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6,500 | Please write an abstract with title: UPHO: Leveraging an Explainable Multimodal Big Data Analytics Framework for COVID-19 Surveillance and Research, and key words: COVID-19, Pandemics, Surveillance, Soft sensors, Sociology, Urban areas, Big Data. Abstract: The coronavirus disease 2019 (COVID-19) is an infectious disease with high transmissibility and acquired through the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). Scientists, physicians, and health officials are seeking innovative approaches to understand the complex COVID-19 pandemic pathway and decrease its morbidity and mortality. Incorporating artificial intelligence and data science techniques across the health science domain could improve disease surveillance, intervention planning, and policymaking. In this paper, we report our effort on the deployment of multimodal big data analytics to improve pandemic surveillance and preparedness. A common challenge for conducting multimodal big data analytics in clinical and public health settings is the issue of the integration of multidimensional heterogeneous data sources. Additional challenges for developers are explaining decisions and actions made by intelligent systems to human users, maintaining interpretability between different data sources, and privacy of health information. We present Urban Population Health Observatory (UPHO), an explainable knowledge-based multimodal data analytics platform to facilitate CoVID-19 surveillance by integrating a large volume of multimodal multidimensional, heterogenous data including social determinants of health indicators, clinical and population health data. |
6,501 | Please write an abstract with title: Spatial-Temporal Correlation-Concerned Measurement Manipulation Detection Based on Gramian Angular Summation Field and Convolutional Neural Networks, and key words: Visualization, Correlation, Power system transients, Conferences, Decision making, Collaboration, Phasor measurement units. Abstract: The growing integration of information and communication technology exposes more exploitable cyber-attack vectors to electric power systems. Measurement manipulation is an impactive type of cyber-attacks that can be launched to cause massive damages by interfering decision-making of control centers. Existing data-driven measurement manipulation detection models often bear criticisms due to the deficient mining of spatial-temporal correlations. In this paper, based on the Gramian Angular Summation Field (GASF) algorithm, various types of phasor time-series measured at different locations are transformed into a series of generalized multichannel images. From these generalized images, Convolutional Neural Networks (CNNs) are trained to discover suspicious patterns. GASF can visualize the temporal features of a single time-series and facilitate collaborative CNNs to figure out spatial-temporal correlations between different measurements. The improvements of the proposed framework in the detection performance are demonstrated through case studies. |
6,502 | Please write an abstract with title: Approximations for end-to-end delay analysis in OBS networks with light load, and key words: Intelligent networks, Optical buffering, Delay, Optical network units, Optical packet switching, Optical burst switching, Optical fiber networks, Telecommunication traffic, Optical wavelength conversion, Computer networks. Abstract: We provide an analysis of end-to-end delay in OBS (optical burst switching) networks and a large deviations approximation. The analysis is based on an exponential approximation of the OBS router blocking time and on the assumption of Poisson arrivals in routers along the path from source to destination. On the other hand, a light load assumption is performed, namely, waiting time is mainly due to the residual life of the output wavelengths and not to buffering. |
6,503 | Please write an abstract with title: Successive occurrences of quasi-circular ribbon flares in a fan-spine-like configuration involving hyperbolic flux tube, and key words: Sun: activity, Sun: filaments, prominences, Sun: flares, Sun: magnetic fields, sunspots. Abstract: We present a comprehensive analysis of the formation and the evolution of a fan-spine-like configuration that developed over a complex photospheric configuration where dispersed negative polarity regions were surrounded by positive polarity regions. This unique photospheric configuration, analogous to the geological ‘atoll’ shape, hosted four homologous flares within its boundary. Computation of the degree of squashing factor (Q) maps clearly revealed an elongated region of high Q-values between the inner and outer spine-like lines, implying the presence of an hyperbolic flux tube (HFT). The coronal region associated with the photospheric atoll configuration was distinctly identified in the form of a diffused dome-shaped bright structure directly observed in Extreme Ultraviolet (EUV) images. A filament channel resided near the boundary of the atoll region. The activation and eruption of flux ropes from the filament channel led to the onset of four eruptive homologous quasi-circular ribbon flares within an interval of ≈11 h. During the interval of the four flares, we observed continuous decay and cancellation of negative polarity flux within the atoll region. Accordingly, the apparent length of the HFT gradually reduced to a null-point-like configuration before the fourth flare. Prior to each flare, we observed localized brightening beneath the filaments which, together with flux cancellation, provided support for the tether-cutting model of solar eruption. The analysis of magnetic decay index revealed favourable conditions for the eruption, once the pre-activated flux ropes attained the critical heights for torus instability. |
6,504 | Please write an abstract with title: A Decision Support Tool for the Optimal Monitoring of the Microclimate Environments of Connected Smart Greenhouses, and key words: Greenhouses, Microgrids, Agriculture, Monitoring, Tools, Production, Desalination. Abstract: In this paper, a comprehensive decision support tool based advanced monitoring system is developed to support transition to smart greenhouses for sustainable and clean food production. The decision framework aims to optimally control and manage the microclimate environments of smart connected greenhouses, where each greenhouse is defined as a self-water producing through an enhanced water desalination process. The main advantage of the current approach lies in the ability of the greenhouses to produce their water loads locally. This paper aims to develop an efficient decision tool able of performing specific monitoring and control functionalities to optimize the operation of the greenhouses where the aim is the energy and water savings. A decision model is implemented for the precise regulation and control of the indoor microclimate defining the optimal growth conditions for the crops. Furthermore, a predictive algorithm is developed to simulate in real time the operation of the greenhouses under various conditions, to assess the response of the system to storage dynamics and renewable sources, as well to control the complex indoor microclimate, energy and water flows, as well to optimize the crops growth. The developed tool is tested through a case study where the influences of climate data on the operation of the whole network are analyzed via numerical results. |
6,505 | Please write an abstract with title: A Bayesian approach for short-term transmission line thermal overload risk assessment, and key words: Bayesian methods, Transmission lines, Risk management, Power system modeling, Power transmission lines, Weather forecasting, Power system simulation, Conductors, Thermal conductivity, Monte Carlo methods. Abstract: An on-line conductor thermal overload risk assessment method is presented in this paper. Bayesian time series models are used to model weather conditions along the transmission lines. An estimate of the thermal overload risk is obtained by Monte Carlo (MC) simulation. We predict the thermal overload risk for the next hour based on the current weather conditions and power system operating conditions. The predicted risk of thermal overload is useful for on-line decision making in a stressed operational environment. |
6,506 | Please write an abstract with title: High-Adhesion Thick-Film Gold Without Glass or Metal-Oxide Powder Additives, and key words: Gold, Glass, Powders, Bonding, Adhesives, Additives, Circuits, Conductors, Ink, Ceramics. Abstract: The problems of bonding gold to glass or ceramic are discussed. Glass-to-gold bonding is necessary to obtain the adhesion of gold conductors in thick- or thin-film circuits. The history of thick-film gold conductors is reviewed from the frit-bonded to the reactively bonded to the mixed-bonded system, Which is the current standard. A new different method of achieving gold thick-film adhesion is presented. This adhesion is caused by a molecular layer of cadmium and bismuth oxide on the surface of gold. The coating is Obtained during firing from base metal resinates contained in the ink vehicle. Such surface active ("surfactive") gold ink without frit or metal-oxide powder additives provides optimized adhesion and wire bondability when used as a top conductor in multilayer circuits. |
6,507 | Please write an abstract with title: Process Variation Analysis of Device Performance Using Virtual Fabrication: Methodology Demonstrated on a CMOS 14-nm FinFET Vehicle, and key words: Semiconductor device modeling, Logic gates, Calibration, Fabrication, Performance evaluation, Semiconductor process modeling, FinFETs. Abstract: A new methodology is demonstrated to assess the impact of fabrication inherent process variability on 14-nm fin field effect transistor (FinFET) device performance. A model of a FinFET device was built using virtual device fabrication and testing. The model was subsequently calibrated on Design of Experiment corner case data that had been collected on a limited number of processed fab wafers. We then performed 400 virtual experiments comprising seven sources of process variation. Using this virtual fabrication technique, we were able to identify a minimum gate-to-source/drain spacer thickness for a high-temperature post-EPI rapid thermal anneal (RTA) anneal process that avoided device subthreshold slope penalties. The model allowed us to determine the optimal Si recess depth target and process window prior to source/drain epitaxy. We obtained these results by reviewing device performance as a function of statistical process sensitivity and highlighting key process parameters requiring variation control. These experiments would have been impractical to perform in an actual fab, due to the time, cost, and equipment requirements of running 400 fab-based process variation experiments for each process parameter. This methodology can be used to avoid wafer-based testing during early technology development. |
6,508 | Please write an abstract with title: InAs quantum dot photonic crystal lasers and their temperature dependence, and key words: Quantum dot lasers, US Department of Transportation, Photonic crystals, Temperature dependence, Pump lasers, Electron beams, High speed optical techniques, Optical pumping, Optical coupling, Gallium arsenide. Abstract: We report on the demonstration of optically pumped photonic crystal lasers with InAs quantum dot active regions operating at room temperature near 1310 nm. Absorbed threshold pump powers as low as 25 μW are observed. We also extract a characteristic temperature of 17 K, which is attributed to limitations caused by surface recombination. |
6,509 | Please write an abstract with title: A study on less computational load of noise reduction method based on ALE and noise estimation filter, and key words: Noise reduction, Acoustic noise, Background noise, Working environment noise, Wideband, Adaptive filters, Microphone arrays, Delay, Speech enhancement, Feedback. Abstract: A noise reduction system based on adaptive line enhancer (ALE) and noise estimation filter has been proposed to reduce both wideband and sinusoidal noise in noisy speech. However, the noise reduction system uses several adaptive filters and thus the system cannot avoid increasing computation load. ALE for estimating the sinusoidal noise especially uses large numbers of taps in order to increase the estimation accuracy of the sinusoidal noise. In this paper, the noise reduction system with less computation load is proposed. The tap coefficients of the ALE have the peak by pitch period of sinusoidal noise. The proposed method takes advantage of the characteristics and decreases the number of taps. |
6,510 | Please write an abstract with title: Label swapping for DPSK encoded labels without wavelength conversion, and key words: Multiprotocol label switching, Differential quadrature phase shift keying, Optical wavelength conversion, Optical modulation, Phase modulation, Optical sensors, Optical crosstalk, Switches, Payloads, Scanning probe microscopy. Abstract: We demonstrate label swapping for DPSK encoded labels using synchronous phase modulation (SPM). For the first time label erasure and insertion is performed in a single step without a need for wavelength conversion. |
6,511 | Please write an abstract with title: Compliant Floating-Base Control of Space Robots, and key words: Space vehicles, End effectors, Task analysis, Attitude control, Regulation, Aerospace electronics, Control systems. Abstract: This letter presents a compliant feedback controller of an arm-equipped spacecraft, which does not enforce requirements on the spacecraft position and attitude. The controller is applicable to the pre-contact, contact, and post-contact phases of a robotic operation. In contrast to conventional floating-base strategies, the controller eliminates the instability of the system during a steady contact, and thus can be used in realistic applications. The controller uses an external-internal transposed-Jacobian control for compliant regulation of the end-effector, together with regulation of the whole-body Center-of-Mass (CoM) and angular momentum for achieving post-contact stability, and force feedback for achieving a stable contact phase. The method is validated experimentally using a hardware-in-the-loop simulator composed of a seven degrees-of-freedom (DOF) arm mounted on a 6 DOF simulated spacecraft. Numerical simulations further validate the method considering a realistic thrusters system, measurement noise, and time delay. |
6,512 | Please write an abstract with title: Magnetic properties of thermally annealed (Ni/sub 80/Fe/sub 20/)/sub 1-x/Mn<sub>x</sub> thin films, and key words: Magnetic properties, Annealing, Iron, Magnetic films, Sputtering, Magnetoresistance, Saturation magnetization, Manganese alloys, Electrons, Diffraction. Abstract: We describe the magnetic properties of thermally annealed (Ni/sub 80/Fe/sub 20/)/sub 1-x/Mn/sub x/ thin films and their inverse magnetoresistance. |
6,513 | Please write an abstract with title: Risk Status Identification During the Takeover of Conditionally Automated Vehicles, and key words: Vehicles, Safety, Classification algorithms, Automation, Hidden Markov models, Manuals, Heart rate. Abstract: In order to identify the risk status during the takeover from automated driving to manual driving in dangerous traffic situations, this study investigated their performance during the takeover based on PreScan. The experiment invited 38 drivers. They all held a valid driving license. A risk status identification model was proposed based on the information of vehicle status and traffic environment status. According to the rate of electrocardiogram(ECG) and the performance of takeover, the risk status was classified into three levels. Using Pearson correlation coefficient algorithm, seven factors were selected as the feature set. Then, the algorithm of Random Forest (RF) was employed to establish the takeover risk status identification model. The results show that the accuracy of RF is 98.8%, increasing 10.4%, 17.7% and 7.3% compared with Support Vector Machine (SVM), Classification and Regression Tree (CART) and Back Propagation Neural Network, and each risk level has good prediction results. Respectively, the results show that the space headway, longitudinal acceleration and lane departure have a great influence on the risk level, and the space headway has the strongest impact on the degree of danger during the takeover of control in Conditionally Automated Vehicles. |
6,514 | Please write an abstract with title: Induction Motor Design Workflow for Variable Frequency and Constant Voltage Applications, and key words: Stator windings, Rotors, Torque, Air gaps, Induction motors, Current density, Windings. Abstract: In some particular application, the induction motor is chosen for the robustness and for the possibility to avoid the power electronic plant. Besides the industrial applications, connected to the grid, the induction motor is used also as airborne equipment for the several advantages that it shows. Basically they are quite high frequency applications (250-525 Hz), in which the motor has to work in an wide range of frequencies but at a constant voltage. In this work, a design flow is proposed based on a set of analytical equations, coupled with the finite element analysis, to get a good estimation of the performance of each analyzed individual during the design and parameterization stage. |
6,515 | Please write an abstract with title: Design and Characterization of a Bellows-Driven Soft Pneumatic Actuator, and key words: Actuators, Robot sensing systems, Stomach, Muscles, Bellows, Strain, Soft robotics. Abstract: The soft robotics field investigates biological bodies’ movements to develop soft actuation with similar behavior seen in nature. The skeletal muscles’ movements are vastly mimicked in soft actuators; however, the contractions of smooth muscles are overlooked in soft robotics. Smooth muscles provide peristaltic contractions to the digestive system, such as the stomach, and their design challenges the limits of soft robot development that simulates digestive organs. In this article, we present a novel, bellows-driven soft pneumatic actuator (SPA) with a self-sensing capability that generates linear displacement to simulate a smooth muscle segment in a stomach. This SPA is proposed as a solution for applications such as stomach simulators. The SPA concept, design, fabrication, creep model, and experimental validation are presented in this article. A lumped viscoelastic model presents the actuator's modeling to predict the SPA's displacement from a known applied pressure. The model is successfully validated, which resulted in a maximum displacement of 20.0 mm with a displacement error of 3%. A sensory system embedded in the SPA measures the displacement, and it is found that a force of 0–8.0 N is produced. A polynomial equation calibrates the sensor readings, with a displacement error of 5%. The results show the SPA's capability as a linear soft actuator that can generate a deformation like a smooth muscle segment. To simulate a circular contraction from a stomach with the SPA, we install multi-SPAs in a ring frame that performs contractions. Although the proposed SPA is specifically designed to mimic the smooth muscle, the ring actuator's contractions can be used for other applications such as gripping soft objects. |
6,516 | Please write an abstract with title: NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization, and key words: Location awareness, Deep learning, Image segmentation, Solid modeling, Manuals, Solids, Reproducibility of results. Abstract: For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks and also been introduced in iris biometrics, especially iris segmentation. To investigate recent developments and attract more interest of researchers in the iris segmentation method, we organized the 2021 NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization (NIR-ISL 2021) at the 2021 International Joint Conference on Biometrics (IJCB 2021). The challenge was used as a public platform to assess the performance of iris segmentation and localization methods on Asian and African NIR iris images captured in non-cooperative environments. The three best-performing entries achieved solid and satisfactory iris segmentation and localization results in most cases, and their code and models have been made publicly available for reproducibility research. |
6,517 | Please write an abstract with title: Real-time volume rendering of time-varying data using a fragment-shader compression approach, and key words: Data visualization, Rendering (computer graphics), Hardware, Image coding, Computational fluid dynamics, Petroleum, Computer graphics, Drilling, Laboratories, Statistical analysis. Abstract: The recent advance of graphics hardware allowed real-time volume rendering of structured grids using a 3D texturing approach. The next challenging problem is to extend the algorithms to time-varying volumetric data (4D functions), which consume more storage and are not directly supported in current graphics hardware. Here we present a new visualization technique that includes (1) a compression scheme of sparse 4D functions into 3D textures, and (2) a visualization algorithm that decompress the stored data from the 3D textures using the programmability of fragment shaders, allowing real-time visualization of such data. We illustrate the system in action with datasets resulting from computational fluid dynamics simulations. |
6,518 | Please write an abstract with title: The design and applications of digital filters with complex coefficients, and key words: Digital filters, Filtering theory, Signal processing, Frequency, Band pass filters, Signal analysis, Low pass filters, Information filtering, Information filters, Speech analysis. Abstract: The digital filter with complex coefficients finds applications in the digital processing of analytic signals and complex envelopes. A theory is developed for designing such filters based on low-pass analog prototypes and digital design techniques for real filters. An example of a filter designed according to this theory is presented. The relative advantages of real and analytic signal processing are discussed. It is shown that the filtering required by either processing technique requires essentially the same amount of signal operations, which is reasonable in view of the fact that the same amount of information is processed in both classes of filter. |
6,519 | Please write an abstract with title: State-space search for improved autonomous UAVs assignment algorithm, and key words: Unmanned aerial vehicles, Remotely operated vehicles, Mobile robots, Sparks, Intelligent vehicles, Aerodynamics, Aerospace engineering, Heuristic algorithms, Laboratories, Performance analysis. Abstract: This paper describes an algorithm that generates vehicle task assignments for autonomous uninhabited air vehicles in cooperative missions. The algorithm uses a state-space best-first search of a tree that incorporates all of the constraints of the assignment problem. Using this algorithm a feasible solution is generated immediately, that monotonically improves and eventually converges to the optimal solution. Using Monte Carlo simulations the performance of the search algorithm is analyzed and compared to the desirable assignment algorithm attributes. It is shown that the proposed deterministic search method can be implemented for given run times, providing good feasible solutions. |
6,520 | Please write an abstract with title: Decoupling localization and mapping in SLAM using compact relative maps, and key words: Simultaneous localization and mapping, Robots, Information filters, Sparse matrices, Information filtering, Data mining, Content addressable storage, Australia, Computational modeling, Computational efficiency. Abstract: In this paper, we propose a new algorithm for SLAM that makes use of a state vector consisting of quantities that describe the relative locations among features. In contrast to previous relative map strategies, the new state vector is compact and always consists of 2n - 3 elements (in a 2D environment) where n is the number of features in the map. It is also shown that the information from observations can be transformed and grouped into two parts: first one containing the information about the map and the second one containing the information about the robot location relative to the features in the map. Therefore the SLAM can be decoupled into two processes where mapping uses the first part of the transformed observation vector and localization becomes a 3-dimensional estimation problem. It is also shown that the information matrix of the map is exactly sparse, resulting in potential computational savings when an information filter is used for mapping. The new decoupled SLAM algorithm is called D-SLAM and is illustrated using simulation. |
6,521 | Please write an abstract with title: Magnetic Fluxgate Based Insulation Testing Solution for DC Systems, and key words: Temperature sensors, Temperature measurement, Structural rings, Photovoltaic systems, Insulation, Temperature distribution, Signal processing. Abstract: Traditional insulation detection schemes are based on Hall sensors, which have large zero drift and temperature drift, are difficult to maintain accuracy in outdoor new energy scenarios. This paper designs a DC system insulation detection scheme based on the fluxgate. The fluxgate sensing module is developed using a single magnetic ring and single-coil structure, which suppresses the zero drift; an offset coil input is introduced to build a closed-loop detection system to solve the temperature drift. The solution has been proven to achieve low zero drift and high accuracy over the full temperature range. |
6,522 | Please write an abstract with title: Research on the Control Strategy of Phase Modulator Based on Voltage Coordination, and key words: Reactive power, Voltage measurement, Phase modulation, Power system dynamics, System integration, Switches, Control systems. Abstract: As a device that can well improve the dynamic performance of the power grid, the phase modulator can well solve various types of grid system problems such as insufficient reactive power provided by the receiving end grid, and strengthen voltage support. Based on the principle of automatic voltage control (AVC) of the phase modulator, this paper analyzes the control mode and switching logic between the AVC substation of the phase modulator in Shaoshan Converter Station and proposed to add voltage coordinated control based on the original AVC control mode. When the DC fails, the power can be adjusted to better maintain the stable operation of the regional power grid. Through experiments based on the phase modulator of the Shaoshan converter station, the correctness and practicability of the proposed strategy are verified, and relevant optimization suggestions are put forward, which can provide reference for the design of the control system of the converter station in the future. |
6,523 | Please write an abstract with title: Detecting Similar and Dissimilar Movement Patterns using Indoor Passive Localization, and key words: Location awareness, Performance evaluation, Legged locomotion, Wireless communication, Estimation, Machine learning, Indoor environment. Abstract: This paper covers passive localization of a device-free user such that the user is not involved in the positioning system. We use the so-called device-free passive localization approach to estimate the most likely movement pattern exhibited by a remote-controlled, passive robot while moving at a walking speed. Our estimation is based only on the changes in received signal strength as a result of the concerned movement patterns of the robot. This involves observation of physical movement of the robot within an indoor area covered by Wi-Fi signals and its resulting impact on the radio environment. We show that the movement patterns of a remotely controlled robot can be predicted from the signal features. |
6,524 | Please write an abstract with title: Theory and design of multirate sensor arrays, and key words: Sensor arrays, Signal sampling, Sensor fusion, Filter bank, Finite impulse response filter, Central Processing Unit, Network synthesis, Sensor systems, Wireless sensor networks, Fuses. Abstract: This paper studies the basic design challenges associated with multirate sensor arrays. A multirate sensor array is a sensor array in which each sensor node communicates a low-resolution measurement to a central processing unit. The objective is to design the individual sensor nodes and the central processing unit such that, at the end, a unified high-resolution measurement is reconstructed. A multirate sensor array can be modeled as an analysis filterbank in discrete-time. Using this model, the design problem is reduced to solving the following two problems: a) how to design the sensor nodes such that the time-delay of arrival (TDOA) between the sensors can be estimated and b) how to design a synthesis filterbank to fuse the low-rate data sent by the sensor nodes given the TDOA? In this paper, we consider a basic two-channel sensor array. We show that it is possible to estimate the TDOA between the sensors if the analysis filters incorporated in the array satisfy specific phase-response requirements. We then provide practical sample designs that satisfy these requirements. We prove, however, that a fixed synthesis filterbank cannot reconstruct the desired high-resolution measurement for all TDOA values. As a result, we suggest a fusion system that uses different sets of synthesis filters for even and odd TDOAs. Finally, we use the H/sub /spl infin// optimality theory to design optimal synthesis filters. |
6,525 | Please write an abstract with title: Bi-Rank: A New Bi-Directional Ranking Method for Goods Selection, and key words: Training, Task analysis, Bidirectional control, Sorting, Mathematical model, Switches, Information retrieval. Abstract: Goods selection is a typical daily routine faced by e-commerce platforms, such as choosing the right goods for on-shelf and off-shelf . In this paper, we turned goods selection problem into a learning-to-rank task (LTR). Instead of ranking the head part and the tail part separately, we proposed a Bi-directional Ranking model, abbreviated as Bi-Rank, to solve this task. Bi-Rank relies on a customized loss function/metric named NDCG PLUS, which is an improved version of NDCG. NDCG PLUS incorporates the ranking loss of tail part in the total ranking loss. In addition, Bi-Rank model can choose different size and weight to balance head and tail. It can also downgrade from double-end to single-end by turn off a designed switch, avoiding the trivial process of manually changing items' label. The experiment shows that Bi-Rank model can achieve a good enough ranking result on collections' head part, while output a similar ranking result on tail part compared to the model that specifically optimizing the tail. In addition, this Bi-Rank model is also very flexible, efficient, and easy to use. |
6,526 | Please write an abstract with title: A Stochastic Coupling-Based Channel Impulse Response Matrix Model for Massive MIMO Channels, and key words: Wireless communication, Signal processing, Conferences. Abstract: A novel stochastic channel impulse response matrix (CIRM) model for massive multiple input multiple output (MI-MO) channels is proposed in this papen Under the framework of this proposed model, the CIRM can be modeled as a sum of couplings between the steering vectors at the base station (BS) end and the eigenbases at the mobile station (MS) side. The fading of the coupling between the steering vector and the eigenbase is modeled as Nakagami distribution. Furthermore, the closed form of the capacity is derived based on the proposed framework. Compared with the traditional Weibchselberger model, the proposed model has lower complexity. To validate the proposed model, extensive massive MIMO channel measurements are carried out in an indoor environment The results show that the new model provides a better fit to the measured results than Weibchselberger model. Finally, the closed form and PDF are validated by Monte Carlo realizations of the proposed model. This CIRM model can be used for massive MIMO design in future fifth-generation communication system design. |
6,527 | Please write an abstract with title: Deep Transfer Learning approach for Classification of Chest Infections in Radiographic X-Ray Images, and key words: COVID-19, Training, Tuberculosis, Pandemics, Computational modeling, Pulmonary diseases, Transfer learning. Abstract: From past two years world is suffering with the COVID-19 pandemic which mainly infecting human lungs. Lung infection can be caused by different viruses and bacteria, diagnosis of Lung infections can be done using Radiography X-ray images. Due to similarity in infections there are high chances that other infections can be falsely considered as COVID-19. Manual chest X-ray diagnosis for COVID-19 requires a radiologist and a time taking process, hence it is not a good choice as the covid-19 can spread in no time from person to person.Hence there is need for automatic process of Covid-19 detection and classification of different chest disease. We worked on developing a deep transfer learning model which will accurately classify various chest infections such as COVID-19, Lung-Opacity, Tuberculosis, Viral Pneumonia, We used transfer learning approach which uses existing deep learning models and adding our layers for classification. This work compares various pre-trained models and also convolutional neural network by considering data set of different infections with total 4526 images belonging to 5 classes for training, 647 images belonging to 5 classes for validation, 746 images for testing. |
6,528 | Please write an abstract with title: Application of Blockchain for Trusted Coordination in Collaborative Software Development, and key words: Contracts, Collaborative software, Software systems, Tools. Abstract: The coordination of developing various complex and large-scale projects using computers has been well established and is the so-called computer-supported cooperative work (CSCW). Collaborative software development requires similar technologies and tools to handle the coordination among participating teams. Development of complex and large-scale software systems can be largely improved by effective collaboration among participating software development teams at both component and system levels, which depends on trusted coordination among the participating teams for sharing, processing, and managing information on various participating teams, which are often operating in a distributed environment, even if they are in the same organization. Existing approaches for coordination in collaborative software development are based on using centralized repository and tools to store, process, and retrieve information on participating software development teams during the development. These approaches use centralized authority, have a single point of failure and restricted rights to own data and software. Although there are approaches for collaborative software development using blockchain, they only verify blockchain transactions using customized agreement techniques, and do not address the coordination in collaborative software development. In this paper, it is shown how private blockchain is used to provide trusted coordination in collaborative software development using smart contracts. This is due to the properties of immutability, auditability, and transparency of the blockchain. |
6,529 | Please write an abstract with title: Efficient numerical techniques for solving Pocklington's equation and their relationships to other methods, and key words: Antennas and propagation, Integral equations, Apertures, Testing, Moment methods, Difference equations, Differential equations, Distributed computing, Costs, Application software. Abstract: It is shown that testing Pocklington's equation with piecewise sinusoidal functions yields an integro-difference equation whose numerical solution is identical to that of the point-matched Hallen's equation when a common set of basis functions is used with each. For any choice of basis functions, the integro-difference equation has the simple kernel, the fast convergence, the simplicity of point-matching, and the adequate treatment of rapidly varying incident fields, but none of the additional unknowns normally associated with Hallen's equation. Furthermore, for the special choice of piecewise sinusoids as the basis functions, the method reduces to Richmond's piecewise sinusoidal reaction matching technique, or Galerkin's method. It is also shown that testing with piecewise linear (triangle) functions yields an integro-difference equation whose solution converges asymptotically at the same rate as that of Hallen's equation. The resulting equation is essentially that obtained by approximating the second derivative in Pocklington's equation by its finite difference equivalent. The authors suggest a simple and highly efficient method for solving Pocklington's equation. This approach is contrasted to the point-matched solution of Pocklington's equation and the reasons for the poor convergence of the latter are examined. |
6,530 | Please write an abstract with title: Plasmonically Enhanced Electronically Addressable Photonic Switches Incorporating Phase-Change Materials, and key words: Performance evaluation, Optical switches, Plasmons, Optical materials, System-on-chip, Optical modulation, Electro-optical waveguides. Abstract: Ever-increasing processing and storage requirements steer us towards co-integration of electronics and photonics. Here, we demonstrate waveguide-integrated plasmonic memory and computing elements by employing phase-change materials with reconfigurable properties and dual electro-optic functionality. |
6,531 | Please write an abstract with title: Efficient belief propagation for early vision, and key words: Belief propagation, Image restoration, Image motion analysis, Optical sensors, Costs, Inference algorithms, Markov random fields, Robustness, Pixel, Labeling. Abstract: Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph cuts and belief propagation yield accurate results, but despite recent advances are often still too slow for practical use. In this paper we present new algorithmic techniques that substantially improve the running time of the belief propagation approach. One of our techniques reduces the complexity of the inference algorithm to be linear rather than quadratic in the number of possible labels for each pixel, which is important for problems such as optical flow or image restoration that have a large label set. A second technique makes it possible to obtain good results with a small fixed number of message passing iterations, independent of the size of the input images. Taken together these techniques speed up the standard algorithm by several orders of magnitude. In practice we obtain stereo, optical flow and image restoration algorithms that are as accurate as other global methods (e.g., using the Middlebury stereo benchmark) while being as fast as local techniques. |
6,532 | Please write an abstract with title: Self-Tuning Nonlinear Iterative Learning for a Precision Testing Stage: A Set-Membership Approach, and key words: Servomotors, Uncertainty, Feedforward systems, Motion control, Iterative methods, Informatics, Convergence. Abstract: Iterative learning control (ILC) is an appealing method in motion control applications that can achieve the performance limit of feedforward compensation in repeating tasks. Compensating for the repetitive errors rapidly (G1) and at the same time reducing the accumulation of the nonrepetitive errors effectively (G2) are two major goals of ILC. However, in the simultaneous presence of model uncertainties and noises, most ILC methods that have been used in the application cannot fully achieve these two goals. To tackle this problem, this article develops a self-tuning nonlinear ILC method (STNILC). First, a new nonlinear ILC method (NILC) is designed in the set-membership framework based on the boundedness noise-uncertainty assumption. Then, a self-tuning algorithm is developed to determine the unknown noise-uncertainty bound that is required by NILC. Theoretical results confirm that desirable transient and steady-state convergence performances can be achieved by the proposed STNILC method. Comparative experimental results on a short-stroke stage for testing the lithographic projection lens verify the superiorities of STNILC in sufficiently achieving G1 and G2. |
6,533 | Please write an abstract with title: A new matrix method for pulse train identification, and key words: Radar, Signal processing, Radiofrequency identification, Pulse measurements, Jitter, Space vector pulse width modulation, Radio frequency, Real time systems, Parallel processing, Histograms. Abstract: In this paper a new matrix-based method is proposed for. identification of radar pulse train. The proposed method, which is called NASH, can be used to identify the PRI for constant, staggered, and jittered signal. Previous matrix-based methods can only identify the first type of signal, i.e. constant PRI. The complexity of computation in NASH is approximately equal to 2.5N/sup 2/ which is lower than histogram-based methods. Also NASH can find missing pulses' position in the pulse train. |
6,534 | Please write an abstract with title: Using Data Mining to Find Patterns Related to Interest and Work Readiness of Students in the Culinary Diploma Program as Indonesian Food Cooks, and key words: Education, Classification algorithms, Data mining, Clustering algorithms, Industries, Urban areas, Sensitivity. Abstract: Several studies have shown that the expertise of young chefs graduating from culinary diploma programs in Indonesia who specialize in Indonesian food has not been able to demonstrate their expertise according to stakeholder needs. The implementation of the curriculum in certain subjects is expected to have an impact on the growing interest of students to take the course and will also affect work readiness in their fields. This study uses data mining techniques to process data obtained from closed instruments distributed to 60 students from 6 universities in Indonesia. As a result, there are some interesting patterns between curriculum management and the interests of young chefs that can be extracted from the data obtained. |
6,535 | Please write an abstract with title: Ultra-low jittering of soliton molecular binding separation towards few hundreds of attoseconds, and key words: Timing jitter, Optical fibers, Laser mode locking, Laser noise, Optical solitons, Solitons, Laser stability. Abstract: Mode-locked lasers with low noise have long been used as a practical test bed for complex dissipative nonlinear dynamics. Bound-state pulses from a mode-locked laser, also known as soliton molecules, attracted special attention due to their substantial intra-molecular dynamics. From the perspective of mathematics, stable self-organization pattern can be represented by a point attractor, surrounded by a finite basin of attraction which warrants stability and robustness against perturbations. One open question regarding wide-spread self-organization phenomena is the strength of the nonlinear attractor that determines stability of the self-organized pattern. In response to this question, we utilize optical cross-correlation technique to probe intra-soliton-molecular motion in real time with unprecedentedly attosecond resolution. We achieve ultra-low jittering of soliton molecular binding separation of 490 as in a stationary soliton molecule with 0.52 ps pulse separation. Furthermore, a number of intriguing soliton molecular dynamics in the boundary of stable domain have been revealed by power spectral analysis. We believe that the study provides novel insights into self-organization dynamics in complex nonlinear systems. |
6,536 | Please write an abstract with title: True random bit generation from a double-scroll attractor, and key words: Cryptography, Circuit testing, Random number generation, Semiconductor device noise, Hardware, Computer simulation, Entropy, Face, Information processing, Integrated circuit testing. Abstract: In this paper, a novel true random bit generator (TRBG) based on a double-scroll attractor is proposed. The double-scroll attractor is obtained from a simple model which is qualitatively similar to Chua's circuit. In order to face the challenge of using the proposed TRBG in cryptography, the proposed TRBG is subjected to statistical tests which are the well-known Federal Information Processing Standards-140-1 and Diehard test suite in the area of cryptography. The proposed TRBG successfully passes all these tests and can be implemented in integrated circuits. |
6,537 | Please write an abstract with title: Extended Dissipativity Analysis for Markovian Jump Neural Networks via Double-Integral-Based Delay-Product-Type Lyapunov Functional, and key words: Delays, Artificial neural networks, Delay effects, Learning systems, Symmetric matrices, Pattern recognition. Abstract: This brief studies the problem of extended dissipativity analysis for the Markovian jump neural networks (MJNNs) with time-varying delay. A double-integral-based delay-product-type (DIDPT) Lyapunov functional is first constructed in this brief, which makes full use of the information of time delay. Moreover, some unnecessary constraints on the system structure are removed, which leads to more general results. A numerical example is employed to illustrate the advantages of the proposed method. |
6,538 | Please write an abstract with title: A Spatio-Temporal-Semantic Environment Representation for Autonomous Mobile Robots equipped with various Sensor Systems, and key words: Three-dimensional displays, Annotations, Robot kinematics, Semantics, Robot sensing systems, Cognition, Planning. Abstract: The large amount of high resolution sensor data, both temporal and spatial, that autonomous mobile robots collect in today’s systems requires structured and efficient management and storage during the robot mission. In response, we present SEEREP: A Spatio-Temporal-Semantic Environment Representation for Autonomous Mobile Robots. SEEREP handles various types of data at once and provides an efficient query interface for all three modalities that can be combined for high-level analyses. It supports common robotic sensor data types such as images and point clouds, as well as sensor and robot coordinate frames changing over time. Furthermore, SEEREP provides an efficient HDF5-based storage system running on the robot during operation, compatible with ROS and the corresponding sensor message definitions. The compressed HDF5 data backend can be transferred efficiently to an application server with a running SEEREP query server providing gRPC interfaces with Protobuf and Flattbuffer message types. The query server can support high-level planning and reasoning systems in e.g. agricultural environments, or other partially unstructured environments that change over time. In this paper we show that SEEREP is much better suited for these tasks than a traditional GIS, which cannot handle the different types of robotic sensor data. |
6,539 | Please write an abstract with title: Artificial Intelligence Based Network Selection in Heterogeneous Wireless Networks, and key words: Costs, Power demand, Wireless networks, Neural networks, Heterogeneous networks, Performance analysis, Information and communication technology. Abstract: With the advancement of technology, wireless network is a must. There are various type of service providers all around us those offer wireless network services. The user needs to make a decision which network service it should take at a minimum cost and at the same time that can fulfill the maximum demand. For this reason, different factors need to take under consideration before connecting with a network from heterogeneous network environment. In this paper, we introduce a network selection method based on artificial intelligence. We train the neural network with some networks parameter and our model successfully suggests the best network a user should connect among those networks. Performance analyses based on python platform show that this method selects the best network with a good accuracy. |
6,540 | Please write an abstract with title: Hardening Trust Models against Slandering Attacks in Relayed Content Delivery Services, and key words: Wireless communication, Computational modeling, Collaboration, Device-to-device communication, Security, Proposals, Communication system security. Abstract: There are a number of application contexts in which services are delivered by a given provider to some clients through other relay clients in a collaborative fashion. This is, for example, the case of sensor networks, vehicular networks, D2D, and so on. In this case, a security problem arises. Indeed, when a service is relayed by a client, it is not sure that it is relayed correctly. Therefore, the final client could be deceived if malicious relay clients exist. The classical way to contrast this problem is to use a trust mechanism, managed by the provider, based on the feedback returned by the clients. Thanks to this mechanism, the trust of malicious relay clients can be decreased, then reducing (even cancelling) the negative effects of these clients in the community. The trust mechanisms of this type often suffer from weakness against slandering attacks. Dishonest final clients can fraudulently decrease the trust of relay clients, by reporting a false feedback. In this paper, we propose a general approach to fortify the trust mechanism against this kind of attacks. |
6,541 | Please write an abstract with title: Multi-Device Low-Latency Internet of Things Networks with Blind Retransmissions in the Finite Blocklength Regime, and key words: Reliability, Error probability, Decoding, Optimization, Conferences, 5G mobile communication, Smart manufacturing. Abstract: This work is related to ultra-reliable and low latency communication (URLLC) in Internet-of-Thing (IoT) networks. In particular, we consider a multi-device IoT network performing blind retransmissions on shared radio resources. We characterize the reliability and goodput performances of such network in the finite blocklength regime. In addition, following the characterization we provide two designs minimizing the error probability and maximizing the network goodput (under reliability constraints), respectively. In particular, the optimal solution is obtained for the reliability-oriented design. In addition, an efficient solution is proposed for the second design maximizing the goodput, which provides a performance tightly close to the one obtained via exhaustive search. Through simulation, we validate our analytical model and evaluate the system performance. |
6,542 | Please write an abstract with title: Finite-Time Adaptive Fuzzy Event-Triggered Control of Constrained Nonlinear Systems via Bounded Command Filter, and key words: Nonlinear systems, Backstepping, Lyapunov methods, Control systems, Time-varying systems, Nonlinear dynamical systems, Adaptive control. Abstract: In this note, finite-time adaptive tracking control is studied for nonlinear systems with unmodeled dynamics, asymmetric time-varying output constraints, and uncertain disturbances. Without any growth conditions, fuzzy logic systems are applied to tackle the unknown complicated functions. A novel backstepping approach is developed by combining barrier Lyapunov functions and bounded finite-time command filter. By regulating the threshold parameters online, a new dynamic event-triggered controller is established to ensure that all the signals of the closed-loop system are bounded and the output can follows the preset signal in finite time. Meanwhile, the output is always staying in an asymmetric time-varying interval all the time. The feasibility of the proposed control algorithm is verified with a numerical example and a practical application. |
6,543 | Please write an abstract with title: Automatic Speech Analysis of Conversations for Dementia Detection Using LSTM and GRU, and key words: Speech analysis, Semantics, Manuals, Syntactics, Predictive models, Linguistics, Feature extraction. Abstract: Neurodegenerative diseases, such as dementia, can impact speech, language, and the capability of communication. A recent study to improve the dementia detection accuracy studied the usage of CA (Conversation Analysis) of interviews among patients and neurologists to distinguish among progressive Neurodegenerative Memory Disorders patients & those with (non-progressive) Functional Memory Disorders (FMD). However, manual CA is costly for routine clinical use and difficult to scale. In this work, we present an early dementia detection system using speech recognition and analysis based on NLP technique and acoustic feature processing technique apply on multiple feature extraction and learning using a LSTM (Long Short-Term Memory) and GRU which remarkably captures the temporal features and long-term dependencies from historical data to prove the capabilities of sequence models over a feed-forward neural network in forecasting speech analysis related problems. |
6,544 | Please write an abstract with title: “Surgical Gps” Proof of Concept for Scoliosis Surgery, and key words: Solid modeling, Surgery, Ontologies, Deformable models, Computational modeling, Ligaments, Finite element analysis. Abstract: Scoliotic deformities may be addressed with either anterior or posterior approaches for scoliosis correction procedures. While typically quite invasive, the impact of these operations may be reduced through the use of computer-assisted surgery. A combination of physician-designated anatomical landmarks and surgical ontologies allows for real-time intraoperative guidance during computer-assisted surgical interventions. Predetermined landmarks are labeled on an identical patient model, which seeks to encompass vertebrae, intervertebral disks, ligaments, and other soft tissues. The inclusion of this anatomy permits the consideration of hypothetical forces that are previously not well characterized in a patient-specific manner. Updated ontologies then suggest procedural directions throughout the surgical corridor, observing the positioning of both the physician and the anatomical landmarks of interest at the present moment. Merging patient-specific models, physician-designated landmarks, and ontologies to produce real-time recommendations magnifies the successful outcome of scoliosis correction through enhanced pre-surgical planning, reduced invasiveness, and shorted recovery time. |
6,545 | Please write an abstract with title: Disk Failure Early Warning Based on the Characteristics of Customized SMART, and key words: Prediction algorithms, Hard disks, Predictive models, Business, Forestry, Hidden Markov models, Monitoring. Abstract: Today, with the deep popularization of the Internet, continuous development of 5G, cloud and artificial intelligence, the total global data volume is increasing explosively. With more and more data stored in the data center, traditional hard drives are still hosting large amounts of data, and the single-drive capacity is increasing with an average annual rate of more than 10%, so the availability of hard drives is increasingly impacting data security. According to statistics, hard disk failure rate is more than 50% in the whole server failure accounted, the data center has to sacrifice disk performance and time to recover data continuously. There are huge problems with traditional SMART-based fault monitoring in the fault alarm aging, coverage, accuracy, it can not be avoided in advance. Disk failure early warning systems based on disk customized SMART features are designed to solve these problems. It customized the status information, error statistics, environmental information, reliability information, etc. for the basic components related to disk, disc, motor, etc., and trained the hard disk characteristics of fault classes and normal classes by analyzing the statistics and clustering of various factors, and using the machine learning method strains related to the decision tree. Gradually establish a fault prediction model. The fault prediction model can handle the failed hard drive in advance, data backup and migration timely, so as to avoid failure and data loss, to protect the data security in the data center. The results show there is strong correlation with hard disk failure for the error rate of hard disk, reallocate sector, command timeout and so on, and the accuracy of the model in disk failure prediction can reach more than 98%. |
6,546 | Please write an abstract with title: A Millimetre-Wave Self-Oscillating Mixer Using a GaAs FET Harmonic-Mode Oscillator, and key words: Gallium arsenide, FETs, Oscillators, Frequency, Mixers, Power generation, Microstrip, Radar detection, Costs, Motion detection. Abstract: A 34 GHz self-oscillating mixer is described. The harmonic-mode oscillator which is constructed in microstrip produces 4 mW and as a mixer has minimum detectable signal sensitivity of -121.6dBm/ Hz at a Doppler frequency of 4 kHz. It is potentially a low cost sensor for motion and proximity detection. |
6,547 | Please write an abstract with title: High-Density Motor Drive Development for Electric Aircraft Propulsion: Cryogenic and non-Cryo Solutions, and key words: Partial discharges, Motor drives, Atmospheric modeling, Asia, Multichip modules, Cryogenics, Power electronics. Abstract: This paper presents an overview for the power electronics converter development effort for Electric Aircraft Propulsion (EAP) Systems, in both non-cryogenic and cryogenic power system configurations, from the authors' research group. The first part of the paper presents an architectural comparison for motor drives in such systems. The second part of the presentation will use examples from the author's development to explain on co-design/co-optimization efforts to achieve high power-density and efficiency for the propulsion motor drives. These efforts include converter-level and component-level optimization/advancement, as well as power module packaging. The last part of the paper will briefly introduce the challenges from modeling, testing, and analysis of the “side-effects” for the power electronics in electric aircraft propulsion systems, including partial discharge, EMI/EMC, and reflected wave influences, in such a compact, high-power, high-altitude application environment. |
6,548 | Please write an abstract with title: Simplified Reed-Muller expressions for residue threshold functions, and key words: Graphics, Boolean functions, Counting circuits, Testing, Input variables. Abstract: Residue threshold functions are a broad class of Boolean functions which includes all the unit-weighted threshold functions. In this paper we investigate the complexity of the Reed-Muller (RM) expressions for these functions. We prove that an important subclass of them has very simple RM expansions and determines the conditions that define it. As an interesting practical application, we show that the output functions of parallel counters belong to this subclass. |
6,549 | Please write an abstract with title: HyNet: 3D Segmentation Using Hybrid Graph Networks, and key words: Representation learning, Deep learning, Solid modeling, Three-dimensional displays, Shape, Biological system modeling, Focusing. Abstract: Mesh is a preeminent and efficient data structure for 3D objects that support high-resolution representation. Recent deep learning techniques applied to unstructured mesh data define rigid convolutions that fail to capture the rich geometric and topological attributes of the mesh. We propose an efficient, deterministic process that converts a mesh into a hybrid graph and captures the geometric features of its constituting components: vertices, edges, and faces. In addition, we introduce a novel representation learning framework that encodes mesh elements by focusing on the most relevant parts of the geometric structure using a dual-level attention architecture. We evaluate the efficacy of the proposed representation in the context of the 3D shape segmentation problem. The superior performance of the proposed representation to the state of the art in supervised segmentation illustrates the soundness of the proposed attention model. |
6,550 | Please write an abstract with title: Modelling and simulation of Quadruple Tank system using SBL-PI controller, and key words: Mathematical model, Process control, Transfer functions, Valves, Stability analysis, MIMO communication, Water resources. Abstract: In this paper, Mathematical Modelling of Quadruple Tank system is derived and this Mathematical Model has been linearized with the help of Taylor Series and Jacobian Matrices to get Multiple Input Multiple Output system Transfer function and then by decoupling technique, Multiple Input Multiple Output transfer function has been converted to Two Single Input Single Output Transfer function. Further, Proportional integral controller have been designed using Stability Boundary Locus method and the results are verified using MATLAB and Simulink. |
6,551 | Please write an abstract with title: A CNN-Based Human Head Detection Algorithm Implemented on Edge AI Chip, and key words: Training, Integrated circuits, Head, AI accelerators, Training data, Real-time systems, Indoor environment. Abstract: This paper presents an integrated circuit implementation of a human head detection algorithm. The technique of image data augmentation for deep learning and the operating procedures of the evaluation board named as Mipy are described in the article. Experimental results demonstrate the effectiveness of the proposed evaluation board to detect the human heads in indoor environments. |
6,552 | Please write an abstract with title: A novel user behavior prediction model based on automatic annotated behavior recognition in smart home systems, and key words: Hidden Markov models, Smart homes, Predictive models, Sensors, Intelligent sensors, Annotations, Data models. Abstract: User behavior prediction has become a core element to Internet of Things (IoT) and received promising attention in the related fields. Many existing IoT systems (e.g. smart home systems) have been deployed various sensors and the user's behavior can be predicted through the sensor data. However, most of the existing sensor-based systems use the annotated behavior data which requires human intervention to achieve the behavior prediction. Therefore, it is a challenge to provide an automatic behavior prediction model based on the original sensor data. To solve the problem, this paper proposed a novel automatic annotated user behavior prediction (AAUBP) model. The proposed AAUBP model combined the Discontinuous Solving Order Sequence Mining (DVSM) behavior recognition model and behavior prediction model based on the Long Short Term Memory (LSTM) network. To evaluate the model, we performed several experiments on a real-world dataset tuning the parameters. The results showed that the AAUBP model can effectively recognize behaviors and had a good performance for behavior prediction. |
6,553 | Please write an abstract with title: A study on the tracking photovoltaic system by program type, and key words: Photovoltaic systems, DC motors, Servomotors, Photovoltaic cells, Energy conversion, Control systems, Servomechanisms, Real time systems, Actuators, Sun. Abstract: In order to increase the efficiency of PV system, it is generally used three method the first is the increasing the efficiency of solar cell, the second is the energy conversion system included MPPT control algorithm and the third is the using solar tracking system. In solar tracking system, it is used DC motors, special motors like step motors, servo motors, real time actuators, to operate moving parts. DC motors are normally used to operate solar tracking system but it is highly expensive to maintain and repair. In this paper, it is proposed 150 W solar tracking system. Proposed system designed as the normal line of the solar cell always runs parallel the ray of the sun. In this paper proposed system can minimize the solar cosign loss of the photovoltaic system |
6,554 | Please write an abstract with title: A ROP Optimization Approach Based on Well Log Data Analysis using Deep Learning Network and PSO, and key words: Mathematical model, Optimization, Predictive models, Machine learning, Particle swarm optimization, Neural networks, Oils. Abstract: One of the key aspects of a successful drilling is effective optimization of ROP (Rate of Penetration). Because of the complexity and heterogeneity of formation permeability, the traditional ROP analysis method are limited by drilling prediction. With the accumulation of geological data and drilling records, new methods such as artificial neural network and particle swarm optimization have become powerful tools for obtaining optimization parameters. A ROP optimization method based on deep learning neural network and particle swarm optimization is proposed. Firstly, the prediction model of target wells is established from well logging data by using deep learning neural network. Secondly, the optimized wellbore operation parameters are obtained by using PSO algorithm. At last, the RNN learning algorithm is updated by introducing recovery factor. And also, for the sake of the realization of constraints, a penalty function is introduced. After analyzed logging data of a group of wells in Shunbei area, the experimental results showed that this method can effectively use engineering data to predict drilling rate and optimize drilling parameters. |
6,555 | Please write an abstract with title: Deep Entwined Learning Head Pose and Face Alignment Inside an Attentional Cascade with Doubly-Conditional fusion, and key words: Head, Task analysis, Three-dimensional displays, Face recognition, Two dimensional displays, Location awareness, Pose estimation. Abstract: Head pose estimation and face alignment constitute a backbone preprocessing for many applications relying on face analysis. While both are closely related tasks, they are generally addressed separately, e.g. by deducing the head pose from the landmark locations. In this paper, we propose to entwine face alignment and head pose tasks inside an attentional cascade. This cascade uses a geometry transfer network for integrating heterogeneous annotations to enhance landmark localization accuracy. Furthermore, we propose a doubly-conditional fusion scheme to select relevant feature maps, and regions thereof, based on a current head pose and landmark localization estimate. We empirically show the benefit of entwining head pose and landmark localization objectives inside our architecture, and that the proposed AC-DC model enhances the state-of-the-art accuracy on multiple databases for both face alignment and head pose estimation tasks. |
6,556 | Please write an abstract with title: A Finite-Dimensional Controller for Robust Output Tracking of an Euler–Bernoulli Beam, and key words: Decentralized control, Numerical simulation, Regulation, Numerical models, Structural beams. Abstract: In this paper, we consider robust output tracking problem of an undamped Euler-Bernoulli beam with boundary control and boundary observation. In particular, we study a cantilever beam which has control and observation at the free end. As our main result, we construct a finite-dimensional, internal model based controller for the output tracking of the beam system. In addition, we consider a case where the controller achieves the robust output tracking for the cantilever beam with distributed control and observation. Numerical simulations demonstrating the effectiveness of the controller are presented. |
6,557 | Please write an abstract with title: Mixed Differential Privacy in Computer Vision, and key words: Training, Privacy, Computer vision, Differential privacy, Visualization, Upper bound, Computational modeling. Abstract: We introduce AdaMix, an adaptive differentially private algorithm for training deep neural network classifiers using both private and public image data. While pre-training language models on large public datasets has enabled strong differential privacy (DP) guarantees with minor loss of accuracy, a similar practice yields punishing trade-offs in vision tasks. A few-shot or even zero-shot learning baseline that ignores private data can outperform fine-tuning on a large private dataset. AdaMix incorporates few-shot training, or cross-modal zero-shot learning, on public data prior to private fine-tuning, to improve the trade-off. AdaMix reduces the error increase from the non-private upper bound from the 167–311% of the baseline, on average across 6 datasets, to 68-92% depending on the desired privacy level selected by the user. AdaMix tackles the trade-off arising in visual classification, whereby the most privacy sensitive data, corresponding to isolated points in representation space, are also critical for high classification accuracy. In addition, AdaMix comes with strong theoretical privacy guarantees and convergence analysis. |
6,558 | Please write an abstract with title: Absolute Load Detection with Microwave Gunn Oscillators (Short Papers), and key words: Gunn devices, Microwave oscillators, Electrical resistance measurement, Microwave theory and techniques, Current measurement, Dielectric measurements, Microwave measurements, Voltage-controlled oscillators, Predictive models, Prototypes. Abstract: The change in the dc I-V properties of Gunn-flange microwave oscillators with a change in microwave load are shown to provide a method of measuring the physical properties of dielectric samples that only requires the measurement of dc voltages and currents. A phenomenological equivalent-circuit model has been developed that predicts a dependence of detection sensitivity on bias resistance that agrees closely with experiment and that explains the restrictions on such a bias resistor's maximum allowed value. Properties of a prototype system capable of measuring sample size with 8-percent accuracy are presented. |
6,559 | Please write an abstract with title: Detection of Transmission Towers and Insulators in Remote Sensing Images with Deep Learning, and key words: Deep learning, Satellites, Poles and towers, Training data, Object detection, Insulators, Data models. Abstract: Intelligent inspections of high-voltage electronic power grids with high-altitude aerial or satellite remote sensing images (RSIs) have attracted more and more attention. The detection of transmission tower and insulator in smart electronic power is of great importance. Traditional image recognition based methods have been proven to be difficult to complete this task effectively and efficiently, lots of deep learning based methods have been adopted due to their promising performance. However, collecting a large number of labeled aerial/satellite imaging data for deep learning requires a lot of manpower/financial costs and the deep models trained on small size of samples are often easy to over-fit. For this reason, it has practical significance to study the automatic detection of towers and insulators in the case of small samples. Aiming at the problem of object detection under small samples, a deep learning framework for simultaneous towers and insulators detection in RSIs based on Faster-RCNN and neural style image synthesis is proposed. Firstly, to alleviate the small sample size problem, a sample generation method based on neural style transfer and alpha channel image fusion techniques is proposed, which randomly combines the foreground towers and background images to expand the training data set. Secondly, upon the expanded training data, an object detection model for towers and insulators based on Faster-RCNN is further trained. Experiments show that the object detection model trained with the extended training data has better generalization performance and can better suppress false alarms. |
6,560 | Please write an abstract with title: A Recent Analytical Approach for Analysis of Sub-Synchronous Resonance in Doubly-Fed Induction Generator-Based Wind Farm, and key words: Wind turbines, Doubly fed induction generators, Shafts, Rotors, Wind speed, Power transmission lines, Eigenvalues and eigenfunctions. Abstract: Sub-synchronous resonance (SSR) phenomenon occurs due to the interaction between wind turbine generators and series-compensated transmission lines. A doubly-fed induction generator (DFIG) is considered one of the most widely implemented generators in wind energy conversion systems. SSR analysis based on the eigenvalue method is the most important among the used methods. The accuracy of the eigenvalue method depends on the initial values of state variables. Previously, the initial values of the state variables were calculated based on the iterative approach which is suffering from convergence problem, lacking accuracy, and requiring a long computation time. Moreover, many steps and details haven't been provided. Consequently, it is urgent to fill this gap and show how can implement the SSR analysis model in detail. In this paper, a new application of a recent analytical approach is proposed for SSR analysis. All information is provided, and the SSR analysis model of a DFIG-based series compensated wind farm is built step-by-step. In order to prove the effectiveness and accuracy of the proposed method, the eigenvalue analysis based on the proposed and iterative methods is compared with the time-domain simulation results at different wind speeds and variable compensation levels. The results prove that the eigenvalue analysis based on the proposed method is more precise, where it is consistent with the simulation results in all studied cases. MATLAB software is used to validate the results. |
6,561 | Please write an abstract with title: Comparative study for the impedimetric detection and quantification of adulterants in different bio-consumables, and key words: Impedance, Electrodes, Dairy products, Sugar, Semiconductor device measurement, Current measurement, Spectroscopy. Abstract: Electrical Impedance Spectroscopy (EIS) technique is found to be an excellent candidate for bio-sensing and food quality monitoring applications due to its rapid, robust, cost-effective and point-of-care approach. The present research work investigates the implementation of EIS technique supported by several optical spectroscopic techniques such as Ultraviolet-Visible (UV-Vis) and Fourier Transform Mid Infrared (FT-MIR) to detect and quantify several toxic adulterants in foods and bio-consumables. In the current work, the technique is applied to adulterated saccharides, honey, turmeric and milk samples. EIS study exhibited a steady variation of the electrical impedance with increasing adulterant percentage in the solution. Variation of such properties due to adulteration provides a systematic sensor plot through which one can determine their percentage of adulteration in unknown adulterated samples. Alternatively, extensive justification of UV-Vis and FT-MIR results have been enclosed in this study and has been corroborated with the EIS results, wherever applicable. Focus has been given on the process of design and fabrication of bio-sensor devices for detection and quantification of a variety of adulterants in milk samples. |
6,562 | Please write an abstract with title: Mitigation of Tampering Attacks for MR-Based Thermal Sensing in Optical NoCs, and key words: Handheld computers, Very large scale integration, Security, Trojan horses, Optical sensors, Thermal sensors. Abstract: As an emerging role in on-chip communication, the optical networks-on-chip (ONoCs) can provide ultra-high bandwidth, low latency and low power dissipation for the data transfer. However, the thermo-optic effects of the photonic devices have a great impact on the operating performance and reliability of ONoCs, where the thermal-aware control is used to alleviate it. Furthermore, the temperature-sensitive ONoCs are prone to be attacked by the hardware Trojans (HTs) covertly embedded in the integrated circuits (ICs) from the malicious third-party components, leading to performance degradation, denial of service (DoS), or even permanent damages. In this paper, we focus on the tampering attacks on optical sampling during the thermal sensing process in ONoCs. Corresponding approaches are proposed to mitigate the negative impacts from HT attacks. Evaluation results indicate that our approach can significantly enhance the hardware security of thermal sensing for ONoC with trivial overheads of up to 3.06% and 2.6% in average latency and energy consumption, respectively. |
6,563 | Please write an abstract with title: ECCA: Efficient Correntropy-Based Clustering Algorithm With Orthogonal Concept Factorization, and key words: Matrix decomposition, Clustering algorithms, Robustness, Optimization, Clustering methods, Linear programming, Noise measurement. Abstract: One of the hottest topics in unsupervised learning is how to efficiently and effectively cluster large amounts of unlabeled data. To address this issue, we propose an orthogonal conceptual factorization (OCF) model to increase clustering effectiveness by restricting the degree of freedom of matrix factorization. In addition, for the OCF model, a fast optimization algorithm containing only a few low-dimensional matrix operations is given to improve clustering efficiency, as opposed to the traditional CF optimization algorithm, which involves dense matrix multiplications. To further improve the clustering efficiency while suppressing the influence of the noises and outliers distributed in real-world data, an efficient correntropy-based clustering algorithm (ECCA) is proposed in this article. Compared with OCF, an anchor graph is constructed and then OCF is performed on the anchor graph instead of directly performing OCF on the original data, which can not only further improve the clustering efficiency but also inherit the advantages of the high performance of spectral clustering. In particular, the introduction of the anchor graph makes ECCA less sensitive to changes in data dimensions and still maintains high efficiency at higher data dimensions. Meanwhile, for various complex noises and outliers in real-world data, correntropy is introduced into ECCA to measure the similarity between the matrix before and after decomposition, which can greatly improve the clustering effectiveness and robustness. Subsequently, a novel and efficient half-quadratic optimization algorithm was proposed to quickly optimize the ECCA model. Finally, extensive experiments on different real-world datasets and noisy datasets show that ECCA can archive promising effectiveness and robustness while achieving tens to thousands of times the efficiency compared with other state-of-the-art baselines. |
6,564 | Please write an abstract with title: System design and long-span transmission experiments on an optical FSK heterodyne single filter detection system, and key words: Optical filters, Optical mixing, Frequency shift keying, Optical transmitters, Phase noise, Optical noise, Optical modulation, Bandwidth, Phase detection, Wideband. Abstract: The influence of LD phase noise on a heterodyne noncoherent detection system was evaluated. Based on the evaluation, an optical FSK heterodyne single filter detection system with large frequency deviation and wide-band IF filter has been developed to allow use of stand-alone DFB LD's. In the system, a phase tunable DFB LD was used as an FSK transmitter light source to improve the FSK modulation characteristics. An IF filter with appropriate bandwidth evaded the influence of LD phase noise. With these configurations, long-span (243 km at 140 Mbit/s and 204 km at 280 Mhit/s) transmission experiments have been successfully carried out on this single filter detection system. To the contrary, influence of LD phase noise appeared in a limited IF bandwidth case, which agrees well with the theoretical evaluation. |
6,565 | Please write an abstract with title: Modeling of transfer gates in ion-implanted bubble devices, and key words: Anisotropic magnetoresistance, Magnetization, Magnetic anisotropy, Perpendicular magnetic anisotropy, Magnetostriction, Stress, Failure analysis, Geometrical optics, High speed optical techniques, Sampling methods. Abstract: In-plane domain structures of rudimentary transfer gates for 2μm bubble devices are calculated by numerical minimization of energy. Results are compared with failure mechanisms observed through high speed optical sampling techniques. Insights into the formation of charged walls are obtained in addition to general design rules for such gates. A uniaxial anisotropy term along the pattern edge was found necessary for the general formation of charged walls, as was previously suggested. The need for this term is especially apparent when the applied field is directed along an easy magnetization direction, a condition that occurs in the model transfer gates. The experimental study shows that small local radii of curvature for both the major and minor loop elements result in lower minimum drive fields. Also, positioning the major loop cusp far from the minor loop element reduces the loss of low bias margin that results from strip-out. |
6,566 | Please write an abstract with title: 3D Imaging using mmWave 5G Signals, and key words: OFDM, 5G mobile communication, Radar imaging, Distance measurement, Prototypes, Bandwidth. Abstract: The ability to create and steer beams, and the availability of large bandwidths have opened up the possibility of using mmWave 5G networks for radar-like sensing applications. In this paper, we introduce a signal processing pipeline that is able to process reflected OFDM-based communications waveforms and create radar images without affecting communications protocols or data throughput. An experimental demonstration system for this concept comprising a prototype basestation transmitter and an auxiliary imaging receiver is also presented. These two components are implemented with Si-based 28-GHz, 64-element phased array transceiver modules and software-defined radios. Measurement results show 3D radar images of indoor scenes with 2° angular and 15 cm ranging resolution using 5G-like communications waveforms at 28-GHz, without any effect on communication functionality. |
6,567 | Please write an abstract with title: Response of socioeconomic groups to dynamic and static tariffs of electricity, and key words: Consumer behavior, Tariffs, Pricing, Companies, Production, Big Data. Abstract: Electricity consumption of a home depends on various socio-economic and dwelling factors, such as area of the house, income, age-groups of the family members, size of the house, number of bed rooms, etc. To cope with the high demand, electricity companies use different pricing strategies that help them regulate electricity consumption. This paper explores how consumers respond to static (fixed) and dynamic pricing strategies. In particular, we analyze a large number of factors (826 socio-economic and dwelling factors), called geo-demographic factors, of consumers and study how these factors influence their response to a pricing strategy. Our study can help electricity companies better understand consumer behaviour when it comes to pricing strategies, and can help these companies plan and manage electricity production. |
6,568 | Please write an abstract with title: Sliding Mode Control of a Piezoelectric Actuator with Neural Network Compensating Rate-Dependent Hysteresis, and key words: Sliding mode control, Piezoelectric actuators, Neural networks, Hysteresis, Nanotechnology, Nonlinear dynamical systems, Creep, Inverse problems, Error correction, Stability. Abstract: Piezoelectric actuators (PEA) are the fundamental elements for high-precision high-speed positioning/tracking task in many nanotechnology applications. However, the intrinsic hysteresis observed in PEAs has impaired their potential, specially, the motion accuracy. In this paper, the complicated nonlinear dynamics of PEA including hysteresis, creep, drift and time-delay etc. are treated as a black-box system exhibited as rate-dependent hysteresis. The multi-valued hysteresis is analyzed as a single-valued function so that a neural network (NN) can be built to model the hysteresis and its inversion. A sliding mode controller (SMC) augmented with inverse hysteresis model is then developed to compensate the hysteretic behavior, modeling error and disturbance to improve the positioning/tracking stability and accuracy. The effectiveness of this algorithm experimentally verified through the actual tracking control of a PEA. |
6,569 | Please write an abstract with title: An Adaptive Overlap-Pipelined Multitasking Superscalar Processor, and key words: Pipelines, Multitasking, Power demand, Clocks, Couplings, Pipeline processing, Multicore processing. Abstract: Low power consumption, high performance, and small die size are the three essential considerations in modern CPU design, from tiny IoT devices to General Purpose Manycore System-on-Chip. With these considerations, we introduce a new CPU design that features Adaptive Overlapping Multitasking pipelines, to better balance the design tradeoffs of the traditional scalar and superscalar CPUs. By providing dynamic reconfigurability, we enable user applications to decide at run-time whether to run the CPU in a high-performance or a low-power mode, to meet their respective application deadlines or power budgets. The low-power mode also provides redundancies that allow the CPU to continue operating, even when some of its pipeline stages are damaged. We used the RISC-V ISA test suite, Dhrystone, Coremark, and ten other benchmarks to validate our CPU design's functionality and performance. Our CPU can consistently deliver up to 2.0 Instruction Per Cycle and score a 3.924 DMIPS/MHz and 6.556 Coremark/MHz with Dhrystone and Coremark benchmarks. |
6,570 | Please write an abstract with title: Separated-Spectral-Distribution Estimation Based on Bayesian Inference with Single RGB Camera, and key words: Reflectivity, Sensitivity, Image color analysis, Estimation, Lighting, Cameras, Robustness. Abstract: In this paper, we propose a novel method for separately estimating spectral distributions from images captured by a typical RGB camera. The proposed method allows us to separately estimate a spectral distribution of illumination, reflectance, or camera sensitivity, while recent hyperspectral cameras are limited to capturing a joint spectral distribution from a scene. In addition, the use of Bayesian inference makes it possible to take into account prior information of both spectral distributions and image noise as probability distributions. As a result, the proposed method can estimate spectral distributions in a unified way, and it can enhance the robustness of the estimation against noise, which conventional spectral-distribution estimation methods cannot. The use of Bayesian inference also enables us to obtain the confidence of estimation results. In an experiment, the proposed method is shown not only to outperform conventional estimation methods in terms of RMSE but also to be robust against noise. |
6,571 | Please write an abstract with title: PnP: parallel and external memory iceberg cube computation, and key words: Concurrent computing, Performance analysis, Clustering algorithms, Sorting, Scalability, Processor scheduling, Load management, Data structures, Delay, Switches. Abstract: We present "Pipe 'n Prune" (PnP), a new hybrid method for iceberg-cube query computation. The novelty of our method is that it achieves a tight integration of top-down piping for data aggregation with bottom-up a priori data pruning. A particular strength of PnP is that it is very efficient for all of the following scenarios: (1) Sequential iceberg-cube queries. (2) External memory iceberg-cube queries. (3) Parallel iceberg-cube queries on shared-nothing PC clusters with multiple disks. |
6,572 | Please write an abstract with title: Optimal Scheduling Policy for Spatio-temporally Dependent Observations using Age-of-Information, and key words: Optimal scheduling, Time measurement, Correlation, Wireless sensor networks, Estimation error, Indexes. Abstract: This paper proposes an optimal scheduling policy for a remote estimation problem, where sensor observations of two spatio-temporally correlated processes are broadcasted to two remote estimators. At each time instant only a single observation can be communicated. For this purpose, a system scheduler determines which sensor measurement is communicated. The scheduler cannot observe measurements, and exploits age-of-information (AoI) to calculate the expected estimation error. We derive an optimal scheduling policy, with AoI as state-variable, that minimizes the average mean squared error for an infinite time horizon. The obtained policy yields a periodic scheduling of the sensor measurements, and we show that the AoI for the process with the largest marginal variance does not exceed one. |
6,573 | Please write an abstract with title: Adversarial Signal Augmentation for CNN-LSTM to Classify Impact Noise in Automobiles, and key words: Training, Recurrent neural networks, Steering systems, Inspection, Acoustics, Transient analysis, Spectrogram. Abstract: The classification of impact noise on vehicle steering gear mainly addresses the issue of modeling the transient and impulsive signals. In particular, variations between the steering systems arising from the differences in manufacturing processes according to the vehicle types extremely limit the conventional deep acoustic models. Focusing on the fact that the major hurdles addressed can be mitigated by generating and modeling the virtual impact noise, we propose an adversarial signal augmentation method for the vehicle noise modeling. The impact noise is represented based on the Fourier transform and the variance between vehicle types is alleviated using a generative adversarial network with an auxiliary classifier in order to improve the generalization performance of the model. Experiments with the dataset of 134,400,000 time-series collected from a global motor corporation show that the proposed method has more than 3% of accuracy improvement against the conventional approaches. |
6,574 | Please write an abstract with title: Economic Connected Cruise Control of Electric CAVs using DHP, and key words: Economics, Energy consumption, Analytical models, Simulation, Numerical simulation, Cost function, Performance analysis. Abstract: In this paper, a dual heuristic programming (DHP) scheme considering energy saving and driving comfort is presented for the economic connected cruise control (Eco-CCC) of electric connected automated vehicles (CAVs). First, the longitudinal dynamics of the vehicle platoon system are modeled, and the factors influencing the control objectives are analyzed. Then, a performance index function including the energy consumption economy of the CAV is established according to the energy consumption optimization objective. Finally, based on the DHP method, an Eco-CCC controller is designed to meet energy saving and riding comfort. Numerical simulation results validate the proposed controller. |
6,575 | Please write an abstract with title: Hyperledger Fabric: Evaluating Endorsement Policy Strategies in Supply Chains, and key words: Distributed ledger, Supply chains, Smart contracts, Organizations, Decentralized applications, Throughput, Size measurement. Abstract: Hyperledger Fabric is a permissioned blockchain solution, in which network participation is controlled by predefined rules. This makes it an attractive platform for enterprise settings. In Fabric, endorsement policies are used to specify the peers that must confirm a transaction before it can be considered as valid and appended to the ledger. This work examines various implications of Fabric's endorsement policy component, for which different endorsement policy strategies (and subsequent trade-offs) are evaluated by modeling two real-world supply chain case studies. This work discusses how vulnerable endorsement policies can lead to admitting inauthentic data on the ledger. To address this issue, several approaches are proposed to balance integrity with limited disclosure of confidential information, with or without hosting a network peer directly. Furthermore, the concept of multi-tenancy in blockchain networks is introduced as a way of reducing the technological barrier in technology adoption. |
6,576 | Please write an abstract with title: HD-Map Aided LiDAR-INS Extrinsic Calibration, and key words: Visualization, Laser radar, Roads, Estimation, Transforms, Sensor fusion, Calibration. Abstract: Sensor calibration is a prerequisite for autonomous driving and is vital for accurate perception, ensuring precise planning and control of the autonomous vehicle. The modern self-driving car considers data inputs from multiple sensors to construct an understanding of its surroundings. These sensors are inherently susceptible to errors arising from measurement uncertainty, and the risk is multiplied under sensor fusion, a critical function for vehicle localization and object detection. Existing works in this field of study largely focus on offline sensor calibration methods where the vehicle is assumed to have undergone the calibration process prior to vehicle operation on the road, typically using a known calibration target such as a checkerboard pattern target. This paper proposes a sensor calibration method for the LiDAR and the inertial navigation system (INS) using high definition (HD) maps as a readily available source of ground truth, giving potential to an online approach to calibration. To match the data between the LiDAR and the INS system, the trajectory from LiDAR odometry based on the normal distributions transform (NDT) and the trajectory from the INS are utilized. The HD map acts as an online calibration target and provides real positional coordinates which can correct for errors inherent to the sensor outputs and enhance the trajectory estimations. Upon the detection of miscalibration, the algorithm finds the optimum transformation matrix that aligns the LiDAR with the INS. Real-world data was used to verify the proposed approach and can be applied to find the correct extrinsic transformation matrix. |
6,577 | Please write an abstract with title: Secure multigroup multicast communication systems via intelligent reflecting surface, and key words: MISO communication, Optimization, Wireless communication, Array signal processing, Communication system security, Interference, Transforms. Abstract: This paper considers a secure multigroup multicast multiple-input single-output (MISO) communication system aided by an intelligent reflecting surface (IRS). Specifically, we aim to minimize the transmit power at Alice via jointly optimizing the transmit beamformer, artificial noise (AN) vector and phase shifts at the IRS subject to the secrecy rate constraints as well as the unit modulus constraints of IRS phase shifts. To tackle the optimization problem, we first transform it into a semidefinite relaxation (SDR) problem, and then alternately update the transmit beamformer and AN matrix as well as the phase shifts at the IRS. In order to reduce the high computational complexity, we further propose a low-complexity algorithm based on second-order cone programming (SOCP). We decouple the optimization problem into two sub-problems and optimize the transmit beamformer, AN vector and the phase shifts alternately by solving two corresponding SOCP subproblem. Simulation results show that the proposed SDR and SOCP schemes require half or less transmit power than the scheme without IRS, which demonstrates the advantages of introducing IRS and the effectiveness of the proposed methods. |
6,578 | Please write an abstract with title: Compact semiconductor optical amplifier with U-turn shape deep-ridge passive waveguide for Si photonic circuits, and key words: Semiconductor optical amplifiers, Temperature, Shape, C-band, Bending, Silicon photonics, Wavelength division multiplexing. Abstract: We propose an SOA with U-turn shape deep-ridge passive waveguide for integration on a silicon photonics platform. We fabricated the U-turn waveguide with the bending radius of 75 μm, and good gain characteristics were obtained in the entire C-band. |
6,579 | Please write an abstract with title: Spike-Like Traveling Waves at the Critical Point of Bifurcation in a Nonextensive Dusty Plasma With Dust Polarity, and key words: Plasmas, Ions, Bifurcation, Dusty plasmas, Electrostatics, Plasma temperature, Mathematical models. Abstract: This article presents a detailed study on the basic features of bifurcation of dust ion acoustic (DIA) traveling waves in a dusty plasma comprising warm adiabatic ions, nonextensive electrons, and arbitrarily charged dust particles. A reduced dynamical system is obtained for plasma waves’ evolution, and the global dynamics of local bifurcation of waves’ motion are determined on the equilibrium points’ dust concentrations’ plane with respect to all possible plasma parametric combinations. The stability and phase portrait analysis indicate a sudden emergence of nonlinear periodic and solitary waves for critical values of negative (positive) dust concentration. At these critical values, waves’ dynamics exhibit a transcritical bifurcation with half-stable fixed points which support new spike-like traveling waves. The analytical and numerical solutions reveal that the decay rate of this localized structure is much slower than ordinary solitary waves that decay exponentially fast. Furthermore, the existence domain of bifurcation parameters and transitions between modes are found for different values of nonextensive electrons and arbitrarily charged dust concentrations. Our results could be applicable to different space and astrophysical plasma systems, particularly in earth atmosphere. |
6,580 | Please write an abstract with title: Wavelength conversion using nonlinear polarization rotation in a single semiconductor optical amplifier, and key words: Optical wavelength conversion, Optical polarization, Semiconductor optical amplifiers, Optical interferometry, Nonlinear optics, Optical filters, Band pass filters, Stimulated emission, Optical pumping, Optical saturation. Abstract: We discuss an all-optical wavelength converter based on nonlinear polarization rotation in a single semiconductor optical amplifier. We show that inverted and noninverted wavelength conversion can be realized. We also demonstrate this wavelength-conversion concept can operate over a large wavelength range. Experiments show that error-free wavelength conversion can be obtained at a bit rate of 10 Gb/s. |
6,581 | Please write an abstract with title: Design of Partial Discharge UHF Microstrip Antenna Based on LS Peano Fractal Structure, and key words: Partial discharges, Antenna measurements, Substations, Microstrip antennas, UHF antennas, Transmission line measurements, Fractals. Abstract: In order to detect the partial discharge of gas insulated substation, based on the fractal structure of LS Peano, this paper uses ANSYS HFSS simulation analysis, and designs a UHF microstrip antenna according to the optimization results. The antenna is small in size, with a size of 27.6*27.6*2mm, with ellipsoidal directivity; tested by a vector network analyzer, the antenna output impedance is 50 ohms, and the VSWR is less than 2 in the 300MHz~3GHz frequency band. A GIS partial discharge test platform was built in the laboratory, and the antenna was used to collect partial discharge UHF signals generated by metal protrusion defects. The actual test results showed that the antenna has a wide detection frequency band, high signal-to-noise ratio, and good directivity. It is suitable for on-line monitoring of partial discharge in GIS. |
6,582 | Please write an abstract with title: Fundamental Limitations in Sequential Prediction and Recursive Algorithms: L<inf>p</inf> Bounds via an Entropic Analysis, and key words: Sufficient conditions, Prediction algorithms, Entropy. Abstract: In this paper, we obtain fundamental ${\mathcal{L}_p}$ bounds in sequential prediction and recursive algorithms via an entropic analysis. Both classes of problems are examined by investigating the underlying entropic relationships of the data and/or noises involved, and the derived lower bounds may all be quantified in a conditional entropy characterization. We also study the conditions to achieve the generic bounds from an innovations’ viewpoint. |
6,583 | Please write an abstract with title: Effect of rotor position error on commutation in sensorless BLDC motor drives, and key words: Rotors, Commutation, Brushless DC motors, Voltage, Pulse width modulation, Equations, Sensorless control, Delay effects, Low pass filters, Space vector pulse width modulation. Abstract: In this paper, two kinds of commutation modes of the brushless DC(BLDC) motor drives, the delaying commutation and the leading commutation, are discussed in detail. The current of the unexcited phase is calculated under an ideal operation condition, and the condition of circulating current occurring is analyzed. The result with the compensated commutation is provided. The theoretical analysis is confirmed by the experiment results. |
6,584 | Please write an abstract with title: A Study on Differences in Control Performance of Skill-Assist System Caused by Different Operational Input Devices, and key words: Accelerometers, Performance evaluation, Band-pass filters, Force, Dynamics, Input devices, System integration. Abstract: In the social context of aging and shortage of workforce at manufacturing sectors, we are developing "Skill-Assist Light," an assist system for transporting heavyweight products. While a typical power assist system uses a force sensor as an input device, Skill-Assist Light uses an accelerometer instead of a force sensor. The control performance of the method using acceleration, applied in this paper, has not been intensively discussed in previous researches on force sensor-less assist control systems. In this paper, we discuss differences in control performance between the power assist system equipped with a force sensor and that with an accelerometer. First, the differences of these systems are theoretically represented in their dynamic equations of motion. Second, band-pass filters are designed for each system. Finally, we conducted a transporting experiment and showed that there was a possibility that the accelerometer power assist system exhibited behavior that caused different performance from the intended one due to a phase delay originated from low-pass filtered input signals. |
6,585 | Please write an abstract with title: Through-wall and wall microwave tomography imaging, and key words: Tomography, Microwave imaging, Polarization, Current distribution, Concrete, Integral equations, Scattering, Frequency, Microwave theory and techniques, Dielectrics. Abstract: In the present work new results of experimental investigation on TWWI with using the microwave tomography technique are submitted. A tomographic algorithm is employed for the cross-section imaging of dielectric and metal objects on the other side of a concrete wall and within a concrete block. The cross-section restoration of studied objects is based on the tomography integral equation. The scattered field of the object is measured on a direct line parallel to the wall investigated. The solution of this integral equation gives the possibility to find the function representing the normalized polarization current distribution in the probing cross-section which is normal to the wall surface and in which the scan line lies (vertical cross-section). The normalized polarization current distribution depends on frequency and can be calculated for a set of frequencies. The image function is defined as modulus of the sum of the normalized polarization current distributions. If the wall material in vertical cross-section is not homogeneous because of the presence of defects or quests within the wall or on the other side of the wall, one can see these inhomogeneities. A set of images in different vertical cross-sections allows us to reconstruct a 3D image of the object. It is shown that advanced through-wall and wall images can be obtained by application of an indemnification procedure to the field caused by final sizes of the scanning line and also by using an algorithm allowing us to allocate from the complete field the scattering component. |
6,586 | Please write an abstract with title: An Extension of Empirical Orthogonal Functions for the Analysis of Time-Dependent 2D Scalar Field Ensembles, and key words: Feature detection, Weather forecasting, Data visualization, Predictive models, Numerical simulation, Numerical models, Reliability. Abstract: To assess the reliability of weather forecasts and climate simulations, common practice is to generate large ensembles of numerical simulations. Analyzing such data is challenging and requires pattern and feature detection. For single time-dependent scalar fields, empirical orthogonal functions (EOFs) are a proven means to identify the main variation. In this paper, we present an extension of that concept to time-dependent ensemble data. We applied our methods to two ensemble data sets from climate research in order to investigate the North Atlantic Oscillation (NAO) and East Atlantic (EA) pattern. |
6,587 | Please write an abstract with title: Image Dehazing Based on Luminance Stretching, and key words: Mathematical model, Image color analysis, Atmospheric modeling, Measurement, Cameras, Scattering, Computer science. Abstract: In this work, a method is proposed to restore the visual effects of hazy images with sky using dark channel prior (DCP) and luminance stretching (LS). The transmissions for the non-sky and sky regions of a hazy image is calculated by DCP and LS respectively. The transmission of the hazy image is computed by combining the transmissions obtained using DCP and LS based on soft segmentation. The proposed method along with two state-of-the-art methods is evaluated on 125 randomly selected images from BSDS500 database. The qualitative and quantitative results depict that the proposed method outperforms two state-of-the-art methods. |
6,588 | Please write an abstract with title: Negative substrate bias enhanced breakdown hardness in ultra-thin oxide pMOSFETs, and key words: Electric breakdown, MOSFETs, Stress, Leakage current, Circuits, Breakdown voltage, Sun, Heating, Numerical analysis, Tunneling. Abstract: Negative substrate bias enhanced breakdown hardness in ultra-thin oxide (1.4 nm) pMOS is observed. This result is believed to be due to the increase of hole stress current during breakdown progression via breakdown induced carrier heating. Numerical analysis of the substrate bias effect on hole tunneling current is performed to support the proposed theory. This phenomenon is particularly significant to gate oxide reliability in floating substrate (PD-SOI) or forward-biased substrate devices. |
6,589 | Please write an abstract with title: A Methodology for Model-Based Validation of Autonomous Vehicle Systems, and key words: Testing, Task analysis, Safety, Tools, Probabilistic logic, Matrix decomposition, Backtracking. Abstract: The deployment of autonomous vehicles requires safety assurance and performance guarantees of the developed system. However, this is complex due to the number of scenario variations and uncertainty associated with the operating environment. To alleviate this challenge, we propose a model-based validation methodology that relies on a functional hierarchy for the breakdown and simplification of the system navigation functions, and the Backtracking Process Algorithm to identify, trace, and probabilistically quantify risk significant event sequences (scenarios) that lead to Top Events of interest (such as requirement violations). This methodology is demonstrated on a scenario with an occluded pedestrian crossing the road. We are able to identify risks associated with the actor classification problem and sudden changes in behavior of the pedestrian. |
6,590 | Please write an abstract with title: Explainable Deep Learning Detection of Gaussian Propeller Noise with Unknown Signal-to-Noise Ratio, and key words: Deep learning, Propellers, Neural networks, Detectors, Signal processing, Robustness, Convolutional neural networks. Abstract: Due to its need for robustness and reliability, underwater target detection is a challenging task for deep learning applications. Though many attempts were made to deal with this problem using expert features, few works assessed the benefit of designing deep raw waveform architecture despite its performance in other domains. This paper is focused on explainable raw waveform based neural network for underwater propeller detection. To this purpose, we design a class of Bayes explainable deep neural networks that contains neural networks whose architecture matches the structure of the optimal Bayes detector. This class is derived from a realistic acoustic model of underwater propeller noise. It is established that the approximation error of our class is as small as desired. We also show that this class can be efficiently implemented as a convolutional neural network. Numerical simulations study the risk and explainability of our class compared to a usual convolutional neural network. |
6,591 | Please write an abstract with title: Investigation of an enhanced nonlinear SIC receiver for the IS-95 downlink, and key words: Silicon carbide, Downlink, Base stations, Signal to noise ratio, Multiaccess communication, Interference cancellation, Code standards, Detectors, Signal design, Computer simulation. Abstract: Several techniques have been introduced to enhance the signal-to-interference-plus-noise ratio (SINR) of the nonlinear successive interference canceler (SIC). Some of these improvements are specific to the downlink (base station to mobile) of Interim Standard 95 (IS-95) for code-division multiple-access (CDMA) cellular systems. We extend this previous work by investigating how inclusion of these enhancements affects the probability of error for a weaker base station being demodulated. In addition to evaluating how SINR enhancement removes additional interference from stronger base station signals, we also discuss a joint detector designed to mitigate the interference of weaker base station signals. By using this joint approach, near-far effects can be reduced further for certain channels in the primary base station. Computer simulations are presented to verify the SINR model and demonstrate the performance gains. |
6,592 | Please write an abstract with title: IBMPS: Incubator Baby Monitoring and Parameter Sensing, and key words: Pediatrics, Microcontrollers, Simulation, Organizations, Robustness, Sensors, Internet of Things. Abstract: This work focuses on the health care industry where new technologies in information and communication are adopted and utilized to provide effective medication and healthcare. Recent developments in communication and the evolution of Internet of things (IoT) have created new areas for exploring and investigating advancements in medicine and healthcare. Hospitals have begun utilizing the cellular equipments for correspondence and IoT have been used by integrated with Wi-Fi sensor, NFC tag, RFID, and other sensors. The application of a cellular agent beneath the Wi-Fi connected location will provide an opportunity for enhancing services to the patients, doctors, nurses and other staffs with increased mobility. This paper provides a novel strategy to include IoT in the field of medicine and wellness. This paper implements and demonstrates an effective health care observation and monitoring framework utilizing RFID tags and IoT. The simulation results from this method depict the robustness provided by the system against various medical emergencies. This system assesses various results by weighing and supervising the patient’s health position using a mixture of microcontroller and sensors connected to internet. |
6,593 | Please write an abstract with title: Formal specification and verification of a group membership protocol for an intrusion-tolerant group communication system, and key words: Formal specifications, Protocols, Broadcasting, Delay, Power system modeling, Scheduling, Educational institutions, Fault tolerant systems, Contracts, Logic. Abstract: We describe a group membership protocol that is part of an intrusion-tolerant group communication system, and present an effort to use formal tools to model and validate our protocol. We describe in detail the most difficult part of the validation exercise, which was the determination of the right level of abstraction of the protocol for formally specifying the protocol. The validation exercise not only formally showed that the protocol satisfies its correctness claims, but also provided information that will help us make the protocol more efficient without violating correctness. |
6,594 | Please write an abstract with title: Thermal generators of stochastic signals and their application in microwave resonance therapy, and key words: Stochastic resonance, Microwave generation, Signal generators, Medical treatment, Microwave technology, Organizing, Power distribution, Power generation, IEEE catalog. Abstract: The paper considers thermal generators of stochastic signals used in quantum medicine technologies and the concepts behind their design. Clinical results have confirmed the efficiency of applying these devices in quantum medicine. |
6,595 | Please write an abstract with title: Participation Factor-Based Adaptive Model Reduction for Fast Power System Simulation, and key words: Adaptation models, Analytical models, Adaptive systems, Simulation, Stability criteria, Rotors, Power system stability. Abstract: This paper describes an adaptive method to reduce a nonlinear power system model for fast and accurate transient stability simulation. It presents an approach to analyze and rank participation factors of each system state variable into dominant system modes excited by a disturbance so as to determine which regions or generators can be reduced without impacting the accuracy of simulation for a study area. In this approach, the generator models located in an external area with large participation factors are nonlinearly reduced and the rest of the generators will be linearized. The simulation results confirm that the assessment of the level of interaction between generators and system modes by participation factors is effective in enhancing the accuracy and speed of power system models. The proposed method is applied to the Northeastern Power Coordinating Council region system with 48-machine, 140-bus power system model and the results are compared with two cases including fully linearized model reduction and model reduction using the rotor angle deviation criteria. |
6,596 | Please write an abstract with title: Evaluation of plasma deposited silicon nitride thin films for microsystems technology, and key words: Silicon, Semiconductor thin films, Sputtering, Plasma temperature, Plasma measurements, Plasma diagnostics, Optical films, Strain measurement, Dielectric measurements, Thermal variables measurement. Abstract: Plasma deposited silicon nitride thin films were deposited at temperatures between 150/spl deg/C and 300/spl deg/C. Diagnostic microstructures were fabricated from the thin films using bulk micromachining, and the strain was calculated from optical measurement of postbuckling deflection. The results indicate that the residual strain of the thin films is dominated by film-substrate thermal mismatch, with the coefficient of thermal expansion monotonically increasing with decreasing deposition temperature. Metal-insulator-metal devices of variable area were also fabricated to measure the dielectric constant, which was shown to be independent of deposition temperature. The importance of these results to microsystems technology (MST) was briefly discussed. |
6,597 | Please write an abstract with title: Kernel-Level Rootkits Features to Train Learning Models Against Namespace Attacks on Containers, and key words: Cloud computing, Conferences, Computational modeling, Neural networks, Machine learning, Containers, Security. Abstract: The container-based cloud computing service is increasingly adopted by many service providers for its efficiency and flexibility. Containers isolated by namespaces share OS kernel. When the kernel-level rootkits exploit vulnerabilities existing in kernel, the namespace can be invalidated leading to critical security incidents. Even though many traditional approaches have been made to detect kernel-level rootkits, it is hard to detect new attacks conducted in the new environment such as container-based cloud computing system. In this paper, we show some possible attack scenarios by kernel-level rootkits exploiting kernel namespaces and suggest key features that can be used to train machine learning and neural network models. |
6,598 | Please write an abstract with title: Community mining tool using bibliography data, and key words: Bibliographies, Data visualization, Informatics, Information technology, Data analysis. Abstract: Research communities are very important for researchers undertaking new research topics. In this paper, we propose a community mining system using bibliography data in order to find communities of researchers. The basic concept of our study is to provide interactive visualization of both local and global research communities. We implement this concept using actual bibliography data and present a case study using the proposed system. |
6,599 | Please write an abstract with title: Dynamic Multi-UAV Cooperative Reconnaissance Task Assignment Based on ICNP, and key words: Protocols, Simulation, Heuristic algorithms, Computational modeling, Reconnaissance, Problem-solving, Task analysis. Abstract: Aiming at the problem of poor timeliness and large communication volume in the traditional contract network protocol (CNP) when dealing with the dynamic multi-UAV cooperative reconnaissance task assignment problem, this paper proposes an improved contract network protocol (ICNP). Firstly, the multi-base, battlefield risk and other factors are considered to establish the multi-UAV cooperative reconnaissance task assignment model; secondly, the credit mechanism and selection mechanism are introduced into the traditional CNP, which improves the bidding efficiency and optimizes the bidding scope; finally, the simulation results show that the ICNP can significantly reduce the system traffic and improve the problem solving timeliness without reducing the reconnaissance efficiency for complex dynamic assignment problem. Keywords Multi-UAV; cooperative reconnaissance; dynamic; task assignment; contract network protocol. |
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