full use of both appearance and motion features of the target. We have extensively evaluated the TS-RCN on most widely used benchmark datasets including VOT2018, VOT2019, and GOT-10K. The experiment results have successfully demonstrated that our two-stream model can greatly outperform the appearance-based tracker, and achieves state-of-the-art performance. The tracking system can run at up to 38.1 FPS. |
14,374 | Please write an abstract with title: MedThaiSAGE2: Enhancing the Decision Support System using Rich Visualization on SAGE 2, and key words: Data visualization, Medical services, Decision support systems, Databases, Python, Public healthcare, Libraries. Abstract: R2R Thailand gathers thousands of medical Routine to Research project data in Thailand and transforms into a valuable knowledge resource for improving healthcare services and supporting healthcare policymakers. MedThaiVis was developed to serve as a tool to visualize these large and complex data and extended to operate on the Scalable Adaptive Graphics Environment (SAGE2). This platform helps healthcare policymakers to use MedThaiSAGE, a Decision Support System based on Association Rules, visualizes insights of the R2R complex data on the SAGE2 high-resolution monitor wall assisting in a policy development. However, MedThaiSAGE has a limitation in terms of visualization from MedThaiVis and these two platforms perform independently. Therefore, we propose an approach to integrate these two platforms in order to enhance their capability. There are three main issues: 1) data integration, 2) communication and cooperative workflow between the two platforms, and 3) fully support on SAGE2. In conclusion, our approach can help users to explore the overview and insights of R2R data and increase the capability to support healthcare policymakers. |
14,375 | Please write an abstract with title: COVID Pneumonia Prediction Based on Chest X-Ray Images Using Deep Learning, and key words: COVID-19, Deep learning, Visualization, Pandemics, Pulmonary diseases, Medical services, Predictive models. Abstract: COVID which is one of the deadliest Pandemic of this era stuck the entire world which emerged from Wuhan, China in 2019. The pandemic had an extensive impact on unemployment and even deaths. This Pandemic was so new that a lot of medical doctors were involved in research towards diagnosing the chest X-ray images for COVID symptoms. Along with COVID, there have been other complications found like Pneumonia which resulted in the second wave of COVID leading to deaths. There has been good research done by Deep learning researchers in predicting the COVID and also COVID with Pneumonia classification based on Chest X-rays. But the challenge in earlier work is the limited data set which ultimately resulted in higher accuracy. The reason being smaller data set had very fewer number features for training which ultimately resulted in higher accuracy during prediction. So, towards obviating the above-mentioned challenge, we here have collected a fairly larger data set for better prediction. In addition, authors have proposed Convolution Neural Network - Long Short-Term Memory (CNN-LSTM) model by allowing ResNEt-101 as pretrained model for CNN along with other pretrained deep learning models like ResNEt-101, Inception V3, DenseNET-169, and Inception-ResNET V2. In addition to the prediction of chest X-ray images into different classes as COVID, COVID with Pneumonia, Viral Pneumonia, and Healthy, GradCAM has been used for giving a visual explanation for deep learning model resulting in higher accuracy which are ResNET-101, DenseNET-169 and CNN-LSTM. The GradCAM shows the Model built can predict the image perfectly. These would be stored in Cloud for access by doctors for medication. |
14,376 | Please write an abstract with title: Massively Parallel Causal Inference of Whole Brain Dynamics at Single Neuron Resolution, and key words: Computational modeling, Heuristic algorithms, Neurons, Time series analysis, Data collection, Supercomputers, Hardware. Abstract: Empirical Dynamic Modeling (EDM) is a nonlinear time series causal inference framework. The latest implementation of EDM, cppEDM, has only been used for small datasets due to computational cost. With the growth of data collection capabilities, there is a great need to identify causal relationships in large datasets. We present mpEDM, a parallel distributed implementation of EDM optimized for modern GPU-centric supercomputers. We improve the original algorithm to reduce redundant computation and optimize the implementation to fully utilize hardware resources such as GPUs and SIMD units. As a use case, we run mpEDM on AI Bridging Cloud Infrastructure (ABCI) using datasets of an entire animal brain sampled at single neuron resolution to identify dynamical causation patterns across the brain. mpEDM is 1,530× faster than cppEDM and a dataset containing 101,729 neuron was analyzed in 199 seconds on 512 nodes. This is the largest EDM causal inference achieved to date. |
14,377 | Please write an abstract with title: A Class Attendance System Based on Cloud Face Recognition for Multi-users, and key words: Image recognition, Target tracking, Target recognition, Databases, Face recognition, Web and internet services. Abstract: This paper introduces a class attendance system for multi-users. This system is based on an OpenCV image recognition module to design a face recognition application that can be used for check-in. OpenCV is used as the primary control recognition module to recognize and track the target face through image processing. Meanwhile, Baidu Cloud stores a face database and provides face recognition and matching scores for face images. This system builds on a client-server structure so that multiple users can use it in different classrooms to check-in at the same time. All faculties can use this for class attendance purposes at any place. |
14,378 | Please write an abstract with title: Wide-Angle Anomalous Refraction Using Efficient Surface Field Optimization for Different Polarizations, and key words: Surface impedance, Optimization methods, Microwave theory and techniques, Metasurfaces, Reflection, Numerical models, Impedance. Abstract: In this work, numerically efficient surface field optimizations for transverse electric (TE) and magnetic (TM) polarizations are presented to design locally lossless and passive metasurfaces (MTSs) performing anomalous refraction. The MTS consists of the cascade of three patterned metallic layers, modeled through homogenized impedance sheets. A certain number of evanescent Floquet modes are introduced through an optimization procedure aiming at minimizing the real part of the sheets surface impedance. Numerical results show a good agreement between the two cases for a near-perfect anomalous refraction without reflection considering arbitrary incidence and refraction angles. |
14,379 | Please write an abstract with title: Compact Balanced Dual-Band BPFs Based on Short and Open Stub Loaded Resonators With Wide Common-Mode Suppression, and key words: Resonant frequency, Resonators, Couplings, Slot lines, Dual band, Microstrip, Band-pass filters. Abstract: Two balanced microstrip dual-band bandpass filters (BPFs) based on short stub loaded resonator (SSLR) and open stub loaded resonator (OSLR) are presented in this brief, respectively. The center frequencies of the two differential-mode (DM) passbands can be controlled quasi-independently by adjusting the lengths of resonators. Moreover, a stepped impedance microstrip line etched with an interdigital coupling line is utilized to introduce a coupling between the two resonators, which generates two extra controlled transmission zeros (TZs) to obtain better selectivities. Furthermore, balanced microstrip/slotline (MS) transition structures are employed as feed networks, which can suppress common-mode (CM) inherently while the DM responses are not affected, thereby the design procedure can be simplified significantly. In order to demonstrate the theoretical design, two balanced dual-band BPFs were designed and fabricated. The simulated responses are compared with the measured ones and a good agreement is obtained. |
14,380 | Please write an abstract with title: Reliability and Validity of Image-Based and Self-Reported Skin Phenotype Metrics, and key words: Skin, Face recognition, Cameras, Optical variables measurement, Performance evaluation, Lighting. Abstract: With increasing adoption of face recognition systems, it is important to ensure adequate performance of these technologies across demographic groups, such as race, age, and gender. Recently, phenotypes such as skin tone, have been proposed as superior alternatives to traditional race categories when exploring performance differentials. However, there is little consensus regarding how to appropriately measure skin tone in evaluations of biometric performance or in AI more broadly. Biometric researchers have estimated skin tone, most notably focusing on face area lightness measures (FALMs) using automated color analysis or Fitzpatrick Skin Types (FST). These estimates have generally been based on the same images used to assess biometric performance, which are often collected using unknown and varied devices, at unknown and varied times, and under unknown and varied environmental conditions. In this study, we explore the relationship between FALMs estimated from images and ground-truth skin readings collected using a colormeter device specifically designed to measure human skin. FALMs estimated from different images of the same individual varied significantly relative to ground-truth FALMs. This variation was only reduced by greater control of acquisition (camera, background, and environmental conditions). Next, we compare ground-truth FALMs to FST categories obtained using the standard, in-person, medical survey. We found that there was relatively little change in ground-truth FALMs across different FST category and that FST correlated more with self-reported race than with ground-truth FALMs. These findings show FST is poorly predictive of skin tone and should not be used as such in evaluations of computer vision applications. Finally, using modeling, we show that when face recognition performance is driven by FALMs and independent of race, noisy FALM estimates can lead to erroneous selection of race as a key correlate of biometric performance. These results demonstrate that measures of skin type for biometric performance evaluations must come from objective, characterized, and controlled sources. Further, despite this being a currently practiced approach, estimating FST categories and FALMs from uncontrolled imagery does not provide an appropriate measure of skin tone. |
14,381 | Please write an abstract with title: Wireless Powering Internet of Things with UAVs: Challenges and Opportunities, and key words: Internet of Things, Wireless communication, Data communication, Optimization, Trajectory, Energy efficiency, Autonomous aerial vehicles. Abstract: Unmanned aerial vehicles (UAVs) have the potential to overcome the deployment constraint of The Internet of Things (IoT) in remote or rural areas. Wirelessly powered communications (WPC) can address the battery limitation of IoT devices through transferring wireless power to IoT devices. The integration of UAVs and WPC, namely UAV-enabled wireless powering IoT (Ue-WPI-o T) can greatly extend the IoT applications from cities to remote or rural areas. In this article, we present a state-of-the-art overview of Ue-WPIoT by first illustrating the working flow of Ue-WPIoT and discussing the challenges. We then introduce the enabling technologies in realizing Ue-WPI-oT. Simulation results validate the effectiveness of the enabling technologies in Ue-WPIoT. We finally outline the future directions and open issues. |
14,382 | Please write an abstract with title: High power diode-pumped laser technology, and key words: Diodes, Power lasers, Laser modes, Fiber lasers, Gas lasers, Power engineering and energy, Cooling, Slabs, Semiconductor laser arrays, Laser noise. Abstract: The paper deals with the progress of diode-pumped laser technologies such as rods, fibers, thin-disks, slabs, and even gases , which are all in the running to engineer systems that are scalable to ever higher power. |
14,383 | Please write an abstract with title: Temperature Sensing System With Flexible Electronics Using Oxide TFTs, and key words: Temperature sensors, Performance evaluation, Temperature measurement, Electric potential, Power demand, Voltage, Packaging. Abstract: This paper presents a novel temperature sensing system using amorphous indium gallium zinc oxide (a-IGZO) thin-film transistor technology for the first time. The system is composed of temperature sensing matrix, a low pass filter and a comparator to sense the increase in temperature beyond the reference value. As an example, human body temperature detection is demonstrated with a single bit output, where the reference temperature is 37°C. The proposed system shows a resolution of 0.1°C with a supply voltage $(\mathrm{V}_{{\mathrm {DD}}})$ of 4V and power consumption of $210 \mu \mathrm{W}$, at a clock frequency of 100KHz. The comparator employs bootstrapped load in the latch to enhance the performance, showing a resolution of 0.15mV with the same $\mathrm{V}_{{\mathrm {DD}}}$ and clock frequency. This system finds potential applications in flexible biomedical healthcare devices and in smart packaging to monitor the temperature of critical items like medicines and provide useful information to the end user. |
14,384 | Please write an abstract with title: Guidance and Control of a Space Robot at Additional Launching and Approaching an Information Geostationary Satellite, and key words: Uncertainty, Aerospace electronics, Satellite navigation systems, Motion control, Robots, Geostationary satellites. Abstract: The methods for guidance and control of a space robot at additional launch and approach to a geostationary satellite under conditions of uncertainty are considered. |
14,385 | Please write an abstract with title: Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon, and key words: Privacy, Loss measurement, Additive noise, Time measurement, Real-time systems. Abstract: We define discounted differential privacy, as an alternative to (conventional) differential privacy, to investigate privacy of evolving datasets, containing time series over an unbounded horizon. We use privacy loss as a measure of the amount of information leaked by the reports at a certain fixed time. We observe that privacy losses are weighted equally across time in the definition of differential privacy, and therefore the magnitude of privacy-preserving additive noise must grow without bound to ensure differential privacy over an infinite horizon. Motivated by the discounted utility theory within the economics literature, we use exponential and hyperbolic discounting of privacy losses across time to relax the definition of differential privacy under continual observations. This implies that privacy losses in distant past are less important than the current ones to an individual. We use discounted differential privacy to investigate privacy of evolving datasets using additive Laplace noise and show that the magnitude of the additive noise can remain bounded under discounted differential privacy. We illustrate the quality of privacy-preserving mechanisms satisfying discounted differential privacy on smart-meter measurement time-series of real households, made publicly available by Ausgrid (an Australian electricity distribution company). |
14,386 | Please write an abstract with title: A New Measurement Technology of Grounded Capacitance Parameters of the Distribution Network Lines Based on Resonance Method, and key words: Capacitance, Voltage measurement, Capacitance measurement, Voltage transformers, Resonant frequency, Current measurement, Frequency measurement. Abstract: Precise measurement of distribution capacitance to ground is always a hot topics discussed by distribution system researchers. Under the certain circumstances, the value of the arc suppression coil value is unknown in distribution network and the grounded parameters cannot be effectively measured by the existing methods. Based on the production of our research group, a new method for grounded capacitance measurement of the distribution network is proposed when the value of arc suppression coil is unknown. In medium and low-voltage distribution network systems of China, the neutral point is commonly used as the arc suppression coil grounding method. Therefore, the accurate and rapid measurement of the grounded capacitance is necessary. After PSCAD and MATLAB joint simulation analysis, experimental verification and the reliability of this method are proved. The measuring process is performed on the secondary side and it does not affect the normal operation of the primary side. |
14,387 | Please write an abstract with title: Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks, and key words: Training, Measurement, Computational modeling, Visualization, Task analysis, Knowledge transfer, Speech recognition. Abstract: Deep neural models, in recent years, have been successful in almost every field, even solving the most complex problem statements. However, these models are huge in size with millions (and even billions) of parameters, demanding heavy computation power and failing to be deployed on edge devices. Besides, the performance boost is highly dependent on redundant labeled data. To achieve faster speeds and to handle the problems caused by the lack of labeled data, knowledge distillation (KD) has been proposed to transfer information learned from one model to another. KD is often characterized by the so-called ‘Student-Teacher’ (S-T) learning framework and has been broadly applied in model compression and knowledge transfer. This paper is about KD and S-T learning, which are being actively studied in recent years. First, we aim to provide explanations of what KD is and how/why it works. Then, we provide a comprehensive survey on the recent progress of KD methods together with S-T frameworks typically used for vision tasks. In general, we investigate some fundamental questions that have been driving this research area and thoroughly generalize the research progress and technical details. Additionally, we systematically analyze the research status of KD in vision applications. Finally, we discuss the potentials and open challenges of existing methods and prospect the future directions of KD and S-T learning. |
14,388 | Please write an abstract with title: Broad-Band Effective Magnetic Response of Two-Component Metaferrite with Spherical Inclusions, and key words: Tensors, Magnetic resonance imaging, Nanocomposites, Magnetization, Metamaterials, Permeability, Magnetic properties. Abstract: The effective magnetic properties of two-component magnetic metamaterial are carried out in this study at the GHz frequencies. The metamaterial is a homogeneous isotropic dielectric material with periodically embedded spherical ferromagnetic inclusions. The inclusions are fully magnetized by a dc bias magnetic field. The expression of effective permeability tensor has derived in the study as well as the expressions of complex effective relative permeability in the direction of external magnetization and perpendicular to it.Analysis of the spectra of real and imaginary parts of the complex effective relative permeability is shortly made in the study. |
14,389 | Please write an abstract with title: News items: Special reamers for electronic components, and key words: Turbines, Lightning, Buildings, Standards, Seminars, Tools, Grounding. Abstract: SOMTA Tools (Pty) Ltd have developed and manufactured a series of small reamers for the electronics communication field. Previously available only from overseas suppliers, the reamers have a tolerance of 0,005 mm which is a far closer tolerance than the ISO standard for corresponding size reamers. |
14,390 | Please write an abstract with title: Practical approach to fuzzy control of inverter pendulum [for inverter read inverted], and key words: Fuzzy control, Inverters, Mathematical model, Fuzzy logic, Control systems, Acceleration, Evolutionary computation, Robust control, Design methodology, Friction. Abstract: A fuzzy PD controller, which can be design without a high amount of effort, is presented. The method using shrinking factors for membership functions is used. For the optimal select of controller parameters the evolutionary algorithm is used. The control of an inverted pendulum using the proposed control method is illustrated. The basic aim of this paper is to balance the pendulum in an upper position. For this purpose a fuzzy logic controller is used. The robustness of the control system against change of pendulum length is investigated. |
14,391 | Please write an abstract with title: QoS for high-performance SMT processors in embedded systems, and key words: Surface-mount technology, Embedded system, Pipelines, Throughput, Resource management, Collaborative work, Costs, Multithreading, Real time systems. Abstract: Although simultaneous multithreading processors provide a good cost-performance tradeoff, they exhibit unpredictable performance in real-time applications. We present a resource management scheme that eliminates a major cause of performance unpredictability in SMTs, making them suitable for many types of embedded systems. |
14,392 | Please write an abstract with title: Safety Ranges for Heart Rate Variability Parameters in Hyperbaric Environments, and key words: Time-frequency analysis, Databases, Electrocardiography, Robustness, Safety, Heart rate variability, Accidents. Abstract: The Autonomic Nervous System (ANS) tries to maintain homeostasis in hyperbaric environments, but its activity may present large variability between subjects. The aim of this study is to establish safety ranges for ANS-related indices derived from the electrocardiographic signal (ECG) during diving and use them to identify subjects with abnormal ANS response and avoid potential diving accidents. A database with ECG recordings from 28 subjects introduced into a hyperbaric chamber was used. During immersion, five stages were studied at 1, 3 and 5 atm during descent and ascent. Indices of heart rate variability, extracted from ECG, reflecting the sympathetic and parasympathetic ANS response, were calculated and regularised with respect to their values at the initial stage at 1 atm. In particular, four time-related parameters extracted from the RR series and four frequency parameters based on the powers of the low and high frequency bands were used. High inter-subject variability in the ANS response was observed in all stages. The eight parameters were analysed for each stage and, as a result, some subjects presented highly uncommon responses with higher chances of suffering a diving accident, reflected in many parameters out of the interquartile range. This allows establishing safety ranges for ANS-related parameters that can help in the identification of subjects with potential health risk. |
14,393 | Please write an abstract with title: The PG2 Gripper: an Underactuated Two-fingered Gripper for Planar Manipulation, and key words: Mechatronics, Automation, Force, Fingers, Grasping, Kinematics, Sensors. Abstract: The flexible grasping, twisting, and force sensing abilities of the gripper are theoretically significant and practically valuable to solve. However, it is still difficult for most existing grippers to realize these three functions simultaneously. In this paper, to realize the purposes of grasping, twisting, and sensing contact force, a novel parallel gripper the PG2 was developed. A two-finger grasping mechanism based on the parallelogram mechanism was designed and constructed. Meanwhile, to sense the contact force between the fingers and the object, a SEA-based force sensing mechanism was proposed. Then the relationship between the rotating angle of the object and the driver angle was calculated through kinematic analysis. Finally, a twisting platform was built and an evaluated experiment was carried out. The experimental results showed that the PG2 can grasp and twist the thin object with a high responding speed in the case of constant contact force. The novel mechanism for grasping, twisting, and sensing contact force has potential in the area that required high responding speed. |
14,394 | Please write an abstract with title: Dynamic Feature Pyramid Networks for Detection, and key words: Convolution, Semantics, Merging, Detectors, Object detection, Feature extraction, Transformers. Abstract: Feature Pyramid Network (FPN) has been a generic feature extractor in computer vision tasks, which utilizes multi-level features to generate discriminative pyramidal representations. However, the way simply using Sum or Concatenate operation on features to integrate multi-scale information is not sufficient to obtain discriminative semantic representations. In this paper, we propose a dynamic feature pyramid network (DyFPN) to merge multi-scale information in both features and weights. DyFPN uses both high-level context features and low-level spatial structural features to obtain dynamic convolution kernel that contains multi-scale information. In this manner, each resolution in the pyramid performs unique and adaptive convolution directly, meanwhile strengthening the information flow. Specially, DyFPN can be regarded as a complementary enhancement to existing feature pyramid networks. We analyze the effective receptive field and attention map of DyFPN. It proves that our method contains more local information and global information compared with merging multi-scale information only on feature level. Benefit from multi-ways of integrating multi-scale information, our method outperforms other existing feature pyramid methods on COCO detection tasks by a large margin. |
14,395 | Please write an abstract with title: Intelligent Exploration and Autonomous Navigation in Confined Spaces, and key words: Semantics, Robot sensing systems, Cognition, Task analysis, Robots, Autonomous robots, Drones. Abstract: Autonomous navigation and exploration in confined spaces are currently setting new challenges for robots. The presence of narrow passages, flammable atmosphere, dust, smoke, and other hazards makes the mapping and navigation tasks extremely difficult. To tackle these challenges, robots need to make intelligent decisions, maximising information while maintaining the safety of the system and their surroundings. In this paper, we present a suite of reasoning mechanisms along with a software architecture for exploration tasks that can be used to underpin the behavior of a broad range of robots operating in confined spaces. We present an autonomous navigation module that allows the robot to safely traverse known areas of the environment and extract features of the unknown frontier regions. An exploration component, by reasoning about these frontiers, provides the robot with the ability to venture into new spaces. From low-level sensory input and contextual information, the robot incrementally builds a semantic network that represents known and unknown parts of the environment and then uses a logic-based, high-level reasoner to interrogate such a network and decide the best course of actions. We evaluate our approach against several mine-like challenging scenarios with different characteristics using a small drone. The experimental results indicate that our method allows the robot to make informed decisions on how to best explore the environment while preserving safety. |
14,396 | Please write an abstract with title: Nanocrystal nonvolatile memory devices, and key words: Nanocrystals, Nonvolatile memory, FETs, Charge transfer, Tunneling, Manufacturing, Nanoscale devices, Semiconductor memory, Flash memory, Dielectric devices. Abstract: In this paper we present an overview of nanocrystal memories - a nascent nonvolatile memory technology that promises to extend the scaling of more conventional charge storage devices to nanometer-scale dimensions. |
14,397 | Please write an abstract with title: Mixed Word Representation and Minimal Bi-GRU Model for Sentiment Analysis, and key words: Semantics, Context modeling, Task analysis, Analytical models, Sentiment analysis, Vocabulary, Neural networks. Abstract: In the mission of natural language processing, sentiment analysis is a formidable challenge due to the complexity of deep network architecture and the lack of standard sentiment word representation. In this paper, we proposed a new learning method of the word representation for the comprehensive information of texts and a minimal Bi-GRU (bidirectional gate recurrent unit) model for the task of sentiment classification. First, for capturing sentiment information of words, the supervised three-layer network is used for construct sentiment word representation. We propose the mixed word representation to denote the classification characteristics, which combines the word embedding of neural probabilistic language model with the proposed the sentiment word representation. Next, we propose bidirectional GRU network including forward and backward propagation to consider the semantic relations before and after sentences, meanwhile, to simple the architecture, we apply minimal GRU network. Then, we combine minimal Bi-GRU model with the mixed word representation taking a full account of semantic and sentiment information to classify the sentiment data set as Movie Reviews and IMDB data set. Experimental results demonstrate that the simplicity of the model and superiority of the performance. |
14,398 | Please write an abstract with title: Dual mode predictive control of buck-boost converters based on state estimation, and key words: Uncertain systems, Observers, Predictive models, Stability analysis, Robustness, Voltage control, Matrix converters. Abstract: In this paper, a dual-mode predictive control strategy for buck boost converter is studied. Firstly, the LPV small signal model of buck boost converter is established and discretized for the later control strategy. Then, because the state variables are unmeasurable, a reduced order unknown input observer is designed, and optimization is used to parameterize the system matrix. Thirdly, a dual-mode predictive control strategy based on state estimation is proposed, which adopts error feedback to ensure the closed-loop stability of the converter, and optimizes the on-line calculation time. Finally, the effectiveness of the design is verified by a simulation example. |
14,399 | Please write an abstract with title: 3D-FDTD Calculation of Lightning-Induced Voltages on an Overhead Wire in Presence of aTower and a Mountain, and key words: Couplings, Power transmission lines, Wires, Poles and towers, Lightning protection, Surge protection, Communications technology. Abstract: The aim of this paper was to study voltages on overhead single wire induced by lightning strikes to a tower located on a mountain, using the three dimension finite difference time-domain (3D-FDTD) method. The overhead wire is located at a close distance from the base of the mountain. The transmission line model extended to include a tall strike object was used to present the lightning channel and the tower. The case of the absence of the mountain is also analyzed. From the comparison between the two cases, it is shown that the induced voltages magnitudes and waveforms are significantly affected by the presence of the mountain. |
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