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13,300 | Please write an abstract with title: Survey, Analysis and Comparison of Radar Technologies for Embedded Vital Sign Monitoring, and key words: Heart rate, Radar measurements, Signal processing algorithms, Estimation, Radar, Radar signal processing, Power systems. Abstract: Contactless vital sign monitoring systems are becoming increasing in demand for a wide range of biomedical applications. Millimetre-wave radars and embedded signal processing are the most promising technologies to enable non-contact vital signs monitoring. In this work, the challenging task of heart rate estimation from radar data has been addressed. Three different radar systems from Infineon, Texas Instruments and Acconeer, and four algorithms, FFT, Median-FFT, STFT and Median-STFT, have been analysed and compared against a reference sensor. Accuracy, as well as power figures, have been reported for all the radar systems. A dataset of 16 volunteers has been acquired, yielding a total of 400 minutes of radar-recorded vital sign data. The accuracy of the four investigated algorithms has been reported on average and per subject for every radar. The algorithm exploiting the Short Time Fourier Transform (STFT) is able to achieve an error as low as 0.02% on a single person and of 6.4% in heart rate estimation on average across the whole dataset. |
13,301 | Please write an abstract with title: CloudRAFT: A Cloud-based Framework for Remote Experimentation for Mobile Networks, and key words: Wireless communication, Cloud computing, Codes, Web services, Real-time systems, Optimization. Abstract: In this article we explore new techniques that can enable open remote experimentation for mobile networks. We first propose a cloud-based framework called CloudRAFT, based on which experimenters are allowed to remotely access and control experimental resources via public cloud AWS and share the resulting data and code via the cloud. Then, we discuss the enabling techniques for CloudRAFT, including Amazon serverless service, VNC-based remote command line, and Websocket-based real time communications, among others. Finally, we showcase the application of these techniques in enabling remote access to UB NeXT, a software-defined testbed that has been developed at University at Buffalo for wireless mobile network modeling, optimization and deployment. This work verifies the feasibility of accessing, controlling and sharing wireless testbeds through a remote public cloud. |
13,302 | Please write an abstract with title: Achieving Acceptable Distribution System State Estimation Performance Through Telemetry and Operational Forecasting, and key words: Sensor placement, Smart grids, Telemetry, Reliability, Forecasting, State estimation, Intelligent sensors. Abstract: Southern California Edison (SCE) is in the process of implementing Smart Grid applications as part of an ongoing grid modernization effort to improve reliability and asset utilization, avoid DER-caused problems, and timely demand response to market and/or other signals. How many sensors are needed, where to deploy them and what data do they need to provide are questions that have a considerable impact on the effectiveness of these applications and significant economic consequences for SCE and other utilities. This paper presents a stochastic methodology that allows utilities to quantify the accuracy of DSSE results for simulated sensor placement and operational forecasting scenarios. We applied this methodology to six real-world distribution circuits located in SCE's service territory to inform the deployment of sensors and operational forecasting that yield sufficiently accurate DSSE results with respect to achieving optimal and violation-free execution of the Volt-Var Optimization (VVO) Smart Grid application. |
13,303 | Please write an abstract with title: VPN-Zero: A Privacy-Preserving Decentralized Virtual Private Network, and key words: Privacy, Production, Virtual private networks, Certification. Abstract: Distributed Virtual Private Networks (dVPNs) are new solutions aiming to solve the trust-privacy concern of a VPN's central authority by leveraging a distributed architecture. In this paper, we discuss the requirements of a successful dVPN system and we present VPN-Zero: a dVPN system with strong privacy guarantees that provides traffic accounting and has minimal performance impact on its users. VPN-Zero guarantees that a dVPN node only carries traffic it has “allowlisted”, without revealing its allowlist or knowing the traffic it tunnels. This is achieved via three main innovations: (a) an attestation mechanism which leverages TLS to certify a user visit to a specific domain, (b) a zero-knowledge proof to certify that some incoming traffic is authorized (e.g., falls in a node's allowlist, without disclosing the target domain), and (c) a dynamic chain of VPN tunnels to both increase privacy and guarantee service continuation while traffic certification is in place. The paper demonstrates VPN-Zero functioning when integrated with two production systems: BitTorrent's Distributed Hash Table and ProtonVPN. Early evaluation results show that the median setup time of VPN-Zero is about 10 seconds. |
13,304 | Please write an abstract with title: Overhead power lines in south africa—the case for rationalisation, and key words: Wires, Insulators, Lightning, Storms, Grounding, Power transmission lines, Magnesium. Abstract: Where the transmission line voltage supplying a town is the same as that of the town's primary distribution network, the author implies that the omission of the added impedance of stepdown transformers is invariably an advantage. This may be so from the supplier's point of view, but the effect of this omission on the rating of the consumer's HV switchgear should not be overlooked. The cost of installing and maintaining medium-size and -ratio transformers might easily be more than offset by the corresponding costs of the higher rating HV switchgear that may be necessitated by the omission of stepdown transformers. |
13,305 | Please write an abstract with title: Dual Hidden Failure Model for Cyber Physical Power System, and key words: Power grids, Network topology, Power system faults, Power system protection, Topology, Dispatching. Abstract: With the increasingly close coupling between the cyber network and the physical power grid in Cyber Physical Power System (CPPS), the failure of cyber network has become an important cause of blackout. Equipment failure or abnormal operation state will be appeared without alarm in complex cyber network, which brings hidden failures not been diagnosed and dealt with in time. The invisibility and harmfulness of hidden failures pose a significant threat to the safe, reliable, and stable operation of CPPS. The dual hidden cascading failure model for CPPS is proposed to reveal the failure characteristics of CPPS accurately, considering not only the hidden faults in the power grid, but also the hidden failures in the cyber network. With the different coupled relationships between power systems and cyber networks, the cyber network topology with corresponding failure threshold is obtained according to the simulation of the model with different hidden failure rates of cyber network nodes. When the hidden failure rate is lower than the failure threshold, the scale-free topology cyber network coupled mode is adopted between power grids and cyber networks, otherwise the small-world topology cyber network coupled mode is adopted, which can effectively reduce the risk of power system blackouts. The method proposed in this paper is tested by using IEEE-118 power system and its cyber network. The results show that the method is effective. |
13,306 | Please write an abstract with title: The Application of Using Supervised Classification Techniques in Selecting the Most Optimized Temporary House Type in Post-disaster Situations, and key words: Conferences, Sociology, Decision making, Sea measurements, Tools, Hurricanes, Statistics. Abstract: The United States spends around 450 million dollars just for lodging the survivors and creating temporary shelters in the wake of hurricane Harvey, Irma, and Maria in 2017. Post-disaster temporary housing is a multi-objective process, thus reaching the optimized model relies on numerous objectives and their interaction with each other. The construction activities, especially in a post-disaster scenario, is considered challenging, leading to ineffective management in post-disaster housing reconstruction. Acknowledging and creating a balance between these issues by the policymakers who provide accommodations to post-disaster victims is one of the main challenges that need to be addressed.Post-disaster temporary housing is an integral part of the recovery process; however, not many research types have been done regarding how the factors and to what degree factors can affect the classification. One way to categorize the temporary housing units (THU) is based on how they get built, either made onsite or created offsite. However, the mechanism of selecting the THU types is mainly based on expert opinion and tacit knowledge, which can result in the insufficiency of the process.This model aims to study how and to what degree the factors that affect the post-disaster temporary housing process dictate the type of THU in terms of being built onsite or modeled offsite. The researchers designed a questionnaire to understand each main factor's importance compared to each other through a ranking process. It also asks each participant to rate the different THUs being used based on their importance. In this study, an ordinal classification framework is introduced using the K-Nearest Neighbor (KNN) model to help decision-makers choose the right type of temporary houses based on their needs. This model's results show how supervised classification models can be an efficient tool and holistic approach to providing more robust, efficient decisions as an alternative to the current strategy, which relies on tacit knowledge. |
13,307 | Please write an abstract with title: Time-dependent self-action of periodically modulated laser beams in resonant media, and key words: Optical modulation, Laser beams, Resonance, Transient analysis, Waveguide lasers, Optical refraction, Time factors, Maxwell equations, Gaussian processes, Diffraction. Abstract: We study the self-action of an amplitude-modulated beam in a two-level saturable absorbing medium. We also consider the radial quadratic dependence of the linear refraction index to apply the results to doped waveguides. As the modulation period approaches the relaxation times, the medium response is no more instantaneous, so that one should solve the full set of Maxwell-Bloch equations. We propose a second-order scheme with the Gauss-Laguerre transformation of the transverse field pattern. A simplified approach based on the synchronous interaction approximation is used for thin layers. We analyze the transient behavior of the medium response and its manifestation in the modulation of the beam diffracting after a thin saturable absorber. Nonlinear distortions of the modulation signal passed through a doped waveguide appear to be unexpectedly small compared with those of the local polarization and population difference. |
13,308 | Please write an abstract with title: An Analytic Approach for Modeling Uplink Performance of Mega Constellations, and key words: Satellites, Uplink, Interference, Analytical models, Satellite antennas, Antennas, Downlink. Abstract: In the mega constellation, hundreds of satellites are launched into space to provide global coverage and high-quality service. The number of served user terminals (UTs) can be large-scale under such a dense distribution of satellites, which may lead to severe intra-constellation interference in uplink communications. Hence, it is quite necessary to analyze the intra-constellation interference and deduce analytical expressions of uplink performance in mega constellations to provide design principles for the constellation construction. In this paper, we investigate the uplink performance of mega constellations in terms of outage probability (OP) and ergodic capacity (EC) with actual antenna patterns under the poisson point process constellation model. The expressions that reveal the relationships between the uplink performance and network parameters are derived, by which the constellation scale that satisfies the demand of EC can be obtained. The accuracy of the analytical results is verified through extensive simulations. Our results indicate that the EC first increases but then diminishes as the scale increases if there is enough UTs to be served, which may provide an insight on the scale construction of a mega constellation. |
13,309 | Please write an abstract with title: Resource allocation protocol based on maximum cell transfer delay for rt-VBR services in wireless ATM LAN, and key words: Resource management, Wireless application protocol, Delay, Wireless LAN, Local area networks, Asynchronous transfer mode, Media Access Protocol, Base stations, Dynamic scheduling, Bandwidth. Abstract: This paper proposes a MAC protocol for real-time VBR (rt-VBR) services in wireless ATM LAN. The proposed protocol is characterized by a contention-based mechanism of the reservation request, a contention-free polling scheme for transferring the dynamic parameters, and a priority scheme of the slot allocation. The design objective of the proposed protocol is to guarantee the real-time constraint of rt-VBR traffic. The resource allocation algorithm uses a priority scheme based on the maximum cell transfer delay parameter. The wireless terminal establishes an rt-VBR connection to the base station with a contention-based scheme. The base station scheduler allocates a dynamic parameter minislot to the wireless terminal for transferring the residual lifetime and the number of requesting slots as the dynamic parameters. Based on the received dynamic parameters, the scheduler allocates the uplink slots to the wireless terminal with the most stringent delay requirement. The simulation results show that the proposed protocol can guarantee the delay constraint of rt-VBR services along with its cell loss rate significantly reduced. |
13,310 | Please write an abstract with title: Delivering Delight: Analyzing Luxury Consumer Satisfaction with Home-Delivered Premium Ingredients for Exquisite Home Cooking in Bangkok, and key words: home delivery, food ingredients, customer satisfaction, SERVQUAL. Abstract: There was an increase in demand for high-quality ingredients delivered for home cooking in response to the COVID-19 pandemic. Even after the pan-demic, this shift in customer demand is ongoing. The purpose of this study was to develop a conceptual framework to identify the factors influencing luxury consumer satisfaction with the consumption of premium home cooking ingredients during and after the Covid-19 pandemic, with a focus on the Bangkok metropolitan area. The American Customer Satisfaction Index (ACSI) model was used to define factors influencing customer satisfaction when purchasing fresh premium ingredients. This study highlights five antecedent factors of customer satisfaction: customer expectation, perceived quality of food, perceived quality of services, perceived value with an emphasis on luxury, and various relevant indicators. Nine key hypotheses were identified while developing the framework model, creating the possibilities for relationship verification. Indicators were then developed to measure consumer expectations of home delivery premium ingredients in terms of quality, value, and satisfaction. |
13,311 | Please write an abstract with title: ALASA: When Service Overlay Networks Meet Peer-to-Peer Networks, and key words: Peer to peer computing, Web and internet services, IP networks, Business, Routing, Context-aware services, Robustness, Proposals, Fault tolerance, Load management. Abstract: A number of service overlay network architecture have been proposed to provide solutions over the existing Internet infrastructure. These range from application layer multicast, QoS provisioning, and application adaptations, to reliable routing. At the same time, peer-to-peer networks have attracted a lot of attention both from business and research communities. They have been considered as one of the architectures capable of providing robust, scalable, and self-organizing networking solutions. In this paper, we present a service overlay network framework, called ALASA (application layer active service architecture), to provide a solution for distributed on-demand services across the Internet. Combining the advantages of service overlay networks and peer-to-peer networks, the ALASA is flexible and dynamic enough to be scaled Internet wide, as well as to create a fair service market place for service provisioning |
13,312 | Please write an abstract with title: Improving Soil Moisture Spatio-Temporal Resolution Using Machine Learning Method, and key words: Spatial resolution, Soil moisture, Remote sensing, Microwave radiometry, Land surface temperature, Moisture, Microwave imaging, Climate change. Abstract: Surface soil moisture (SM) plays an essential role in the water and energy balance between the land surface and the atmosphere. The published soil moisture products, having a low spatial resolution of 25–40 km, and low temporal resolution of 2–3 days, limits their applications at regional scale. In this study, the spatio-temporal resolution of Fengyun (FY) SM products was improved using a machine-learning model named the General Regression Neural Network (GRNN), with the help of selected six high spatial resolution parameters, including Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), albedo, Digital Elevation Model (DEM), Longitude (Lon) and Latitude (Lat) after gap-filled as input variables. An implements tested over the Tibetan Plateau (TP) showed that the spatio-temporal resolution of FY-3B SM was improved from 0.25° and 2–3 days to 0.05° and 1-day. The high spatio-temporal resolution SM can enhance our understanding of water-energy cycle under climate change. |
13,313 | Please write an abstract with title: A low-cost plastic package for 2.5Gbps optical transceiver module with high electromagnetic shielding, and key words: Plastic packaging, Transceivers, Electromagnetic shielding, Costs, Optical polymers, Electromagnetic interference, Electromagnetic measurements, Weaving, Liquid crystal polymers, Carbon dioxide. Abstract: A high electromagnetic shielding, light weight, and low cost plastic package for a 2.5 Gbps optical transceiver module is developed by using a woven continuous carbon fiber (CCF) epoxy composite. The shielding effectiveness (SE) of the packaged optical transceiver modules is measured and theoretically modeled. By weaving the CCF in a balanced twill structure (BTS) with excellent conductive networks, the SE of the proposed package is significantly higher (about 20 dB) than a previous package using a liquid crystal polymer (LCP) composite. Besides better SE performance, the package is lower cost due to reduced usage of the carbon fiber. The proposed package for the optical transceiver module is suitable for use in low cost and low electromagnetic interference (EMI) lightwave transmission systems. |
13,314 | Please write an abstract with title: Automatic detection of voice impairments due to vocal misuse by means of Gaussian mixture models, and key words: Diseases, Acoustic signal detection, Speech analysis, Signal analysis, Speech processing, Signal processing, Surgery, Pathology, Speaker recognition, Neural networks. Abstract: There is an increasing risk of vocal and voice diseases due to the modern way of life. It is well known that most of the vocal and voice diseases cause changes in the acoustic voice signal. These diseases have to be diagnosed and treated at an early stage. Acoustic analysis is a non-invasive technique based on digital processing of speech signal. Acoustic analysis could be a useful tool to diagnose this kind of diseases, furthermore it presents several advantages: it is a non-invasive tool, provides an objective diagnostic, moreover, it can be used for the evaluation of surgical and pharmacological treatments and rehabilitation processes. ENT clinicians use acoustic voice analysis to characterise pathological voices. In this paper, we study a well known classification approach-in speaker recognition and identification-applied to the automatic detection of voice disorders. Former and actual works demonstrate that impaired voice detection can be carried out by means of supervised neural nets: multilayer perceptron. We have focused our task in detection of impaired voices by means of Gaussian mixture models and parameters such as mel frequency cepstral coefficients extracted from the windowed voice signal. |
13,315 | Please write an abstract with title: Automatic traffic surveillance system Utilizing object detection and image processing, and key words: Head, Surveillance, Roads, Object detection, Traffic control, Safety, Vehicles. Abstract: In our day and age where the numbers of cars on the road are rapidly increasing, thereby causing traffic. Drivers are becoming more reckless and carefree as the burden on the current human and automated system grows. Drivers and bikers who may wish to save a few minutes may break red lights and avoid wearing helmets but these small actions can have a significant impact and can result in the loss of lives. We propose a system that will intelligently use deep learning-based object detection to identify traffic offenders and provide methods to penalize them by recognizing their number plate. Our system will be able to detect traffic light violators and bikers without helmets. It has been designed in such a way that it is robust enough to work in drastic conditions and intelligent enough to reduce human dependence. |
13,316 | Please write an abstract with title: Embedded MPLS architecture, and key words: Multiprotocol label switching, Hardware, Computer architecture, Protocols, Internet, Bandwidth, Application software, Software performance, Degradation, Software design. Abstract: This paper presents a hardware architecture for multiprotocol label switching (MPLS). MPLS is a protocol used primarily to prioritize Internet traffic and improve bandwidth utilization. Furthermore it increases the performance of Internet applications and overall efficiency. However, most existing MPLS solutions are entirely software based. MPLS performance can be enhanced by executing core tasks (i.e. label stack modification) in hardware while allowing other tasks to be executed in software to guard against performance degradation. This paper proposes a hardware/software design of MPLS on an FPGA for increased performance and efficiency. Greatest emphasis is placed on the hardware components. |
13,317 | Please write an abstract with title: Stability analysis of two-dimensional systems by means of finitely constructed bilateral quadratic forms, and key words: Stability analysis, Automatic control, Stochastic systems, Control systems, Stochastic resonance, Noise robustness, Robust control, Linear systems, Filtering, Riccati equations. Abstract: Asymptotic stability of two-dimensional (2-D) systems in the state-space representation is studied. The concept of finitely constructed bilateral quadratic forms is introduced for the set of bilateral sequences of vectors, and the positivity of a bilateral quadratic form is characterized in terms of the solvability of an algebraic Riccati matrix inequality. A Lyapunov-like stability analysis of 2-D systems is conducted by resorting to positivity tests for a sequence of bilateral quadratic forms generated by a recurrence formula. The effectiveness is proved in an illustrative example. |
13,318 | Please write an abstract with title: MEMTONIC: A Neuromorphic Accelerator for Energy Efficient Deep Learning, and key words: Photonics, Training, Machine learning, Backpropagation, Feature extraction, Iron, Acceleration. Abstract: Most deep learning accelerators in the literature focus only on improving the design of inference phase. We propose a novel photonics-based backpropagation accelerator for high performance deep learning training. The proposed MEMTONIC architecture is a first-of-its-kind memristor-integrated photonics-based deep learning architecture for end-to-end training and prediction. We evaluate the architecture using a photonic CAD framework (IPKISS) on deep learning benchmark models including LeNet and VGG-Net. The proposed design achieves at least 35× acceleration in training time, 31× improvement in computational efficiency, and 45× energy savings compared to the state-of-the-art designs, without any loss of accuracy. |
13,319 | Please write an abstract with title: Short term prediction of Ht value using BPNN during LCAP, and key words: Neural networks, Engineering in medicine and biology, Biomedical engineering, Back, Sequences, Data analysis, Patient monitoring, Sampling methods. Abstract: At present the number of patients of ulcerative colitis(UC) has been increasing in Japan. A leukocytapheresis (LCAP) is one of the cure to the patients of UC. LCAP is a kind of blood purification treatments. It is said that the blood pressure is decreased during the blood purification. This takes place according to the change of the water balance in the body. The water balance is expressed as a hematcrit(Ht) value. Prediction of the Ht value during the LCAP is important to prevent patients from decrease in blood pressure. The purpose of this study is to develop a method to predict the Ht value during the LCAP. In this study, a moving-average type back propagation neural network(MANN) is used for analyzing the nonlinear signals. The MANN is one of the suitable methods to analyze biological signals. In this study, Ht values after one minute, three minutes, and five minutes are predicted using BPNN. At first, Ht values are predicted using the various structures of BPNN to obtain precise prediction. |
13,320 | Please write an abstract with title: The convergence of AML, and key words: Convergence, Condition monitoring, Stochastic processes, Lyapunov method, Stability analysis, Predictive models, Information analysis, Technological innovation, Australia. Abstract: In this work it is shown that provided a certain positive real condition is satisfied, the AML recursion for the parameters of a scalar ARMAX time series model converges with probability one without the need of monitoring. Previous proofs of convergence had effectively required that the recursion be monitored. |
13,321 | Please write an abstract with title: A Comparative Evaluation of Power Converter Circuits to Increase the Power Transfer Capability of High Voltage Transmission Lines, and key words: Fault tolerance, Multilevel converters, Power transmission lines, Fault tolerant systems, Capacitors, Frequency conversion, Topology. Abstract: AC transmission lines with lengths greater than 80km cannot be used to their maximum capacity due to limits in voltage drops and transient stability. This inefficient way of using conductors in a transmission line can be overcome if the electrical frequency at which energy is transmitted is reduced. This is why this work focuses on the comparison of the Modular Multilevel Matrix Converter (MMMC) and the Back-to-Back Modular Multilevel Converter (BTB-MMC), topologies that have shown qualities as frequency converters. For comparison, an analytical model of each topology is used to relate design considerations to their operational variables. Among the aspects to be compared are, the requirements of the semiconductors, the required reactive components, operating losses and fault tolerance. Detailed design equations, EMTP simulations, and comparison table are presented. |
13,322 | Please write an abstract with title: Recognition System of Hand Signals of a Police Officer for Automated Driving, and key words: Law enforcement, Cameras, Switches, Skeleton, Roads, Estimation, Automobiles. Abstract: Current road traffic law prescribes that hand signals performed by a police officer has higher priority compared with that of traffic lights. Therefore, in automated driving system of SAE level 3 or higher, the system needs to recognize the instruction from the motion of the police officer. We developed a method to recognize such hand signals from on-vehicle camera, based on deep-learning technique. The skeleton coordinate of the performer is input to a deep learning method, to classify the signal state into Red/Green or Red/Green/Other. From the state and the continuation conditions, the instruction Stop/Go is determined. Our preliminary experiment proved that quite similar short actions are included both in Red and Green, and it is better to separate such actions as “Other”. In the final result, Stop/Go can be appropriately determined, and at the same time, the temporal difference of estimation between switching Stop/Go (Too-early Go and Too-late Stop) was less than 0.43 seconds. |
13,323 | Please write an abstract with title: QWI based on group V inter-diffusion for SOA photonic integration, and key words: Photonic band gap, Conferences, Gain, Photonics. Abstract: Local group V atom inter-diffusion in InGaAsP quantum wells was used for quantum well intermixing (QWI), enabling low-temperature bandgap engineering in selected area. Controllable QWI was confirmed through PL and TEM, leading to highperformance integrated functions of 14 dB gain in SOA and 20 nm/V QCSE. |
13,324 | Please write an abstract with title: The Research on Navigation Technology of Dead Reckoning Based on UWB Localization, and key words: Dead reckoning, Position measurement, Mathematical model, Real-time systems, Coordinate measuring machines, Time measurement. Abstract: Aiming at the problem that the accuracy and stability of indoor positioning navigation can not meet the requirements of engineering, a navigation method based on UWB positioning is designed. First of all, in view of the positioning error of UWB, the TOF algorithm is applied to measure distance, and an algorithm of inner quadrilateral positioning is proposed to improve the positioning accuracy. Secondly, In the aspect of the large deviation of navigation direction, the dead reckoning algorithm based on nine-axis module surveying angle and encoder range are designed, which effectively settle the problem of zero drift and improve the navigation precision. Finally, an integrated navigation algorithm is proposed, it combines the advantages of UWB positioning technology and dead reckoning. This method can improve the performance of positioning navigation effectively. The system can carry out indoor positioning navigation stably, rapidly and accurately through practice. |
13,325 | Please write an abstract with title: A Novel Distributed Task Scheduling Framework for Supporting Vehicular Edge Intelligence, and key words: Processor scheduling, Network topology, Quality of service, Dynamic scheduling, Dispatching, Partitioning algorithms, Resource management. Abstract: In recent years, data-driven intelligent transportation systems (ITS) have developed rapidly and brought various AI-assisted applications to improve traffic efficiency. However, these applications are constrained by their inherent high computing demand and the limitation of vehicular computing power. Vehicular edge computing (VEC) has shown great potential to support these applications by providing computing and storage capacity in close proximity. For facing the heterogeneous nature of in-vehicle applications and the highly dynamic network topology in the Internet-of-Vehicle (IoV) environment, how to achieve efficient scheduling of computational tasks is a critical problem. Accordingly, we design a two-layer distributed online task scheduling framework to maximize the task acceptance ratio (TAR) under various QoS requirements when facing unbalanced task distribution. Briefly, we implement the computation offloading and transmission scheduling policies for the vehicles to optimize the onboard computational task scheduling. Meanwhile, in the edge computing layer, a new distributed task dispatching policy is developed to maximize the utilization of system computing power and minimize the data transmission delay caused by vehicle motion. Through single-vehicle and multi-vehicle simulations, we evaluate the performance of our framework, and the experimental results show that our method outperforms the state-of-the-art algorithms. Moreover, we conduct ablation experiments to validate the effectiveness of our core algorithms. |
13,326 | Please write an abstract with title: Sentiment analysis of healthcare Tweets using SVM Classifier, and key words: Support vector machines, Sentiment analysis, Social networking (online), Blogs, Medical services, Extremities, Diseases. Abstract: Web-based social media offers countless opportunities to have their valuable suggestions for experiences. Twitter can be used effectively in current circumstances and with open modern developments to collect data as opposed to social relationship data in traditional techniques. Twitter is perhaps the most loyal member's online large frequency advantage that encourages individuals to communicate and collect data. Here we discuss which country/place frequently speaks about specific diseases. We can forecast where the disease's impact will be important. This system handles the problems that occur during the Sentiment Analysis cycle spent; ongoing tweeting are known to be rich sources of data for evaluation extraction and feeling study. The basic aim of this system is to carry out a continuous sentimental review of the tweets removed by twitter. |
13,327 | Please write an abstract with title: Intent imitation using wearable motion capturing system with on-line teaching of task attention, and key words: Education, Humanoid robots, Learning systems, Humans, Artificial intelligence, Intelligent robots, Character generation, Trajectory, Pattern recognition, Emulation. Abstract: In order for humanoids to imitate humans behavior, it is important to extract a needful parameter for target of imitation. Especially in daily-life environment, only simple joint angles are insufficiency because position and posture of hands and remarkable point of target object are needed for intent imitation. In this paper, we describe a development methods of motion capturing system with interactive teaching of task attention, and show its feasibility in daily-life environments. |
13,328 | Please write an abstract with title: Two-dimensional Modeling and Analysis of Lithium-ion Cell for Electric Vehicle Application, and key words: Performance evaluation, Electrodes, Analytical models, Power engineering, Storage management, Electric vehicles, Discharges (electric). Abstract: The process of modelling a device is dependent on the details one intends to derive from the model. In the context of energy storage devices in general and lithium-ion cell in particular; two-dimensional modelling provides meaningful insights into the cell’s electrical observables and their time dependencies. These observables and their time-dependencies are crucial for development of energy storage management systems. The work presented herein, describes graphically, the functional electrical observables of the lithium-ion unit cell, and finally supplies the average state of charge variation with respect to time. In this simulation study, the state of charge manifests nearly 75% increase for the positive electrode during discharge time of forty-five minutes. |
13,329 | Please write an abstract with title: Bm3d Vs 2-Layer Onn, and key words: AWGN, Conferences, Neurons, Computer architecture, Computational efficiency, Convolutional neural networks, Biological neural networks. Abstract: Despite their recent success on image denoising, the need for deep and complex architectures still hinders the practical usage of CNNs. Older but computationally more efficient methods such as BM3D remain a popular choice, especially in resource-constrained scenarios. In this study, we aim to find out whether compact neural networks can learn to produce competitive results as compared to BM3D for AWGN image denoising. To this end, we conFigure networks with only two hidden layers and employ different neuron models and layer widths for comparing the performance with BM3D across different AWGN noise levels. Our results conclusively show that the recently proposed self-organized variant of operational neural networks based on a generative neuron model (Self-ONNs) is not only a better choice as compared to CNNs, but also provide competitive results as compared to BM3D and even significantly surpass it for high noise levels. |
13,330 | Please write an abstract with title: Architecting Analytics Across Multiple E-Learning Systems to Enhance Learning Design, and key words: Predictive models, Electronic learning, Interoperability, Tools, Learning systems, Biological system modeling, Analytical models. Abstract: With the wide expansion of distributed learning environments the way we learn became more diverse than ever. This poses an opportunity to incorporate different data sources of learning traces that can offer broader insights into learner behavior and the intricacies of the learning process. We argue that combining analytics across different e-learning systems can potentially measure the effectiveness of learning designs and maximize learning opportunities in distributed settings. As a step toward this goal, in this study, we considered how to broaden the context of a single learning environment into a learning ecosystem that integrates three separate e-learning systems. We present a cross-platform architecture that captures, integrates, and stores learning-related data from the learning ecosystem. To demonstrate the feasibility and the benefits of cross-platform architecture, we used regression and classification techniques to generate interpretable models with analytics that can be relevant for instructors in understanding learning behavior and sensemaking of the instructional method on learner performance. The results show that combining data across three e-learning systems improve the classification accuracy compared to data from a single learning system by a factor of 5. This article highlights the value of cross-platform learning analytics and presents a springboard for the creation of new cross-system data-driven research practices. |
13,331 | Please write an abstract with title: Fusion of Local and Global Feature Representation With Sparse Autoencoder for Improved Melanoma Classification, and key words: Image resolution, Melanoma, Streaming media, Feature extraction, Skin, Biology, Convolutional neural networks. Abstract: Automated skin cancer diagnosis is challenging due to inter-class uniformity, intra-class variation, and the complex structure of dermoscopy images. Convolutional neural networks (CNN) have recently made considerable progress in melanoma classification, even in the presence of limited skin images. One of the drawbacks of these methods is the loss of image details caused by downsampling high-resolution skin images to a low resolution. Further, most approaches extract features only from the whole skin image. This paper proposes an ensemble feature fusion and sparse autoencoder (SAE) based framework to overcome the above issues and improve melanoma classification performance. The proposed method extracts features from two streams, local and global, using a pre-trained CNN model. The local stream extracts features from image patches, while the global stream derives features from the whole skin image, preserving both local and global representation. The features are then fused, and an SAE framework is subsequently designed to enrich the feature representation further. The proposed method is validated on ISIC 2016 dataset and the experimental results indicate the superiority of the proposed approach. |
13,332 | Please write an abstract with title: Rate two full-diversity space-frequency code design for MIMO-OFDM, and key words: Receiving antennas, Transmitting antennas, OFDM, Broadband antennas, Fading, Diversity reception, Sufficient conditions, Antennas and propagation, Data communication, Channel capacity. Abstract: In this paper we propose a high-rate full-diversity space-frequency code (SFC) for MIMO-OFDM system over multipath fading channels. The proposed SFC can achieve full-diversity with a transmission rate up to 2 symbols per channel use (pen) for two transmit antennas. The theoretical claims are confirmed by simulations and the performance compared with existing SFC. |
13,333 | Please write an abstract with title: Assessing the Needs of the Quantum Industry, and key words: Companies, Industries, Quantum computing, Education, Stakeholders, Quantum information science, Investment. Abstract: Background: Quantum information science and technology (QIST) has progressed significantly in the last decade, such that it is no longer solely in the domain of research labs, but is now beginning to be developed for, and applied in, industrial applications and products. With the emergence of this new quantum industry, a new workforce trained in QIST skills and knowledge is needed. Research Questions: To help support the education and training of this workforce, universities and colleges require knowledge of the type of jobs available for their students and what skills and degrees are most relevant for those new jobs. What are these jobs, skills, and degrees? Methodology: We report on the results from a survey of 57 companies in the quantum industry, with the goal of elucidating the jobs, skills, and degrees that are relevant for this new workforce. Findings: We find a range of job opportunities from highly specific jobs, such as quantum algorithm developer and error correction scientist, to broader jobs categories within the business, software, and hardware sectors. These broader jobs require a range of skills, most of which are not quantum related. Furthermore, except for the highly specific jobs, companies that responded to the survey are looking for a range of degree levels to fill these new positions, from bachelors to masters to Ph.D.s. Contribution: With this knowledge, students, instructors, and university administrators can make informed decisions about how to address the challenge of increasing the future quantum workforce. |
13,334 | Please write an abstract with title: Influence of ischemic and infarcted tissue on the surface potential, and key words: Conductivity, Conducting materials, Myocardium, Automata, Heart rate, Electrocardiography, Ischemic pain, Anisotropic magnetoresistance, Conductors, Biomedical signal processing. Abstract: The influence of ischemic and infarcted tissue on the body-surface potential was investigated. A cellular automaton was employed for modeling the heart's specialized conduction system, junction points, action potentials, and fiber orientation. The cellular automaton generated a transmembrane potential distribution providing the source distribution for the electrocardiographic forward problem. The body-surface potential was calculated with a bidomain-based forward model of a patient's volume conductor. Several scenarios were simulated including anterior and posterior myocardial infarction. The simulations demonstrated the influence on the body-surface potential displaying ST elevations and depressions as well as changes in polarity depending on the location of the ischemic region and electrode position. |
13,335 | Please write an abstract with title: Distilling a crowded spectrum: the overlap of terahertz protein collective vibrations with functional motions, and key words: Proteins, Vibrations, Frequency dependence, Absorption, Sociology, Statistics. Abstract: We use massive averaging over the thermally populated energy landscape to calculate a realistic terahertz vibrational density of states (VDOS), isotropic absorption and anisotropic absorption for the protein chicken egg white lysozyme (CEWL). We find that the VDOS shows little variation with starting structure, however both the isotropic and anisotropic absorption vary considerably with starting structure. Averaging over the population leads to a smooth featureless average isotropic spectrum, in agreement with THz absorption measurements however resonant bands emerge for the anisotropic averaging. Further we find the vibrational ensemble in fact has frequency dependent features associated with large overlap with functional displacements. |
13,336 | Please write an abstract with title: EEG Classification for MI-BCI using CSP with Averaging Covariance Matrices: An Experimental Study, and key words: Covariance matrices, Electroencephalography, Geometry, Symmetric matrices, Brain-computer interfaces, Mathematical model, Feature extraction. Abstract: To assist disabled people by controlling an external system by using motor imagery (MI) is a common applications of brain computer interface (BCI) field. This paper we focused on an experimental comparison of covariance matrix averaging ways of EEG signal and EEG classification of two types of MI tasks (right-hand*foot and right-hand *left hand). Indeed averaging covariance matrices of EEG signal might be a used in brain computer interfaces (BCI) with common spatial pattern (CSP) method. Structured into trials is a usually paradigms of BCI which we have a tendency to use this structure into account. In addition, covariance matrices with non-Euclidean structure should be consideration likewise. We review much method for averaging covariance matrices in SVM from literature and observe through the experimented result using publicly available four datasets. Our experimental result show that for the case of averaging covariance matrices using Riemannian geometry with small dimension feature issue improve the classification performance. Our result shows the performance increase (2% >performance), but also the limit of this method once the increase feature dimension. |
13,337 | Please write an abstract with title: Space-time decoding with imperfect channel estimation, and key words: Channel estimation, Receiving antennas, Maximum likelihood estimation, Frequency estimation, Space time codes, MIMO, Maximum likelihood decoding, Fading, Energy measurement, Time measurement. Abstract: Under the assumption of a frequency-flat slow Rayleigh fading channel with multiple transmit and receive antennas, we examine the effects on system performance of imperfect estimation of the channel parameters when the receiver either assumes that the estimate is perfect or uses a proper maximum-likelihood decision metric. An algorithm for the recursive calculation of the maximum-likelihood decision metric is developed for application to trellis space-time codes. |
13,338 | Please write an abstract with title: Dynamic programming for LR-PCR segmentation of bacterium genomes, and key words: Dynamic programming, Genomics, Bioinformatics, Capacitive sensors, Sequences, Heuristic algorithms, Polymers, Performance analysis, Testing, Microorganisms. Abstract: Summary form only given. Bacterium genome plasticity can efficiently be studied by long-range PCR: genomes of different strains are split into hundreds of short segments which, after LR-PCR amplification, are used to sketch profiles. The segments have : (1) to cover the entire genome, (2) to overlap each other, and (3) to be of nearly identical size. We address the problem of finding a list of segments satisfying these constraints "as much as possible". Two algorithms based on dynamic programming approach are presented. They differ on the optimization criteria for measuring the quality of the covering. The first one considers the maximal deviation of the segment lengths relatively to an ideal length. The second one automatically finds a segment length which minimizes the maximal deviation. |
13,339 | Please write an abstract with title: The Optimal Control of an HIV/AIDS Reaction-Diffusion Epidemic Model, and key words: Asymptotic stability, Epidemics, Sociology, Optimal control, Size measurement, Stability analysis, Human immunodeficiency virus. Abstract: In this article, we consider the HIV AIDS system proposed by K.O. Okosun [4]. We study the local and global asymptotic stability of the model’s equilibria in the presence of a diffusion term. An optimal controller is presented that considers the use of three different measures to combat the spread of HIV/AIDS, namely: the use of condoms and the screening and treatment of unaware infective individuals. The objective of the optimal controller is to minimize the size of the susceptible and infected populations. The study starts with an investigation of the existence and uniqueness of solutions. Then, we establish estimates of the controlled system’s positive strong solution by means of the semigroup theory of operators, and make use of minimal sequence techniques to show the existence of an optimal control. In doing so, we establish the necessary optimality conditions of the developed scheme. |
13,340 | Please write an abstract with title: Load-Aware Energy Efficient Adaptive Large Scale Antenna System, and key words: OFDM, Precoding, Quality of service, Optimization, Transmitting antennas, Antenna arrays. Abstract: This paper proposes an adaptive large scale antenna system (ALSAS) for enhancing energy efficiency in low density wireless network scenarios. The proposed ALSAS comprises of two stages, a novel adaptive discontinuous transmission (ADTx) stage and an antenna array optimization (AAO) one. The basic idea is to utilize prior knowledge of the users' quality of service (QoS) requirements as well as precoding selection in the ADTx stage to maximize the transmitter hibernation periods subject to a certain complexity constraint. In the AAO stage, further power saving is achieved by reducing the number of active antenna elements subject to a certain QoS requirement. It is shown that, relative to conventional large scale antenna system (LSAS), the proposed ALSAS system achieves significant energy efficiency improvements under various scenarios. The results show that the proposed technique can provide energy efficiency improvement between 125% and 1124% in the suburban scenario, and between 196% and 952% in the rural scenario. It is also demonstrated that for rural environments with relatively small short inter-site-distance (ISD) values, ALSAS can provide up to 500% power saving for the fixed bit rate requirement case. |
13,341 | Please write an abstract with title: Linear matrix inequalities for robust strictly positive real design, and key words: Linear matrix inequalities, Robustness, Polynomials, Uncertainty, Sufficient conditions, Transfer functions, Control systems, Uncertain systems, Algorithm design and analysis, Asymptotic stability. Abstract: A necessary and sufficient condition is proposed for the existence of a polynomial p(s) such that the rational function p(s)/q(s) is robustly strictly positive real when q(s) is a given Hurwitz polynomial with polytopic uncertainty. It turns out that the whole set of candidates p(s) is a convex subset of the cone of positive semidefinite matrices, resulting in a straightforward strictly positive real design algorithm based on linear matrix inequalities. |
13,342 | Please write an abstract with title: New CRT-based RNS converter using restricted moduli set, and key words: Residue arithmetic. Abstract: This paper presents a new RNS converter using any number of relatively prime moduli of the form 2/sup n/ and 2/sup n/ /spl plusmn/ 1. With the exception of common 3 moduli sets such as {2/sup n/ - 1,2/sup n/, 2/sup n/ + 1}, FINS output converters based on the CRT require the computation of a sum of products modulo a large number. The new converter presented in this paper uses the fractional representation for the output and eliminates the requirement for multiplications, thereby reducing area and delay. Further area improvements are possible by exploiting the period of terms to be added. An algorithmic approach is used to obtain full adder-based architectures that are optimized for area and delay. |
13,343 | Please write an abstract with title: RDF triple processing methodology for the recommendation system using personal information, and key words: Resource description framework, Semantic Web, Information filtering, Information filters, Demography, Ontologies, Collaborative work, Information analysis, Web services, Computer science. Abstract: In this paper, we design and implement the personalized recommend system that provides more semantic information to users using the RDF triples and personal information. The system consists of the data storage, information search module, document collection module, data merge module and recommend module. These new modules are different from the existing modules that have been using in the current Web. These new modules are suitable for the semantic Web environment. Especially, in this paper, we focus on the RDF that is one of the ontology languages. And all modules are newly designed for processing the RDF triple. Finally, we have the test to give the necessity of our study in the virtual semantic Web environment. |
13,344 | Please write an abstract with title: Learning-Based Distributionally Robust Model Predictive Control of Markovian Switching Systems with Guaranteed Stability and Recursive Feasibility, and key words: Markov processes, Switching systems, Switches, Kernel, Closed loop systems, Stability criteria, Probability distribution. Abstract: We present a data-driven model predictive control scheme for chance-constrained Markovian switching systems with unknown switching probabilities. Using samples of the underlying Markov chain, ambiguity sets of transition probabilities are estimated which include the true conditional probability distributions with high probability. These sets are updated online and used to formulate a time-varying, risk-averse optimal control problem. We prove recursive feasibility of the resulting MPC scheme and show that the original chance constraints remain satisfied at every time step. Furthermore, we show that under sufficient decrease of the confidence levels, the resulting MPC scheme renders the closed-loop system mean-square stable with respect to the true-but-unknown distributions, while remaining less conservative than a fully robust approach. |
13,345 | Please write an abstract with title: Electronic News Sentiment Analysis Application to New Normal Policy During The Covid-19 Pandemic Using Fasttext And Machine Learning, and key words: Support vector machines, COVID-19, Analytical models, Adaptation models, Pandemics, Social networking (online), Feature extraction. Abstract: The new phase in handling COVID-19 in Indonesia, called New Normal, gives various public perspectives regarding this policy. This study aims to analyze public sentiment towards the New Normal policy through an electronic news comment column. This study uses text data in the form of comments were collected from electronic news media sites, namely www.detik.com and www.kompas.com, and taken from the comments column on Instagram social media, namely the @detikcom account. Also, use FastText method to extract features by converting data into vector values and using three classification methods, Naive Bayes (NB), Support Vector Machine (SVM), and Multilayer Perceptron (MLP). This study conducted a hyperparameter test to obtain the most optimal model. Testing the hyperparameters from FastText produces an optimal model with dimensions of 250, window size 8, epoch 1.000, and a learning rate of 0,0025. Hyperparameter testing was also carried out on the SVM and MLP classifiers. Hyperparameter testing of the SVM and MLP classifiers produces the most optimal model with the SVM method using the RBF kernel, C of 1.000, gamma of 10. In contrast, the MLP method uses the relu activation function, hidden size layer (250,250), adam optimizer, alpha 0,0001, and adaptive learning rate. The classification model was evaluated using K-fold cross-validation to produce an average f1score. The result is for the NB method 72,25% f1score, for the SVM method 92,21% f1score, and for the MLP method 90,75% f1score. |
13,346 | Please write an abstract with title: Design and Experimental Validation of A SU-8 Based Micro-Psychrometer, and key words: Humidity measurement, Microchannel, Monitoring, Voltage, Glass, Psychology, Delay, Measurement standards, Measurement units, Prototypes. Abstract: In this paper, a new approach to design micro-psychrometers devoted to measuring relative humidity is presented. Such devices are based on a planar thermopile fitted with an appropriate set of microchannels arranged for monitoring the evaporation process as a Seebeck voltage. They are fabricated out of a glass substrate, sputtered metals, and near vertical side walls made of SU-8, according to standard micro technology processes for MEMs. Considering classical psychrometers, the new design is aimed at reducing both size and response time. Indeed, besides being far less invasive than a standard unit, fast measurements (tau=5 s) are enabled. A straightforward modeling, aimed at deriving the relative humidity, is given with a view to integrating the signal conditioner. A prototype is calibrated and compared to a reference probe, and a brief discussion on its enhancement is also presented |
13,347 | Please write an abstract with title: When Hammerstein Meets Wiener: Nonlinearity Modeling for End-to-End Visible Light Communication Links, and key words: Visible light communication, Linear systems, Light emitting diodes, Broadband communication, Nonlinear distortion, Solid modeling, Optical distortion. Abstract: Visible light communication (VLC) emerges as a promising technology for the explosively growing wireless services and demands. However, the system performance is severely impaired by the inherent nonlinearity of the VLC channel. In existing studies, the Hammerstein and Wiener models are widely used and often assumed for VLC channels due to the simple structure and low complexity. Yet, their effectiveness remains unclear and controversial. This work aims to figure out which one between the Hammerstein and Wiener models is more suitable for characterizing the VLC channel. We first design a single-tone test for qualitative analysis and further conduct an experiment based on multi-level pseudorandom sequences for quantitative evaluation. From the two well-designed experiments, we obtain a consistent conclusion that the Hammerstein model is more proper for describing the VLC nonlinearity and also more effective for post-distortion in VLC systems. |
13,348 | Please write an abstract with title: Resonant Frequencies of the Axial Symmetric Modes in a Dielectric Resonator, and key words: Resonant frequency, Temperature, Dielectric materials, Reflection, Microwave theory and techniques, Microwave circuits, Circuit analysis, Mode matching methods, Eigenvalues and eigenfunctions, Scattering. Abstract: Dielectric resonators have been proven possible for a long time. However, they had not been popular in the past due to the absence of temperature stable and low loss materials. The recent advent of low loss, temperature stable materials has made them useful in a number of microwave circuit applications, The analysis of such a resonator in the past has relied on approximate methods. We shall present a rigorous field analysis of the circular dielectric resonator embedded in an in homogeneous medium. The analysis is via a numerical mode matching method, whereby the problem of finding the modes of the circular dielectric cylinder is cast into a conventional eigenvalue problem which could be solved rapidly on the computer. This method bypasses the need to use Hankel and Bessel functions, which could be time consuming to evaluate. The scattering of the field off the ends of the resonator are characterized by reflection operators. The resonant frequencies of the resonator could be easily found by requiring the phase coherence of the wave after reflection off the two ends of the resonator. |
13,349 | Please write an abstract with title: Window effect on wall penetration loss in mobile communications, and key words: Mobile communication, Transmitting antennas, Directive antennas, Electromagnetic modeling, Windows, Antenna measurements, Size measurement, Context, Ray tracing, Signal analysis. Abstract: In mobile communication scenarios, a window opening on a wall enhances the field strength inside the room, as compared to a whole wall. Scarce models in the literature address this topic, or objectively quantify this effect relating it to window dimensions - this is the objective of the present paper. Wall and window are treated as an antenna aperture with the appropriate field distribution, which re-radiates its near field into the room. Measurements on a scaled model of a wall with different window sizes show good agreement with simulations. Based on simulation results, a statistical model is constructed to enable fast quantification of the window effect through a "window gain" parameter. |
13,350 | Please write an abstract with title: Predicting World Energy Consumption: Comparison of ANN and Regression Analysis, and key words: Energy consumption, Artificial neural networks, Regression analysis, Neurons, Economic indicators, Sociology. Abstract: World energy consumption is responsible for the growth of the economy. Having it in abundant will do more to the continuous global growth. Fundamental factors to how energy is consumed are population and gross domestic product (GDP). This study focusses on predicting the global energy consumption from 1995 to 2009 using the fundamental factors as inputs. Statistical and evolutionary algorithm in the form of regression analysis and artificial neural network (ANN) were compared in their prediction performance. Both techniques performed brilliantly as indicated by the coefficient of correlation and visual inspection, however, ANN performed better. Analyzing the factors through the connection weights of ANN reported population to be the significant factor contributing more to how energy is consumed globally. It is important to have policies that can influence population positively in order to have abundant supply of energy whenever there is demand for it. |
13,351 | Please write an abstract with title: PD Control for Passivity of Coupled Reaction-Diffusion Neural Networks with Multiple State Couplings, and key words: Couplings, Neural networks, Numerical models, PD control, Synchronization. Abstract: This paper studies the passivity for coupled reaction-diffusion neural networks with multiple state couplings (CRDNN-MSCs) by employing the proportional-derivative (PD) control method. Firstly, a PD control strategy is presented for the sake of ensuring the passivity of CRDNNMSCs. In addition, a synchronization condition is also given by utilizing the output-strict passivity of CRDNNMSCs. Lastly, the correctness of the obtained passivity and synchronization criteria for the proposed model is verified by a numerical example. |
13,352 | Please write an abstract with title: Towards Cost-Effective and Lightweight Doppler Radars: Papercraft-Based Components and Comparisons with Aluminum and 3D Printed Alternatives, and key words: radar, antenna, coating, additive manufacturing, papercraft. Abstract: Doppler radar systems have an essential role in various applications, including aviation, weather forecasting, and military surveillance. However, their high fabrication costs and heavy weight may limit their utilization in rapid prototyping, small-scale applications, and seamless transportation. To address these challenges, a novel papercraft-based approach for producing the entire Doppler radar system’s horn antenna, hybrid tee, and short termination components in the X-band was investigated with details in this study, alongside conventional aluminum and 3D printing methods. This paper presents the first attempt to develop a Doppler radar using papercraft-based manufacturing. The papercraft-based approach is cost-effective, lightweight, flexible, and readily available, offering a promising route for improving and fabricating Doppler radar systems that are both affordable and accessible, particularly in resource-limited settings. The experimental results show that the papercraft-based components can perform comparably to conventional aluminum-based and 3D-printed components, making it an innovative and cost-effective solution for fabricating Doppler radar systems. |
13,353 | Please write an abstract with title: Pareto depth sampling distributions for gene ranking, and key words: Sampling methods, Retina, Probes, Mice, Aging, Humans, Stability, Image sampling, Filtering, Pareto optimization. Abstract: In this paper we propose a method for gene ranking from microarray experiments using multiple discriminants. The novelty of our approach is that a gene's relative rank is determined according to the ordinal theory of multiple objective optimization. Furthermore, the distribution of each gene's rank, called Pareto depth, is determined by resampling over the microarray replicates. This distribution is called the Pareto depth sampling distribution (PDSD) and it is used to assess the stability of each ranking. Graphical representation of the PDSD as an image communicates information about the stability of each gene's rank. We illustrate on data from a mouse retina microarray experiment. |
13,354 | Please write an abstract with title: Efficient design of system test: a layered architecture, and key words: System testing, Unified modeling language, Embedded system, Automotive applications, International collaboration, Magnetic materials, Computer architecture, Embedded software, Research and development, Design methodology. Abstract: Starting from the idea of a general methodology to transform design specifications into system level functional test patterns for complex embedded systems, we propose a layered architecture as basis of such process. The architecture aims at strongly simplifying the test design, allowing the test engineer to concentrate on the high level parts of the system and wrapping all the complexity of the test environment. The results are then verified on a complex case study of automotive applications. |
13,355 | Please write an abstract with title: Improving Post-Processing of Audio Event Detectors Using Reinforcement Learning, and key words: Filtering, Detectors, Labeling, Event detection, Reinforcement learning, Smoothing methods, Audio systems, Event detection. Abstract: We apply post-processing to the class probability distribution outputs of audio event classification models and employ reinforcement learning to jointly discover the optimal parameters for various stages of a post-processing stack, such as the classification thresholds and the kernel sizes of median filtering algorithms used to smooth out model predictions. To achieve this we define a reinforcement learning environment where: 1) a state is the class probability distribution provided by the model for a given audio sample, 2) an action is the choice of a candidate optimal value for each parameter of the post-processing stack, 3) the reward is based on the classification accuracy metric we aim to optimize, which is the audio event-based macro F1-score in our case. We apply our post-processing to the class probability distribution outputs of two audio event classification models submitted to the DCASE Task4 2020 challenge. We find that by using reinforcement learning to discover the optimal per-class parameters for the post-processing stack that is applied to the outputs of audio event classification models, we can improve the audio event-based macro F1-score (the main metric used in the DCASE challenge to compare audio event classification accuracy) by 4-5% compared to using the same post-processing stack with manually tuned parameters. |
13,356 | Please write an abstract with title: Changes in walking strategies after spaceflight, and key words: Legged locomotion, Head, Earth, Control systems, Jacobian matrices, Motion analysis, Frequency domain analysis, Pediatrics, Stability, Retina. Abstract: Over the last several years, our laboratory has investigated postflight astronaut locomotion with the aim of better understanding how adaptive changes in underlying sensorimotor mechanisms contribute to postflight gait dysfunction. One of the first questions we asked focused on the effects of spaceflight on head movement control during postflight locomotion. We hypothesized that adaptive modification in multiple sensorimotor systems caused by exposure to the microgravity conditions of spaceflight would lead to disruption in head-trunk coordination during postflight walking. These changes in head-trunk coordination strategies would then disrupt gaze control and alter the organization of terrestrial locomotor control strategies. The data presented indicate that some behavior observed after spaceflight may represent an adaptive reorganization of motor responses targeted at restoring functional mobility but in a novel way that is not observed or required during preflight walking. This observation has implications for the interpretation of all tests of postflight sensorimotor function. |
13,357 | Please write an abstract with title: Thermomechanical Analysis on Stress Mitigation of FCPBGA with Low Melting Temperature Solder and Low Elastic Modulus Cu Pillar, and key words: Thermal expansion, Temperature, Thermomechanical processes, Joining materials, Silicon, Dielectrics, Reliability. Abstract: Increasing thermomechanical stress in complex and large flip-chip packages is a critical issue in maintaining mechanical integrity and reliability of the packages. Effects of varying mechanical properties of joining materials and organic substrate on stress mitigation in low-k dielectric layer under Cu pillar bump were studied using thermomechanical analysis. Lowering coefficient of thermal expansion (CTE) of organic substrate and lowering melting temperature of solder contribute to significant stress reduction. The effect of Cu pillar’s elastic modulus becomes relevant when its value is greatly reduced. |
13,358 | Please write an abstract with title: Imaging of buried objects by low frequency SAS, and key words: Buried object detection, Frequency, Synthetic aperture sonar, Sonar detection, Signal resolution, Chirp modulation, Wideband, Object detection, Azimuth, Signal processing. Abstract: Search for buried objects are normally done by normal incidence sonar, working with wide-band low frequency signals. Especially the parametric sonar has proven to be a reliable tool to detect buried objects, as well as for mapping of internal stratification in sub-bottom layers. However, due to the small foot-print searching with normal incidence sonar is tedious. Also, in a mine hunting situation, the platform has to pass over the mine, which of course is undesirable. Forward looking and side-scan sonar have the capability to detect and classify objects at some distance from the platform. Their azimuth resolution is dependent on aperture length compared to the wavelength. A long aperture gives better resolution than a short. For proud or floating targets it is always possible to increase resolution by increasing frequency although that would decreases the possible operating range. To find buried objects the frequency has to be low for the sound to penetrate into the bottom. Synthetic Aperture Sonar (SAS) is a signal processing method designed to increase the resolution without changing the frequency. The physical aperture is moved and data from several positions are used for synthesizing a longer synthetic aperture. The long wavelengths used for buried targets means that the aperture has to be increased even more to achieve good resolution. Obviously SAS is even more useful for bottom penetrating sonar than the extensively reported purpose of imaging objects lying on the seafloor. We have developed a side-scan sonar using SAS processing to image buried objects. The sonar has been tested at our pontoon laboratory, which has been equipped with a 16 m long rail for SAS related research. Objects of various types have been placed both on the bottom and in the sediment. A 20 - 30 kHz frequency modulated signal was transmitted from a small transducer and echoes were received by a 1.5 m horizontal linear array. SAS images of both proud and buried targets will be shown indicating that SAS is an obvious choice for future mine-hunting sonar, both penetrating and none penetrating. |
13,359 | Please write an abstract with title: Luminance weighted color constancy, and key words: Integrated circuit technology, Image color analysis, Brightness, Lighting, Prediction algorithms, Image restoration, Light sources. Abstract: Color constancy is widely used in the field of image processing. It can restore the color of the object itself from color deviation image. At present, color constancy methods based on statistics mainly focus on part of the image information such as brightness information. In order to better reflect the illumination from the aspect of brightness, this paper proposes a novel color constancy algorithm based on luminance weighting, and discusses the influence of different luminance block sizes on light source prediction. The experiments demonstrate that the proposed color constancy algorithm decrease by 10.17%, 4.79% and 7.66% in mean, median and trimean angular errors compared with the optimal algorithm. |
13,360 | Please write an abstract with title: Summarization and Prioritization of Amazon Reviews based on multi-level credibility attributes, and key words: Medical services. Abstract: It is common for most people to check Amazon reviews of competing products before a purchase decision. However, the ratings and reviews could be from a customer who has not actually purchased the product on Amazon. There is also a chance that the reviews are doctored by paid reviewers either to enhance a particular product's appeal or lower that of a competitor's product. So, the ratings and reviews do not always reflect the reality. We provide a mechanism to eliminate un-authenticated reviews prioritizing them based on their credibility score and summarize both positive and negative keywords. In this paper, we present a methodology to eliminate un-authenticated reviews based on three levels of pruning. The final rating of the review is adjusted using helpfulness ratio of the review, how old the review is and the helpfulness and experience of the reviewer. We also summarize the positive and negative keywords using ‘term frequency-inverse document frequency’ and ‘Long Short-Term Memory networks’. The reviews are prioritized the based on their credibility score. We were able to summarize and prioritize the reviews for easy analysis by the user. We also did an empirical validation of our proposed solution and found that the overall helpfulness factors improved. |
13,361 | Please write an abstract with title: Cross-Layer Multi-Attention Guided Spectral-Spatial Classification of Hyperspectral Images, and key words: Deep learning, Convolutional codes, Cross layer design, Fuses, Geoscience and remote sensing, Feature extraction, Convolutional neural networks. Abstract: Deep learning based methods are very popular for hyperspectral image classification. However, those methods usually ignore the fact that discriminative information lies on specific spatial positions and spectral bands. To solve this problem, we introduce the attention mechanism, and propose a cross-layer multi-attention guided classification network (CLMA-Net) for HSIs. First, a backbone network, which is a two-branch convolutional neural network, is developed to extract spectral and spatial features. Then, cross-layer multi-attention modules, which integrate attention information of multiple convolutional layers, are embedded into two branches. As a result, spectral and spatial features are optimized by making the network attend to interested parts. Finally, spectral and spatial features are concatenated and used to predict class label by a fully connected layer. Experimental results demonstrate the effectiveness of the proposed method. The code will be available at https://github.com/mengkai-liu/CLMA-Net. |
13,362 | Please write an abstract with title: Optical Neural Networks of Handwriting Recognition Using Optical Scattering Unit System, and key words: Handwriting recognition, Optical interconnections, Optical computing, Optical network units, Optical scattering, Nonlinear optics, Photonics. Abstract: We simplify the classic convolutional neural network (CNN) of handwriting recognition - LetNet-5, and achieve classification based on the dataset MNIST by using an interconnected system of inverse-designed optical scattering units. © 2020 The Author(s) |
13,363 | Please write an abstract with title: Efficient Mobile Computation Offloading over a Finite-State Markovian Channel using Spectral State Aggregation, and key words: Wireless communication, Degradation, Heuristic algorithms, Computational modeling, Markov processes, Mobile handsets, Computer networks. Abstract: This paper considers the problem of mobile computation offloading under stochastic wireless channels while task completion times are subject to deadline constraints. Our objective is to conserve energy for the mobile device by making an optimal decision to execute the task either locally or remotely. In the case of computation offloading, we dynamically vary the data transmission rate, in response to channel conditions. The wireless transmission channel is modelled using a Finite-State Markov Chain (FSMC). We formulate the problem of computation offloading as a constrained optimization problem, and develop an online algorithm to derive the optimal offloading policy. Moreover, to reduce the complexity, we estimate a suboptimal solution of the proposed online algorithm by reducing the size of the FSMC with the help of Markovian aggregation. The numerical results indicate that by applying Markovian aggregation, the running time of the algorithm can be significantly reduced without suffering unreasonable performance degradation. |
13,364 | Please write an abstract with title: Modeling and Analysis of a Magnetic Geared Linear Motor, and key words: Poisson equations, Atmospheric modeling, Force, Windings, Predictive models, Mathematical models, Power electronics. Abstract: A special magnetic geared tubular linear mo-tor which combines a tubular magnetic gear and a tubular linear motor for direct-drive applications is presented in this paper. The structure and operating principle of the machine are introduced, then magnetic flux distribution of the gear and thrust force generated by winding coils are simulated by using 2-D modeling. Finite-element calculation is used to confirm the accurate of results. |
13,365 | Please write an abstract with title: Intelligent Text Clustering Based on Semantics Similarity, and key words: Vocabulary, Social networking (online), Semantics, Clustering algorithms, Tools, Ontologies, Text processing. Abstract: Clustering text documents have become an increasingly important problem in recent years due to the availability of a huge amount of unstructured data in various forms, such as the web, social networks, and other information networks. It aims to organise and classify large document groups into smaller groups of meaning. This process is crucial because it is challenging to deal with a large amount and an increasing number of digital data. The documents are organised and classified to facilitate faster information retrieval (IR) and try to extract information with semantic knowledge. The process above enables the retrieve information, browsed and understood instead of clustering texts in the traditional way, i.e. compilation of data without descriptive concepts. As textual data has become a diverse set of vocabulary hence, there is an urgent need for text aggregation techniques based on semantic similarity is the primary solution to this problem as it is grouped into groups according to meaning rather than keywords. Several Papers that are using semantic similarity in various scopes. It has been reviewed in this research; some of them which are using similarity based on semantic using document cluster. For developing an effective and efficient clustering methodology to take care of the semantic structure of the text documents, and a compare of between them is presented according to (algorithms, tools, and assessment methods). Finally, extensive study and comparison of work are presented. |
13,366 | Please write an abstract with title: Segment-wise Level Generation using Iterative Constrained Extension, and key words: video games, procedural content generation, constraints. Abstract: Generating game levels via constraint satisfaction can become slow as levels grow large. In this work, we explore constraint-based generation of large levels by iteratively extending smaller intermediate levels. In each iteration, a new segment is created by generating a new, larger, intermediate level. The tiles and solution path at the beginning of the new intermediate level are constrained to match the previous intermediate level. We evaluated our approach using three games and two low-level solvers. We found that generating a level using more segments improves performance up to a point, and then decreases performance. We also saw a slight but noticeable decrease in the tile-based differences between levels generated as the number of segments increases, and saw that later segments usually took more time to generate than earlier segments. |
13,367 | Please write an abstract with title: Fine-Grain Numerical Computations in Dynamic SMP Clusters with Communication on the Fly, and key words: Network-on-a-chip, Communication switching, Computer science, Information technology, Electronic mail, Computer architecture, Scalability, System-on-a-chip, Concurrent computing, Matrix decomposition. Abstract: This paper presents a new version of the dynamic SMP cluster -based architecture oriented towards networks on chip implementation technique. Smaller sub-networks with many dynamic SMP clusters and communication on the fly are connected by a central global network. Processors are provided with multi-ported data caches that enable parallel data transactions with memory modules, including parallel data pre-fetching and communication on the fly. Simulation experiments are described, based on a graph program representation and an automatic graph evaluator. They show efficiency of the proposed solution for very fine grain numerical problems. |
13,368 | Please write an abstract with title: CreaMe: human augmentation platform for the creation of training in educational lakes inherent to dangerous situations, and key words: Training, Productivity, Industries, Conferences, Virtual environments, Tools, Lakes. Abstract: Human Augmentation is a field of science that seeks to improve human capabilities and productivity through the application of technologies. The prevention of occupational risks is one of the areas where such technologies may make a valuable contribution. In this paper, we introduce CreaMe, a platform with the ability to create immersive virtual experiences. The objective is to create training content quickly and at a low cost by employing human augmentation technologies to transfer theoretical principles into real work. Data from the pilot experience are also presented. We collected over 280 minutes of virtual experiences by using CreaMe in 3 different training lessons. Following the pilot experience, we analysed variables on the evolution of knowledge about occupational risks, improvement of general user knowledge, user satisfaction with the new virtual experience, and the user's ability to use the virtual environment. We can point out that 83.18% of users successfully completed tasks, and 92.13% of users rated post-experience satisfaction very positively. Also, CreaMe was deemed a tool that can contribute to the prevention of occupational risks and, therefore, to workers' wellbeing, health, and productivity in any industry. The development of CreaMe will also allow for the application of human augmentation in the prevention of occupational risks from any work that may pose a hazard to the worker. |
13,369 | Please write an abstract with title: Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks, and key words: Convolutional codes, Visualization, Image coding, Annealing, Vector quantization, Neural networks, Rate-distortion. Abstract: Compressing large neural networks is an important step for their deployment in resource-constrained computational platforms. In this context, vector quantization is an appealing framework that expresses multiple parameters using a single code, and has recently achieved state-of-the-art network compression on a range of core vision and natural language processing tasks. Key to the success of vector quantization is deciding which parameter groups should be compressed together. Previous work has relied on heuristics that group the spatial dimension of individual convolutional filters, but a general solution remains unaddressed. This is desirable for pointwise convolutions (which dominate modern architectures), linear layers (which have no notion of spatial dimension), and convolutions (when more than one filter is compressed to the same codeword). In this paper we make the observation that the weights of two adjacent layers can be permuted while expressing the same function. We then establish a connection to rate-distortion theory and search for permutations that result in networks that are easier to compress. Finally, we rely on an annealed quantization algorithm to better compress the network and achieve higher final accuracy. We show results on image classification, object detection, and segmentation, reducing the gap with the uncompressed model by 40 to 70% w.r.t. the current state of the art. All our experiments can be reproduced using the code at https://github.com/uber-research/permute-quantize-finetune. |
13,370 | Please write an abstract with title: A Machine Learning-Based Early Landslide Warning System Using IoT, and key words: Landslides, Analytical models, Wireless sensor networks, Static VAr compensators, Machine learning, Predictive models, Data models. Abstract: Landslides are ubiquitous than any other geological event and can betide anywhere in the world, making its effect on human lives devastating. The development of a predictive model for landslides and their early warning in real-time based on machine learning and IoT techniques is delineated here. A predictive model was trained using data of various geotechnical parameters like soil moisture, shear strength of the soil, severity of the rain, the slope of the terrain, etc. The hardware consists of a set of sensors that obtains the required soil and terrain parameters in real-time. The model was validated using standard validation techniques, obtaining an accuracy of 98% and zero false negatives. This paper discusses the deployment and data acquisition from the geophysical sensors, the algorithms utilized by the predictive model, the communication between the models and the sensor modules. |
13,371 | Please write an abstract with title: Container problem in substring reversal graphs, and key words: Containers, Polynomials, Concurrent computing, Distributed computing, Network topology, Parallel machines, Hypercubes, Fault diagnosis, Routing, Parallel architectures. Abstract: In this paper, we propose an algorithm that solves the container problem in n-substring reversal graphs in polynomial order time of n. Its correctness is proved and estimates of time complexity and sum of path lengths are given. We also report the results of computer experiment conducted to measure the average performance of our algorithm. |
13,372 | Please write an abstract with title: Distributed Observer for General Linear Leader Systems over Periodic Switching Digraphs, and key words: Switches, Observers, Eigenvalues and eigenfunctions, Switched systems, Multi-agent systems, Numerical stability. Abstract: A long-standing assumption on the existence of the distributed observer for a linear leader system over jointly connected switching networks is that none of the eigenvalues of the system matrix of the leader system have positive real parts. In this paper, after establishing a stability result for a class of linear periodic switched systems, we show that a distributed observer for general linear leader systems over jointly connected switching networks exists provided that the switching signal is periodic with its period sufficiently small. As an application of the distributed observer, we solve the cooperative output regulation for linear multi-agent systems with general linear leader systems over periodic jointly connected switching networks. A numerical example is provided to illustrate our design. |
13,373 | Please write an abstract with title: Simulation of negative permittivity and negative permeability by means of evanescent waveguide Modes-theory and experiment, and key words: Permittivity, Permeability, Plasma simulation, Plasma waves, Waveguide theory, Anisotropic magnetoresistance, Plasma measurements, Magnetic analysis, Propagation constant, Dielectrics. Abstract: In this paper, the theoretical foundations of the equivalence between waveguide propagation below cutoff and artificial plasmas are carefully analyzed through the derivation of the propagation constants of normal modes in waveguides filled with anisotropic plasmas. The equivalence between waveguide and dielectric plasma proposed by Marquees et al., which is valid for evanescent TE modes, has a dual counterpart for magnetic plasmas and evanescent TM modes. This new equivalence states that a negative magnetic permeability medium can be simulated by means of TM modes below their cutoff frequencies. The need of an anisotropic filling of the waveguide for the equivalence between plasmas and evanescent modes is also highlighted. To exemplify the applicability of this new equivalence, a structure that implements a double-negative medium has been proposed. Full-wave simulations of the proposed structure and measurements from an experimental setup are presented, both of which corroborate the new equivalence's validity. |
13,374 | Please write an abstract with title: Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis, and key words: Training, Adaptation models, Computer vision, Uncertainty, Computational modeling, Benchmark testing, Data models. Abstract: Synthesizing pseudo samples is currently the most effective way to solve the Generalized Zero Shot Learning (GZSL) problem. Most models achieve competitive performance but still suffer from two problems: (1) Feature confounding, the overall representations confound task-correlated and task-independent features, and existing models disentangle them in a generative way, but they are unreasonable to synthesize reliable pseudo samples with limited samples; (2) Distribution uncertainty, that massive data is needed when existing models synthesize samples from the uncertain distribution, which causes poor performance in limited samples of seen classes. In this paper, we propose a non-generative model to address these problems correspondingly in two modules: (1) Task-correlated feature disentanglement, to exclude the task-correlated features from task-independent ones by adversarial learning of domain adaption towards reasonable synthesis; (2) Controllable pseudo sample synthesis, to synthesize edge-pseudo and center-pseudo samples with certain characteristics towards more diversity generated and intuitive transfer. In addation, to describe the new scene that is the limit seen class samples in the training process, we further formulate a new ZSL task named the ‘Few-shot Seen class and Zero-shot Unseen class learning’ (FSZU). Extensive experiments on four benchmarks verify that the proposed method is competitive in the GZSL and the FSZU tasks. |
13,375 | Please write an abstract with title: Phase synchronization of brain alpha wave in response to temporally alternating color stimuli, and key words: Nonlinear dynamical systems, Oscillators, Scalp, Epilepsy, Couplings, Brain modeling, Spatiotemporal phenomena, Frequency synchronization, Electroencephalography, Humans. Abstract: Response of the alpha wave to flicker stimuli is investigated with temporally alternating red/blue flicker stimuli. Entrainment phenomenon of the alpha wave is enhanced in comparison with that to single-color stimuli; either a quasi-phase-locking or a clear phase reversal is observed over the scalp. The result is useful for considering the underlying mechanism of hyper-synchronization of brain waves such as the photosensitive epilepsy. |
13,376 | Please write an abstract with title: Hyperledger Fabric Performance Characterization and Optimization Using GoLevelDB Benchmark, and key words: Fabrics, Peer-to-peer computing, Benchmark testing, Proposals, Optimization. Abstract: Hyperledger Fabric is an implementation that enables permissioned blockchains, which provide a general blockchain framework with identifiable participants for a variety of business applications. Although many performance issues of Hyperledger Fabric have been alleviated to some extent, its performance is still limited - e.g. 2.2k transactions per second in our experiment that executes two reads and two writes in a transaction. A major performance bottleneck is incurred by accesses to the databases that store the latest key-value pairs in the ledger data, indexes to transactions, and the update history. In this paper, we characterize the performance of database systems used in Hyperledger Fabric to identify optimization opportunities by running a Hyperledger Fabric GoLevelDB (HLF-GLDB) benchmark. We developed HLF-GLDB as a standalone benchmark to simulate database accesses in Hyperledger Fabric. Results of the performance characterization revealed that: (1) the data compression of GoLevelDB is a major performance bottleneck in Hyperledger Fabric, and disabling the compression improved the performance by 54%; (2) the size of a database affects the performance significantly. For example, when the size increased by four times, the performance degraded by 25%; (3) To reduce the database access overhead in chaincode, it is better to combine small values so that they can be represented by a single key. |
13,377 | Please write an abstract with title: Discussion of "Measurement of /spl lambda/-i characteristics of asymmetric three-phase transformers and their applications", and key words: Phase transformers, Reactive power, Transformer cores, Power generation, Power engineering and energy, DC generators, Iron, Power system analysis computing, Nuclear power generation, Power system measurements. Abstract: In the original paper (see ibid., vol.17, p.983-90, 2002), the authors addressed the complicated issue of balanced and unbalanced DC currents in asymmetric three-phase transformers with three limbs. This discussor requests the original authors' comments to a number of queries. |
13,378 | Please write an abstract with title: Ethical and Sustainability Considerations for Knowledge Graph based Machine Learning, and key words: Training, Ethics, Pipelines, Transfer learning, Hardware, Artificial intelligence, Sustainable development. Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are becoming common in our daily lives. The AI-driven processes significantly affect us as individuals and as a society, spanning across ethical dimensions like discrimination, misinformation, and fraud. Several of these AI & ML approaches rely on Knowledge Graph (KG) data. Due to the large volume and complexity of today's KG-driven approaches, enormous resources are spent to utilize the complex AI approaches. Efficient usage of the resources like hardware and power consumption is essential for sustainable KG-based ML technologies. This paper introduces the ethical and sustainability considerations, challenges, and optimizations in the context of KG-based ML. We have grouped the ethical and sustainability aspects according to the typical Research & Development (R&D) lifecycle: an initial investigation of the AI approach's responsibility dimensions; technical system setup; central KG data analytics and curating; model selection, training, and evaluation; and final technology deployment. We also describe significant trade-offs and alternative options for dedicated scenarios enriched through existing and reported ethical and sustainability issues in AI-driven approaches and research. These include, e.g., efficient hardware usage guidelines; or the trade-off between transparency and accessibility compared to the risk of manipulability and privacy-related data disclosure. In addition, we propose how biased data and barely explainable AI can result in discriminating ML predictions. This work supports researchers and developers in reflecting, evaluating, and optimizing dedicated KG-based ML approaches in the dimensions of ethics and sustainability. |
13,379 | Please write an abstract with title: Proposing an Automatic Evaluation Method of Shoulder Joint ROM during Calisthenics Exercises of Older Adults as Adjunct to the Radio Exercise Program of Pepper, and key words: Shoulder, Patient rehabilitation, Geriatrics, Medical robotics, Muscles. Abstract: Continuous exercise is essential to prevent motor dysfunction among older adults. Maintaining and improving the regularity of physical activity are considered to be effective for enhancing muscle strength and preventing the onset of dementia. In recent years in Japan, there has been a lack of caregivers taking care of the super-aging population. As one of the solutions, a program was developed to introduce care robots promoting activities of daily living particularly for older adults, especially those with chronic and psychiatric conditions. Care robots, like Pepper, can give instructions on radio calisthenics exercises (RCEs) for older adults. However, it does not have an automatic function of evaluation for ROM of older during shoulder joint RCEs. The aim of this study is to describe the proposal for an automatic evaluation method of shoulder joint ROM exercises during RCEs for older adults. A standard criterion for automatically evaluating the maximum range of motion (M-ROM) of the shoulder joint through RCEs of older adults is added to the radio exercise program in Pepper. The proposed method is an automatic evaluation system much like the scoring by performers like a Karaoke machine. In the future, we will experiment to see if it can actually be judged and examine it for practical use. |
13,380 | Please write an abstract with title: Breast Imaging by Convolutional Neural Networks From Joint Microwave and Ultrasonic Data, and key words: Acoustics, Imaging, Breast, Microwave imaging, Microwave theory and techniques, Convolutional neural networks, Real-time systems. Abstract: Convolutional neural networks to achieve joint inversion of microwave and ultrasonic data for breast imaging are investigated. Source and field quantities, obtained via backpropagation, are used as inputs. A multistream structure is employed to benefit from data of different modalities. The network outputs the distribution maps of electric and acoustic parameters directly to achieve real-time imaging. Apart from the regression task, a multitask learning strategy is used with a classifier that associates each pixel to a tissue type to yield a segmentation image. Weighted loss is used to assign a higher penalty to pixels in tumors when wrongly classified. Comparisons are carried out between different network structures with the same datasets. The prediction results of the networks are evaluated by Intersection over Union for segmentation results and relative error of retrievals. The simulations on breast phantoms extracted from a dedicated repository show that, with both microwave and ultrasonic data, the network can provide a proper estimate of the breast structure and detection of small tumors. Meanwhile, multitask learning improves the regression results, and multistream input helps to exploit data from different modalities. |
13,381 | Please write an abstract with title: Research on An Approach of ARP Flooding Suppression in Multi-Controller SDN Networks, and key words: Protocols, Switches, Reinforcement learning, Floods, Synchronization. Abstract: ARP flooding has become an urgent problem in the deployment and application of SDN networks, which has been only effectively solved in single controller SDN networks. But it still has ARP flooding and data synchronization problems in multi-controller SDN networks. So we propose a two-stage "storing-blocking" suppression algorithm to suppress ARP flooding in multi-controller SDN networks. It stores the ARP response messages as ARP suppression entries, and uses the strong consistency algorithm to synchronize ARP suppression entries among controllers. Once an ARP request message matches the ARP suppression entries the mechanism blocks the flooding of ARP request messages, which can achieve the goal of the suppression of ARP flooding. Our experimental results show that our proposed mechanism can effectively reduce the impact of ARP flooding in multi-controller SDN networks in terms of flooding time, flooding scope, and controller overhead. |
13,382 | Please write an abstract with title: Intelligent control method of heating process including model prediction and climate compensation, and key words: Heating systems, Predictive models, Water heating, Heat transfer, Neural networks, Mathematical model, Buildings. Abstract: This paper takes the intelligent optimization control of the heating process as the technological background. Not only analyzes the shortcomings of the existing control strategies, but alse proposes and establishes a model predictive control strategy based on RBF neural network. In this paper, the mechanism model is used instead of the actual building, and the RBF neural network model is used as the predictive model. Furthermore, the control strategy includes the prediction of future interference and the feedback of indoor real-time temperature. This paper realizes the improvement of the traditional algorithm, improves the control effect, and finally reduces the energy consumption in the heating process while improving the comfort of thermal users. |
13,383 | Please write an abstract with title: A fault diagnosis method for Marine shore power based on a phased analytical model, and key words: Fault diagnosis, Analytical models, Correlation, Circuit breakers, Linear programming, Circuit faults, Mathematical model. Abstract: When the fault occurs when the port ship is connected to the land power grid, the fault elements can be found quickly and accurately. After in-depth analysis and comparison of the unique improved analytic model of fault diagnosis and the traditional analytic model of Marine shore power system, combining the advantages and disadvantages of the two models, a hierarchical analytic model of Marine shore power system is established. In the first stage, the influence of circuit breakers and other components on the objective function value is analyzed. On this basis, the fault measurement index of components is established from the two aspects of protection action correlation and circuit breaker action correlation, so as to realize the rapid screening of suspicious components. In the second stage, the fault hypothesis is introduced into the suspect elements, and the diagnostic objective function reflecting the action logic error and information communication error of the protection system is established. Finally, the improved particle swarm optimization algorithm is used to solve the mathematical model of fault diagnosis. Compared with the common genetic algorithm and particle swarm optimization algorithm, the improved particle swarm optimization algorithm is not easy to fall into the local optimal solution and the convergence speed is faster. The calculation results show the rapidity of the fault diagnosis model and the accuracy of the diagnosis results |
13,384 | Please write an abstract with title: Evaluation of the Strenght of Reflection and Dispersion of High Frequency in the Ionosphere by VOACAP model, and key words: Ionosphere, Absorption, Sun, Reflection, Ions, Receivers, Magnetic fields. Abstract: The ionosphere can be described as a complex natural world. The whole edifice of contemporary science stands on the shoulders satellite communication interconnected theories. The ionosphere has crude arguments. The ionosphere is a giant layer that extends from 80 to 1000 km above Earth. The ionosphere contains free electrons and ions. These particles contribute to disturb the propagation of the electromagnetic waves that pass through the ionosphere. These particles could refract or disperse the electromagnetic waves that pass through the ionosphere. This paper will study the impact of the reflection and the absorption in the ionosphere for the propagation of the electromagnetic waves and what is the relation among them. The comprehension of absorption of the ionosphere is coming from VOACAP model. VOACAP model is an indirect track to extract the estimation values of the absorption in the ionosphere. |
13,385 | Please write an abstract with title: A New Load Detection Method and Circuit Analysis for Quasi Resonant Inverter, and key words: Electromagnetic heating, Power control, RLC circuits, Reliability engineering, Circuit analysis, Integrated circuit reliability, Integrated circuit modeling. Abstract: Induction Heating (IH) technology is very popular in-home usage due to its safety, efficiency, and fast heating advantages. Although common induction heaters are designed to heat ferromagnetic pans, it is not easy to determine load conditions in every working condition. Because of the relationship between inverter circuit parameters and induction loads, load identification methods are very critical in induction hob applications. On the other hand, circuit elements (e.g., capacitor, inductor, frequency, etc.) are very important not only for the accurate power control but also reliability to design an induction hob. This study focuses on a new load detection method based on circuit analysis for quasi resonant induction hobs. Proposed method is theoretically examined and proven by the help of simulations and prototyped circuit. |
13,386 | Please write an abstract with title: Big Data Lakes: Models, Frameworks, and Techniques, and key words: Warehousing, Semantics, Big Data, Lakes, Market research, Data models, Research initiatives. Abstract: Nowadays, big data lakes are prominent components of emerging big data architectures. Basically, big data lakes are the natural evolution of data warehousing systems in the big data context, and deal with several requirements deriving from the well-known 3V nature of big data. Along with the emerging of big data lake research initiative, several issues appeared, such as: (i) big data lake models; (ii) big data lake frameworks; (iii) big data lake techniques. In line with this exciting research perspective, this paper proposes an overview of state-of-the-art approaches that are at the foundations of big data lake research, and innovative open problems and issues, which drive future research directions, on advancing the big data lake research trend. |
13,387 | Please write an abstract with title: Detecting Manipulated Facial Videos: A Time Series Solution, and key words: Deep learning, Correlation, Face recognition, Time series analysis, Memory architecture, Physiology, Complexity theory. Abstract: We propose a new method to expose fake videos based on a time series solution. The method is based on bidirectional long short-term memory (Bi-LSTM) backbone architecture with two different types of features: Face-Alignment and Dense-Face-Alignment, in which both of them are physiological signals that can be distinguished between fake and original videos. We choose 68 landmark points as the feature of Face-Alignment and Pose Adaptive Feature (PAF) for Dense-Face-Alignment. Based on these two facial features, we designed two deep networks. In addition, we optimize our network by adding an attention mechanism that improves detection precision. Our method is tested over benchmarks of Face Forensics/Face Forensics++ dataset and show a promising performance on inference speed while maintaining accuracy with state-of art solutions that deal against DeepFake. |
13,388 | Please write an abstract with title: Causal Analysis of Customer Churn Using Deep Learning, and key words: Deep learning, Measurement, Analytical models, Artificial neural networks, Predictive models, Data models, Bayes methods. Abstract: Customer churn describes terminating a relationship with a business or reducing customer engagement over a specific period. Two main business marketing strategies play vital roles to increase market share dollar- value: gaining new and preserving existing customers. Customer acquisition cost can be five to six times that for customer retention, hence investing in customers with churn risk is smart. Causal analysis of the churn model can predict whether a customer will churn in the foreseeable future and assist enterprises to identify effects and possible causes for churn and subsequently use that knowledge to apply tailored incentives. This paper proposes a framework using a deep feedforward neural network for classification accompanied by a sequential pattern mining method on high-dimensional sparse data. We also propose a causal Bayesian network to predict cause probabilities that lead to customer churn. Evaluation metrics on test data confirm the XGBoost and our deep learning model outperformed previous techniques. Experimental analysis confirms that some independent causal variables representing the level of super guarantee contribution, account growth, and customer tenure were identified as confounding factors for customer churn with a high degree of belief. This paper provides a real-world customer churn analysis from current status inference to future directions in local superannuation funds. |
13,389 | Please write an abstract with title: Analog circuit cell model based on single C/sub 60/ molecular transistor, and key words: Analog circuits, Electrodes, Electrons, Springs, Vibrations, Capacitance, Equivalent circuits, Gold, Voltage, Fluctuations. Abstract: In this paper, in the enlightenment of nanomechanical oscillations' experiment in single-C/sub 60/ transistor, utilizing improved shuttle mechanism for charge transfer in Coulomb blockade nanostructures, we give a new model of transistor based OD C/sub 60/ by combining the resistance with the spring, and simulate the I-V/sub ds/, where we find the Coulomb blockade and Coulomb staircase, and I-V/sub g/ characteristics, where we find periodical attenuation phenomenon. And on the basis of this transistor mechanism model, we construct a new model of an amplifier with the resistant load, and give the new small-signal equivalent circuit model. Here we solve master equation with the three-state model because of its simplicity and higher precision. |
13,390 | Please write an abstract with title: Lie theoretical approach to synthesizing T(3) parallel kinematic manipulators, and key words: Fasteners, Space technology, Manipulators, Robot kinematics, Orbital robotics, Mechanical engineering, Constraint theory, Jacobian matrices, Prototypes, Topology. Abstract: Various parallel kinematic manipulator (PKM) type design papers enumerate eligible links as the combination of revolute and prismatic joints and synthesize using local screw theory, but analysis and comparison on real capacity of different types has not been developed yet. This paper applies differential Lie group tools to developing a spectrum of so called regular link spatial translation (T(3)) PKM, which maximized workspace from a topological point of view. |
13,391 | Please write an abstract with title: Microelectromechanical system (MEMS) based microcantilever sensing platforms for explosive detection: A review, and key words: Explosives, Sensor arrays, Sensitivity, Stress, Micromechanical devices, Resonant frequency. Abstract: Explosive-based terrorism has been emerging since most explosives like trinitrotoluene (TNT), hexahydro-1,3,5 trinitroazine (RDX) and pentaerythritol tetranitrate (PETN) are; easy to deploy, cause massive damage and simple to handle. These types of explosives are difficult to detect and require devices that are expensive, time-consuming and large devices which cannot be used at many public places. With the help of miniature sensor devices like microelectromechanical system based microcantilevers which are low cost, more sensitive can overcome this problem. Microcantilever sensors can be fabricated as arrays which can eliminate any inborn noise or surrounding noises and improve the accuracy as well as the sensitivity of the device. |
13,392 | Please write an abstract with title: Multi-Modal fake news Detection on Social Media with Dual Attention Fusion Networks, and key words: Social networking (online), Fuses, Blogs, Bit error rate, Neural networks, Feature extraction, Solids. Abstract: Most of the existed fake news detection works on social media driven-fake news mainly focused on text. However, more and more social media platforms like Twitter, facebook, etc, allow users to create multi-modal contents, including text, image and video. Hence, it is obvious that only investigating text contents is insufficient to achieve solid detection. In this paper, we study the fake news on social media platforms composed of multimodal contents (text and images), and propose Dual Attention Fusion Networks for fake news detection on social media. We explore three modalities, (text modality, image modality and image attributes modality), and further propose a Dual Attention Fusion Networks (DAFN) model for this task. First, our proposed model extracts text modality and image modality, respectively. We then pass combinations of image attributes modality and text modality through BERT to extract text features. Finally, we reconstruct features of three modalities and fuse them into a feature vector for prediction. Our method is verified on realworld datasets consisting of collected social media platforms. Experiments show that the our method achieves promising results on real world datasets. outperforming all baseline models. |
13,393 | Please write an abstract with title: Basic concept of the interactive surrogate travel system, and key words: Computer displays, Humans, Skin, Biomedical imaging, Three dimensional displays, Virtual environment, Space exploration, Psychology, Medical tests, System testing. Abstract: The primary objective of this pilot project was to investigate the effectiveness Interactive Surrogate Travel (heretofore referred to as IST) in psychiatric testing involving culture-sensitive symptoms. Assuming that IST will soon become available for various clinical applications, this investigates may shed light on this important technology. High speed computing has drastically improved image processing in various forms. Furthermore, cost and size reductions have made it possible to process 3-D images using personal computers by simply adding an image-processing board to the computer. In this pilot trial, a CAVE system was used to display three-dimensional images. |
13,394 | Please write an abstract with title: A KNN-based classification algorithm for growth stages of Haematococcus pluvialis, and key words: Image segmentation, Liquids, Algae, Process control, Feature extraction, Stability analysis, Classification algorithms. Abstract: The growth of Haematococcus pluvialis is divided into the cell proliferation stage and the astaxanthin accumulation stage, and the culture environment requirements of the two stages are quite different. This paper proposes a classification algorithm based on KNN, which can realize the stage classification of the sample algae liquid through the microscopic image of Haematococcus pluvialis, which can better guide the experiment and improve the efficiency of the experiment. A series of image processing and feature extraction methods are also proposed, which can extract the cell area in the RGB microscopic image, and extract the corresponding features from the image for KNN classification. Experimental verification shows that this algorithm maintains a good effect and high stability under a large number of sample tests, and has certain application value. |
13,395 | Please write an abstract with title: A Review of Feature Selection Techniques in Sentiment Analysis Using Filter, Wrapper, or Hybrid Methods, and key words: Text mining, Sentiment analysis, Analytical models, Machine learning algorithms, Filtering algorithms, Feature extraction, Computational efficiency. Abstract: Sentiment analysis is one of the text mining fields that classify the polarity of document texts and determine positive, neutral, or negative opinions. Document texts tend to have noise features or irrelevant features, so that feature selection is needed to overcome the problems. The feature selection is a challenge in sentiment analysis to produce accurate models. It is crucial for improving machine learning algorithms because it can reduce the dimensionality of feature space, remove irrelevant features, select valuable features, and increase learning accuracy. Therefore, this study focuses on reviewing feature selection techniques classified into three categories, such as filter, wrapper, and hybrid methods. The review results concluded that all feature selection techniques could select essential features, reduce the dimensionality of feature space, and improve the accuracy of machine learning algorithms. Filter methods are easy to implement and faster than wrapper and hybrid methods, whereas wrapper methods are better than filter methods in terms of accuracy but slower than filter methods. The hybrid techniques are the best feature selection method to resolve redundant and irrelevant data and increase the classifier's performance. However, hybrid methods are complicated. Thus, they need a high computational cost. |
13,396 | Please write an abstract with title: Leveraging Frequency Based Salient Spatial Sound Localization to Improve 360° Video Saliency Prediction, and key words: Location awareness, Visualization, Social networking (online), Computational modeling, Predictive models, Streaming media, Observers. Abstract: Virtual and augmented reality (VR/AR) systems dramatically gained in popularity with various application areas such as gaming, social media, and communication. It is therefore a crucial task to have the knowhow to efficiently utilize, store or deliver 360° videos for end-users. Towards this aim, researchers have been developing deep neural network models for 360° multimedia processing and computer vision fields. In this line of work, an important research direction is to build models that can learn and predict the observers' attention on 360° videos to obtain so-called saliency maps computationally. Although there are a few saliency models proposed for this purpose, these models generally consider only visual cues in video frames by neglecting audio cues from sound sources. In this study, an unsupervised frequency-based saliency model is presented for predicting the strength and location of saliency in spatial audio. The prediction of salient audio cues is then used as audio bias on the video saliency predictions of state-of-the-art models. Our experiments yield promising results and show that integrating the proposed spatial audio bias into the existing video saliency models consistently improves their performance. |
13,397 | Please write an abstract with title: Upgrading the process control system at GCC Rio Grande's Tijeras, New Mexico plant, and key words: Process control, Voltage control, Control systems, Kilns, Milling machines, Programmable control, Aging, Cement industry, Sea level, Centralized control. Abstract: The Tijeras, New Mexico plant is located about 6 miles east of Albuquerque just south of Interstate 40 nestled in the Southern Rocky mountains. The plant is in Tijeras (Spanish for Scissors) canyon at an elevation of 6,300 feet or 1920 meters above sea level. It was originally built by Ideal Cement Company, and the first clinker from the new plant was produced on May 6, 1959. This paper describes a project to upgrade this cement plant's process control system. |
13,398 | Please write an abstract with title: Laplacian Deep Echo State Network Optimized by Genetic Algorithm, and key words: Analytical models, Laplace equations, Wind speed, Urban areas, Reservoirs, Stability analysis, Mathematical model. Abstract: In recent years, the applications of Deep Echo State Network (DESN) are increasing in wind speed prediction, energy consumption prediction, temperature prediction, etc. However, when the reservoir structure of the DESN is too deep, its overall stability decreases, and its generalization ability decreases. For applications where the input dimension is much lower than the dimension of the reservoir structure, we proposed a novel strategy which uses genetic algorithms to optimize the Laplacian Echo State Network (LAESN) to solve the problems caused by the deep reservoir structure. We took the chickenpox case in New York City as a case, simulated the optimized DESN, and compared it with the three models - Echo State Network (ESN), DESN and LAESN, to verify its effectiveness. |
13,399 | Please write an abstract with title: Interconnection System Simulation Analysis of Transient Micro-grid Stability in Indonesia, and key words: Analytical models, Wind energy, Microgrids, Power system stability, Stability analysis, Software, Generators. Abstract: Global economic development causes higher energy demand. The superiority of technology in distributed power generation from renewable energy sources is a solution to these problems. The writers designed a system modeling in ETAP software to design a micro-grid interconnection system that utilized the potential sources of solar and wind energy in Indonesia. This design is combined with models in the ETAP software such as wind turbine, photovoltaic, inverter, energy storage, generator, user-side loads, industrial system loads, transmission-distribution, transformers, and conventional power grid. The simulation of the micro-grid interconnection system is designed in operating conditions in order to analyze the load flow and transient stability analysis when a three-phase fault occurs on the main bus. This system is modeled in graphical form to determine the effect of errors on stress recovery to return to normal operating conditions. The use of wind turbine in a micro-grid system causes the transient stability conditions in the main bus voltage to fluctuate. To maintain calm on the main bus, a variable picth control setting is required on the wind turbine generator. The effect of energy storage on the micro-grid interconnection system in the event of an error can reduce the voltage drop on the main bus. |
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