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15,200 | Please write an abstract with title: Operational DER Scheduling Tool for Unbalanced Distribution Systems Considering Watt-VAr Controllers of PV Smart Inverters, and key words: Distributed Energy Resources (DERs), Watt-VAr Controller, AC optimal power flow, PV smart inverters, Volt-VAr Controller. Abstract: Increased penetration of Distributed Energy Resources (DERs) in distribution feeders may have reduced dependency to meet demand with power from substation, but has also lead to a rapid rise in several power quality issues. An effective DER scheduling model is required to combat issues related to system requirements and power quality. This paper proposes a DER scheduling tool using a robust AC optimal power flow (ACOPF) model for an unbalanced distribution system with Watt-VAr curves modeled. The Watt-VAr curves are mathematically modeled using a mixed-integer formulation based on the IEEE 1547–2018 standard. This ensures accurate real-time reactive power dispatch to support local and system-wide over-voltage issues. The proposed tool is tested on a snapshot of a distribution feeder in Arizona. The proposed tool is also compared with the Volt-VAr control mode, generally deployed among DERs. The potential of the tool for feeder-wide deployment is illustrated by the results. |
15,201 | Please write an abstract with title: A Resampling Univariate Analysis Approach to Ovarian Cancer From Clinical and Genetic Data, and key words: Genetics, Databases, Data science, Standards, Measurement, Tumors, Sequential analysis. Abstract: Ovarian cancer (OC) is the second most common gynecological malignancy and the gynecological tumor with the worst prognosis. To try to improve this situation, Data Science technologies could be a useful tool to help clinicians to know more about the disease. In our case, we are interested in exploring OC data to discover relationships between clinical and genetic factors and the disease progression. For it, we propose an analysis framework for simple and univariate statistical descriptions of features of different types, based on bootstrap resampling. Foremost, we define the framework for metric, categorical, and dates variables and determine what are the advantages and disadvantages of using different bootstrap resampling strategies, based on their statistical basis. Then, we use it to perform a univariate analysis over an OC dataset that allows to explore how is the disease progression, having platinum-free interval as indicator, in relation to clinical and genetic features of different types. Also, it provides a first set of variables possibly relevant for survival prediction. Results obtained show that some features have led to individual differences between both platinum resistant (<; 6 months) and platinum sensitive(>6 months) groups. It can be concluded that this could be an indicator that the database could be discriminatory for the hypotheses studied, though it is convenient to make multivariate analyses to check how relationships among features are influenced. |
15,202 | Please write an abstract with title: Frequency Domain Modelling of an LCLC Resonant Converter with Capacitive Output Filter Under Hybrid Modulation, and key words: Frequency modulation, Frequency-domain analysis, Prototypes, Resonant converters, Harmonic analysis, Transformers, Topology. Abstract: The LCLC resonant converter topology is popular and frequently used in high voltage applications as it can more accurately describe the effect of parasitic elements in high turns ratio transformers over LLC or LCC. The accuracy of the Fundamental Harmonic Approximation (FHA) analysis technique suffers from low-quality factor (Q) designs which is desired to minimize component stress. Presented in this paper is a new frequency domain model incorporating effects of both input and load side harmonics under a duty cycle-variable frequency-based hybrid modulation technique previously shown to be advantageous under light load conditions. Generalized curves of converter resonant tank gain describe its operation. Steady-state waveforms from the model and a 400V, 250W experimental prototype is used to verify the accuracy |
15,203 | Please write an abstract with title: Characterization of EMAT Guided Wave Reflectivity on Welded Structures for Use in Ranging, and key words: Welding, Distance measurement, Reflectivity, Reflection, Robots, Inspection, Receivers. Abstract: Guided wave ranging measurements offers an elegant method to localize an inspection robot relative to the geometric features, such as welds, of a structure under test. This paper characterizes the suitability of various EMAT generated guided wave modes when reflecting from butt welds for the purpose of choosing a low frequency mode suitable for accurate ranging. Wave modes were tested in 10mm mild steel plate in experiment and simulation, the method of data extraction is discussed as well as the determination of the wave mode best suited for weld ranging by means of comparison of the reflection coefficients. The authors conclude SH1 at a frequency-thickness product of 2 MHz.mm, is shown to be a highly suitable wave mode for gaining a large reflection from a weld, with an average reflection co-efficient of approximately 0.45 across four different sized weld crowns. A ranging over 1 meter experimentally was demonstrated to have a 2.65% error using our method. This work will enable simultaneous detailed mapping through ranging and inspection of large welded structures by mobile robotic inspection systems using EMAT’s. |
15,204 | Please write an abstract with title: PianoSyncAR: Enhancing Piano Learning through Visualizing Synchronized Hand Pose Discrepancies in Augmented Reality, and key words: Human-centered computing, Human computer interaction (HCI), Interaction paradigms-Mixed / augmented reality. Abstract: Motor skill acquisition involves learning from spatiotemporal discrepancies between target and self-generated motions. However, in dexterous skills with numerous degrees of freedom, understanding and correcting these motor errors are challenging. This issue becomes crucial for experienced individuals who seek for mastering and sophisticating their skills, where even subtle errors need to be minimized. To enable efficient optimization of body posture in piano learning, we present PianoSyncAR, an augmented reality system that superimposes the time-varying complex hand postures of a teacher over the hand of a learner. Through a user study with 12 pianists, we demonstrate several advantages of the proposed system over conventional tablet-screen, which implicate the potential of AR training as a complementary tool for video-based skill learning in piano playing. |
15,205 | Please write an abstract with title: RT-RMS: A Real-Time Resiliency Management System for Operational Decision Support, and key words: Software packages, Data visualization, Restful API, Distribution networks, Computer architecture, Tools, Real-time systems. Abstract: Power system resiliency has become a key priority for multiple stakeholders, given an observed increase in severe weather events in recent years and impact on the power distribution grid. Distribution network operators need to assess and analyze the resiliency of the system through carefully designed visualization driven by data and model based analytics. Operators require real-time data visualization of system states and resiliency indicators to make correct operational decisions and to control actions to minimize system impact. This paper describes a resilience-driven visualization tool, the Real-Time Resilience Management System Tool (RT-RMS), developed to assist operators in decision making and resilience assessment. RT-RMS utilizes multi-dimensional resilience metrics, geospatial visualization, and data monitors assessing resilience indicators and other key data points. This paper describes the basis of design, design considerations, open-source software components, and use cases demonstrating implementation and discusses the importance of the presented tool, especially in geographically isolated communities, where resilience is valued more than economic operation. The challenge of handling large amounts of data in a web-based application is analyzed by implementing a three-layered architecture and applying RESTful APIs in the back-end. Case studies are presented to highlight key RT-RMS features. |
15,206 | Please write an abstract with title: Generating Flood Probability Map Based on Combined Use of Synthetic Aperture Radar and Optical Imagery, and key words: Floods, Optical sensors, Optical imaging, Adaptive optics, Laser radar, Urban areas, Synthetic aperture radar. Abstract: Despite a lot of efforts to respond flood hazards with remote sensing data, it is still difficult to generate an accurate flood map using solely optical or radar imagery. While optical data is relatively high-resolution and does not suffer from speckle noise compared to radar data, it is very likely to be impacted by cloud and shadow. On the other hand, radar imagery can be used in all weather conditions due to its capability of penetrating clouds. Although a significant improvement of flood monitoring capability is achieved by using radar data, it is still challenging to map urban floods because of strong backscattering by man-made structures. Therefore, complementary use of optical and radar imagery in flood response is required, particularly in urban areas. In this study, we have adopted the Bayesian Joint Probability function to combine two different flood products generated from SAR and optical imagery. Flood detection with SAR data relies on the difference of backscatter signals between standing water and rougher land surface, while a Normalized Difference Water Index (NDWI) approach is used for optical data. Specifically, Planet Dove data with its 3m spatial resolution is used with higher weight values to detect flood extent in urban areas. |
15,207 | Please write an abstract with title: Writability enhancement using exchange spring media, and key words: Springs, Anisotropic magnetoresistance, Magnetic recording, Couplings, Signal to noise ratio, Magnetic heads, Magnetization, Magnetic properties, Antiferromagnetic materials, Automatic frequency control. Abstract: We have investigated the magnetic reversal and recording properties of layered ferromagnetically exchange coupled (or exchange spring) structures made of a hard layer and a soft layer. The hard layer is a longitudinal antiferromagnetically-coupled (AFC) media which is exchange coupled to a soft CoCrX layer via a CoRu interlayer. We find that optimizing the CoCrX and CoRu layer thicknesses is critical to achieve optimum improved writability while maintaining the media signal to noise ratio (SNR). Furthermore although we successfully decrease substantially the media coercive field (Hc) of these exchange spring structures, the energy barrier K/sub u/V appears unchanged. Finally, we show that these structures have the potential of improved SNR. |
15,208 | Please write an abstract with title: A spatial smoothing formulation for location systems, and key words: Smoothing methods, Sensor arrays, Geometry, Shape, Solid modeling, Demodulation, Signal processing, Stochastic processes, Differential equations, Motion analysis. Abstract: Two extensions of the classic passive location problem are considered. The first examines the ranging ability of passive receivers. The second presents alternative ways of describing the geometric content in positioning problems. The implications of the different approaches on the structure and performance of the location receiver are discussed. Because range determination by passive means is missing, the classical formulation of passive location may be viewed as a local geometry demodulation problem. With the explicit consideration of range, passive location becomes a global problem. At stake is what may be gained by processing the small but valuable amount of information carried by the wavefront curvature of the signals. Relevant questions relate to the design of passive receivers that aptly demodulate the range and the remaining quantities defining the geometry. There are passive applications where models exhibiting a high degree of (geometric) regularity are viable from a practical point of view. These occur, for example, when one can assume that the array sensors are collinear and that the moving target follows a deterministic linear path. In these models, the geometry is completely determined by a finite set of (unknown) parameters (e.g., range, bearing, speed, etc.). Accordingly, it is said that the regular models use an integral or ensemble approach for the description of the geometry. In many other problems, the geometry is more adequately described by statistical processes. Examples arise when the source follows a disturbed path, or when, due to towing, the array shape deforms, acquiring a not-completely-known shape. The paper models these constraints via a set of stochastic differential equations. The resulting representation is termed a differential description. It is emphasized that the differential approach is not only applied to the time content (relative dynamics), but also to the spatial dimension (array shape). The technique dualizes the space and time aspects of the problem. It provides a more flexible framework than the previous one. More general motions and array shapes than the traditional collinear ones can be considered by the analysis, e.g., irregular line arrays or arrays where the sensors are located at positions with a certain degree of randomness. Each approach fits a different design framework. The ensemble description is associated with the maximum likelihood technique. The differential representation uses recursive estimation methods (as provided by the Kalman-Bucy filtering theory). The paper discusses the main aspects of the structure of the resulting receivers and the associated measures of error performance. A second advantage of the differential model is immediately apparent The recursiveness of the differential receiver reduces its computational load. The speed-up obtained is fully appreciated in tracking applications, where the observations are sequentially updated. Finally, it is interesting to note that the time/space duality provided by the differential approach exhibits a remarkable distinction: the location recursive receiver behaves in time as a filter, while it behaves in space as a smoother. |
15,209 | Please write an abstract with title: How CHAID-Based Rule Induction Algorithm Helps Managements of Tourism Sites Improve Tourists' Experiences, and key words: Decision making, Data collection, Cleaning, Information management, Business. Abstract: The purpose of this study is to generate a set of hypotheses on dataset of tourists’ experiences resulted from CHAID-based rule induction processes. This study is particularly needed because the generated hypotheses can help managements of any tourism sites improve decision making processes on tourists’ experiences. Methodology in this study follows four major steps i.e. 1) data collection, 2) data cleaning, 3) CHAID processing, and 4) hypotheses generation based on rule induction. The result of this study is a set of hypotheses which can be in general adopted by managements of any tourism sites. However, tourism sites are so various and divergent in their types that the managements are suggested to modify and complement the dataset with their specific attributes to achieve a more relevant set of hypotheses to their sites. This study can be benefit of any businesses in the arena of tourism sites especially for winning the competition, increasing their level of competitive advantages or even for surviving in the arena. |
15,210 | Please write an abstract with title: Fault Location of the Renewable Energy Sources Connected Distribution Networks Based on Time Differences of the Modal Traveling Waves, and key words: Fault location, traveling wave modulus time difference, renewable energy sources, weighted deviation, preferred frequency band. Abstract: The topology of the distribution network and direction of the power flow will change when distributed generators (DGs) are connected to it, making it difficult to locate faults using conventional techniques like the impedance approach. Aiming at the two-phase short-circuit grounding faults of active distribution networks, this paper proposes a fault location method based on the time difference of the traveling wave modulus. The first step is the proposal of a zero-mode time-of-arrival calibration method for the ideal frequency band through the analysis of the attenuation of zero-mode traveling wave transmission. Next, define the relative wave velocity, research the quantitative relationship between the modulus transmission time difference and the zero-mode and aerial-mode wave velocities, and establish equation constraints between the modulus transmission time difference, relative wave velocity, and transmission distance. Then, time bounds and dynamic inequality constraints that establish relative wave velocities by fitting. Finally, combined with the abnormal data processing strategy, with the goal of minimizing the weighted deviation of the modulus time difference, the particle swarm optimization (PSO) algorithm is used to solve the fault distance. The PSCAD simulation result demonstrates that the method proposed in this paper has the advantages of high accuracy, strong error tolerance, and strong adaptability, and can quickly and accurately locate faults. |
15,211 | Please write an abstract with title: Hexagonal Radiator for Cellular Satellite Communication System, and key words: Satellite broadcasting, Shape, Array signal processing, Satellite antennas, Reflector antennas, Antenna radiation patterns, Satellite communication. Abstract: This paper tries to address the importance of beamforming for cellular satellite communication systems. In contrast to terrestrial cellular communication systems that the shape of the radio cells is more function of propagation loss and terrain features, the space version seems to be more function of beam projection on the earth curvature. In this way, beamforming may help to promote the system specifications regarding the shape of service area and cochannel interference. Here, the feasibility of hexagonal radiator for space cellular communications has been investigated for the first time. |
15,212 | Please write an abstract with title: Ultrawide-Angle and High-Scanning-Rate Leaky Wave Antenna Based on Spoof Surface Plasmon Polaritons, and key words: Dispersion, Phased arrays, Leaky wave antennas, Frequency measurement, Coplanar waveguides, Surface plasmon polaritons, Conductors. Abstract: An ultrawide-angle frequency beam scanning leaky-wave antenna (LWA) with a high scanning rate based on spoof surface plasmon polaritons (SSPPs) waveguide is proposed in this communication. A row of elliptical patches is placed periodically near the SSPPs waveguide, which can shift the fundamental mode of SSPPs waveguide to the fast-wave region and radiate electromagnetic (EM) waves. The simulated results show that the proposed LWA achieves an ultrawide scanning angle range of 172° over a narrow operation bandwidth of 9.8–12.28 GHz, which implies a high scanning rate. The simulated average gain of the proposed LWA is 10.13 dBi and its average total efficiency is 75.35%. The proposed LWA is fabricated and measured. The measured scanning angle range is 167° in the frequency band of 9.9–12.25 GHz, and the measured average gain is 9.73 dBi. Good agreements between the simulated and measured results are obtained, validating the proposed design. |
15,213 | Please write an abstract with title: Behavior of Berenger PML for absorbing TE/TM waves in rectangular waveguide, and key words: Tellurium, Electromagnetic waveguides, Rectangular waveguides, Finite difference methods, Time domain analysis, Cutoff frequency, Waveguide theory, Equations, Performance analysis, EMP radiation effects. Abstract: The behavior of Berenger perfectly matched layer (PML) for absorbing nonTEM (TE & TM) waves in rectangular waveguide is analyzed in this paper. The attenuation constant and the phase constant of TE & TM waves in rectangular waveguide filling with Berenger PML are given. It is shown that Berenger PML can be used in finite-difference time-domain (FDTD) simulation of rectangular waveguide operating at or near cutoff frequencies, due to the very small phase constant at these frequencies. A numerical example is given to show this. |
15,214 | Please write an abstract with title: Assessing Palliative Care Needs Using Machine Learning Approaches, and key words: Training, Hospitals, Computational modeling, Biological system modeling, Training data, Machine learning, Tools. Abstract: Palliative care improves quality of life for patients and their families when facing a life-threatening illness. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in underutilization of end-of-life care plans. In our study, we apply machine learning methods to patients’ Electronic Health Record (EHR) data to predict patients who are likely to benefit from palliative care. Our work is based on a real-world dataset of 1,462,862 hospitalization records from the State Inpatient Database (SID) of Florida from 2012 to 2015. We examine the performance of five popular machine learning algorithms on all-cause and ten individual disease subgroups. Our experimental results demonstrate that machine learning models can achieve approximately 68% and 60% predictive accuracy for the patients who "need" and "do-not-need" end-of-life care respectively. Given the successful palliative needs identification rate is less than 50% among current hospital practices, our models can be used as an auxiliary tool to assist in palliative care resource allocation. |
15,215 | Please write an abstract with title: Contrastive Domain Adaptation, and key words: Training, Computer vision, Adaptation models, Visualization, Machine learning algorithms, Pipelines, Machine learning. Abstract: Recently, contrastive self-supervised learning has become a key component for learning visual representations across many computer vision tasks and benchmarks. However, contrastive learning in the context of domain adaptation remains largely underexplored. In this paper, we propose to extend contrastive learning to a new domain adaptation setting, a particular situation occurring where the similarity is learned and deployed on samples following different probability distributions without access to labels. Contrastive learning learns by comparing and contrasting positive and negative pairs of samples in an unsupervised setting without access to source and target labels. We have developed a variation of a recently proposed contrastive learning framework that helps tackle the domain adaptation problem, further identifying and removing possible negatives similar to the anchor to mitigate the effects of false negatives. Extensive experiments demonstrate that the proposed method adapts well, and improves the performance on the downstream domain adaptation task. |
15,216 | Please write an abstract with title: Development of a Transfer Standard for DC Power Quality Reference Systems, and key words: Renewable energy sources, Uncertainty, Transducers, Systematics, Software architecture, Power quality, Hardware. Abstract: Most renewable energy sources are operated in direct current (DC) and require dedicated inverter to be integrated in the power system. This results in loss of rotational inertia as well as degradation of the power quality (PQ) indices. A promising alternative is represented by low-voltage DC grids, whose standardization though is still incomplete. Reference systems are being developed for DC metering and DCPQ, but their validation requires inter-laboratory comparison. To this end, we propose the design and preliminary characterization of a transfer standard for DCPQ measurements. The obtained results confirm the reliability of the proposed architecture, that guarantees a worst-case power uncertainty of 1 % over the frequency range from DC to few tens of kHz. |
15,217 | Please write an abstract with title: Resource-Oriented Timed Workflow Nets and Simulation Tool Design, and key words: Concurrent computing, Analytical models, Petri nets, Toy manufacturing industry, Explosions, Timing, Social intelligence. Abstract: This paper introduces resource-oriented timed workflow nets (ROTWNs), a type of Petri nets extended with resources and timing specifications. ROTWNs are designed to facilitate the analysis of the resource requirements in business workflow, as well as the timespan of the process. The analysis of ROTWN models is presented. Due to the nature of concurrency of business processes, state explosion is a common issue that makes it hard to find analytical solutions to ROTWN models, and thus it is necessary to automate the analysis through simulation. The design of such a tool is explained in this paper as well. A toy example of 4-task workflow is also used to illustrate the concept and analysis of ROTWNs. |
15,218 | Please write an abstract with title: Training Neural Network Controllers Using Control Barrier Functions in the Presence of Disturbances, and key words: Artificial neural networks, Trajectory, Safety, Nonlinear systems, Computational modeling, Adaptive control, Training. Abstract: Control Barrier Functions (CBF) have been recently utilized in the design of provably safe feedback control laws for nonlinear systems. These feedback control methods typically compute the next control input by solving an online Quadratic Program (QP). Solving QPs in real-time can be a computationally expensive process for resource-constrained systems. In the presence of disturbances, finding CBF-based safe control inputs can get even more time consuming as finding the worst-case of the disturbance requires solving a nonlinear program in general. In this work, we propose to use imitation learning to learn Neural Network based feedback controllers which will satisfy the CBF constraints. In the process, we also develop a new class of High Order CBF for systems under external disturbances. We demonstrate the framework on a unicycle model subject to external disturbances, e.g., wind or currents. |
15,219 | Please write an abstract with title: Pruning Deep Reinforcement Learning for Dual User Experience and Storage Lifetime Improvement on Mobile Devices, and key words: Cleaning, Mobile handsets, Performance evaluation, Learning (artificial intelligence), Neural networks, Training, Machine learning. Abstract: Background segment cleaning in log-structured file system has a significant impact on mobile devices. A low triggering frequency of the cleaning activity cannot reclaim enough free space for subsequent I/O, thus incurring foreground segment cleaning and impacting the user experience. In contrast, a high triggering frequency could generate excessive block migrations (BMs) and impair the storage lifetime. Prior works address this issue either by performance-biased solutions or incurring excessive memory overhead. In this article, a pruned reinforcement learning-based approach, MOBC, is proposed. Through learning the behaviors of I/O workloads and the statuses of logical address space, MOBC adaptively reduces the number of BMs and the number of triggered foreground segment cleanings. In order to integrate MOBC to resource-constraint mobile devices, a structured pruning method is proposed to reduce the time and space cost. The experimental results show that the pruned MOBC can reduce the worst case latency by 32.5%-68.6% at the 99.9th percentile, and improve the storage endurance by 24.3% over existing approaches, with significantly reduced overheads. |
15,220 | Please write an abstract with title: Statistical current monitor for the cosmic ray experiment Pierre Auger, and key words: Monitoring, Fluorescence, Telescopes, Photomultipliers, Cameras, Atmosphere, Anodes, Statistical analysis, Fluctuations, Field programmable gate arrays. Abstract: The air fluorescence telescopes are one essential part of the Pierre Auger Project, currently under construction in Argentina. With a pixel camera of 440 photomultiplier tubes the telescopes observe fluorescence light induced by cosmic ray extensive air showers passing through the atmosphere. In this paper we report on a method to monitor the dc anode current in each photomultiplier by statistical analysis of the signal fluctuations. The method has in our case the advantage that we were able to implement it using free resources of FPGA logic; therefore no additional electronics is required. We present details of the current monitor design and its performance measured with a prototype device. |
15,221 | Please write an abstract with title: Improving design quality and value in the built environment through knowledge of intangibles, and key words: Educational institutions, Business, Buildings, Investments, Engineering drawings, Feedback, Design engineering, Knowledge engineering, Floors, Ventilation. Abstract: Raising design quality and value in the built environment requires continuous improvement, drawing on feedback from clients or occupiers and other industry players. The challenging task for architectural and engineering designers has always been to use their intellectual knowledge to deliver both forms of benefits, tangibles and intangibles, in the built environment. Increasingly as clients demand best value for money, there is a greater need to understand the potential from intangibles, to see projects not as ends in themselves but as means to improved quality of life and wealth creation. As we begin to understand more about how - through the design of the built environment - to deliver these improvements in outcomes, clients are better placed to expect their successful delivery from designers, and designers themselves are better placed to provide them. This paper discusses cross-disciplinary issues about intangibles and is aimed at designers, clients, investors and entrepreneurs within the built environment. It presents some findings from a minuscule study that investigated intangible benefits in a new primary school. |
15,222 | Please write an abstract with title: The optimum linear smoother as a combination of two optimum linear filters, and key words: Nonlinear filters, Equations, Delay effects, Stochastic processes, Automatic control, State estimation, Maximum likelihood detection, Noise measurement, Delay estimation, Standards development. Abstract: A solution to the optimum linear smoothing problem is presented in which the smoother is interpreted as a combination of two optimum linear filters. This result is obtained from the well-known equation for the maximum likelihood combination of two independent estimates and equivalence to previous formulations is demonstrated. Forms of the solution which are convenient for practical computation are developed. |
15,223 | Please write an abstract with title: Frequency-Tunable Absorptive Bandpass Filter Using Substrate-Integrated Waveguide Structure, and key words: Prototypes, Resonators, Resonant frequency, Admittance, Substrates, Resistors, Inverters. Abstract: This work, for the first time, presents an absorptive frequency-tunable substrate-integrated waveguide (SIW) filter. For the filter design, an absorptive bandpass filter prototype tailored to an SIW structure has been formulated. The proposed absorptive bandpass filter prototype is capable of having a return loss larger than 20 dB at all frequencies although it has a simple matching circuit. The filter prototype has been attained by comprehensive formula-based synthesis of a new matching circuit equivalent to an existing one. To validate our filter prototype, a second-order absorptive bandpass filter that can alter its center frequency has been designed, fabricated, and measured. This article demonstrates approaches to find physical dimensions by comparing each section of the filter structure with the corresponding part of the prototype. The fabricated absorptive bandpass filter has a compact structure by virtue of its simple matching section. The frequency-tunable SIW resonators allow our absorptive bandpass filter to adjust its center frequency from 1.76 to 2.69 GHz while having absorptive performance. The measured reflection of the filter centered at 2.50 GHz is smaller than −10 dB between 1.56 and 3.27 GHz (2.10:1). It is shown that theory, simulation results, and measured responses are in good agreement. |
15,224 | Please write an abstract with title: Commonsense Generative Model for Chinese Automatic Knowledge Graph Construction, and key words: Training, Adaptation models, Conferences, Knowledge based systems, Question answering (information retrieval), Commonsense reasoning. Abstract: Commonsense knowledge graph support applications in commonsense reasoning, question answering, and so on. However, automatic knowledge graph construction is still a continuing goal for AI researchers due to the difficulty of obtaining tractable and objective commonsense information. Besides, the relative researches have so far been mainly limited to English, making it slow to develop the research of commonsense knowledge in other languages. Previous studies constructed the knowledge bases as the relational schemas which use the expert knowledge, semi-structured text extraction and unstructured text extraction. However, with the way of extraction, these methods can only capture the explicit knowledge mentioned in the text, while the commonsense knowledge in the text is usually implicit. In this paper, we propose a commonsense generative model with a novel attention mechanism and discuss whether pre-trained language models can effectively learn and generate novel knowledge. The empirical results show that our model could generate correct commonsense knowledge with high scores which up to 50.10% precision on ATOMIC dataset humans given. |
15,225 | Please write an abstract with title: Delay-hopped transmitted-reference RF communications, and key words: Delay, Radio frequency, Pulse modulation, Receivers, Wideband, Working environment noise, DH-HEMTs, Multiaccess communication, Signal to noise ratio, Radio communication. Abstract: Previously, the authors have invented and experimented with a new radio communications scheme called delay-hopped transmitted-reference (DHTR) radio. This technique can function either as an impulse radio, or can employ a more traditional spread-spectrum carrier such as broadband noise. The DHTR method is well-suited to short-range transmissions in a high multipath environment, and, in contrast to time-modulated impulse radio, is easy to synchronize at the receiver. Finally, DHTR receivers and transmitters are not highly complex, and can be implemented in a cost-effective way. |
15,226 | Please write an abstract with title: Faulty Phase Detection Method Under Single-Line-to-Ground Fault Considering Distributed Parameters Asymmetry and Line Impedance in Distribution Networks, and key words: Circuit faults, Grounding, Resistance, Fault diagnosis, Distribution networks, Impedance, Voltage control. Abstract: Accurate faulty phase detection under single-line-to-ground (SLG) fault is the basis of the emerging voltage-based fault arc suppression technology. Most conventional faulty phase recognition criteria assume the distributed line-to-ground parameters are symmetrical, therefore suffering invalidity in actual distribution networks especially under high-resistance ground-fault conditions. This paper firstly analyzes the magnitude and phase angle variation models of the phase-to-ground voltages before and after the SLG fault. Considering the asymmetrical distributed parameters and the line impedance, the specific phase-to-ground voltage variation rules corresponding to SLG fault on each phase are then discussed. Based on the voltage variation rules, a robust and practical method for faulty phase identification is proposed, which does not need the distributed parameters. Finally, the correctness of the variation rules and the availability of the proposed method is verified by simulation. Comparative study shows the proposed method has better accuracy and applicability with the conventional methods when the asymmetry and ground-fault resistance are high. |
15,227 | Please write an abstract with title: Application of uncertain variables to planning resource allocation in a class of research projects, and key words: Resource management, Decision making, Knowledge management, Technology planning, Information science, Paper technology, Mathematical model, Project management, Systems engineering and theory, Roentgenium. Abstract: The paper concerns research projects composed of tasks that must be performed in a sequence. Execution time of each task depends on an amount of a resource allocated to this task and is described by an expert in a form of inequality with unknown parameter. All unknown parameters are assumed to be values of uncertain variables characterized by certainty distributions. The paper contains formulation and solution of the knowledge-based resource allocation problem, an example illustrating the presented approach, and analysis of quality of expert's knowledge. |
15,228 | Please write an abstract with title: Quasi groups and Chaotic maps Cryptosystem based on Image Space, and key words: Databases, Internet, Encryption, Indexes. Abstract: Images used from ages to describe events and memorize worth occasions. Databases such as google, index images for easy access, for special cases images need to be secured, where used for certain purposes, such as shown only for authorized personal. In this paper, we present a revolutionary approach for crypto images. This crypto-images applied on the level of image space components, the suggested cryptosystem employs quasi groups’ and chaotic maps’ transpositions, the obtained results were outstanding. |
15,229 | Please write an abstract with title: P1617/D5, May 2022 - IEEE Approved Draft Guide for Assessment, Mitigation, and Control of Corrosion of Metallic Shields in Extruded Dielectric Cables rated 5 kV to 46 kV, and key words: IEEE Standards, Resistance, Power cables, Corrosion, Cable shielding, Dielectrics, Cable insulation. Abstract: A summary of the methods for detection, mitigation, and control of metallic shield corrosion in 5 kV to 46 kV underground distribution cable installed in conduit or direct buried is provided in this guide. The causes of corrosion in metallic shields and the methods available to detect this corrosion are described. The purpose of the metallic shield and the consequences of significant loss of the metallic shield are discussed. Recommendations are made for the mitigation and control of the cable metallic shield corrosion. |
15,230 | Please write an abstract with title: How Reduced Data Precision and Degree of Parallelism Impact the Reliability of Convolutional Neural Networks on FPGAs, and key words: Field programmable gate arrays, Biological neural networks, Reliability, Parallel processing, Quantization (signal), Sensitivity, Resource management. Abstract: Convolutional neural networks (CNNs) are becoming attractive alternatives to traditional image-processing algorithms in self-driving vehicles for automotive, military, and aerospace applications. The high computational demand of state-of-the-art CNN architectures requires the use of hardware acceleration on parallel devices. Field-programmable gate arrays (FPGAs) offer a great level of design flexibility, low power consumption, and are relatively low cost, which make them very good candidates for efficiently accelerating neural networks. Unfortunately, the configuration memories of SRAM-based FPGAs are sensitive to radiation-induced errors, which can compromise the circuit implemented on the programmable fabric and the overall reliability of the system. Through neutron beam experiments, we evaluate how lossless quantization processes and subsequent data precision reduction impact the area, performance, radiation sensitivity, and failure rate of neural networks on FPGAs. Our results show that an 8-bit integer design can deliver over six times more fault-free executions than a 32-bit floating-point implementation. Moreover, we discuss the tradeoffs associated with varying degrees of parallelism in a neural network accelerator. We show that, although increased parallelism increases radiation sensitivity, the performance gains generally outweigh it in terms of global failure rate. |
15,231 | Please write an abstract with title: Infrared and Visible Image Fusion Based on Multiscale Network with Dual-channel Information Cross Fusion Block, and key words: Fuses, Neural networks, Feature extraction, Data mining, Image fusion, Image reconstruction. Abstract: The purpose of infrared and visible image fusion is to combine the complementary information of an infrared image and a visible image into a single image. In this paper, we propose an infrared and visible image fusion method based on dual-channel information cross fusion block (DICFB), which is developed to crossly extract and preliminarily fuse the multi-scale features of the source images. With the cascaded DICFB, we can obtain a series of fusion feature maps of the source images at different scales. Then, a progressive feature reconstruction module (PFRM) is designed to reconstruct the multi-scale fusion features to obtain the final fused image. Moreover, to better train the network, we design a joint loss function, in which a saliency map-based loss term is proposed to enhance the saliency targets in the fused images. Experimental results show that the proposed method has better performance than other state-of-the-art image fusion methods both objectively and subjectively. |
15,232 | Please write an abstract with title: Mixer linearisation for software defined radio applications, and key words: Software radio, Application software, Receivers, RF signals, Radio frequency, Filtering, Interchannel interference, Communication systems, Baseband, High definition video. Abstract: The inherent non-linearity of mixers is particularly acute in broadband receiver design for software defined radio (SDR) applications. Here, the receiver frontend 'sees' not only the wanted channel, but also a number of nearby signals. A conventional mixer will downconvert all of these received channels to IF, thus adding inband interband interference to the wanted channel. In this paper, known mixer linearisation schemes are explained and a new technique using frequency retranslation within a linearised mixer architecture is presented. Two-tone-test results from a prototype offered 33 dB reduction in the distortion products and 22 dB suppression of adjacent channel interference (ACI) for a /spl pi//4-DQPSK modulated carrier. A theoretical analysis is also carried out to demonstrate the amplitude and phase matching requirements of the technique. |
15,233 | Please write an abstract with title: Federated Learning Over Wireless Networks: Convergence Analysis and Resource Allocation, and key words: Convergence, Computational modeling, Training, Data models, Resource management, Wireless communication, Wireless networks. Abstract: There is an increasing interest in a fast-growing machine learning technique called Federated Learning (FL), in which the model training is distributed over mobile user equipment (UEs), exploiting UEs' local computation and training data. Despite its advantages such as preserving data privacy, FL still has challenges of heterogeneity across UEs' data and physical resources. To address these challenges, we first propose FEDL, a FL algorithm which can handle heterogeneous UE data without further assumptions except strongly convex and smooth loss functions. We provide a convergence rate characterizing the trade-off between local computation rounds of each UE to update its local model and global communication rounds to update the FL global model. We then employ FEDL in wireless networks as a resource allocation optimization problem that captures the trade-off between FEDL convergence wall clock time and energy consumption of UEs with heterogeneous computing and power resources. Even though the wireless resource allocation problem of FEDL is non-convex, we exploit this problem's structure to decompose it into three sub-problems and analyze their closed-form solutions as well as insights into problem design. Finally, we empirically evaluate the convergence of FEDL with PyTorch experiments, and provide extensive numerical results for the wireless resource allocation sub-problems. Experimental results show that FEDL outperforms the vanilla FedAvg algorithm in terms of convergence rate and test accuracy in various settings. |
15,234 | Please write an abstract with title: AR Hero: Generating Interactive Augmented Reality Guitar Tutorials, and key words: Human computer interaction, Visualization, Three-dimensional displays, Conferences, Tutorials, Light fields, User experience. Abstract: We introduce a system capable of generating interactive Aug-mented Reality guitar tutorials by parsing common digital guitar tablature and by capturing the performance of an expert using a multi-camera array. Instructions are presented to the user in an Augmented Reality application using either an abstract visualization, a 3D virtual hand, or a 3D video. To support individual users at different skill levels the system provides full control of the play-back of a tutorial, including its speed and looping behavior, while delivering live feedback on the user's performance. |
15,235 | Please write an abstract with title: RF plasma assisted process for the deposition of silicon carbide thin films, and key words: Radio frequency, Silicon carbide, Semiconductor thin films, Sputtering, Plasma temperature, Substrates, Plasma chemistry, Plasma devices, Temperature sensors, Plasma materials processing. Abstract: Summary form only given, as follows. Recently, interest has increased about silicon carbide (SiC) thin films deposited onto various substrates because of the possibility of widespread applications such as high power electronic devices and high temperature sensors. The chemical vapor deposition of the SiC thin films on the heated silicon (Si) substrate is a widely used technique in the microelectronics areas. However, in these processes, the Si substrate must be raised to near 1400/spl deg/C to form a crystalline SiC film. Such a high temperature, being close to the melting temperature of Si, makes critical problems in the mass production of the devices. It is possible to decrease the temperature by using radio frequency (RF) plasma activation during the film deposition process. The SiC thin films were deposited on silicon substrate by the thermal decomposition of CH/sub 3/SiCl/sub 3/ (methyl-thrichloro-silane) molecules and by the RF plasma chemical method, operating at a frequency of 13.56 MHz. The deposited SiC thin films were analyzed with varying the process conditions of the RF plasma and the substrate temperature. The transmission electron microscopy (TEM) and Raman spectroscopy have been mainly used for the material analysis. |
15,236 | Please write an abstract with title: Parametric estimation of multi-dimensional affine transformations: an exact linear solution [image recognition applications], and key words: Image recognition, Object recognition, Lighting. Abstract: We consider the general framework of planar object recognition based on a set of known templates. Given an observation on one of the known objects, subject to an unknown affine transformation of it, our goal is to estimate the deformation that transforms some pre-chosen representation of this object (template) into the current observation. The direct approach for estimating the transformation is to apply each of the deformations in the affine group to the template to search for the deformed template that matches the observation. We propose a method that employs a set of non-linear operators to replace this high-D problem by an equivalent linear problem, expressed in terms of the unknown affine transformation parameters. This solution is further extended to include the case where the deformation relating the observed signature of the object and the template is composed both of the geometric deformation due to the affine transformation of the coordinate system and a constant illumination change. The proposed solution is unique and exact and is applicable to any affine transformation regardless of the magnitude of the deformation. |
15,237 | Please write an abstract with title: NMOSFET ESD self-protection strategy and underlying failure mechanism in advanced 0.13-/spl mu/m CMOS technology, and key words: MOSFET circuits, Electrostatic discharge, Stress, Hot carriers, CMOS technology, MOS devices, Protection, Leakage current, Current measurement, Electrostatic measurements. Abstract: In this paper, the high current characteristics encountered during electrostatic discharge (ESD) stress using nMOS/L/sub npn/ protection devices in a 0.13-/spl mu/m CMOS technology are investigated for different device parameters: channel length, channel width, gate-oxide thickness, and drain/source contact to gate (DCG/SCG) spacing. From leakage current measurements following ESD stress, it is concluded that the shorter (0.13 /spl mu/m) devices fail because of source/drain filamentation, whereas longer (0.3 /spl mu/m) devices with thin (22 /spl Aring/) oxide gate fail because of oxide breakdown. This conclusion is consistent with and supported by numerical simulations of the electric field. It is also supported by the observed effect of hot carrier stress on I/sub t2/. Hot carrier stress experiments additionally revealed that ESD stress can and does affect subsequent hot carrier degradation of the device. |
15,238 | Please write an abstract with title: Interactive SLAM using Laser and Advanced Sonar, and key words: Simultaneous localization and mapping, Mobile robots, Robot sensing systems, Sonar navigation, Robotics and automation, Orbital robotics, Fusion power generation, Laser fusion, Sonar measurements, Mesh generation. Abstract: This paper presents a novel approach to mapping for mobile robots that exploits user interaction to semiautonomously create a labelled map of the environment. The robot autonomously follows the user and is provided with a verbal commentary on the current location with phrases such as “Robot, we are in the office”. At the same time, a metric feature map is generated using fusion of laser and advanced sonar measurements in a Kalman filter based SLAM framework, which is later used for localization. When mapping is complete, the robot generates an occupancy grid for use in global task planning. The occupancy grid is created using a novel laser scan registration scheme that relies on storing the path of the robot along with associated local SLAM features during mapping, and later recovering the path by matching the associated local features to the final SLAM map. The occupancy grid is segmented into labelled rooms using an algorithm based on watershed segmentation and integration of the verbal commentary. Experimental results demonstrate our mobile robot creating SLAM and segmented occupancy grid maps of rooms along a 70 metre corridor, and then using these maps to navigate between rooms. |
15,239 | Please write an abstract with title: A lattice problem in quantum NP, and key words: Lattices, Quantum computing, Upper bound, Autocorrelation, Polynomials, Computer science, Cryptography, Algorithm design and analysis, Quantum mechanics. Abstract: We consider coGapSVP/sub /spl radic/n/, a gap version of the shortest vector in a lattice problem. This problem is known to be in AM /spl cap/ coNP but is not known to be in NP or in MA. We prove that it lies inside QMA, the quantum analogue of NP. This is the first non-trivial upper bound on the quantum complexity of a lattice problem. The proof relies on two novel ideas. First, we give a new characterization of QMA, called QMA+ formulation allows us to circumvent a problem which arises commonly in the context of QMA: the prover might use entanglement between different copies of the same state in order to cheat. The second idea involves using estimations of autocorrelation functions for verification. We make the important observation that autocorrelation functions are positive definite functions and using properties of such functions we severely restrict the prover's possibility to cheat. We hope that these ideas will lead to further developments in the field. |
15,240 | Please write an abstract with title: An Improved DC Circuit Breaker Topology Capable of Efficient Current Breaking and Regeneration, and key words: Topology, Circuit breakers, Network topology, Inductance, Mathematical models, Frequency modulation, Fault currents. Abstract: The dc power system, due to its convenience of conversion, integration, and use, is getting immense attention in the field of power transmission and distribution. It is superior to the traditional ac systems in terms of efficiency, reliability, and control simplicity as well. A dc circuit breaker is one of the important elements of any dc power system. It is a sophisticated technology designed to break dc current only. The breaking of a dc current is always challenging compared with the breaking of an ac current, as dc current does not have natural zero crossing points like ac current has. Moreover, dc current breaking becomes more critical when the current is inductive as energy stored in the network inductance opposes instantaneous current breaking. Hence, this energy needs to be absorbed and dissipated as heat during the current breaking operation, which is exactly what is done in the traditional dc circuit breaker topologies. This article introduces a new topology for dc circuit breakers with a mechanism to reuse this stored energy instead of dissipating it. The mechanism is analogous to regenerative braking in electric drive systems and can enhance the overall system efficiency. The proposed scheme was analyzed through rigorous computer simulation and was experimentally validated. |
15,241 | Please write an abstract with title: Randomness, arrays, differences and duality, and key words: Stochastic processes, Polynomials, Linear codes, Statistics. Abstract: Random variables that take on values in the finite field of q elements are considered. It is shown that joint distributions of such random variables are equivalently described by the individual distributions of their linear combinations. Random vectors X that are equally likely to take on any row of an arbitrary q-ary rectangular array as their value are treated extensively, together with the random vector /spl Delta/X defined as the difference between two independent versions of such a random vector. It is shown that linear combinations of exactly /spl tau/ of the components of X are always biased toward 0. A quantitative measure /spl beta//sub /spl tau//, of this bias is introduced and shown to be given by a sum of Krawtchouk polynomials. The vanishing of /spl beta//sub /spl tau// is shown to be equivalent to the maximal randomness of linear combinations of exactly /spl tau/ of the components of X as well as of /spl Delta/X. When the rows of the original array are the codewords of a q-ary linear code, then the bias /spl beta//sub /spl tau// coincides with the number of codewords of Hamming weight /spl tau/ in the dual code. The results of this article generalize certain well-known results such as the MacWilliams' (1977) identities and Delsarte's (1973) theorem on the significance of the "dual distance" of nonlinear codes. |
15,242 | Please write an abstract with title: Multi-stream Feature Aggregation Network for 3D Object Detection in Point Cloud, and key words: Point cloud compression, Location awareness, Three-dimensional displays, Semantics, Object detection, Feature extraction, Market research. Abstract: In the recent 3D object detection methods for point clouds, the combination of point-based methods and voxel-based methods is gradually becoming a trend. Point-based methods retain the accurate position and pose information in the raw points and voxel-based methods get multi-scale structure information through the 3D backbone. However, because of the sparsity and irregularity of point clouds, both representations ignore the context information, which is important for the detection of sparse and small objects. To solve this problem, we propose a multi-stream feature aggregation network to extract features from three representations of the point cloud for object detection. Specifically, we exploit multi-stream features extracted from point, voxel, and perspective view (PV) respectively on a parallel way, where the complementary information between different perspectives can be used to enrich the feature representations, especially for the perspective view containing rich semantic context information. Secondly, to eliminate redundant information and better exploit the correlation between different feature representations, we design an attention-based multi-stream feature fusion module (MSFF) to combine features from three information streams. Besides, we introduce a new voxel RoI pooling with the self-attention in the second refinement stage, which can further strengthen the connection between local features in the proposal to obtain accurate classification and localization predictions. Our method achieves progressive results on the KITTI dataset, especially in the cyclist category, which improves the baseline significantly by 5.56%, 4.73%, 5.16% AP in the test set for easy, moderate, and hard levels respectively. Code will be available at https://github.com/june2678/MR F. |
15,243 | Please write an abstract with title: Vision-based Autonomous Disinfection of High-Touch Surfaces in Indoor Environments, and key words: COVID-19, Autonomous systems, Spraying, Autonomous aerial vehicles, Indoor environment, Reliability, Task analysis. Abstract: Autonomous systems have played an important role in response to the Covid-19 pandemic. Notably, there have been multiple attempts to leverage Unmanned Aerial Vehicles (UAVs) to disinfect surfaces. Although recent research suggests that surface transmission is less significant than airborne transmission in the spread of Covid-19, surfaces and fomites can play, and have played, critical roles in the transmission of Covid-19 and many other viruses, especially in settings such as child daycares, schools, offices, and hospitals. Employing UAVs for mass spray disinfection offers several potential advantages, including high-throughput application of disinfectant, large scale deployment, and the minimization of health risks to sanitation workers. Despite these potential benefits and preliminary usage of UAVs for disinfection, there has been little research into their design and effectiveness. In this work, we present an autonomous UAV capable of effectively disinfecting indoor surfaces. We identify relevant parameters such as disinfectant type and concentration, and application time and distance required of the UAV to disinfect high-touch surfaces such as door handles. Finally, we develop a robotic system that enables the fully autonomous disinfection of door handles in an unstructured and previously unknown environment. To our knowledge, this is the smallest untethered UAV ever built with both full autonomy and spraying capabilities, allowing it to operate in confined indoor settings, and the first autonomous UAV to specifically target high-touch surfaces on an individual basis with spray disinfectant, resulting in more efficient use of disinfectant. |
15,244 | Please write an abstract with title: Soundtrack Matching and Recommendation System of Film and TV Series, and key words: TV, Motion pictures, Rhythm, Libraries, Mood, Harmonic analysis, Bars. Abstract: There is an inseparable relationship between the storyline and soundtrack of film and TV series works. The paper aims to reveal the relationship between the storyline and soundtrack and develop a soundtrack matching and recommendation system to improve the quality of Film and TV series. Intelligent tag analysis can be used to build the linear relationship between the soundtrack and film or TV series works, and then the matching and recommendation system can provide the most matched type of soundtrack and corresponding composer for the story, and could recommend the composer to the film producer. Moreover, the results illustrate that it will reduce the time consuming for producer finding proper music for film and TV series works, and improve the efficiency of film and television production significantly. |
15,245 | Please write an abstract with title: Transmission Line Records Synchronization Based on Traveling Waves Analysis, and key words: Synchronization, Clocks, Power transmission lines, Transient analysis, Monitoring, Fault location. Abstract: This application paper proposes a practical solution for transmission line records time synchronization based on the analysis of traveling waves (TWs) launched by internal faults, or by external events in the vicinity of the monitored line. Aiming on field applications, procedures that can be carried out by using commercially available TW digital recorders (TWDRs) are presented, allowing a practical computation of a synchronization factor which is used to align local and remote time references. Manual procedures are described and guidelines for the implementation of an automated scheme are presented. To evaluate the proposed procedures, the Alternative Transients Program (ATP) is used to generate realistic transmission line fault records, which are played back into real TWDRs. The obtained results show that the proposed solution is feasible, easy to apply in the field and reliable, being useful for multi-terminal records evaluation when no common time reference is available. |
15,246 | Please write an abstract with title: An integrated analog-CMOS control system for low-cost applications, and key words: Control systems, Analog circuits, CMOS technology, Circuit testing, Microelectronics, Cost function, CMOS digital integrated circuits, CMOS analog integrated circuits, Micromotors, Drilling machines. Abstract: This paper is intended to show that even using analog techniques an integrated microsystem can be realized. Especially, by integrating particular analog functions, a big advantage can be obtained in terms of overall fabrication costs. A motor controller was chosen as an example to present the specific components of the control system. Furthermore, their contribution to the entire system is discussed. Based upon statistical examinations, it can be shown that the yield of this analog system is competitive to respective digital solutions when considering mismatch behavior in an early design stage. |
15,247 | Please write an abstract with title: A TWN Inspired Speaker Verification Processor with Hardware-friendly Weight Quantization, and key words: Industries, Integrated circuit technology, Power demand, Quantization (signal), Biometrics (access control), Information security, Speech recognition. Abstract: Speaker verification (SV) is not only a convenient biometric recognition technology but also an important method to ensure information security. Since SV systems are often deployed in mobile terminals, this places a higher demand on the trade-off between ensuring recognition accuracy and reducing system power consumption. Thus, this paper proposes an implementation of a speaker verification system based on a ternary weight network (TWN). First, we design a TWN structure for the SV system. Then a weight quantization scheme to reduce hardware storage overhead is adopted. After that, the hardware of the SV system is designed and simulated. The recognition accuracy of the proposed TWN is tested to be 83.3%@5dB, 87.9%@15dB, and 93.1%@clean, respectively. Using an industry of 22nm ULL process, the overall power consumption of the system is 16.3µW. |
15,248 | Please write an abstract with title: Delayed virtual environments: a port-Hamiltonian approach, and key words: Delay, Haptic interfaces, Virtual environment, Scattering, Displays, Human robot interaction, Frequency, Employee welfare, Production, Sampling methods. Abstract: In this paper the problem of delayed virtual environments in haptics is addressed. We show that the approach outlined is no longer passive in case of (computational) delay on the output of the virtual environment. Passivity can be recovered using scattering theory; a discretization algorithm which leads to a discrete passive port-Hamiltonian systems with respect to any delay on the output is proposed. |
15,249 | Please write an abstract with title: T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation, and key words: Training, Adaptation models, Tensors, Correlation, Benchmark testing, Data structures, Matrix decomposition. Abstract: Most existing domain adaptation methods focus on adaptation from only one source domain, however, in practice there are a number of relevant sources that could be leveraged to help improve performance on target domain. We propose a novel approach named T-SVDNet to address the task of Multi-source Domain Adaptation (MDA), which is featured by incorporating Tensor Singular Value Decomposition (T-SVD) into a neural network’s training pipeline. Overall, high-order correlations among multiple domains and categories are fully explored so as to better bridge the domain gap. Specifically, we impose Tensor-Low-Rank (TLR) constraint on a tensor obtained by stacking up a group of prototypical similarity matrices, aiming at capturing consistent data structure across different domains. Furthermore, to avoid negative transfer brought by noisy source data, we propose a novel uncertainty-aware weighting strategy to adaptively assign weights to different source domains and samples based on the result of uncertainty estimation. Extensive experiments conducted on public benchmarks demonstrate the superiority of our model in addressing the task of MDA compared to state-of-the-art methods. Code is available at https://github.com/lslrh/T-SVDNet. |
15,250 | Please write an abstract with title: The Role of Familial Influences in African American Women's Persistence in Computing, and key words: Interviews, Engineering profession, Bonding, Gender issues, Education, Pipelines, Organizations. Abstract: Because African American women represent a vastly underrepresented population in the field of computing (i.e., 1% of bachelor's degrees awarded to African American women in 2018), multiple approaches have been utilized to increase the representation of African American women in the computing pipeline. However, strategies to recruit and retain African American women in computing emphasize mentorship in educational settings, ignoring the significance of familial influences in African American women's decision to pursue a degree in computing or how this impacts their ability to successfully navigate the computing pipeline. Furthermore, familial influences represent one form of social capital that can be leveraged to gain access to opportunities in computing. In this exploratory study, we investigate the role of family members and the family values that influence African American women's decision to pursue computing as a preferred field of study and a viable career option. Leveraging Black Feminist Thought as a critical framework, we interview 34 African American women in various stages of the computing pipeline to explore their lived experiences. Qualitative analysis reveals that families play a pivotal role in African American women's persistence in computing in six crucial ways: 1) early exposure and access to computing; 2) support for African American women's self-efficacy; 3) education as a family value; 4) career guidance and advice; 5) emotional support; and 6) family members as role models. We provide recommendations to leverage African American women's strong ties with family members. |
15,251 | Please write an abstract with title: Conflict Detection of Device Linkage Rules in Smart Home Systems, and key words: Couplings, Actuators, Smart homes, Sensors, Databases, Security, Data mining. Abstract: With the increasing types and functions of smart home devices, due to the lack of experience of users, they may cause unexpected errors and risks when configuring a large number of device linkage rules.In response to the above problems, in this paper, we propose an efficient conflict detection method to avoid unexpected situations.First, to reduce the complexity of subsequent rule conflict detection, we divide each rule into five categories according to its functions and characteristics. At the same time, we configure the priority, user rights, and execution area for each rule. Second, we filter out the rules of the same priority, user rights, and execution area. Third, we define five types of rule conflicts. Finally, the conflict detection algorithm is used to determine whether the filtered rules conflict with the rules in the corresponding database. We have created 379 non-conflicting rules in each type of rule storage database to detect whether the newly created rules conflict with them. Through experimental comparison, we find that our approach has more advantages than previous work in terms of performance and conflict detection types. |
15,252 | Please write an abstract with title: A new method based on sparse component decomposition to remove MRI artifacts in the continuous EEG recordings, and key words: Magnetic resonance imaging, Electroencephalography, Dictionaries, Matching pursuit algorithms, Discrete cosine transforms, Frequency, Transient analysis, Enterprise resource planning, Brain modeling, Analytical models. Abstract: How to effectively remove the magnetic resonance imaging (MRI) artifacts in the electroencephalography (EEG) recordings, induced when EEG and functional magnetic resonance imaging (FMRI) are simultaneously recorded, is a challenge for integration of EEG and FMRI. According to the temporal-spatial difference between MRI artifacts and EEG, a new method based on sparse component decomposition in the mixed over-complete dictionary is proposed in this paper to remove MR artifacts. A mixed over-complete dictionary(MOD) of wavelet and discrete cosine which can exhibit the temporal-spatial discrepancy between MRI artifacts and EEG is constructed first, and then the signals are separated by learning in this MOD with matching pursuit(MP) algorithm. After the sparse decomposition in MOD, the filtered EEG is approximately represented by the linear combination of atoms in the wavelet overcomplete dictionary and the removed MRI artifacts by that in the discrete cosine dictionary. The method is applied to the MRI artifacts corrupted EEG recordings and the decomposition result shows its validation |
15,253 | Please write an abstract with title: Lessons Learned in Designing and Evaluating Railway Control Systems, and key words: Object oriented modeling, Random access memory, Rail transportation, Safety, Software, Monitoring, Testing. Abstract: Demonstrating the safety of modern Railway Control Systems based on microprocessors is more complicated than showing that of traditional relay systems, because the behaviour of microprocessors when faults occur is unpredictable. This paper presents an overview of the main Verification and Validation (V&V) methods used by the Reliability, Availability, Maintainability and Safety (RAMS) team at Ansaldo Segnalamento Ferroviario: how we specify and demonstrate that the system under testing is Reliable, Available, Maintainable and Safe in compliance with the European Railway Standard CENELEC. Tests are executed on a system prototype with an environment simulator and consist of Code Inspection, monitoring I/O Variables, measuring performances by means of a Logic Analyzer, and exercising the diagnostics via a proprietary Fault Injection Board. For critical parts, formal specifications are used (e.g., in SDL). |
15,254 | Please write an abstract with title: A Probability-based Channel Selection Algorithm for Bluetooth Low Energy: A Preliminary Analysis, and key words: Wireless communication, Bluetooth, Simulation, Heuristic algorithms, Packet loss, Interference, Reliability. Abstract: In this paper, an improved channel selection algorithm for Bluetooth Low Energy is investigated under various interference levels. Its performance is studied in terms of two factors: channel selection probability and packet loss rate. The improved channel selection algorithm, according to simulation results, is more effective and reliable when handling interference with a high probability of transmission failure. The relationship between transmission failure probability and packet loss rate is also explored. |
15,255 | Please write an abstract with title: Designing and implementing an AI education program for learners with diverse background at scale, and key words: Training, Computer science, Educational programs, Technological innovation, Navigation, Focusing, Distance measurement. Abstract: This Research to Practice Full Paper presents an AI Education program. In January 2021 MIT entered into an agreement with the United States Air Force (USAF) and the Department of Defense (DoD) to design and offer a new educational research program focusing on Artificial Intelligence (AI) training. The goal of this collaboration is to design and advance educational research activities that promote maximum learning outcomes at scale for learners with diverse roles and educational backgrounds, ranging from Air Force and DoD personnel to the general public. This program is expected to offer different learning tracks addressing different groups of USAF employees based on their unique professional needs and backgrounds. The first pilot is currently underway and will provide the research team with data and insights that will inform the next iteration of the program, with the ultimate goal of formulating recommendations for the USAF and general public on how to reach large numbers of learners at scale in an optimum way. Currently, the program offers three different learning journeys for each of three different cohorts of USAF employees (i.e., leaders, developers, and users). These learning journeys span from online asynchronous and synchronous courses to in-person activities. Our research goals focus on exploring and understanding the learner experience via the study and analysis of AI content and curriculum, pedagogical approaches, learning modalities, and technological innovations to deliver learning experiences at scale. Key research activities involve evaluating a range of existing digital AI courses, mapping out the landscape of educational needs and competencies, and developing and piloting experiential learning experiences (to advance innovative technology-enabled training and learning technologies and methods). This paper discusses how preliminary research findings from this first pilot are informing the design and implementation of the next program iteration. The research provides insights that will benefit AI learners across the US while supporting the DoD’s objective to develop elite and world-class AI-ready services. |
15,256 | Please write an abstract with title: Machine sensing for mining optimization, and key words: Computer integrated manufacturing, Intelligent systems, Machine intelligence, Optimized production technology, Petroleum, Ores, Adaptive algorithm, Image segmentation, Statistics, Size measurement. Abstract: In this talk, I will present some of the recent research activities in the Centre for Intelligent Mining Systems (CIMS) on applying machine sensing technologies to the optimization of oil sand mining operations. Much of the research effort is concerned with the development of the capability to accurately measure the sizes of ore fragments as they are processed and moved along the production pipeline. The research directions of CIMS will be first highlighted, followed by a description of our current research in two specific areas, namely, adaptive algorithms for image segmentation and the use of image statistics for object size characterization. Adaptive algorithms are necessitated by the demanding environment of outdoor Northern Alberta, under all weather conditions, whereas the study of image statistics points to the possibility of acquiring ore size information without the difficult step of segmentation. We believe that oil sand mining creates both challenges to - and opportunities for - the machine sensing community and, at the same time, our research at CIMS demonstrates the relevance of our research community in both industrial and economical terms. |
15,257 | Please write an abstract with title: Daff-Net: Dual Attention Feature Fusion Network for Aircraft Detection in Remote Sensing Images, and key words: Image resolution, Convolution, Semantics, Interference, Network architecture, Military aircraft, Feature extraction. Abstract: Aircraft detection in remote sensing images has always been a research hotspot which has great significance in both civil and military applications. Due to the variations of aircraft types, poses, sizes and complex backgrounds, it is still difficult to effectively and accurately detect aircrafts in remote sensing images. This paper proposes DAFF-Net (Dual Attention Feature Fusion Network), which makes full use of the semantic information of the high-level feature map and the location information of the shallow feature map, and integrates the local features with its global dependency adaptively. Experiments on RSOD aircraft dataset have been implemented, and the results have proved that the detection accuracy of aircraft objects with different scales and densities can all be improved. |
15,258 | Please write an abstract with title: New rerouting link-state algorithm using connected dominating set, and key words: Routing, Floods, Costs, Graph theory, Computer science, Fault tolerance, Internet, Delay effects, Algorithm design and analysis, Broadcasting. Abstract: This article focuses on an efficient rerouting algorithm in wired network for a failed link using connected dominating set (CDS), a graph theory based concept. As the problem of link failure thawed the researcher to derive a method with loop-free manner, this ACDS (adaptive CDS) can grantee a loop-free and hassle tussle free incorporation to the link-state algorithm. The algorithm has been modified to withstand the link failure when it has to handle other path forwarding mechanism for a normal routing. The results show that the performance in-terms of end-to-end delay and packet delivery ratio is better than the existing method for single link failure. |
15,259 | Please write an abstract with title: The Construction of Progressive Management System of Teaching Practice Base, and key words: Training, Industries, Economics, Conferences, Educational technology, Software, Optimization. Abstract: The construction of practice base is the key point of engineering teaching reform and the important guarantee of cultivating high level practical talents. In order to implement the directive of the Ministry of Education on deepening the integration of enterprise and education, combining with the practical teaching of software engineering major in the college, based on the idea of process improvement and in the form of step by step, the progressive training system of software engineering practice base was established. At the same time, based on the software test training process as the experimental basis, the implementation process and effect of the practice training system are elaborated, which provides reference and demonstration for the in-depth exploration of the construction of the characteristic practice base. |
15,260 | Please write an abstract with title: The Comparison of the Dry Electrodes to wet Ag/AgCI electrode for Decoding Imagined Speech from the EEG, and key words: Electrodes, Wearable computers, Vocoders, Scalp, Signal processing, Feature extraction, Electroencephalography. Abstract: People who are suffering from an autism speech disorder, paralysis, or mute cannot communicate through speech. These people can think but are not able to articulate and create overt speech. Therefore, there is a need for the system to acquire and decode the electrical signals generated during the imagined speech or intended speech at the Scalp. These electrical signals are also called EEG(Electroencephalography). This system needs to be non-invasive, easily wearable, and user-friendly in day-to-day life. The system contains multiple electrodes, the signal processing block, feature extraction block, and vocoder. The selection of proper electrodes for this system is significant since the signal acquired at the Scalp is weak and contaminated due to different sources. Moreover, these electrodes must be comfortable to the user as the system is wearable. This paper compares various EEG electrodes used and discusses the pros and cons of these electrodes. This paper discusses how the self-made graphene-copper-based electrodes are made and compared with existing electrodes for various parameters and found suitable for Decoding the Spectrotemporal features of imagined speech using the EEG. |
15,261 | Please write an abstract with title: Automatic Selection and Insertion of HLS Directives Via a Source-to-Source Compiler, and key words: Manuals, Benchmark testing, Tools, Software, Hardware, Data mining, Optimization. Abstract: High-level Synthesis (HLS) is of paramount importance to leverage the use of FPGA-based accelerators by software developers. To achieve efficient FPGA implementations, code restructuring and source code annotating with HLS directives are necessary. However, this is still a manual process conducted by experienced developers. This paper proposes a step on a framework to automatically optimize C code via directives, using a source-to-source compiler on a stage before HLS. This optimization is primarily applied by strategies that select, configure, and insert directives on the code input to the Vivado HLS tool to synthesize more latency-efficient FPGA hardware. Those strategies rely on very simple but effective heuristics, which use a small set of properties extracted from the control/dataflow graphs generated from the input source code. We evaluate the framework using a variety of source codes. The experiments show that it can achieve efficient results while maintaining a low resource usage in most cases. Our experiments also compare the framework results to code optimized manually with directives, and they show that for most benchmarks used, it achieves similar results. |
15,262 | Please write an abstract with title: Employing Machine Learning with Optimized SVM Parameter to Detect Water Pipe Leakage, and key words: Support vector machines, Solid modeling, Machine learning algorithms, Oils, Machine learning, Prediction algorithms, Petrochemicals. Abstract: Most products, such as drinking water, oil, gas, and other petrochemical products, are distributed through pipe lines which are considered economical and safe. Regardless the fact, pipe line distribution is susceptible to leakage that could bring about loss to business institutions and pollution to surrounding environment. This study is focusing on the detection of water pipe leak using flow rate parameter. Testing is carried out on dataset format, both using direct data and already processed data format using volume balance method in detecting leakage. The teaching of machine learning needs to highlight some critical phases such as pre-processing, normalization method, and the applied kernel function method that enable to improve the prediction accuracy performance of both size and location of pipe leak. The data collected shows that size accuracy of leak of SVM model for raw dataset is 96.07% at min-max normalization, and for processed dataset is 69.71% at min-max normalization. For location classification, on the other hand, leak accuracy for raw dataset is 84.5% without normalization, and for processed dataset is 75.24% at z-score normalization. The use of optimized kernel function at z-score normalization has shown accuracy improvement in both size and location classification. The accuracy of leak size for raw dataset has improved to 98.25% and for processed dataset to 89.7%. For location classification, the improvement shows 88.96% for raw dataset and 74.42% for processed dataset respectively. |
15,263 | Please write an abstract with title: Asymmetric Self-Coherent Detection Based on Mach-Zehnder Interferometers, and key words: Optical transmitters, Image reconstruction, Photoconductivity, Signal to noise ratio, Delays, Optical receivers, Coherence. Abstract: We propose an asymmetric self-coherent detection scheme (ASCD) based on Mach-Zehnder interferometers (MZI) for the field reconstruction of self-coherent (SC) complex double-sideband (DSB) signals. The MZI-ASCD scheme approaches the high electrical spectral efficiency (ESE) of homodyne coherent detection via a direct detection (DD) receiver having only two photodiodes (PD) and two analog-to-digital converters. The incoming SC-DSB signal is split into two parts at the receiver in this approach, one of which is delayed and beats with the other part at the outputs of an MZI. We show that the field reconstruction can be performed from the two tributaries of photocurrents. In addition, we present a modified MZI-ASCD scheme referred to as AUX-ASCD which introduces an auxiliary DD branch to improve the SNR of the detected signal. It is found that both the MZI-ASCD scheme and the AUX-ASCD scheme achieve higher OSNR sensitivity compared to the Kramers-Kronig scheme and in the meantime increases the ESE by a factor of 2 using a cost-effective DD receiver. These advantages make the ASCD scheme attractive for short-reach optical communications including edge cloud connections and mobile X-haul systems. |
15,264 | Please write an abstract with title: Simultaneous Distributed Estimation and Attack Detection/Isolation in Social Networks: Structural Observability, Kronecker-Product Network, and Chi-Square Detector, and key words: Linear systems, Social networking (online), Gaussian noise, Estimation, Detectors, Sensor fusion, Probabilistic logic. Abstract: This paper considers distributed estimation of linear systems when the state observations are corrupted with Gaussian noise of unbounded support and under possible random adversarial attacks. We consider sensors equipped with single time-scale estimators and local chi-square $(\chi^{2})$ detectors to simultaneously observe the states, share information, fuse the noise/attack-corrupted data locally, and detect possible anomalies in their own observations. While this scheme is applicable to a wide variety of systems associated with full-rank (invertible) matrices, we discuss it within the context of distributed inference in social networks. The proposed technique outperforms existing results in the sense that: (i) we consider Gaussian noise with no simplifying upper-bound assumption on the support; (ii) all existing $\chi^{2}$-based techniques are centralized while our proposed technique is distributed, where the sensors locally detect attacks, with no central coordinator, using specific probabilistic thresholds; and (iii) no local-observability assumption at a sensor is made, which makes our method feasible for large-scale social networks. Moreover, we consider a Linear Matrix Inequalities (LMI) approach to design block-diagonal gain (estimator) matrices under appropriate constraints for isolating the attacks. |
15,265 | Please write an abstract with title: Observability with a conic observation set, and key words: Observability, Eigenvalues and eigenfunctions, Controllability, Jacobian matrices, Linear systems, Control systems, Africa, Fasteners, Constraint theory. Abstract: A geometric proof of Brammer's theorem on observability with a conic observation set is given; indeed, Brammer's result is generalized because we do not require that the observation cone be polyhedral. |
15,266 | Please write an abstract with title: Predicting drug dissolution profiles with an ensemble of boosted neural networks: a time series approach, and key words: Drugs, Neural networks, Pharmaceuticals, Predictive models, Mathematical model, Boosting, In vitro, Performance evaluation, Artificial neural networks, Nonlinear equations. Abstract: Applicability of an ensemble of Elman networks with boosting to drug dissolution profile predictions is investigated. Modifications of AdaBoost that enables its use in regression tasks are explained. Two real data sets comprising in vitro dissolution profiles of matrix-controlled-release theophylline pellets are employed to assess the effectiveness of the proposed system. Statistical evaluation and comparison of the results are performed. This work positively demonstrates the potentials of the proposed system for predicting desired drug dissolution characteristics in pharmaceutical product formulation tasks. |
15,267 | Please write an abstract with title: Dynamic optimization of dissipative PDE systems using nonlinear order reduction, and key words: Partial differential equations, Chemical engineering, Distributed computing, Optimization methods, Eigenvalues and eigenfunctions, Differential equations, Nonlinear dynamical systems, Physics computing, Finite difference methods, Valves. Abstract: In this work, we propose a computationally efficient method for the solution of dynamic constraint optimization problems arising in the context of spatially-distributed processes governed by highly-dissipative nonlinear partial differential equations (PDEs). The method is based on spatial discretization using combination of the method of weighted residuals with spatially-global basis functions and approximate inertial manifolds. We use the Kuramoto-Sivashinsky equation, a model that describes incipient instabilities in a variety of physical and chemical systems, to demonstrate the implementation and evaluate the effectiveness of the proposed optimization method. |
15,268 | Please write an abstract with title: Expectile Regression on Distributed Large-Scale Data, and key words: Distributed databases, Optimization, Computational modeling, Convex functions, Data models, Iterative methods. Abstract: Large-scale data presents great challenges to data analysis due to the limited computer storage capacity and the heterogeneous data structure. In this article, we propose a distributed expectile regression model to resolve the challenges of large-scale data by designing a surrogate loss function and using the Iterative Local Alternating Direction Method of the Multipliers (IL-ADMM) algorithm, which is developed for the calculation of the proposed estimator. To obtain nice performance only after fewer rounds of communications, the proposed method only needs to solve an M-estimation problem on the master machine while the other working machines only to compute the gradients based on local data. Moreover, we show the consistency and the asymptotic normality of the proposed estimator, and illustrate the efficient proof by numerical simulations and positive analysis on the superconductor data. |
15,269 | Please write an abstract with title: Design of high-efficiency and high-torque-density switched reluctance motor for vehicle propulsion, and key words: Reluctance motors, Vehicles, Propulsion, Strontium, Finite element methods, Geometry, Steady-state, Acoustic noise, Liquid cooling, Machine windings. Abstract: A high-density and high-efficiency switched reluctance (SR) motor has been designed and built for vehicle propulsion. Extensive finite-element analyses have been carried out to optimize the geometry for high density. Steady-state performance of the drive has been simulated to ensure good efficiency at all speeds. Special attention has been given during machine design to lower the acoustic noise. Direct liquid cooling of the winding has been designed to improve the machine overload capability. Dyno test results are presented which show good overall performance of the SR drive for vehicle propulsion. |
15,270 | Please write an abstract with title: Compressed Sensing Based Low-Power Multi-View Video Coding and Transmission in Wireless Multi-Path Multi-Hop Networks, and key words: Streaming media, Encoding, Wireless sensor networks, Decoding, Image coding, Wireless communication, Spread spectrum communication. Abstract: Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption. |
15,271 | Please write an abstract with title: Scribe Line Self Reference Targets to enable Accurate and Robust After-Etch Overlay Metrology of Active layer, and key words: Training, Conferences, Semiconductor device reliability, Random access memory, Metrology, Reliability engineering, Silicon. Abstract: Direct in-device after etch overlay metrology on DRAM structures is highly demanded, because of a need to correct dense intra- and inter-die process variations. However, finding a robust and cost-effective metrology solution is challenging on active to active cut, due to low signal strength. The active cut litho and etch process is meant to cut the slanted multiple-patterned Si lines, creating isolated Si regions that form the active area of the device. To be able to measure the overlay of the Active to Active cut currently a special wafer with under-etch is needed (to enhance the contrast). This extra process step and the need for a sacrificial wafer make the approach expensive, not easier for high order correction and not suitable for High Volume Manufacturing (HVM). In this work we successfully introduce for the first time the method of ASML Self Reference (ASR) target based recipe setup for Active cut layer. This method uses training targets positioned on the scribe line to train a recipe. ASML's Self Reference (ASR) In-Device Metrology (IDM) has already been demonstrated on the other Front End Of Line (FEOL) layers and used successfully in HVM. |
15,272 | Please write an abstract with title: Three-dimensional cartography of space charge by FLIMM, and key words: Space charge, Temperature, Frequency, Electrodes, Thermal conductivity, Acoustic beams, Laser beams, Thermal expansion, Conducting materials, Inorganic materials. Abstract: The FLIMM (Focused Laser Intensity Modulation Method) allows the experimental determination of space charge or polarization profiles in thin (<100 /spl mu/m) polymers by detection of a periodic thermally induced current. In this paper, we propose to show that a bidimensional scanning of the beam and a three-dimensional modelling of the temperature can lead to a 3D spatial determination of the space charge profile. Some results on PE test samples are discussed. |
15,273 | Please write an abstract with title: Transient response of a corrugated surface, and key words: Transient response, Corrugated surfaces, Radar scattering, Optical scattering, Sea measurements, Optical surface waves, Sea surface, Extraterrestrial measurements, Velocity measurement, Radar measurements. Abstract: A calculation is presented for the signal scattered by a corrugated surface due to a point source above the surface which transmits a short pulse of high frequency radiation. The analysis is based on the physical optics approximation. This problem is pertainent, although in a much simplified context, to problems of radar sensing of undulating surfaces, such as a swell dominated sea. In particular, this analysis leads to a definition of the criteria applicable to the use of a short pulse radar to sense the dominate wave structure of a sea. |
15,274 | Please write an abstract with title: Narrow Linewidth Electro-Optic Modulator Based Comb Generation with a Simple Modulator Configuration, and key words: Voltage-controlled oscillators, Erbium-doped fiber lasers, Optical feedback, Frequency modulation, Optical modulation, Phase modulation. Abstract: We demonstrate a narrow linewidth electro-optic modulator based frequency comb with a simple modulator configuration. It was achieved by a servo control of a fragment of a high-frequency modulation signal through a low-frequency voltage-controlled oscillator. |
15,275 | Please write an abstract with title: Research on the Application of Blockchain Technology in the Weapon and Equipment Testing, and key words: Command and control systems, Military computing, Weapons, Force, Memory, Production, Blockchains. Abstract: Blockchain technology has a broad application prospect in the military field due to its advanced technical concept, and as an important link in the development of the weapon and equipment, the testing plays a key role in the process of development, production and combat force formation. As a new application model of computer technology such as distributed data storage, peer-to-peer transmission, consensus mechanism, cryptographic algorithms, blochchain is strongly correlated with the weapon and equipment in command and control, data management, security and confidentiality, and has great potential for application in the weapon and equipment testing. Aiming at the application of blockchain technology in the weapon and equipment testing, this paper introduced the concept and principle of blockchain technology, described the characteristics of blockchain technology, and then analyzed the application scenarios and methods of blockchain technology in the weapon and equipment testing, such as test command and control, data management, security and confidentiality according to the advantages of its technology application. Combining with the limitations of blockchain technology itself, the problems that need to be solved such as the large scale of network nodes, storage space requirements, and bearer network densities being not equal were analyzed, and the challenges that blockchian may face such as the poor compatibility of deployment methods, the low response speed and the conflict with centralized control were studied. In the end, suggestions were made for the application and development of blockchain technology in the weapon and equipment testing in the future. |
15,276 | Please write an abstract with title: Dynamic modeling and control of three phase pulse width modulated power converters using phasors, and key words: Pulse width modulation converters, Phase modulation, Pulse width modulation, Power system dynamics, Power system modeling, Pulse power systems, Power electronics, Motor drives, Power quality, Distributed control. Abstract: Although the application of power electronic converters in ac power systems has been mostly limited to unidirectional loads like motor drives, various evolving applications such as power quality conditioners and distributed generation systems feature complex dynamic interactions affecting the operation of the ac power system. The focus of this paper is to present systematic technologies for modeling switching power converters in conjunction with their controls to determine their dynamic properties and assess their performance in an ac power network. The paper presents a dynamic phasor-oriented modeling technique that is readily compatible with classical power system analysis techniques. A state space model that represents the dynamic properties of the system in the magnitude-angle form is developed. The model can be used for obtaining steady state small signal dynamic properties at various operating conditions, and hence be used for design of appropriate regulators. Application of the technique is illustrated using a current source inverter example. |
15,277 | Please write an abstract with title: Least Square Based Jitter Decomposition Algorithm for a PAM4 link, and key words: Jitter, Threshold voltage, Standards, Modulation, Mathematical model, Estimation, Bandwidth. Abstract: Increasing demand for higher data transfer rates is bringing 4 level pulse amplitude modulation (PAM4) scheme to the forefront of high-speed serial link design. Jitter estimation is an important part of high-speed serial link design and testing. This paper presents a least square based algorithm for jitter decomposition in a PAM4 link. The proposed algorithm provides an accurate estimate of the periodic jitter, random jitter and inter-symbol interference while using fewer data samples. The efficacy of the algorithm is shown using MATLAB simulations. |
15,278 | Please write an abstract with title: Grid-Voltage Extraction for Grid-Connected Power Converters, and key words: Heuristic algorithms, Low-pass filters, Filtering algorithms, Harmonic analysis, Filtering theory, Robustness, Time factors. Abstract: The timely and accurate extraction of the grid-voltage is essential to the normal operation of the grid-connected converter. The phase-locked loop based on the synchronous reference frame (SRF-PLL) does not have fast response and superior filtering performance at the same time, so it cannot be applied to the applications of non-ideal power grid. By adding some high-order notch filters (NF) on the q-axis of SRF-PLL, a new algorithm called NFSRF-PLL is proposed, which can effectively filter out harmonics while ensuring that the response time is the same as that of SRF-PLL. In addition, for LVRT applications, based on the theory of coordinate transformation, a simple and effective method for detecting the grid-voltage sag-depth is also designed. By adding a second-order notch filter and a low-pass filter to the dq axis, the fundamental negative-sequence components and higher harmonics can be suppressed, respectively. At the same time, the bandwidth of the low-pass filter can be set relatively high. Therefore, the detection method has the characteristics of fast detection speed, high detection accuracy and good robustness. Finally, experimental comparison results verify the effectiveness of the proposed algorithms. |
15,279 | Please write an abstract with title: Saving energy with just in time instruction delivery, and key words: Pipelines, Decoding, Microprocessors, Power engineering and energy, Permission, Degradation, Energy consumption, Monitoring. Abstract: Just-In-Time instruction delivery is a general method for saving energy in a microprocessor by dynamically limiting the number of in-flight instructions. The goal is to save energy by (1) fetching valid instructions no sooner than necessary, avoiding cycles stalled in the pipeline - especially the issue queue, and (2) reducing the number of fetches and subsequent processing of mis-speculated instructions. A simple algorithm monitors performance and adjusts the maximum number of in-flight instructions at fairly long intervals, 100 K instructions in this study. The proposed JIT instruction delivery scheme provides the combined benefits of more targeted schemes proposed previously. With only a 3% performance degradation, energy savings in the fetch, decode pipe, and issue queue are 10%, 12%, and 40%, respectively. |
15,280 | Please write an abstract with title: Spark Structured Streaming: Customizing Kafka Stream Processing, and key words: Sparks, Task analysis, Monitoring, Data mining, Conferences, Real-time systems, Containers. Abstract: The aim of the present paper is to develop an improvement of large-scale multi-party data exchange and stream processing solution. The method of choice uses Apache Kafka streams as well as HDFS file granulation, and is exemplified in a real project of data ingestion into the Hadoop ecosystem. The management and conditional stream controlling procedures are proposed. Various ways to manage Kafka offsets during stream processing are considered. |
15,281 | Please write an abstract with title: SCNN: A Secure Convolutional Neural Network using Blockchain, and key words: Blockchain, Cryptography, Computer architecture, Public key, Encryption, Computational modeling, Data models. Abstract: Real-time applications like object detection, fire detection, face recognition and cancer detection are solely or partially relying on deep learning algorithms. Any tempering in these models can cause huge damages in many ways, therefore an utter need to secure these deep learning models is critically required. Blockchain technology has gained a wide popularity in tractability and security. In this article, the properties of blockchain are applied on the CNN models to produce secure CNN models. Each layer of a CNN model relates to a block, which contains the hash keys, public and private keys of their neighbors, while there exists a ledger block, which contains the detailed information about each layer of the model. The proposed SCNN model is tested using SVGG19 and SInceptionV3 models on publicly available datasets, which provides satisfactory results. |
15,282 | Please write an abstract with title: Frequency-dependent spherical-wave nonlinear AVO inversion in elastic media, and key words: Fourier analysis, Wave propagation, Inverse theory, Numerical modelling, Numerical solutions. Abstract: The plane-wave reflection coefficient (PRC) plays a remarkable role in conventional amplitude variation with offset (AVO) analysis and inversion. Compared with the widely exploited PRC that breaks down at the near- and supercritical incidence angles, the spherical-wave reflection coefficient (SRC) can overcome the influence of wide-angle reflection and give an accurate description of the actual seismic wave reflection phenomenon based on spherical-wave fronts. However, SRC is not widely used in AVO inversion due to its nonlinearity and computational complexity. In our study, the characteristics of frequency–depth-dependent monochromatic SRC are discussed and a novel three‐parameter SRC is derived. Compared with the conventional six-parameter SRC, the novel three‐parameter SRC improves the stability of spherical-wave AVO inversion. In addition, the concept of SRC within the Fresnel zone is proposed, and the accuracy of SRC within the Fresnel zone in the deep subsurface is tested. Finally, a nonlinear spherical-wave AVO inversion method for elastic media is proposed, which can make full use of all frequency components of wavelet. The robustness of the proposed method is verified by the application on synthetic seismogram with white Gaussian noise. The feasibility and practicability of this method are verified by comparing the spherical-wave AVO inversion results with the filtered well logs at the known well location. |
15,283 | Please write an abstract with title: Control from Signal Temporal Logic Specifications with Smooth Cumulative Quantitative Semantics, and key words: Robustness, Semantics, Optimization, Predictive control, Aerospace electronics, Automata, Prediction algorithms. Abstract: We present a framework to synthesize control policies for nonlinear dynamical systems from complex temporal constraints specified in a rich temporal logic called Signal Temporal Logic (STL). We propose a novel smooth STL quantitative semantics called cumulative robustness, and efficiently compute control policies through a series of smooth optimization problems that are solved using gradient ascent algorithms. Furthermore, we demonstrate how these techniques can be incorporated in a model predictive control framework. The advantages of combining the cumulative robustness function with smooth optimization methods as well as model predictive control are illustrated in case studies. |
15,284 | Please write an abstract with title: Calibration of Stochastic Channel Models Using Approximate Bayesian Computation, and key words: Stochastic processes, Computational modeling, Calibration, Channel models, Data models, Bayes methods, Delays. Abstract: Calibration of stochastic radio channel models is the process of fitting the parameters of a model such that it generates synthetic data similar to the measurements. The traditional calibration approach involves, first, extracting the multipath components, then, grouping them into clusters, and finally, estimating the model parameters. In this paper, we propose to use approximate Bayesian computation (ABC) to calibrate stochastic channel models so as to bypass the need for multipath extraction and clustering. We apply the ABC method to calibrate the well-known Saleh-Valenzuela model and show its performance in simulations and using measured data. We find that the Saleh-Valenzuela model can be calibrated directly without the need for multipath extraction or clustering. |
15,285 | Please write an abstract with title: A low complexity soft-output MIMO decoding algorithm, and key words: MIMO, Detectors, Iterative decoding, Receiving antennas, Equations, Transmitting antennas, Baseband, Quadrature amplitude modulation, Gaussian noise, Transfer functions. Abstract: The K-best Schnoff-Euchner (KSE) decoding algorithm is shown to be capable of supporting soft-outputs for MIMO detection. A modified KSE (MKSE) decoding algorithm is further proposed to improve the performance of the soft-output KSE with minor modifications. Simulation results show that the proposed MKSE algorithm can approach near-optimal performance with lower complexity and is suitable for coded MIMO detection without iterations |
15,286 | Please write an abstract with title: A Data-based Platform for Supporting Profit-driven Strategy in the Italian Spot Electricity Markets, and key words: Electricity supply industry, Optimization, Crawlers, Forecasting, Databases, Predictive models, Machine learning. Abstract: This paper proposes a data-based web platform to maximize the profit of a player participating in the Italian spot electricity markets. To ensure the scalability and portability of the platform, the micro-services approach are chosen with four stand-alone services communicating among one another. In the platform, a web crawler module retrieves data from the official and open sources, and a machine learning-based module is created to forecast the bidding strategies of all the market players for the next day across different spot markets. Based on the forecasted strategies, simplified market-clearing mechanisms are adopted to obtain the initial market information. Then by focusing on a single player, his/her strategy is optimized to maximize the daily profit over multiple spot markets with different payment schemes. The client can access the system through a simple, user-friendly web application. The simulation of the platform shows that around 92% of the market players can increase their profits. An example of a randomly selected player shows that the platform suggests a strategy leading to a 127.6% increase in its profit compared with its real bids in the markets. |
15,287 | Please write an abstract with title: Statistical analysis of correlation between weather parameters and new COVID-19 cases: a case study of Bosnia and Herzegovina, and key words: COVID-19, Temperature distribution, Technological innovation, Correlation, Statistical analysis, Wind speed, Urban areas. Abstract: This study analyzes the correlation between meteorological parameters and COVID-19 new daily cases for the period March-December 2020 in three large cities in Bosnia and Herzegovina: Sarajevo, Banja Luka and Mostar. The following weather parameters were included in the analysis: the mean temperature (TEMP), the maximum temperature (MAX), the minimum temperature (MIN), the mean wind speed (WDSP), the maximum sustained wind speed (MXSPD), the mean dew point (DEWP) and the mean visibility (VISIB).Two statistical approaches were performed in this study: Spearman rank correlation test and multiple linear regression method. Spearman rank correlation test indicated that there is a significant negative correlation between the number of new COVID-19 cases and TEMP, WDSP, MXSPD, MAX and VISIB in Banja Luka, TEMP, WDSP, MXSPD and VISIB in Sarajevo, while in Mostar all seven parameters are negatively correlated with the number of COVID-19 cases. In order to construct linear regression models, recursive feature elimination method was used for identifying independent variables. For each city, the proper linear regression models is constructed, with relatively satisfying values of R-squared value. To the best of our knowledge, no such study had been conducted in Bosnia and Herzegovina so far. |
15,288 | Please write an abstract with title: Feature Enhanced Projection Network for Zero-shot Semantic Segmentation, and key words: Training, Knowledge engineering, Visualization, Automation, Conferences, Semantics, Benchmark testing. Abstract: In environmental perception of autonomous driving, zero-shot semantic segmentation that can make prediction of new categories without using any labeled training samples is considered as a challenging task. One key step in this task is to transfer knowledge across categories via auxiliary semantic word embeddings. In this paper, we propose a feature enhanced projection network (FEPNet) that takes full advantage of transferred knowledge to enrich semantic representations. In FEPNet, two projection layers are added to a segmentation network so as to map features into seen (S) and unseen (U) category spaces, respectively. During training, U-space features are transferred to S-space using similarity relations to enhance the representation of seen categories. In the inference stage, the representation of unseen categories is also strengthened by incorporating features transferred from S-space. Moreover, a novel strategy is proposed to effectively alleviate prediction bias by performing segmentation independently in separate areas that contain seen and unseen categories. We conduct extensive experiments on three benchmark datasets. The experimental results show that our FEPNet achieves new state-of-the-art results compared to existing approaches. |
15,289 | Please write an abstract with title: Energy-Aware Multilevel Clustering Scheme for Underwater Wireless Sensor Networks, and key words: Routing, Energy efficiency, Wireless sensor networks, Routing protocols, Mathematical models, Energy consumption, Acoustics. Abstract: The expansion of wireless sensor networks in the underwater environment resulted in underwater wireless sensor networks. It has dramatically impacted the research arena because of its widespread and real-time applications. But successful implementation of underwater wireless sensor networks faces many issues. The primary concern in the underwater sensor network is sensor nodes’ energy depletion problem. In this paper, to improve the lifetime of the underwater wireless sensor network, an Energy-Aware Multi-level Clustering Scheme is proposed. The underwater network region is considered 3D concentric cylinders with multiple levels. Further, each level is divided into various blocks, representing one cluster. The proposed algorithm follows vertical communication mode from the sea bed to the surface area in a bottom-up fashion. Multiple levels with varying heights overcome the communication issues due to high water pressure towards the sea bed. Simulations are carried out to show the efficiency of the proposed algorithm, which performs better in terms of a prolonged network lifetime and average residual energy. The simulation result shows significant improvement in the network lifetime compared with current algorithms. |
15,290 | Please write an abstract with title: Simple Automated Narrative Generator (SANG), and key words: Conferences, Natural languages, Coherence, Ontologies, Turning, Generators, Creativity. Abstract: In this paper, we propose a planning-based story generation system SANG. SANG addresses some of the most important aspects of the story, causality, coherence, consistent characters, and emotions. For it, we built an action ontology representing causal information of events, and we used it to generate a plot between a pair of events. We then extend it to generating a plot between more events. We finally discuss how SANG uses the natural language generation to deliver the story in English. In the Turning Test performed over 106 participants, 64.1% of participants confidently believed that the story was written by a human being, higher than the baseline story generators. |
15,291 | Please write an abstract with title: Coifman wavelets in 3D scattering from very rough surfaces, and key words: Surface waves, Rough surfaces, Surface roughness, Multiresolution analysis, Electromagnetic scattering, Filling, Electromagnetic analysis, Moment methods, Wavelet analysis, Laboratories. Abstract: Scattering of electromagnetic waves from rough surfaces has been studied by analytical, experimental, and numerical means. In the numerical approaches, the Monte Carlo method has been used for decades employing the method of moments (MoM). Traditional MoM in conjunction with the Galerkin procedure requires that the computation time be on the order of n/sup 2/ for matrix filling and n/sup 3/ for matrix inversion if Gaussian elimination is employed. In this paper we employ the Coifman wavelets (Coiflets) which have compact supports, permit the multiresolution analysis (MRA) and form an orthonormal basis with zero moments, smoothness, and Dirac-/spl delta/-like property. The Coiflets reduce the matrix filling into O(n). In a benchmark case of a very rough surface with /spl sigma/ = 1/spl lambda/, /spl lscr/ = 2/spl lambda/, the matrix size has been reduced from 32,768 /spl times/ 32,768 to 8192 /spl times/ 8192. Numerical results agree well with the laboratory measurements. The backscattering enhancements axe observed for both the like- and crosspolarizations. |
15,292 | Please write an abstract with title: Deep Visual Odometry With Adaptive Memory, and key words: Cameras, Task analysis, Tracking, Simultaneous localization and mapping, Pose estimation, History. Abstract: We propose a novel deep visual odometry (VO) method that considers global information by selecting memory and refining poses. Existing learning-based methods take the VO task as a pure tracking problem via recovering camera poses from image snippets, leading to severe error accumulation. Global information is crucial for alleviating accumulated errors. However, it is challenging to effectively preserve such information for end-to-end systems. To deal with this challenge, we design an adaptive memory module, which progressively and adaptively saves the information from local to global in a neural analogue of memory, enabling our system to process long-term dependency. Benefiting from global information in the memory, previous results are further refined by an additional refining module. With the guidance of previous outputs, we adopt a spatial-temporal attention to select features for each view based on the co-visibility in feature domain. Specifically, our architecture consisting of Tracking, Remembering and Refining modules works beyond tracking. Experiments on the KITTI and TUM-RGBD datasets demonstrate that our approach outperforms state-of-the-art methods by large margins and produces competitive results against classic approaches in regular scenes. Moreover, our model achieves outstanding performance in challenging scenarios such as texture-less regions and abrupt motions, where classic algorithms tend to fail. |
15,293 | Please write an abstract with title: An FRTDS Real-Time Simulation Optimized Task Scheduling Algorithm Based on Reinforcement Learning, and key words: Task analysis, Hardware, Random access memory, Mathematical model, Computational modeling, Real-time systems, Field programmable gate arrays. Abstract: This paper presents a deep reinforcement learning (DRL)-based task scheduling algorithm that is applied to an FPGA-based real-time digital simulation (FRTDS) system to generate arrangements to minimize the makespan of a task sequence with limited resources. The algorithm has two parts, which are synthetic cost construction and DRL processing to make arrangements. The synthetic cost represents the cost of different selections of arrangements in both resource usage and blockage arranging probability. This study uses the cost to measure the state-action value function to process the deep Q network (DQN) procedure to generate an optimized scheduling strategy. We establish the reinforcement learning strategy generation process by instantiating the computing components in the hardware as agents, and RAM resources and communication I/O ports as environment. A hardware-design-based decision rule is constructed to ensure that the computing variables are distributed as evenly as possible in storage, while making full use of the pipeline characteristics of FPGA. A compiler is written to generate an FRTDS binary stream to drive FRTDS. Accuracy and performance of the proposed method are verified and evaluated. We present simulation results of the modeling method, as well as from a classic method. Comparing these results, the makespan obtained by the proposed method is significantly shorter. It corresponds to the possibility of having higher computing power and dealing with larger-scale real-time simulation. |
15,294 | Please write an abstract with title: On-the-fly Resource-Aware Model Aggregation for Federated Learning in Heterogeneous Edge, and key words: Runtime, Wireless networks, Machine learning, Collaborative work, Particle measurements, Servers, Reliability. Abstract: Edge computing has revolutionized the world of mobile and wireless networks world thanks to its flexible, secure, and performing characteristics. Lately, we have witnessed the increasing use of it to make more performing the deployment of machine learning (ML) techniques such as federated learning (FL). FL was debuted to improve communication efficiency compared to conventional distributed machine learning (ML). The original FL assumes a central aggregation server to aggregate locally optimized parameters and might bring reliability and latency issues. In this paper, we conduct an in-depth study of strategies to replace this central server by a flying master that is dynamically selected based on the current participants and/or available resources at every FL round of optimization. Specifically, we compare different metrics to select this flying master and assess consensus algorithms to perform the selection. Our results demonstrate a significant reduction of runtime using our flying master FL framework compared to the original FL from measurements results conducted in our EdgeAI testbed and over real 5G networks using an operational edge testbed. |
15,295 | Please write an abstract with title: Techniques of feature extraction and optimal position in reverse engineering, and key words: Feature extraction, Reverse engineering, Surface fitting, Maximum likelihood estimation, Surface reconstruction, Solid modeling, CADCAM, Parameter estimation, Educational institutions, Data mining. Abstract: Feature extraction is one of key techniques in feature-based reverse engineering. In this paper, a novel methodology of feature extraction is presented based on collected data points of mechanical part. Firstly, regular surface is used to model individual segmented data points patch based on maximum likelihood estimate. And then the resulting surfaces are used to determine the feature primitives approximately and afterwards extract the feature parameters. Finally, Mahalanobis distance is used to evaluate the error between feature primitives and the resulting surfaces, and feature is positioned optimally utilizing a similarity transformation which minimizes the error. |
15,296 | Please write an abstract with title: Fast pattern-based throughput prediction for TCP bulk transfers, and key words: Throughput, Bandwidth, Telecommunication traffic, Predictive models, Access protocols, Size measurement, Traffic control, Time measurement, Steady-state, Computer science. Abstract: The ability to quickly predict the throughput of a TCP transfer between a client and a server, or between peers, has wide application in scientific computing and commercial computing. This paper presents a new approach to fast prediction of overall throughput of a large TCP file transfer. The method constructs the time series of windows of segments arriving at the receiver, and predicts future throughput by exploiting knowledge of how TCP manages transfer window size. When the file transfer time series resembles a known TCP pattern, this information is utilized for prediction, otherwise simple heuristics are used. We have compared TCP pattern based prediction against traditional methods like a simple moving average, exponential weighted moving average, and aggregate measured throughput on a large suite of real life TCP traces. Our results show that TCP pattern based prediction generally performs as well or better than the best of other methods in any given scenario. |
15,297 | Please write an abstract with title: A Novel Meander Line SWS for Low Voltage and High Efficiency Ka-Band TWT, and key words: Low voltage, Simulation, Metals, Bandwidth, Electron tubes, Vacuum electronics, Power generation. Abstract: A novel meander line slow-wave structure (ML-SWS) based on a series of concentric arcs was proposed for applications on low voltage and high efficiency Ka-band traveling-wave tube (TWT). The simulated results demonstrate that the proposed novel ML-SWS has a good transmission performance in Ka-band. The peak output power of the TWT can reach 60.1 W at 35 GHz. The corresponding gain and the electron efficiency is 22.2 dB and 41.71%, respectively. Furthermore, the 3-dB bandwidth can cover 25 GHz-44 GHz and the electron efficiency is over 26.8% in Ka-band. |
15,298 | Please write an abstract with title: Develompment of flexible sensors based on piezoelectric nanofibers, and key words: Electrodes, Mechanical sensors, Production, Sensor phenomena and characterization, Biosensors, Rubber, Piezoelectric devices. Abstract: This paper deals with the production of nanofibrous piezoelectric sensors for flexible applications. The nanofibers produced via electrospinning are integrated a soft hosting material (epoxy resin and polyurethane rubber) and the electrodes are manufactured by using conductive carbon powder. The process described in this work leads to the realization of a piezoelectric sensor suitable for flexible applications without any delamination risks or mechanical failures that could occur by using traditional piezoelectric films and metallic electrodes. The piezoelectric response results to be comparable with traditional piezoelectric devices. |
15,299 | Please write an abstract with title: An improved neural-network-based face detection and facial expression classification system, and key words: Face detection, Psychology, Informatics, Face recognition, Pattern recognition, Application software, Feature extraction, Artificial neural networks, Humans, State estimation. Abstract: Automatic facial expression recognition is one of the most difficult and important problems in the scientific areas of cybernetics, pattern recognition and computer vision and their technological applications. New, friendlier human-computer interaction modes and multimedia interactive services require processing of images obtained with the use of multiple cameras to detect the presence and location of computer users' faces and determine their affective state. In order to be fully automated, the system proposed in this paper, consists of two modules: firstly, we use a face detection algorithm to determine whether or not there are any faces in the image and, if so, return the location and extent of each face, and secondly, we use a facial expression classification module to determine the facial expression of a person |
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