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5,700 | Please write an abstract with title: The Paradoxical Effects of Jitter on Fairness in Financial Exchanges: Engineering Implications, and key words: Jitter, Consumer electronics, Resource management, Clocks, Time factors, Instruments, Technological innovation. Abstract: Electronic financial exchanges, like computer systems generally, exhibit jitter, i.e., variability in the time taken to perform a given operation. This can affect fairness in the manner by which an exchange allocates scarce resources to market participants competing for them. The engineering responses to this by major financial exchanges have, seemingly paradoxically, been either (1) to try to minimize jitter, or (2) to deliberately introduce additional jitter through the adoption of batch-style resource allocation schemes in place of first-come, first-served schemes. An analysis of the various forces leading to these opposing engineering responses is provided. |
5,701 | Please write an abstract with title: Computational intelligence characterization method of semiconductor device, and key words: Computational intelligence, Semiconductor devices, Phase detection, Manufacturing processes, Neural networks, Fuzzy neural networks, Fuzzy sets, Genetic algorithms, Semiconductor device testing, Test equipment. Abstract: Characterization of semiconductor devices is used to gather as much data about the device as possible to determine weaknesses in design or trends in the manufacturing process. We propose a novel multiple trip point characterization concept to overcome the constraint of the single trip point concept in the device characterization phase. In addition, we use computational intelligence techniques (e.g., neural networks, fuzzy and genetic algorithms) to manipulate further these sets of multiple trip point values and tests based on semiconductor test equipment. Our experimental results demonstrate an excellent design parameter variation analysis in the device characterization phase, as well as detection of a set of worst case tests that can provoke the worst case variation, while the traditional approach was not capable of detecting them. |
5,702 | Please write an abstract with title: An Online One-Step Method to Identify Inertial Parameters of the Base and the Target Simultaneously for Space Robots in Postcapture, and key words: Robots, Space vehicles, Mathematical model, Torque, Force, Dynamics, Force measurement. Abstract: Space robots are in free-flying or free-floating mode, motions especially attitude motion of the base and motion of the manipulator are strongly coupled. Regarding to the uncertainties of the target's inertial parameters and variation of the base's inertial parameters, this paper presents a novel online one-step parameter identification method to estimate all the inertial parameters of the target and the base simultaneously. Momentum- and force-based identification equations are derived from the linear and angular momentum equations of the system and their derivation, and the modified recursive least square method is used for solving the equations efficiently. Compared with the traditional methods, the momentum-based equation can estimate all the inertial parameters of the base and the target simultaneously at each steps, while the force-based equation does not require torque of the joints. To verify the validity and feasibility of the proposed methods, 2D and 3D models with different targets and initial velocities are simulated and analyzed. The results show that all the estimated values show convergence to their ideal values and the method can be easily achieved online via recursive techniques. |
5,703 | Please write an abstract with title: Recognition and classification of surface defects of aluminum castings based on machine vision, and key words: Support vector machines, Casting, Image segmentation, Shape, Aluminum, Neural networks, Production. Abstract: In order to improve the efficiency of surface defect detection of casting parts in industrial production, machine vision method was used to automatically identify and classify the surface defects of castings. Image processing technology is used to preprocess the collected sample image, enhance the image information and segment the defect area. The geometric features, shape features and gray features of various defect images are analyzed, and the supervised learning classifier is designed to classify and recognize the parameters of casting feature set. By comparing radial basis function kernel function SVM, BP neural network and polynomial kernel function SVM. Experimental verification: The average recognition rate of RBF kernel SVM is 96%, which is higher than the other two methods. The results show that the classifier can meet the needs of industrial detection. |
5,704 | Please write an abstract with title: Empirical Analysis on Market-Making Hedging Problem based on Quadratic Programming with Time-Decay and Sparse-Term, and key words: Industries, Economics, Time series analysis, Dynamic programming, Quadratic programming, Reliability, Optimization. Abstract: This paper considers a market-making hedging problem with real market demands. To minimize multi-day hedging error square, a procedure based on dynamic quadratic programming problem is designed. Considering that the confidence and predictive ability of time series attenuate with the length of interval, we add a time-decay factor to adjust sample influence. Besides, the smoothly clipped absolute deviations (SCAD) penalty term is applied to enhance the sparsity, and meanwhile remain the original properties of parameters. In addition, the economic meaning of solutions has been found for matching the industry distribution, which provides a reliable way to explain and verify the model practicability. |
5,705 | Please write an abstract with title: Construction of power marketing user knowledge graph based on <tex>$\text{BERT}+\text{BILSTM}+\text{CRF}$</tex> model, and key words: Analytical models, Power demand, Power measurement, Bit error rate, Tools, Transformers, Data models. Abstract: In order to solve the fierce competition in the power market caused by the continuous improvement of the power consumption level of users, to reasonably deal with the contradiction between power supply and demand and to provide effective marketing strategies, the author proposes to construct the user knowledge graph based on the power marketing data. After preliminary data preprocessing, BERT (Pre-training of Deep Bidirectional Transformers for Language Understanding) model is selected for entity recognition. Bi-lstm (Bidirectional Long short-term Memory) model and CRF (Conditional Random Field) model are combined to extract the relationship, build triples and establish knowledge graph. The graph can clearly show the relationship between users and power load, address, price package, etc., which is conducive to relevant enterprises to put forward corresponding marketing or emergency measures, and provide theoretical support for optimization schemes such as “power demand side management” and “peak load shifting and valley filling” under the new situation. |
5,706 | Please write an abstract with title: How well does file size predict wide-area transfer time?, and key words: Size measurement, Processor scheduling, Computer science, Bandwidth, Delay, Time measurement, Admission control, Predictive models, Context modeling, Marine vehicles. Abstract: In scheduling connections at busy Web servers, it is commonly assumed that transmission duration (or time in system) is directly proportional to the size of the file transferred. For example, a scheduling discipline such as SRPT (shortest remaining processing time) could use this assumption to order connections according to the residual size of the transfer. However, with a diverse client population, network effects such as packet loss, heterogeneous end-to-end bandwidths and latencies render this assumption invalid. In this measurement study, we explore this relationship and investigate the predictive value of file size in determining transfer time. We use the publicly available sanitized cache access logs which are collected on a daily basis as a part of IRCache, the NLANR Web caching project, to explore this relationship for HTTP traffic serviced by the NLANR caches over a weeklong interval. Over this dataset, we first confirm an earlier finding: that for small transfers of up to 30 KB, there is virtually no correlation between file size and transfer time; moreover, transfer times vary over 5 orders of magnitude. For larger files, we find that file size and transfer time are increasingly well correlated as file size increases but we still find that predictions of transfer time from file size alone are not highly accurate. Our findings motivate further investigation of incorporating network-awareness into end-system scheduling disciplines. |
5,707 | Please write an abstract with title: Network analysis, adaptive control and imitation simulation for multi-agent telecommunication systems, and key words: Control system analysis, Adaptive control, Analytical models, Telecommunication control, Computer networks, Informatics, Programmable control, Man machine systems, User interfaces, Control systems. Abstract: Criteria of communicability of global telecommunication networks (TCN) on the base of network analysis of their graph and matrix models are formulated. Algorithms of adaptive routing and control for information flows in dynamic TCN with multi-agent structure are synthesized. Module library of imitation simulation of multi-agent TCN with adaptive and neural control is described. |
5,708 | Please write an abstract with title: Managing memory in changing engineering design firms: a closer look at the cultural dimension, and key words: Engineering management, Memory management, Design engineering, Cultural differences, Knowledge management, Aerospace industry, Project management, Technology management, Buildings, Business. Abstract: Engineering design firms have increasingly moved toward providing clients with "total service solutions", adding finance and maintenance services to their traditional engineering design services. This paper investigates the consequences of such a shift on the mechanisms employed by engineering design firms to support their organizational memory. In doing so, the paper builds on a review of the literature on memory and on the preliminary results of a three-year case study to extend and adapt the current transactive memory model of organizations. In doing so, it provides a way to unpack some of the factors that make up for the cultural component of managing engineering organizations in a fast changing competitive environment. |
5,709 | Please write an abstract with title: Intracavity wave mixing of self-generated fields in semiconductor lasers for mid/far-infrared generation, and key words: Semiconductor lasers, Quantum cascade lasers, Pump lasers, Quantum well lasers, Nonlinear optics, Optical mixing, Optical pumping, Laser modes, Frequency, Laser theory. Abstract: This study analyzes various types of semiconductor nonlinearities and discuss the most promising schemes of nonlinear-mixing lasers (NML), which may be used for the sum- and difference-frequency generation in a wide infrared range. The NMLs can be implemented both in the interband lasers (diode-type lasers) and intersubband lasers (quantum cascade lasers). This paper reviews theoretical and experimental investigations in the field and discusses possible applications. |
5,710 | Please write an abstract with title: Optimal Control of Iron-Removal Systems Based on Off-Policy Reinforcement Learning, and key words: Optimal control, Inductors, Iron, Zinc, Process control, Leaching, Learning (artificial intelligence). Abstract: The goethite iron-removal process is an important procedure to remove the iron ions from the zinc hydrometallurgy. However, as a coherent system with complex reaction mechanism, associated uncertainties, and interconnected adjacent reactors, it is difficult for the process to accurately control the ion concentration. Because a large amount of historical data can be obtained during the process, an optimal control algorithm based on off-policy reinforcement learning is proposed in this paper to overcome these difficulties. According to the historical data, the weights of neural network are learned offline, and the optimal control strategy is solved online. Firstly, a bounded function is introduced to define the maximum effect of the coherent system on the subsystem cost function and to extend the cost function of the nominal system, so that the decentralized guaranteed cost control problem can be expressed as the optimal control problem of the nominal system. Then, an approximate iterative control algorithm based on actor-critic structure is proposed. The actor and critic neural networks are used to approximate control strategies and cost functions respectively. To achieve complete off-line, a new neural network is added to the actor-critic structure to approximate a part of the unknown system structure, and the three neural network parameters are optimized by the state transition algorithm. Finally, the strategy update and strategy iteration operations are performed alternately to learn optimal control strategies. The effectiveness and flexibility of the proposed off-policy optimal control method is validated by data from a real industrial goethite iron-removal process. |
5,711 | Please write an abstract with title: Electrical characterization of indium tin oxynitride thin films for infrared sensor application, and key words: Indium tin oxide, Sensors, Optical sensors, Optical films, Optical device fabrication, Nitrogen, Conductivity. Abstract: Transparent conductive oxides (TCOs) are one class of materials with wide band gap (~ 3.1 eV). These materials have good transparency and conductivity. Indium Tin Oxide (ITO) is a degenerate semiconductor material with high band gap, transparent in the visible range of the solar spectrum and belonging to TCO class. When nitrogen is added to the ITO thin film, it is formed a new semiconductor, ITON (or indium tin oxynitride). The properties and characteristics of this material depend on the nitrogen concentration that is incorporated in its structure. Characteristics such as band gap and resistivity differ if compared to ITO. ITON thin film also has a higher light response. In this work, Indium Tin Oxynitride films were fabricated by evaporation and PECVD techniques and electrical parameters were characterized. Incorporation of nitrogen into the film by plasma annealing with different temperatures (140 °C, 200 °C, 260 °C and 320 °C) could improve further the optical and electrical properties of the ITON films and thus making ITON film an ideal transparent and conducting material for opto-electronic applications. Substrates were silicon (75 mm, p-type, 1-10 ohm.cm) and optical three-inch glass wafers with 0.5 mm thickness. The thin films were analyzed with spectral response, IxV (current x voltage) and Hall effect analyses. The main objective of this study is the development of optoelectronic devices. The current versus voltage curve show the response of light. With the spectral response measures it is possible to verify that ITON based devices have higher quantum efficiency for the near infrared region. In conclusion, the ideal would be the application of these materials in sensors that operate in the infrared range. |
5,712 | Please write an abstract with title: Author index, and key words: Indexes. Abstract: The author index contains an entry for each author and coauthor included in the proceedings record. |
5,713 | Please write an abstract with title: Linking Authentic Leadership to Change-Oriented Behaviors: The Mediating Effect of Workplace Trust, and key words: Leadership, Uncertainty, Employment, Force, Companies, Data science, Market research. Abstract: The modern organizational environment faces constant change and uncertainty. The modern organizational environment is becoming increasingly complex, dynamic, and commercial. Also, interest in new leadership is increasing due to many illegal activities taking place in society and organizations. To cope with changes, uncertainties, and negative social trends, researchers are paying attention to authentic leadership with a new perspective. This study aims to research the effect of the authentic leadership of the immediate supervisor on the change-oriented behavior of organizational members who can actively cope with organizational change. In this process, the mediating effect of trust in the workplace was empirically verified. For the study, a survey was conducted on 400 office workers currently working at domestic companies. The result of the survey showed, first, that authentic leadership had a positive (+) effect on the change-oriented behavior of organizational members. Second, it was found that authentic leadership had a positive (+) effect on both organizational trust, immediate supervisor trust, and coworker trust. Third, it was found that organizational trust, direct supervisor trust, and co-worker trust all had a positive (+) effect on change-oriented behavior. Fourth, it was confirmed that organizational trust, direct supervisor trust, and peer trust partially mediate between authentic leadership and change-oriented behavior. The study confirmed that authentic leadership and trust in the workplace can have a significant influence on the change-oriented behavior of organizational members. |
5,714 | Please write an abstract with title: Analysis of the Compliance between Cape Town Agreement and China's Technical Rules for Statutory Inspection of Ocean Going Fishing Vessels, and key words: Conferences, Wireless communication, Smart grids, Inspection. Abstract: Through the comparative analysis of the technical provisions of Cape Town agreement and the technical provisions of China's "technical rules for statutory inspection of ocean going fishing vessels", this paper finds out the main gaps, revises the lagging and obsolete technical provisions, and lays the foundation for accession to the convention from the legal system, striving for a favorable position in the performance of the Convention. |
5,715 | Please write an abstract with title: Electromagnetic Disruption Force Identification in Tokamaks through Kalman Filtering, and key words: Filtering, Force, Electromagnetic forces, Tokamak devices, State-space methods, Object recognition, Kalman filters. Abstract: A Kalman filter based technique is proposed for the identification of disruption forces in tokamak devices. The method is applied to some ITER-relevant test cases to show its effectiveness. |
5,716 | Please write an abstract with title: Social Media Application for Specially Challenged, and key words: Visualization, Image recognition, Social networking (online), Assistive technologies, Blindness, Deafness, Machine learning, Information retrieval, Computer applications, Optical character recognition, Videos, Gesture recognition, User interfaces, Speech recognition. Abstract: Every person has an equal right to information, therefore, impairments shouldn't restrict people from gaining this knowledge from any form of source. Social Networking applications have tremendously grown their popularity among all kinds of age groups for providing socialising opportunities, entertainment and exchange of knowledge. Hence, the motive of this paper is to propose a social networking application pipeline with a strong Machine Learning backend which makes it more accessible to the blind, deaf and dumb section of the society who otherwise do not enjoy the features of social networking platforms. |
5,717 | Please write an abstract with title: Self-Supervised Feature Enhancement Networks for Small Object Detection in Noisy Images, and key words: Feature extraction, Object detection, Noise measurement, Training, Detectors, Task analysis, Visualization. Abstract: Recent CNN-based approaches have shown impressive improvements in object detection, but detecting small objects in images is still a challenging task. Small object detection becomes more difficult if the image contains a lot of noise, which is frequent in real environments. The main reason is that the ratio of visual signal to noise on small objects is very low, making it difficult to extract rich features for detection. To address this issue, we propose a feature enhancement network (FEN) that is trained in a self-supervised manner. Specifically, FEN takes features from input images whose values randomly were erased, then predicts the erased values by aggregating neighboring values. This scheme enables FEN to improve features using surrounding values, which have great effects on enriching features from small-object regions during the test phase. To verify the robustness of our method against small object detection from noisy images, we adopt vehicle detection in aerial images as the main target task. The proposed method consistently outperformed the baseline methods in our experiments. We further present a variety of empirical studies, quantitatively and qualitatively, for in-depth analysis. |
5,718 | Please write an abstract with title: Sparse Array Channel Estimation for Subarray-Based Hybrid Beamforming Systems, and key words: Array signal processing, Antenna arrays, Antenna measurements, Sparse matrices, OFDM, Channel estimation. Abstract: Subarray-based hybrid beamforming communication systems are a cost- and power-efficient architectural solution to realize massive multiple-input multiple-output (MIMO) systems. To estimate the required channel state information (CSI) current research focuses on beam training algorithms, which suffer from long estimation times and require precise system calibration. In order to overcome these problems, two channel estimation algorithms in combination with suitable beamforming algorithms are proposed. The presented algorithms are based on sparse array measurements, where only one antenna per subarray is active during the estimation process. This allows for the reconstruction of the complex MIMO channel matrix by performing multiple sparse array measurements. Channel estimation algorithms, which drastically reduce the channel estimation time are proposed in this letter. Their high performance is proven in small cell communication measurements around 28 GHz. |
5,719 | Please write an abstract with title: A Large-Core Microstructure Optical Fiber for Co-Transmission of Signal and Power, and key words: Optical fibers, Optical fiber dispersion, Optical receivers, Power transmission, Optical attenuators, Nonlinear optics, Propagation losses. Abstract: A microstructure optical fiber (MOF) for co-transmission of signal and power is manufactured to provide power for remote antenna units (RAUs) and make the deployment of central stations fast and flexible. For a high laser damage threshold and a great refractive index difference, the MOF we proposed has a large core and an air ring in cladding pattern with regular holes. To realize high-quality signal transmission and flexible deployment, the MOF is made of pure silica. In this case, material dispersion, nonlinearity effects and bending loss can be restrained. Above all, the MOF with a high optical local capability and multiband optical transmission could be fabricated easily by traditional stack drawing method. Specifically, fiber loss is 2.26 dB/km at 976 nm and 1.44 dB/km at 1550 nm, acquired by the cut-back method. When the MOF was connected to a communication system with a 64-level quadrature amplitude modulation (64-QAM) 4 GHz frequency signal, an error vector magnitude (EVM) of 0.89% to 1.07% was obtained by the receiver. To the best of our knowledge, it is the first time a MOF has achieved co-transmission of signal and power. This work strongly suggests that MOF is applicable for the deployment of communication central station and emergency communication system in the future. |
5,720 | Please write an abstract with title: Multi-Objective Optimization Operation of CCHP System Under Continuous Shock Load Using Time-Varying Weighting Factors, and key words: Job shop scheduling, Load modeling, Natural gas, Optimization, Cooling, Costs, Resistance heating. Abstract: Improving the energy efficiency and maintaining the energy balance of integrated energy systems is a common concern. This study investigated the optimal operation of combined cooling, heating, and power (CCHP) systems under conventional and impact load scenarios. For the conventional operation, a time-varying weight factor was proposed to calculate the multi-objective function to optimize the system scheduling under off-grid and grid-connected modes. For the impact load scenario, the characteristics of the energy storage device was reasonably utilized to stabilize the impact of power. The simulation results revealed that the establishment of the time-varying weight factor optimized the energy economy level of the CCHP system and significantly improved its energy efficiency. Particularly, the energy storage device can cut off the impact peak when the system is under continuous impact load, and improve the energy supply reliability of the system. |
5,721 | Please write an abstract with title: An enhanced scheduling approach in a distributed parallel environment using mobile agents, and key words: Mobile agents, Application software, Workstations, Packaging, Processor scheduling, Software packages, Load management, Programming profession, Microcomputers, Throughput. Abstract: Our goal is to apply mobile agent technology to provide a better scheduling for MPI applications executing in a cluster configuration. This approach could represent in a distributed cluster environment an enhancement on the load balancing of the parallel processes. MPI in a cluster of heterogeneous machines could lead parallel programmers to obtain frustrated results, mainly because of the lack of an even distribution of the workload in the cluster. As a result, before submitting a MPI application to a cluster, we use our JOTA mobile agent approach to acquire a more precise information of machine's workload. Therefore, with a more precise knowledge of the load and characteristics in each machine, we are ready to gather lightweight workstations to form a cluster. Our empirical results indicate that it is possible to spend less elapsed time when considering the execution of a parallel application using the agent approach in comparison to an ordinary MPI environment. |
5,722 | Please write an abstract with title: Integrating heterogeneous IT systems: a standards based approach using SOAP, and key words: Simple object access protocol, Application software, SCADA systems, Computer architecture, Software systems, Power industry, Standards development, Investments, Software architecture, Middleware. Abstract: Integration architectures are often found where large investments in software systems lead to heterogeneous IT landscapes. Existing application components cannot be easily replaced without huge effort, but recently standards and technologies for interoperability are evolving. This paper presents a SOAP based software architecture for the integration of interconnected, heterogeneous IT systems, discusses key solution concepts and our experiences from realizing such architectures. SOAP services are used together with existing middleware solutions in realizing a case study from the field of electric utilities, where the main business drivers for integration are the optimization of work processes to reach higher efficiency. |
5,723 | Please write an abstract with title: On-line gyro-based, mass-property identification for thruster-controlled spacecraft using recursive least squares, and key words: Space vehicles, Least squares methods, NASA, Least squares approximation, Sensor systems, Equations, Intelligent vehicles, Accelerometers, Fault detection, Vectors. Abstract: Spacecraft control, state estimation, and fault-detection-and-isolation systems are affected by unknown variations in the vehicle mass properties. It is often difficult to accurately measure inertia terms on the ground, and mass properties can change on-orbit as fuel is expended, the configuration changes, or payloads are added or removed. Recursive least squares-based algorithms that use gyro signals to identify the center of mass and inverse inertia matrix are presented. They are applied in simulation to 3 thruster-controlled vehicles: the X-38 and Mini-AERCam under development at NASA-JSC, and the S4, an air-bearing spacecraft simulator at the NASA-Ames Smart Systems Research Lab (SSRL). |
5,724 | Please write an abstract with title: A hierarchical method for wiring congestion prediction, and key words: Wiring, Very large scale integration, Computer Society, Partitioning algorithms, Tree graphs, Routing, Upper bound. Abstract: Interconnect congestion estimation plays an important role in the physical design of integrated circuits. This paper presents a novel probabilistic approach to predicting wiring space in two-dimensional arrays. We propose a hierarchical estimation method to derive approximated upper bounds for wiring space. We use the net density distribution for predicting the routing congestion. Experimental results demonstrate the promising performance of the new approach. |
5,725 | Please write an abstract with title: MV Multi-functional Retrofit Converter for Enhanced Power Quality on O&G Platforms, and key words: Reactive power, Passive filters, Power quality, Medium voltage, Drives, Transformers, Power electronics. Abstract: Retrofit solutions have been proposed and tested on Oil and Gas (O&G) platforms to ensure modernization and efficiency improvement, and to extend the lifetime of aging platforms. In this regard, many O&G rigs, both offshore and onshore, had to employ combinations of old DC motor drives and modern AC drives assigned to critical tasks. Taking advantage of the non-simultaneous load cycles on the target O&G platform, this paper proposes a medium voltage multi-functional retrofit Three Level Neutral point clamped (NPC) converter to enhance the power quality, not only of the connected load, but also at the point of common coupling (PCC), retiring the tuned passive filters, and reducing the burden of voltage regulation on On-load tap changing transformer. The selected system is modeled in MATLAB/SIMULINK and the results with the proposed retrofit are presented in detail, while comparing with the baseline system. |
5,726 | Please write an abstract with title: Application of Convolutional Neural Networks in Remote Sensing Image Classification, and key words: Remote sensing, Training, Feature extraction, Convolutional neural networks, Image classification, Learning systems, Task analysis. Abstract: Aiming at the problem of remote sensing image classification, this paper designs an improved convolutional neural network structure. Combined with the transfer learning method, the classification experiments of different remote sensing image datasets are compared, and the effectiveness and versatility of the proposed method are verified. |
5,727 | Please write an abstract with title: Skin detection using neighborhood information, and key words: Skin, Face detection, Color, Humans, Robustness, Lighting, Gaussian processes, Histograms, Table lookup, Pixel. Abstract: Skin detection is employed in tasks like face detection and tracking, naked people detection, hand detection and tracking, people retrieval in databases and Internet, etc. However, skin detection is not robust enough for dealing with some real-world conditions, like changing lighting conditions and complex background containing surfaces and objects with skin-like colors. This situation can be improved by incorporating context information in the skin detection process. For this reason in this article a skin detection approach that uses neighborhood information is proposed. A pixel will belong to the skin class only if a direct neighbor does. This idea is implemented through a diffusion process. Two new algorithms implementing these ideas are described and compared with state-of-the-art skin detection algorithms. |
5,728 | Please write an abstract with title: A Radiation Based Topographic Correction Method on Landsat 8/Oli Surface Reflectance, and key words: Remote sensing, Surface topography, Earth, Artificial satellites, Land surface, Reflectivity, Lighting. Abstract: To reduce the topographic influence on the high-resolution optical remote sensing data, a radiation based topographic correction method was developed in this study by normalizing the solar illumination differences in mountain areas with the use of high-resolution downward shortwave radiation data (DSR). The coarse-resolution Meteosat Second Generation (MSG) SEVIRI DSR product was downscaled to the same spatial scale as the Landsat 8/OLI data to obtain the high-resolution DSR. The correction results indicated that the corrected spectral reflectance is poorer correlated with solar illumination than the original one. In addition, the corrected images also maintain the spectral characteristics with few overcorrections. Therefore, the proposed method will be of good potential in mountain remote sensing data process to reduce the topographic impacts. |
5,729 | Please write an abstract with title: The significance of linearity of quantities in electrophoresed and blotted materials demonstrated by BandScan/spl copy/ - an analytical program, and key words: Linearity, Biological materials, Bioinformatics, Biology, Genetics, DNA, RNA, Proteins, Displays, Graphics. Abstract: There is still an undervalued need for quantitation in the biological, biochemical, and the molecular genetic sciences. Quantitation of electroblotted materials such as DNA, RNA, and proteins and the quantitation of molecular weights in electrophoresed gels is often necessary to an undistorted analysis. Quantitation would ensure, for instance, that the quantities of the substances being assayed fall within the linear range of that method by which they are being studied, once the linear range has been determined by a linearity study: the common phenomenon of saturation and its reverse, insufficient samples, could be easily detected. A biological data representation program is discussed that converts the results of gels and blots to numerical values and presents these values in a graphical display that is amenable to meaningful comparisons. The main goal of this work is to be able to quantitate electrophoresed and blotted molecular and biochemical results while insuring that the samples processed are within the linear range of the methods employed. This study demonstrates errors that can occur when a linearity study is not conducted. Versatile, easy-to-use quantitative graphics programs, such as the BandScan program, can further pipe numerical output to spreadsheets or statistical packages and provide the bridge between modern computation and traditional wet lab techniques. This analytical bioinformatics program that allows for statistical analysis is also a valuable tool for teaching purposes in Bioinformatics and Molecular Biology. BandScan is available free for academic institutions and class room work from the corresponding author. |
5,730 | Please write an abstract with title: FAST: Enabling Fast Software/Hardware Prototype for Network Experimentation, and key words: Hardware, Software, Field programmable gate arrays, Programming, Prototypes, Hardware design languages, Engines. Abstract: The evolution of new technologies in network community is getting ever faster. Yet it remains the case that prototyping those novel mechanisms on a real-world system (i.e. CPU-FPGA platforms) is both time and labor consuming, which has a serious impact on the research timeliness. In order to bring researchers out of trivial process in prototype development, this paper proposed FAST, a software hardware co-design framework for fast network prototyping. With the programming abstraction of FAST, researchers are able to prototype (using C, verilog or both) a wide spectrum of network boxes rapidly based on all kinds of CPU-FPGA platforms. FAST framework takes care of managing DMA, PCIe and Linux Kernel while providing a unified API for researchers so they can focus only on the packet processing functions. We demonstrate FAST framework's easy to use features with a number of prototypes and show we can get over 10x gains in performance or 1000x better accuracy in clock synchronization compared with their software versions. |
5,731 | Please write an abstract with title: Mahaganana: An Approach to a Smart Census in India, and key words: cross platform, census, cloud based census, machine learning. Abstract: In a large country like India where the population of states is equal to the population of other countries, it is very difficult to obtain the count of the population in a given minimum time and cost. Although the year 2021 is going to be the Census year for India, the 2021 Census is 8th Census (since independence) of country. In India, Census is conducted in every ten years by the government. This census is going to be very important due to many reasons. The previous censuses took place by the manual procedure that is very typical and is used since it has been introduced by the British in 1872. This procedure is very time consuming and requires large effort by mankind. So the need of the time is to simplify it. This could be simplified using technology. So we are using a Cross-Platform portal to conduct the entire process in a digital manner and introducing several changes in procedure of conduction of Census. This portal will serve to all. (i.e. Citizen, Census Officer, Ministers, etc.) and the entire procedure will be described as Mahaganana. |
5,732 | Please write an abstract with title: AR-Child: Analysis, Evaluation, and Effect of Using Augmented Reality as a Learning Media for Preschool Children, and key words: Testing, Three-dimensional displays, Media, Animals, Lighting, Education, Cameras. Abstract: The use of technology to improve the experience and teaching and learning process in the classroom has been promoted now. One of these technologies is Augmented Reality (AR). Users are in a virtual space while still having nuances in real life called AR. AR has been proven to offer several solutions in the context of education, namely increasing learning involvement and increasing understanding of some materials. This study proposes AR-assisted learning media with the method of 3D Based Tracking and audio Marker, which is used by preschool children to recognize animals and fruits in English alphabetically, then analyze, evaluate, and know the effects on their use. The Extreme Programming (XP) method is used as an application development method. Application testing is done by black box testing, testing variations between distance, angle, lighting, background, and font size of the marker, and AR-Child response time to the detection of markers by the camera for the appearance of virtual objects. Thirty preschool children aged 4-6 years were involved in using the AR-Child application and analyzing application testing on the attractiveness and fun elements of students with fun testing. The effect of using AR-Child is seen from the learning outcomes at the end of the second meeting. |
5,733 | Please write an abstract with title: Correlation of Segregation and Social Networks' Majority Opinion in the Social Impact Model, and key words: Analytical models, Correlation, Social networking (online), Network topology, Biological system modeling, Sociology, Stochastic processes. Abstract: Everyone may influence others to change or persist in their current opinions via face-to-face or online communications. Predicting a society's majority opinion about a specific topic is an interesting challenge with many applications, e.g., predicting social movements, political votings, economical marketing. Among the various opinion formation models, the social impact model of opinion formation is very suitable for online social networks and online communities. In this model, three main factors affect a society's overall opinion: (1) the initial population of opinion groups, (2) the noise of the individuals to be persuaded or persist on their opinions, and (3) the topology of the network of interactions among individuals. In this research, to analyze the effect of segregation on the dynamics of opinion in the model, we assumed a noise-free model. Furthermore, the network of individuals is a scale-free network, and the initial population size of both opinion groups are the same with randomly assigned opinions. Using an agent-based modeling approach, we studied how the segregation of opinion groups may affect the dynamics of opinion formation. The results reveal that there is a strong correlation between segregation and the trend of society's opinion. It could be concluded from the results that if starting from the same population size in both opinion groups, it is expected that the more segregated opinion group dominates the less one and determines the majority opinion of the society. |
5,734 | Please write an abstract with title: The choice of a commercial broadband communication system for ABC4CarE, and key words: Broadband communication, Hospitals, Cardiology, Biomedical imaging, User interfaces, Application software, Bidirectional control, Internet, Hardware, X-ray imaging. Abstract: In order to inquire the hard- and software possibilities for broadband communication applications, an inventory was made of specific solutions for the three main goals of the ABC4CarE project: teleconsulting, teleguiding and teleteaching. As the project plans for ABC4CarE are maturing, three of these telecommunication applications have been chosen, and a thorough survey was made on the usefulness of the application in each specific situation. For the Groningen-Leeuwarden X-ray cathlab teleconsulting connection the Philips VISU solution will be used because of the low cost. For the Amsterdam-Alkmaar X-ray cathlab teleconsulting and teleguiding connection, the Lucent MediaBuilder solution was chosen because of the broad spectrum of possibilities. The Rotterdam-Rotterdam echocardiographic teleguiding connection uses a home built application using a toolkit from Berkeley University. |
5,735 | Please write an abstract with title: Choosing a Consensus Mechanism for a Blockchain Based P2P Instant Transaction System Integrated with IoT, and key words: Databases, Smart contracts, Earth Observing System, Peer-to-peer computing, Blockchains, Plasmas, Security. Abstract: The Internet of Things (IoT) will play a significant role in the future market of services. Services require payments. Payments must be confirmed as fast as possible to protect customers and merchants. Integration of IoT to peer-to-peer networks provides a need for choosing an appropriate consensus mechanism and other ways to make transactions faster without losing the required level of security. As security of modern blockchain projects is controlled by decentralized applications like smart contracts, reviewed protocols are supporting this technology. |
5,736 | Please write an abstract with title: Design of Mathematical Online Training Interactive Framework based on AI-assisted Data Modeling Algorithm Visualization Process, and key words: Training, Visualization, Heuristic algorithms, Computational modeling, Time series analysis, Data visualization, Mathematical models. Abstract: Based on the artificial intelligence algorithm, the data model of the optimal time series is researched and designed, and the data is classified by collecting and processing the time series data. A dynamic visual demonstration process is formed and applied to the design of the interactive framework for mathematical online training. The test results show that the 16 classic experimental algorithms of artificial intelligence courses included in the platform can be clearly and dynamically demonstrated, and the detailed description of the principles and steps of algorithm execution can help students deeply understand the execution process of the algorithm. The analysis of interactive behavior is intelligent, and can carry out targeted training according to the problems that arise in the learning process of students, thereby improving the learning efficiency of students. |
5,737 | Please write an abstract with title: Multi-objective autonomous vehicle navigation in the presence of cooperative and adversarial moving contacts, and key words: Remotely operated vehicles, Mobile robots, Navigation, Decision making, Marine vehicles, Uncertainty, Oceans, Automotive engineering, Weight control, Optimization methods. Abstract: Effective control of autonomous marine vehicles is a difficult problem that continues to increase in complexity as our aspirations and expectations become more ambitious. We discuss here two factors that lead this trend: the need to operate in environments with other moving vehicles, and the expectation that control reflect some sense of optimality where there is the opportunity and payoff for doing so. We present here a method for representing and solving multi-objective optimization problems suitable for controlling vehicles in such situations. This method is called Interval Programming (IvP). |
5,738 | Please write an abstract with title: AE-MLP: A Hybrid Deep Learning Approach for DDoS Detection and Classification, and key words: Denial-of-service attack, Feature extraction, Computer crime, Random forests, Deep learning, Neurons, Electronic mail. Abstract: Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet connectivity massively grows in recent years. Conventional shallow machine learning-based techniques for DDoS attack classification tend to be ineffective when the volume and features of network traffic, potentially carry malicious DDoS payloads, increase exponentially as they cannot extract high importance features automatically. To address this concern, we propose a hybrid approach named AE-MLP that combines two deep learning-based models for effective DDoS attack detection and classification. The Autoencoder (AE) part of our proposed model provides an effective feature extraction that finds the most relevant feature sets automatically without human intervention (e.g., knowledge of cybersecurity professionals). The Multi-layer Perceptron Network (MLP) part of our proposed model uses the compressed and reduced feature sets produced by the AE as inputs and classifies the attacks into different DDoS attack types to overcome the performance overhead and bias associated with processing large feature sets with noise (i.e., unnecessary feature values). Our experimental results, obtained through comprehensive and extensive experiments on different aspects of performance on the CICDDoS2019 dataset, demonstrate both a very high and robust accuracy rate and F1-score that exceed 98% which also outperformed the performance of many similar methods. This shows that our proposed model can be used as an effective DDoS defense tool against the growing number of DDoS attacks. |
5,739 | Please write an abstract with title: Synthetic exercises on the Web, and key words: Education, Computer languages, Java, HTML, Automation, Information technology, Educational technology. Abstract: This paper considers a teaching approach applied to an introductory computer science course. The individual work with each of the students attending such a course consists of assigning examples, exercises and problems corresponding to the respective level of the student's preparation. These exercises and problems are generated by a system that uses templates which are developed in advance. Each template is a parameterized program or program fragment written in a programming language such as C, C++, Java, etc. The parameters are XML-like elements and represent statements interpreted by a specific system. As a consequence of this, items similar to the initial program text are generated. Simultaneously, the system also generates the results from their execution. The generated examples are in HTML format and are stored on the class Website. |
5,740 | Please write an abstract with title: SectorGSnet: Sector Learning for Efficient Ground Segmentation of Outdoor LiDAR Point Clouds, and key words: Point cloud compression, Laser radar, Image segmentation, Three-dimensional displays, Semantics, Convolution, Image restoration. Abstract: Ground segmentation of outdoor LiDAR point clouds remains challenging due to its sparse and irregular nature. This paper presents SectorGSnet: a ground segmentation framework for outdoor LiDAR point clouds, aiming to accomplish this task efficiently and effectively. The framework consists of a sector encoder module and a segmentation module. The former module introduces a novel bird’s-eye-view (BEV) sector partition strategy that discretizes the point cloud into sectors of varying sizes to enhance the 2D representation ability of the point cloud. Then, the points within each sector are fed into a multimodal PointNet encoder to obtain the corresponding sector feature map. In the latter module, a lightweight segmentation network next learns binary classification from the sector feature map, and point labels are restored from the sector segmentation results. Our proposed framework is trained and evaluated on SemanticKITTI against state-of-the-art 2D projection-based approaches and achieves an excellent balance between performance and computational complexity. We conducted inference at 170.6 Hz on a desktop PC with a GTX2080Ti GPU, and also experimented on a resource-limited platform with only 10 watts of power. |
5,741 | Please write an abstract with title: Neuronal Slidding Mode Output Control Application in a Attitude for Quadrotor, and key words: Robust control, State feedback, Uncertainty, Attitude control, Computational modeling, Observers, Reliability. Abstract: The primary goal of this research report is to investigate the challenging topic of flight dynamics control-regulation over a quadrotor UAV's orientation (attitude) in the presence of wind disturbances and unmodeled dynamics. To do this, we first create a viable output feedback controller-regulator that incorporates Filters High Gain Observers (FHGO) of ultimate generation, feedback and Radial Basis Function Neural Network (RBF) compensation of estimated disturbances. Furthermore, the usage of reliable sliding mode controllers. Then, despite wind dynamics, noise in sensor outputs, velocity estimates, and common modeling mistakes, a quadrotor UAV is maintained at a given orientation utilizing such a controller. Finally, the effectiveness of the suggested controller is investigated in a simulation framework using a realistic physical model of a quadrotor UAV. |
5,742 | Please write an abstract with title: Wind and Solar Farms Site Selection Using Geographical Information System (GIS), Based on Multi Criteria Decision Making (MCDM) Methods: A Case-Study for East-Azerbaijan, and key words: Renewable energy, Geographical Information System (GIS), Multi-criteria Decision Making (MCDM), Analytic hierarchy process (AHP), Echnique for Order Preference by Similarity to Ideal Solution (TOPSIS), Vlse Kriterijumsk Optimizacija Kompromisno Resenje (VICOR). Abstract: Economic and industrial development raise the demand for energy. Renewable energies have replaced fossil fuels. because the fossil fuels emission greenhouse gases and damage the environment. The sitting of renewable power plants is of great importance because there is a direct relationship between the production efficiency and the location of the renewable power plant. In this paper, using of multi criteria decision making (MCDM) methods a suitable location for the construction of a renewable power plant is proposed. Prioritization map of the hybrid power plant was prepared using AHP, VICORE and TOPSIS. The final map is obtained of the overlap of other maps. |
5,743 | Please write an abstract with title: Compression of periodic optical pulses without propagation in dispersive delay line, and key words: Optical pulses, Optical propagation, Dispersion, Delay lines, Pulse modulation, Pulse compression methods, Phase modulation, Optical pulse generation, Laser tuning, Optical pulse compression. Abstract: Summary form only given. Conventional optical pulse compression is accomplished in two stages: first by performing quadratic phase modulation of the pulses and then propagating the modulated pulses through a dispersive delay line. We demonstrate a novel method of periodic pulse compression that does not require propagation of the pulses in a dispersive delay line. This method is based on the use of pulse repetition rate multiplication, and can be explained with the help of the temporal Talbot effect. The pulses were generated from cw radiation of a tunable laser diode. The phase modulated light was reflected from the fiber Bragg gratings and a circulator directed it to the measuring equipment. To obtain the desired pulses, fine tuning was required for the laser wavelength, the modulation frequency and the modulation index. Pulses obtained (with a rate multiplication M = 4) using four fiber Bragg gratings are shown. The original pulse repetition rate and modulation index were 6.25 GHz and 3.3 rad, respectively. |
5,744 | Please write an abstract with title: DGA Warning Values for PD Defects Obtained from Normal Data Analysis on a Transformer Experimental Platform, and key words: Partial discharges, Data analysis, Log-normal distribution, Fitting, Gaussian distribution, Transformers, Medical diagnosis. Abstract: This paper presents an approach to determine the DGA warning values for a transformer experimental platform by using the normal data from on-line DGA. In order to collect normal data and PD-defect data, an experimental platform of a 10 kV transformer with a capacity of 100 kVA is established for long-term operation. Five sets of DGA data are obtained, 1 set from the normal data, 2 sets from the PD-defect in developing-discharge stage (D1-1) and 2 sets from PD-defect in severe-discharge stage (D1-2). All sets of data are analyzed and found better suitable for the lognormal distribution, in which there are 2 parameters, µ and σ. It is found that the position parameters µ for 5 sets of data are nearly linear with the PD values and the scale parameters σ for 5 sets of data are nearly equal for certain discharges. Therefore, PD-defect data distribution can be approximately deduced from the normal data. In general, there is a common domain between the distributions of either PD-defect data and normal data or D1-1 and D1-2. A ROC curve, widely used in medical diagnosis, is employed to determine the warning values in common domain data. The optimal cut-point in common domain between the normal data and the deductive data of D1-1 is chosen as the Typical Value, and the cut-point between the deductive data of D1-1 and that of D1-2 is chosen as the Alarm Value. |
5,745 | Please write an abstract with title: A Novel Superstrate for Low RCS Antenna, and key words: Phased arrays, Varactors, Fabrication, Degradation, Patch antennas, Conferences, Scattering. Abstract: Superstrate implementation over the antenna is one of the techniques to reduce the antenna scattering. A novel design of superstrate consisting of periodic structure with varactor diode is presented to demonstrate the RCS reduction of patch antenna array. Radiation and scattering performance of two configurations of superstrate, viz. 2-layered and 3-layered are shown for both single patch and 4-element patch array. In each case, it is shown that significant RCSR is achieved over X-band without degrading VSWR and the antenna gain. |
5,746 | Please write an abstract with title: SPDC Conversion from Bound State in the Continuum in Semiconductor Metasurfaces: Polarization Properties, and key words: Polarization, Semiconductor lasers, Metasurfaces, Electrooptical waveguides, Photonics. Abstract: We study the polarization properties of photon pairs emitted via spontaneous parametric down-conversion from a nonlinear metasurface driven by symmetry-protected, bound state in the continuum. |
5,747 | Please write an abstract with title: Learning DNF concepts by constrained clustering of positive instances, and key words: Machine learning algorithms, Machine learning, Systems engineering and theory, Engineering management, Error analysis, Performance analysis, Algorithm design and analysis, Clustering algorithms, Stochastic processes, Logic. Abstract: In this paper, we define the conjunctive learnability of nominal-attribute instances space, and set up a propositional concept learning paradigm by clustering positive instances into multiple divisions. All divisions are conjunctive learnable against the total negative instances set. Similarity measuring is introduced to guide the clustering process, and a procedure to generate CNF rules for clusters is described. A post pruning procedure is designed to deal with the overfitting problem, and two criteria as minimum covering rate and minimum error rate are defined. Experiments are implemented on several data sets, and the performance of the proposed method is analyzed and compared with existing algorithms. |
5,748 | Please write an abstract with title: Predicting risk of dementia with machine learning and survival models using routine primary care records, and key words: Costs, Biological system modeling, Soft sensors, Predictive models, Boosting, Data models, Calibration. Abstract: Worldwide, it is forecasted that 131.5 million people will suffer from dementia by 2050, and the annual cost of care will increase from 818 billion USD in 2016 to 2 trillion USD by 2030, with burgeoning social consequences. Given a timely prediction of a dementia outcome in patients, appropriate mitigating interventions can be applied to reduce risk. However such prediction facilities need to be made available to wider populations, and these facilities cannot rely on specialised, costly and invasive testing (such as neuroimaging, cerebrospinal fluid collection, etc which constitute important instruments used in diagnosis), for interventions to have a meaningful quantitative impact. Hence an emerging need exists for the wider application of prognostic measures which can be deployed using lower cost data sources such as longitudinal records routinely collected by general practices. This paper proposes an efficient prediction modelling approach to the risk of dementia, using CPRD data collected from GP practices in UK, and based on machine learning in particular the Gradient Boosting Machines model combined with a survival model such as the Cox Proportional Hazard, encapsulated in a semi-supervised learning and model calibration methodology. |
5,749 | Please write an abstract with title: Tatum-Level Drum Transcription Based on a Convolutional Recurrent Neural Network with Language Model-Based Regularized Training, and key words: Music, Hidden Markov models, Decoding, Spectrogram, Convolution, Training, Feature extraction. Abstract: This paper describes a neural drum transcription method that detects from music signals the onset times of drums at the tatum level, where tatum times are assumed to be estimated in advance. In conventional studies on drum transcription, deep neural networks (DNNs) have often been used to take a music spectrogram as input and estimate the onset times of drums at the frame level. The major problem with such frame-to-frame DNNs, however, is that the estimated onset times do not often conform with the typical tatum-level patterns appearing in symbolic drum scores because the long-term musically meaningful structures of those patterns are difficult to learn at the frame level. To solve this problem, we propose a regularized training method for a frame-to-tatum DNN. In the proposed method, a tatum-level probabilistic language model (gated recurrent unit (GRU) network or repetition-aware bi-gram model) is trained from an extensive collection of drum scores. Given that the musical naturalness of tatum-level onset times can be evaluated by the language model, the frame-to-tatum DNN is trained with a regularizer based on the pretrained language model. The experimental results demonstrate the effectiveness of the proposed regularized training method. |
5,750 | Please write an abstract with title: Experiment design for MPC relevant identification, and key words: Predictive models, Magnetic resonance imaging, Open loop systems, Optimal control, Noise reduction, Chemical engineering, Shape control, Maximum likelihood estimation, Filtering algorithms, Filters. Abstract: The bias and variance properties of identified models depend on various factors including the input spectrum. These properties of an estimated model have to be shaped in such a way that the resulting model is commensurate with the controller. This paper presents a few results on experiment design for Model Predictive Controllers. It is important to minimize multi step ahead predictions, as opposed to one step ahead prediction errors, if Model Predictive Controllers are used. An optimal weighting on the model error for multi step ahead prediction errors is derived. Using this weighting, optimal input spectra are derived for the open loop systems. |
5,751 | Please write an abstract with title: 1/spl phi/ 3W grid-connection PV power inverter with partial active power filter, and key words: Inverters, Active filters, Reactive power, Power harmonic filters, Power system harmonics, Switches, Power generation, Photovoltaic systems, Solar power generation, Power supplies. Abstract: This paper presents a single-phase three-wire (1/spl phi/ 3W) grid-connection photovoltaic (PV) power inverter with a of partial active power filter (PAPF) feature, which can not only deal with PV power but filter current harmonics and improve power factor. Once the processed power exceeds the switch ratings, the inverter can reduce its output reactive power and harmonic power, while still supplying the maximum real power generated by the PV arrays. In the derivation of control laws, a limit circle is defined to confine the output power of the inverter. To determine the power that the inverter can process, the instantaneous reactive power of a 1/spl phi/ 3W system is defined and used to calculate reactive power, which can avoid complex detections of phase angle and magnitude of the fundamental component of a nonlinear load current. Simulation results and experimental measurements have verified the proposed algorithm and the feasibility of the inverter. |
5,752 | Please write an abstract with title: Feature Extraction Amazon Customer Review to Determine Topic on Smartphone Domain, and key words: Manufacturing industries, System performance, Tagging, Media, Feature extraction, Mobile handsets, Information and communication technology. Abstract: The growth of information affects social development. It makes long distance become shorter so that it is not a problem, it also changes someone of doing business activity through internal media or often called as electronic commercial or more popular with the name of e-commerce. Information about a particular product is called a review, whereas information about certain products obtained from other customer is customer review. Review is useful for consumers and manufacturing industries because determine consumer decisions in choosing a particular product. To determine a sentence that contains a particular feature of extraction on a sentence can be seen from words that contain product features directly is explicit, but there are some words that indirectly product feature or show characteristic of features is implicit. This paper aims to extract product features both explicit and implicit features to a review sentence on the mobile phone domain. The review format used is free text from the amazon e-commerce website but it raises ambiguous words to the product features, therefore takes dummy data to separate the word on product features. The method used to extract the feature is called SLTM (Sentence Level Topic Model) in previous [7] on online review. The dummy dataset, the system performance to extract the explicit feature is 76% and the implicit feature is 92.59%. While in the dataset amazon customer review, system performance to extract explicit features of 88.24% and implicit features of 60%. |
5,753 | Please write an abstract with title: Decentralized Control of Pedundulatory and Peristaltic Locomotion Inspired by Polycheates, and key words: Adaptation models, Robot kinematics, Decentralized control, Switches, Aerospace electronics, Robot sensing systems, Mathematical models. Abstract: Polychaete worms move effectively using pedundulatory locomotion (i.e., body undulation coordinated with parapodia motions) and peristalsis in response to the environment. However, the essential control mechanism underlying adaptive multi-modal locomotion in polychaetes remains unclear. In this study, we observed the locomotion when a part of the body was placed in a narrow space and found that the worm exhibited a mixed locomotor pattern along the body. Based on this finding, we proposed a decentralized control model that can produce the adaptive switch between the pedundulatory and peristaltic locomotion in polychaetes and validated it in simulation. |
5,754 | Please write an abstract with title: Performance-limitations in Cu(In,Ga)Se/sub 2/-based heterojunction solar cells, and key words: Heterojunctions, Photovoltaic cells, Zinc oxide, Reflectivity, Doping, Electron mobility, Semiconductor process modeling, Tail, Schottky barriers, Spontaneous emission. Abstract: Cu(In,Ga)(S,Se)/sub 2/ (CIGS) solar cells have been modeled using analytical and computer models. A detailed set of parameters was developed for the AMPS computer program along with a procedure for estimating band edge positions from composition depth profiles. Three solar cells were modeled. An ungraded University of Delaware absorber provided a basic set of parameter values. These were modified only in density of defects to model the other devices. Results suggest that the defect density in the absorber limited device performance. Carrier mobilities have a moderate effect on model results, while acceptor density has a much larger effect. In the Shell (Siemens) Solar device, sulfur penetration beyond the depletion region may also have contributed to lower red-response. |
5,755 | Please write an abstract with title: Data-Driven Predictive Maintenance, and key words: Maintenance engineering, Predictive maintenance, Data models, Predictive models, Mathematical models, Digital twins, Sensors, 5G mobile communication, Internet of Things. Abstract: With the growth of 5G networks, the Internet-of-Things is becoming a reality. The advances in networking, machine learning, data analytics, and robotics largely improve industrial processes. Industry 4.0 is a term for the fourth industrial revolution: the digitization and automation of manufacturing.1 Predictive maintenance is one of the techniques with high impact in today’s industry. |
5,756 | Please write an abstract with title: A Split-Type FMICW-Based Guided Wave Radar With Multisegmental Probe for Liquid Level Measurement, and key words: Radar, Liquids, Sensors, Receivers, Radar measurements, Containers, Temperature measurement. Abstract: In this paper, a specially designed guided wave radar device for measuring the liquid level in the nuclear industry is proposed. A split-type design is introduced to adapt to a strong radiation environment. An L-band frequency modulated interrupted continuous wave (FMICW) radar is designed to ensure the signal-to-noise ratio of echo signal after long-distance signal transmission, which provides the isolation between transmitter and receiver of more than 60 dB using the gating technology. To overcome the shortcomings of limited installation and maintenance space, a novel coaxial waveguide probe with a multi-segmental structure is proposed and simulated. An adaptive signal processing algorithm is developed to remove false echoes and eliminate measurement fluctuations. A prototype of the proposed measurement system is fabricated and evaluated. Static and dynamic liquid level experiments are performed in an outdoor environment to assess performance and verify the effectiveness of the proposed radar. The results show that the standard deviation measurement error of the proposed radar is within 0.4 cm. The proposed system is expected to have a high potential for applications in liquid level measurement under complex conditions. |
5,757 | Please write an abstract with title: amulog: A General Log Analysis Framework for Diverse Template Generation Methods, and key words: Databases, Particle separators, Clustering algorithms, Systems architecture, Software development management, Real-time systems, Computational complexity. Abstract: One of the ways to analyze unstructured log messages from large-scale IT systems is to classify log messages with log templates generated by template generation methods. However, there is currently no shared knowledge pertained to the comparison and practical use of log template generation methods because they are implemented on the basis of diverse environments. To this end, we design and implement amulog, a general log analysis framework for diverse log template generation methods. There are three key functions of amulog: (1) parsing log messages into headers and segmented messages, (2) classifying the log messages using a scalable template-matching method, and (3) storing the structured data in a database. This framework helps us easily utilize time-series data corresponding to the log templates for further analysis. We evaluate amulog with a log dataset collected from a nation-wide academic network and demonstrate that it works in a reasonable amount of time even with over 100,000 log template candidates. |
5,758 | Please write an abstract with title: An Adaptive Machine Learning Framework for Behind-the-Meter Load/PV Disaggregation, and key words: Load modeling, Meteorology, Data models, Machine learning, Adaptation models, Predictive models, Smart meters. Abstract: A significant amount of distributed photovoltaic (PV) generation is “invisible” to distribution system operators since it is behind the meter on customer premises and not directly monitored by the utility. The generation essentially adds an unknown varying negative demand to the system, which causes additional uncertainty in determining the total load. This uncertainty directly impacts system reliability, cold load pickup, load behavior modeling, and hence cost of operation. Thus, it is essential to create low-complexity localized models for estimating power generation from these invisible sites behind the meters. This article proposes an adaptive machine learning framework to: a) learn using weather data and a minimal number of BTM PV generation measurement sensors, b) forecast PV generation using weather, location of PV, and trained ML model at location for unmeasured BTM PV; c) use estimated PV and net load measured by smart meter or smart transformer to estimate total true load at each time step; and d) learn the specific load patterns eventually to adapt localized models. The proposed framework's core idea is to transform the data such that: a) the machine learning model can effectively utilize the time dependency of measurements; and b) the measurements are transformed into a lower dimensional space to reduce complexity while maintaining accuracy. The transformed measurements are then used to train the machine learning models for load/PV disaggregation. Machine learning models investigated include linear regression, decision tree, random forest (RF), and multilayer perceptron. The proposed framework's efficacy is demonstrated using two datasets, a real dataset from Hawaii and a simulated dataset using detailed models in GridLab-D. Several test/training split scenarios, including 90-10% split, one-month-out, one-season-out, and panel-independent split are presented to provide a thorough evaluation of the proposed framework. Results on both datasets show that the proposed framework can estimate PV generation with high accuracy using low-complexity methods. The accuracy results are comparable to higher complexity models (e.g., deep architectures), and RF is found to provide superior performance with these specific datasets compared to the other ML models investigated. |
5,759 | Please write an abstract with title: Calculating Worst-Case Response Time Bounds for OpenMP Programs with Loop Structures, and key words: Analytical models, Upper bound, Computational modeling, Heuristic algorithms, Real-time systems, Software, Dynamic programming. Abstract: OpenMP is a promising framework for developing parallel real-time software on multi-cores. Recently, many graph-based task models representing realistic features of OpenMP task systems have been proposed and analyzed. However, all previous studies did not model the loop structures, which is common in OpenMP task systems. In this paper, we formulate the workload of OpenMP task systems with loop structures as the cyclic graph model and study how to compute safe upper bounds for the worst-case response time (WCRT). The loop structures combined with the creation of tasks and conditional branches result in a large state space. %of the possible execution flows, i.e., the actual paths taken in the program to generate workload at runtime. Simply unrolling the loop and/or enumerating all the possible execution flows would be computationally intractable. As the major technical contribution, we develop a linear-time dynamic programming algorithm to compute the WCRT bound without unrolling loops or explicitly enumerating the execution flows. Experiments with both synthetic task graphs and realistic OpenMP programs are conducted to evaluate the performance of our method. |
5,760 | Please write an abstract with title: Power Scaling Law Analysis and Phase Shift Optimization of RIS-Aided Massive MIMO Systems With Statistical CSI, and key words: Massive MIMO, Rician channels, Uplink, Computational modeling, Costs, Buildings, Base stations. Abstract: This paper considers an uplink reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) system, where the phase shifts of the RIS are designed relying on statistical channel state information (CSI). Considering the complex environment, the general Rician channel model is adopted for both the users-RIS links and RIS-BS links. We first derive the closed-form approximate expressions for the achievable rate which holds for arbitrary numbers of base station (BS) antennas and RIS elements. Then, we utilize the derived expressions to provide some insights, including the asymptotic rate performance, the power scaling laws, and the impacts of various system parameters on the achievable rate. We also tackle the sum-rate maximization and the minimum user rate maximization problems by optimizing the phase shifts at the RIS based on genetic algorithm (GA). Finally, extensive simulations are provided to validate the benefits by integrating RIS into conventional massive MIMO systems. Our simulations also demonstrate the feasibility of deploying large-size but low-resolution RIS in massive MIMO systems. |
5,761 | Please write an abstract with title: Digital Innovations for Post-CoViD-19 Pandemic Recovery, and key words: COVID-19, Technological innovation, Pandemics, Navigation, Organizations, Tools, Turning. Abstract: The Corona Virus Disease-2019 (CoViD-19) that broke out in Wuhan, China in December 2019 forced businesses to scramble for solutions. These are meant to keep them afloat during and after the lockdowns and other restrictions that were imposed as precautionary measures to curb the rapid spread of the virus. Educational institutions, organizations and businesses around the world had to devise mechanisms that would enable business continuity with minimal disruptions. Consequently, most organizations utilized latest technologies to combat challenges experienced and survive the pandemic's wave, while also making reaching their clients to remain a top priority even within the pandemic amidst the associated restrictions and regulations. Thus, digital technologies offered some solutions and afforded organizations the ability to navigate the effects of the pandemic especially where physical contacts with others are enormous. Without technological tools that were deployed and utilized by organizations, most of their activities would have come to a total halt. This paper examines some lessons learnt from the CoViD-19 crisis, the need for embracing digital innovations as solutions and the various factors that individuals, businesses, and governments at various levels as well as other stakeholders should consider during the pandemic and for post-pandemic recoveries. |
5,762 | Please write an abstract with title: Computation of Multi-Scenario Hydropower Equivalents Using Particle Swarm Optimization, and key words: Hydropower, Equivalent model, Particle swarm optimization, Power system simulation. Abstract: Simulation of large hydro-thermal power systems requires several extensive simplifications and model reductions. For hydropower systems with several interconnected power stations, these reductions can be particularly challenging and are denoted Equivalent models. The purpose of the Equivalent model is to mimic a more detailed hydropower model, while decreasing computation time, to be used in larger power system models. In this paper different Equivalent models for hydropower systems have been computed with a novel approach using a Particle swarm optimization-algorithm and are evaluated with respect to accuracy in hourly and total power generation as well as computation time. For each of the Equivalent models, computation time is decreased with over 99.99 % and the difference in power production is less than 11% compared to a more detailed model. |
5,763 | Please write an abstract with title: Manufacturing reliable unlanded vias without CVD barrier layers, and key words: Manufacturing, Chemical technology, Tin, Chemical vapor deposition, Atherosclerosis, Semiconductor device manufacture, Semiconductor device reliability, Titanium, Costs, Anisotropic magnetoresistance. Abstract: As device dimensions shrink in semiconductor technology, new tools and techniques are needed to solve reliability issues due to small overlap tolerances. For the 0.25 /spl mu/m technology and beyond, Titanium Nitride (TiN) Chemical Vapor Deposition (CVD) tools and processes were developed to improve the reliability of unlanded vias with small overlap tolerances in these processes. These tools are expensive and thus cost prohibitive to implement for smaller companies. In this paper, a financially preferable solution using more conventional Physical Vapor Deposition (PVD) equipment that is already in use is presented. Depositing and anisotropically etching PVD TiN can create a protective sidewall on the underlying metal prior to the deposition of the Inter-Metal Dielectric (IMD). The resulting quality of via strings in extreme misaligned (unlanded) conditions with and without this sidewall is examined. |
5,764 | Please write an abstract with title: Study on Optimization of Passenger Flow at a Metro Station Based on AnyLogic—Case Study of Youfangqiao Station of Nanjing Metro Line 2, and key words: Rails, Simulation, Logic gates, Inspection, Software, Planning, Security. Abstract: In this study, simulation software AnyLogic was used to establish a station simulation model for a metro line. First, a basic model of the environment of the metro station was drawn, and accordingly, reasonable assumptions and simplifications were proposed. Then, a diagram of the passenger walking path was created and the simulation variables and functions for passenger flow management were designed. Considering Youfangqiao Station of Nanjing Metro Line 2 in China as an example, the real passenger flow data of this station were statistically analyzed. To simulate the station passenger flow management, input parameters such as the passenger space diameter, passenger flow generation rate, delay rate of automatic fare collection equipment and security check machine, and the number of gates were considered. Passenger flow management was optimized for the morning and evening peak periods, and reasonable suggestions were proposed based on the optimization results, providing a theoretical basis for the construction planning and pre-evaluation of station operation capacities of urban rail transit systems. |
5,765 | Please write an abstract with title: Numerical Analysis of a Tubular Phononic Crystal Sensor, and key words: Electron tubes, Acoustics, Photonic band gap, Sensors, Dispersion, Solids, Liquids. Abstract: We present a theoretical investigation of the dispersion and transmission properties of a tubular phononic crystal for sensing application. We show the existence of modes confined in a cavity with displacement field spreading over both the solid and fluid parts. Therefore, the frequency of the transmission peak associated to this mode should be sensitive to the sound velocity of the fluid filling the tube. |
5,766 | Please write an abstract with title: The PREVENTION Challenge: How Good Are Humans Predicting Lane Changes?, and key words: Vehicles, Accidents, Roads, Labeling, Delays, Cameras, Trajectory. Abstract: While driving on highways, every driver tries to be aware of the behavior of surrounding vehicles, including possible emergency braking, evasive maneuvers trying to avoid obstacles, unexpected lane changes, or other emergencies that could lead to an accident. In this paper, human's ability to predict lane changes in highway scenarios is analyzed through the use of video sequences extracted from the PREVENTION dataset, a database focused on the development of research on vehicle intention and trajectory prediction. Thus, users had to indicate the moment at which they considered that a lane change maneuver was taking place in a target vehicle, subsequently indicating its direction: left or right. The results retrieved have been carefully analyzed and compared to ground truth labels, evaluating statistical models to understand whether humans can actually predict. The study has revealed that most participants are unable to anticipate lane-change maneuvers, detecting them after they have started. These results might serve as a baseline for AI's prediction ability evaluation, grading if those systems can outperform human skills by analyzing hidden cues that seem unnoticed, improving the detection time, and even anticipating maneuvers in some cases. |
5,767 | Please write an abstract with title: Assessment of Incident Power Density on Spherical Head Model up to 100 GHz, and key words: Surface treatment, Mathematical models, Graphical models, Distribution functions, Power system measurements, Guidelines, Dipole antennas. Abstract: This article presents a technique for the accurate assessment of the spatially averaged incident power density (IPD) on a spherical human head model from 3.5 to 100 GHz. The spatially-averaged IPD is defined either by averaging components of the power density vector normal to an evaluation surface, or by averaging its norm. The electromagnetic exposure assessment is provided for a dipole antenna placed at a separation distance of 2–150 mm from the model. We compare the IPD averaged over a proposed spherical surface with differently positioned planar surfaces. Results show that, for appropriate settings of the ex- posure above 6 GHz, the IPD averaged on a spherical surface is up to 12% larger for the normal definition, while marginally lower for the norm definition. In the worst case scenario, the spatially averaged IPD on a spherical surface is up to about 30% larger regardless of the definition. Comparative analysis between the definitions of the IPD averaged on a spherical model demonstrates that the norm definition yields significantly larger values in the reactive near field at characteristic frequencies, whereby this difference is marginal out of the reactive near field. |
5,768 | Please write an abstract with title: Algorithm implementation for iris identification, and key words: Iris, Wavelet packets, Wavelet analysis, Partitioning algorithms, Cameras, Histograms, Hardware, Biometrics, Wavelet transforms, Lighting. Abstract: This paper presents an architecture dedicated to iris identification based on wavelet packet analysis and its implementation on SoPC. The identification algorithm starts with iris capture, localization and unwrapping. Then a signature is extracted thanks to wavelet packet decomposition. Two packets are enough for signature encoding. Finally, the signature is compared to a database for matching. The complete algorithm is implemented on a SoPC which is composed by a NIOS processor and some hardware IP. |
5,769 | Please write an abstract with title: Long Short-Term Memory Model Based Microaneurysm Sequence Classification in Fundus Images, and key words: Sensitivity, Image color analysis, Retinopathy, Computational modeling, Conferences, Signal processing algorithms, Signal processing. Abstract: Diabetic Retinopathy (DR) has emerged as one of the serious medical conditions over the years leading to blindness among patients. Microaneurysms (MAs) are generally the earliest objective evidence of DR captured in fundus imaging. This work proposes a novel methodology based on long short-term memory (LSTM) to exploit the sequence dependencies of 1-D feature signals extracted from MAs and aid in their classification in colour fundus images. The model is trained using 1-dimensional intensity based signals generated from various patches of preprocessed fundus images. The model is tested on e-ophtha & ROC datasets and sensitivity scores are computed against seven unique values of false positive per image. The average of these scores is utilized as performance measurement of the proposed model which shows 66.6% and 60.5% sensitivity for e-ophtha and ROC datasets, respectively. |
5,770 | Please write an abstract with title: Space Applications of a Trusted AI Framework: Experiences and Lessons Learned, and key words: Machine learning algorithms, Autonomous systems, Space missions, OWL, Software, Artificial intelligence, Research and development. Abstract: Artificial intelligence (AI), which encompasses machine learning (ML), has become a critical technology due to its well-established success in a wide array of applications. However, the proper application of AI remains a central topic of discussion in many safety-critical fields. This has limited its success in autonomous systems due to the difficulty of ensuring AI algorithms will perform as desired and that users will understand and trust how they operate. In response, there is growing demand for trustability in AI to address both the expectations and concerns regarding its use. The Aerospace Corporation (Aerospace) developed a Framework for Trusted AI (henceforth referred to as the framework) to encourage best practices for the implementation, assessment, and control of AI-based applications. It is generally applicable, being based on terms and definitions that cut across AI domains, and thus is a starting point for practitioners to tailor to their particular application. To help demonstrate how the framework can be tailored into mission assurance guidance for the space domain, Aerospace sought the involvement of the Jet Propulsion Laboratory (JPL) to engage with actual examples of AI-based space autonomy. We report here on the framework's application to two JPL projects. The first, Machine learning-based Analytics for Automated Rover Systems (MAARS), is a suite of algorithms that is intended to run onboard a rover to enhance its safety and productivity. The second, the Ocean Worlds Life Surveyor (OWLS), is comprised of an instrument suite and onboard software that is designed to search for life on an icy moon using microscopy and mass spectrometry while judiciously summarizing and prioritizing science data for downlink. Both MAARS and OWLS are intended to have minimal manual control while relying on complex autonomy software to operate within the unforgiving environment of deep space. Therefore, trusted AI for these systems is required for successful adoption of the autonomy software. To capture the needs for trust, interviews with a variety of JPL personnel responsible for developing autonomy solutions were conducted and are summarized here. Additionally, the application of the framework is presented as a means to lower the barrier for AI deployment. The intent of this document is to encourage researchers, engineers, and program managers to adopt new strategies when considering whether to leverage AI in autonomous systems. |
5,771 | Please write an abstract with title: The dynamic performance of fast digitisers used for recording non-repetitive signals, and key words: Standards, Measurement uncertainty, Ions, Acoustics, Signal resolution, Multiprotocol label switching, Generators. Abstract: The dynamic performance of fast digitisers is discussed in this paper in an attempt to answer the fundamental question: “What is the maximum instantaneous error in the recorded digital waveform of a fast non-repetitive impulse?”. |
5,772 | Please write an abstract with title: Performance analysis of space-time coding schemes for the correlated Rayleigh fading channel, and key words: Performance analysis, Fading, Rayleigh channels, Karhunen-Loeve transforms, Error probability, Integral equations, Receiving antennas, Mobile antennas, Transmitting antennas, Base stations. Abstract: In this paper, the performance of a space-time channel coding scheme is discussed in a Rayleigh fading channel with correlated fading amplitudes and an additive white Gaussian noise. A closed formula on the bit error rate is obtained by the introduction of a new method, which is based on a Karhunen-Loeve transform. The correlated fading amplitudes vector is mapped to an uncorrelated one by the Karhunen-Loeve transform. So we generalize the well-known analytical expressions for the bit error probability of the uncorrelated Rayleigh channel to the case of correlated fading one. Meanwhile, the bit error probability we obtained can be expressed by an integral over a finite interval, which can be easily evaluated numerically. Numerical result shows the correlation among the transmission path decreases the performance of the system. |
5,773 | Please write an abstract with title: Long Short-Term Memory Customer-Centric Power Outage Prediction Models for Weather-Related Power Outages, and key words: Machine learning, Predictive models, Power system reliability, Long short term memory, Meteorology. Abstract: Severe weather phenomena have become more prevalent resulting in frequent and significant power disruptions and outages. Several weather-related power outage prediction models have been developed. However, most of the developed models focus on predicting outages at the utility’s equipment level, and not at the customer’s level. This paper introduces Long short-term memory (LSTM) power outages prediction models, with high prediction accuracy that have the potential to predict outages at a single customer’s location. The developed models can be deployed into smart energy agents to assist customers in preparing for outages |
5,774 | Please write an abstract with title: Conditional Generative Adversarial Network Aided Digital Twin Network Modeling for Massive MIMO Optimization, and key words: conditional generative adversarial network (C-GAN), data augmentation, digital twin network (DTN), massive multi-input-multi-output (MIMO), pre-validation. Abstract: With the widespread use of massive multi-input-multi-output (MIMO) technology in current wireless networks, network optimization faces much higher costs due to the significantly increased angular space. Digital twin (DT), as a promising tool to enhance the effectiveness and efficiency of performance evaluation, still faces many challenges for massive MIMO optimization, where the complex channel characteristics and the system performance uncertainty over randomly distributed user equipment (UE) position both make it difficult to obtain an explicit relationship expression between the beamforming parameters at the base station (BS) and the system performance. In this article, we propose a conditional generative adversarial network (C-GAN) based digital twin network (DTN), which can fit the mapping from the beamforming to the system performance and match the distribution of system performance under a certain beamforming configuration over different UE position simultaneously. Moreover, it provides a generalized way for pre-validation of different key performance indicators (KPIs) and further raises the accuracy via data augmentation. QuaDRiGa based simulations validate the effectiveness of our proposed method in system performance modeling and KPI prediction. |
5,775 | Please write an abstract with title: Research on the recognition and location method of stacked bagged agricultural materials based on monocular vision, and key words: Image segmentation, Image recognition, Target recognition, Stacking, Signal processing algorithms, Transforms, Trademarks. Abstract: In this paper, we propose a monocular vision based recognition and location method to solve the problom of recognition and location of stacked bagged agricultural materials in the train, including image recognition algorithm based on watershed transformation and target location algorithm based on image moments. In addition, the proposed algorithms are validated by carrying out experiments on the machine vision test platform for 25kg flour bags. The experimental results showed that the image recognition algorithm based on watershed transform is good. The target location algorithm based on image moments can effectively control the camera to move to the desired position. |
5,776 | Please write an abstract with title: IoT Cooking Workflows for End-Users: A Comparison Between Behaviour Trees and the DX-MAN Model, and key words: Visualization, Computer languages, Semantics, Model driven engineering, Complexity theory, Internet of Things. Abstract: A kitchen underpinned by the Internet of Things (IoT) requires the management of complex procedural processes. This is due to the fact that when supporting an end-user in the preparation of even only one dish, various devices may need to coordinate with each other. Additionally, it is challenging— yet desirable—to enable an end-user to program their kitchen devices according to their preferred behaviour and to allow them to visualise and track their cooking workflows. In this paper, we compared two semantic representations, namely, Behaviour Trees and the DX-MAN model. We analysed these representations based on their suitability for a range of end-users (i.e., novice to experienced). The methodology required the analysis of smart kitchen user requirements, from which we inferred that the main architectural requirements for IoT cooking workflows are variability and compositionality. Guided by the user requirements, we examined various scenarios and analysed workflow complexity and feasibility for each representation. On the one hand, we found that execution complexity tends to be higher on Behaviour Trees. However, due to their fallback node, they provide more transparency on how to recover from unprecedented circumstances. On the other hand, parameter complexity tends to be somewhat higher for the DX-MAN model. Nevertheless, the DX-MAN model can be favourable due to its compositionality aspect and the ease of visualisation it can offer. |
5,777 | Please write an abstract with title: Research on individual wheel drive and control of mobile robot at bent pipeline, and key words: Wheels, Robot control, Mobile robots, Pipelines, Robot vision systems, Fuzzy control, Orbital robotics, Control systems, Inspection, Nondestructive testing. Abstract: This paper studies the passing problem of a mobile robot with three group driving wheels in the bent pipeline, provides a visual servo control system, and discusses the prediction of robot moving parameters and a fuzzy control system. Considering the special problem in such pipeline robot, the paper mainly researches an individual wheel drive control algorithm. The research results show that the algorithm has a good adaptation under different initial moving condition and complex environment. The fuzzy controller not only makes the driving motor go back to normal status, but also drives the robot pass the bent pipe quickly and improves the system efficiency. |
5,778 | Please write an abstract with title: Astrobotics: Swarm Robotics for Astrophysical Studies, and key words: Robot kinematics, Optical fibers, Optical fiber devices, Convergence, Telescopes, System recovery, Automation. Abstract: This article introduces the emerging field of astrobotics, a branch of robotics recently established to be of service to astrophysics and observational astronomy. We describe a modern requirement of dark matter studies, i.e., the generation of a map of the observable universe, using astrobots. Astrobots differ from conventional two-degreesof-freedom (DoF) robotic manipulators in two respects. First, the dense formation of astrobots gives rise to the extremely overlapping dynamics of neighboring peers, which makes the devices severely subject to collisions. Second, the structure of astrobots and their mechanical specifications are specialized due to the embedded optical fibers passing through them. |
5,779 | Please write an abstract with title: Pseudo-maximum-likelihood speech pitch extraction, and key words: Vocoders, Frequency measurement, Nonlinear filters, Telephony, Pulse measurements, Time measurement, Speech synthesis, Data mining, Speech processing, Fault diagnosis. Abstract: The pitch of a voiced speech segment may be estimated by minimizing the squared error in approximating the segment by the repeated weighted average of successive assumed pitch periods, after a "maximum-likelihood" solution originally due to Slepian. A modification is proposed which allows use of an arbitrary window function and corrects two faults of the "likelihood" function noted by Noll: a linear baseline rise and ambiguous identification of the proper peak. Computationally, the entire formulation is in the time domain. Results are presented for speech both before and after bandpass filtering to simulate telephone transmission. Comparison of these two cases implies that the algorithm is effective for speech in which the fundamental frequency itself is missing. |
5,780 | Please write an abstract with title: Bridge Type Series Resonance Transient Current Limiter for Medium-Voltage Smart Grids Application, and key words: Capacitors, Smart grids, Topology, Inductors, Fault current limiters, Transient analysis, Fault currents. Abstract: The main propose of this paper is to protect medium voltage smart grid applications from damages of the destructive fault current based on resonant type fault current limiter. Because of the series connection of a capacitor and a reactor, the Series Resonance Fault Current Limiter (SRFCL) is invisible during normal operation and shows negligible impedance in the line. During the fault, a control circuit connects a rectifier bridge to the series reactor and induces a DC voltage on it. In this instant, the series reactor is short circuited, and the series capacitor remains in the line. Thus, the impedance of the series capacitor reduces the amplitude of the fault current. |
5,781 | Please write an abstract with title: Aggregation and Comparison of Probabilistic Linguistic Term Sets with Interval Probabilities, and key words: Uncertainty, Aggregates, Decision making, Medical services, Linguistics, Programming, Probabilistic logic. Abstract: The probabilistic linguistic term set (PLTS), composed by linguistic terms and their probabilities, is effective to represent uncertain evaluations. Given that the precise probabilities are weaker than interval forms to portray uncertainty, this paper investigates the PLTS with interval probabilities. A probabilistic linguistic dominance method is proposed to determine the preference relation between PLTSs. In addition, we develop a pair of programming models to aggregate PLTSs that maximum and minimum combined PLTSs can be estimated. A framework of multi-criteria decision making is introduced to measure the performances of alternatives considering both comprehensive evaluations and the ability to achieve the toleration and expectation values of criteria. The method is illustrated by a case study of elderly health care. |
5,782 | Please write an abstract with title: Prediction of Physiological Tremor Based on Deep Learning for Vascular Interventional Surgery Robot, and key words: Deep learning, Mechatronics, Operating systems, Surgery, Prediction methods, Master-slave, Prediction algorithms. Abstract: Physiological tremor seriously affects the operation accuracy of the master-slave vascular interventional surgery robot (VISR), which is very necessary to be eliminated. However, there are some issues in the existing methods. For instant, some methods require the prior knowledge of the prediction horizon for accurate estimation tremor signal. Furthermore, these methods assume the process to be nonstationary in the given prediction horizon. Besides, the phase delay of the system has a great influence on the performance of the surgical operating system. Therefore, the effective tremor signal compensation that can be used to generate the reverse motion signal in real time is needed. The paper proposes a multi-step signal prediction method based on LSTM. Combined with the existing method, the deep learning method improves the accuracy of tremor prediction compared with the other prediction method. |
5,783 | Please write an abstract with title: Connectivity resilience assessment of urban road networks under earthquake based on Bayesian network, and key words: Resilience, Roads, Bayes methods, Earthquakes, Cognition, Seismic measurements, Time measurement. Abstract: In view of the fact that existing metrics such as reliability and vulnerability cannot effectively and comprehensively describe road network performances under sudden major disruptive events, a connectivity resilience metric together with two resilience-based component importance measures are proposed. Bayesian network (BN) is served as a modelling tool which is used to assess the road network resilience and component importance under different earthquake magnitudes, and a case study is conducted on the Nguyen and Dupuis network. The results show that the higher the earthquake level, the lower the system resilience. The road network resilience can be deduced from links resilience and critical links can be found by BN. Two resilience-based link importance measures can effectively rank the importance of links, and the importance ranks of most links change over time. All these conclusions verify the feasibility of the proposed model. |
5,784 | Please write an abstract with title: Key Points in the Determination of the Interfacial Dzyaloshinskii–Moriya Interaction From Asymmetric Bubble Domain Expansion, and key words: Magnetic domains, Saturation magnetization, Perpendicular magnetic anisotropy, Magnetic domain walls, Anisotropic magnetoresistance, Velocity measurement, Frequency modulation. Abstract: Different models have been used to evaluate the interfacial Dzyaloshinskii–Moriya interaction (DMI) from the asymmetric bubble expansion method using magneto-optics. Here, we investigate the most promising candidates over a range of different magnetic multilayers with perpendicular anisotropy. Models based on the standard creep hypothesis are not able to reproduce the domain wall (DW) velocity profile when the DW roughness is high. Our results demonstrate that the DW roughness and the interface roughness of the sample layers are correlated. Furthermore, we give guidance on how to obtain reliable results for the DMI value with this popular method. A comparison of the results with Brillouin light scattering (BLS) measurements on the same samples shows that the BLS approach often results in higher measured values of DMI. |
5,785 | Please write an abstract with title: Avatarizing Children with Autism Spectrum Disorder into Serious Games for Social Communication Skill Intervention, and key words: Training, Autism, Technological innovation, Neurons, Psychology, Games, Serious games. Abstract: Many researchers have tried to build serious games with virtual agents/characters to help children with Autism Spectrum Disorder (ASD) practice social communication skills. However, children with ASD inherently have difficulties with simulations, empathy, and comprehension of actions and emotions. Games that use virtual agents/characters don't consider these inherent defects of mirroring dysfunction of children with ASD and hence are not effective for training autistic children's social communication skills. In this paper, an intervention tool based on serious games is designed for children with ASD to train their social communication skills. By avatarizing the autistic child who is undergoing intervention in the game scenarios, they can intuitively see themselves participating in the virtual social communication situations created by the game and produce psychological hints of “I should do or say this under this situation”. We hope that this avatar-based intervention tool helps children with ASD overcome the dysfunction of the mirror neuron system and improve their social communication skills. |
5,786 | Please write an abstract with title: Decomposition of noise sources in recording applications using symbol-rate readback samples, and key words: Magnetic noise, Additive noise, Signal to noise ratio, Magnetic recording, Band pass filters, Kernel, Sampling methods, Fluctuations, Signal processing, Bandwidth. Abstract: Noise in recording applications is often modeled as a combination of additive noise and medium noise. In addition to the total noise power, the nature of the different noise processes and their relative contributions to the total noise affect detection performance. Two methods for noise decomposition that are based on symbol-rate readback samples of arbitrary channel input sequences are presented. They rely on the estimation of the variance of an ensemble of noise samples as a function of sample index, and its cross correlation with the input data sequence. Performance is assessed by using well-established models of the magnetic recording channel. |
5,787 | Please write an abstract with title: Knowledge-based Services for Creating Functional Models of Building Automation Components, and key words: Energy consumption, Conferences, Knowledge based systems, Buildings, Tools, Design tools, Complexity theory. Abstract: Building automation systems have enabled advanced applications for reducing energy consumption and providing comfort in living and working environments. This incurs increasing engineering complexity, raising the need for automated engineering approaches in the future. As a consequence, a high quantity of detailed formal models of building automation component functionality needs to be created by component manufacturers. However, this task is not yet sufficiently supported by design tools, which renders it very arduous and error-prone. As a possible solution, this paper aims to provide a foundation for developing appropriate support functionality. Based on a detailed analysis of available knowledge sources for modeling support, exemplary suggestion services are discussed and evaluated. These web-based services can be integrated in legacy modeling tools in order to reduce the overall effort of the component modeling process by 60 % to 70 %. |
5,788 | Please write an abstract with title: Practical examples used information and communication technologies in study of "Signals and Systems", and key words: Communications technology, Transfer functions, Education, Game theory, Writing, Computer aided instruction, Computational modeling, Computer simulation, Feedback, Stability analysis. Abstract: The study of Signals and Systems is one of the basic subjects of study at the Faculty of Electrical Engineering and Computing. For a better understanding of this subject, it is necessary for the students to connect theory with the practical examples. The introduction of new technologies discloses great opportunities for a high-quality organization of the study. The purpose of this paper is to shows in detail two examples where theory is linked to practice in order to achieve a better education. The examples have been chosen according to the criteria of proximity, comprehension and actuality. We assume that the majority of students taking Signals and Systems have a basic knowledge of electronics and an elementary everyday understanding of economics. This paper therefore portrays a simple electronic amplifier as the first example and a game based on a simplified economic interaction as the second example of the application of the theory of signals and systems. This is going to show how to bring the theory closer to the students through practical examples by means of ICT. |
5,789 | Please write an abstract with title: Prefix and interval-partitioned dynamic IP router-tables, and key words: Communication system routing, Table lookup, String matching, Data structures, Database management systems, Tree searching. Abstract: Two schemes - prefix partitioning and interval partitioning - are proposed to improve the performance of dynamic IP router-table designs. While prefix partitioning applies to all known dynamic router-table designs, interval partitioning applies to the alternative collection of binary search tree designs of Sahni and Kim [S. Sahni et al., (2004)]. Experiments using public-domain IPv4 router databases indicate that one of the proposed prefix partitioning schemes - TLDP - results in router tables that require less memory than when prefix partitioning is not used. Further significant reduction in the time to find the longest matching-prefix, insert a prefix, and delete a prefix is achieved. |
5,790 | Please write an abstract with title: Lameness Detection in Cows Using Hierarchical Deep Learning and Synchrosqueezed Wavelet Transform, and key words: Time-frequency analysis, Cows, Sensors, Accelerometers, Legged locomotion, Harmonic analysis, Acceleration. Abstract: Objectives: Identification of cow lameness is important to farmers to improve and manage cattle health and welfare. No validated tools exist for automatic lameness detection. In this research, we aim to early detect the cow lameness by identifying the instantaneous fundamental gait harmonics from low frequency (16Hz) acceleration signals recorded using leg-worn sensors. Methods: A triaxial accelerometer has been worn on each cow leg. Synchrosqueezed wavelet transform (SSWT) has been applied to acceleration signals to generate the initial time-frequency spectrum related to the gait. This spectrum is given as an input to a designed deep neural network including time-frequency based long short-term memory (LSTM) to estimate instantaneous frequencies at each time point. An inverse SSWT (ISSWT) is then used to recover the gait harmonic and to estimate an enhanced spectrum. Results: Validation of instantaneous frequencies has been provided for each cow leg (combined signals from 23 cows) and the time-series cross validator across the three folds are provided. The average of mean squared errors in frequencies across 3 folds for each leg is obtained as 0.036, 0.033, 0.044 and 0.042 for left-front, right-front, right-back and left-back legs, respectively. Conclusion: Estimation of instantaneous gait frequencies is proved useful for identification of cow gait phases, lameness detection, accurate estimation of gait speed, coherency in movement among the legs and identification of non-gait episodes. Moreover, the proposed method can be used as a new frequency ridge estimation method exploiting SSWT for many other applications. |
5,791 | Please write an abstract with title: Capacitor Clamped Boost Inverter for Fuel Cell-based Distributed Generation system with Battery Back Up, and key words: Low voltage, Capacitors, Power quality, Fuel cells, DC-DC power converters, Inverters, Batteries. Abstract: In this manuscript Capacitor Clamped Boost Inverter (CCBI) is utilized for the power extraction from the unregulated dc bus formed by low voltage fuel cell along with the energy storage unit. Inherent properties of CCBI offers single stage power conversion, high power quality and lower capacitor voltage stresses in the power conversion. Dual loop voltage control strategy in voltage control mode to CCBI and current mode control of Bidirectional DC-DC converter (BDC) offers effective energy management to meet the load requirement, and offers better dynamic performance under load varying condition. Furthermore, performance exploration has been carried out to assess the effectiveness of the proposed converter with the existing similar type of single stage power converters for the same dc-ac conversion. Simulation-based results proved that proposed inverter offers enhanced power quality, lower capacitor voltage stresses and enhanced life of the converter in such single stage converter systems. |
5,792 | Please write an abstract with title: Semi-analytical Modelling of Boundary-tunable Metasurface Antenna for Compressive Sensing, and key words: Computational modeling, Imaging, Switches, Metasurfaces, Frequency diversity, Metamaterials, Planar waveguides. Abstract: A proof-of-concept semi-analytical demonstration is presented for practically implementable boundary-tunable metasurface antenna. Proposed antenna consists of reverberating planar parallel-plate waveguide with two via layers on the boundary. Different radiation pattern can be generated by electronically switching vias in the inner boundary layer. This arrangement allows to select different measurement modes necessary for interrogating a scene in the computational imaging framework. The advantage of this design is increased beam diversity compared to the passive frequency tuned approach while maintaining a planar configuration. The performance of the antenna is verified by analysing the singular values of the waveguide modes inside the antenna. |
5,793 | Please write an abstract with title: Accurate Real-time Estimation of the Inertia Tensor of Package Delivery Quadrotors, and key words: Tensile stress, Mathematical model, Estimation, Payloads, Adaptation models, Numerical models, Linear regression. Abstract: The need for quadrotors to provide grasping and payload carrying abilities is ever-growing in several industries. Additional payloads attached to a quadrotor alter its dynamics and eventually affect its control system’s performance. In this work, an accurate real-time estimation of the varying mass and inertia tensor elements of a quadrotor carrying a variable payload is proposed. Parameter estimation is performed via a recursive least squares algorithm that is implemented on the quadrotor’s dynamic model using proper input-output data. Covariance resetting is integrated into the algorithm to increase the convergence rate and accuracy of the obtained estimates. The vertical motion is used to estimate the mass of the system, whereas the rotational motions around the x−, y− , and z − axes are used to identify the elements of the 3x3 inertia tensor matrix. The experiment is designed such that a persistently exciting input is generated to guarantee the convergence of the parameter estimates towards their true values. The proposed identification scheme is validated in numerical simulations and experimentation on a physical quadrotor, the Quanser QBall-2. The obtained results demonstrate the accuracy and convergence rate of the designed estimator, paving the way in front of its integration into an adaptive control system. |
5,794 | Please write an abstract with title: Evolving Lockdown Strategies to Minimize Infections in an Epidemic, and key words: Epidemics, Sociology, Evolutionary computation, Statistics, Bioinformatics, Computational biology. Abstract: In this paper we evaluate the impact of different lockdown strategies upon the total number of infections during an epidemic. The strategies are based upon the percentage of the population infected during a given time step, as well as upon the amount by which interactions must be reduced during lockdown. We use a weighted personal contact network to represent the population, its interactions, and the relative strengths of those interactions. During lockdown edges from this network are removed. We use an evolutionary algorithm to choose the set of edges to be removed so as to minimize infections, comparing different strategies. We show that allowing the evolutionary algorithm to choose which edges to remove significantly reduces the overall number of infections in comparison to random selection. In fact, the EA results for the least stringent conditions were similar or better to the random results for the most stringent conditions, showing that a judicious choice of restrictions during lockdown has the greatest effect on reducing infections. The evolutionary algorithm tends to favour a situation in which during lockdown individuals would reduce their number of contacts, as opposed to lessening the strength of their connections. |
5,795 | Please write an abstract with title: Adaptive-SMO-Based Traction Force Fluctuation Suppression Strategy Considering Suspension System for High-Speed Maglev Train, and key words: High-speed maglev, long stator linear synchronous motor (LSLSM), sliding mode observer (SMO), traction force fluctuation. Abstract: The excitation pole of the long stator linear synchronous motor (LSLSM) used to drive the high-speed maglev train is also used as the suspension electromagnet, which makes the adjustment of the suspension system affect the excitation flux linkage of the motor when the train is running at high speed, resulting in significant nonperiodic traction force fluctuations. This article proposes a traction force fluctuation suppression strategy based on the flux linkage observation. First, based on the mathematical model of the LSLSM in double feed mode, the voltage equation based on the new extended back electromotive force is derived, which is less sensitive to the changes of parameters, load current, and speed, so that the flux linkage can be estimated more accurately. Then, to meet the high dynamic requirements of flux linkage observation at high speed, a sliding mode flux linkage observer is designed and a design method of the adaptive sliding mode gain is proposed to achieve fast convergence of the system. Finally, the stator reference current required to suppress the traction force fluctuation is calculated. Hardware-in-the-loop experiments verify the effectiveness of the strategy. |
5,796 | Please write an abstract with title: Towards Robust Pattern Recognition: A Review, and key words: Pattern recognition, Robustness, Task analysis, Neural networks, Distributed control, Big Data, Machine intelligence. Abstract: The accuracies for many pattern recognition tasks have increased rapidly year by year, achieving or even outperforming human performance. From the perspective of accuracy, pattern recognition seems to be a nearly solved problem. However, once launched in real applications, the high-accuracy pattern recognition systems may become unstable and unreliable due to the lack of robustness in open and changing environments. In this article, we present a comprehensive review of research toward robust pattern recognition from the perspective of breaking three basic and implicit assumptions: closed-world assumption, independent and identically distributed assumption, and clean and big data assumption, which form the foundation of most pattern recognition models. Actually, our brain is robust at learning concepts continually and incrementally, in complex, open, and changing environments, with different contexts, modalities, and tasks, by showing only a few examples, under weak or noisy supervision. These are the major differences between human intelligence and machine intelligence, which are closely related to the above three assumptions. After witnessing the significant progress in accuracy improvement nowadays, this review paper will enable us to analyze the shortcomings and limitations of current methods and identify future research directions for robust pattern recognition. |
5,797 | Please write an abstract with title: ResViT: Residual Vision Transformers for Multimodal Medical Image Synthesis, and key words: Transformers, Biomedical imaging, Subspace constraints, Task analysis, Image synthesis, Magnetic resonance imaging, Computer architecture. Abstract: Generative adversarial models with convolutional neural network (CNN) backbones have recently been established as state-of-the-art in numerous medical image synthesis tasks. However, CNNs are designed to perform local processing with compact filters, and this inductive bias compromises learning of contextual features. Here, we propose a novel generative adversarial approach for medical image synthesis, ResViT, that leverages the contextual sensitivity of vision transformers along with the precision of convolution operators and realism of adversarial learning. ResViT’s generator employs a central bottleneck comprising novel aggregated residual transformer (ART) blocks that synergistically combine residual convolutional and transformer modules. Residual connections in ART blocks promote diversity in captured representations, while a channel compression module distills task-relevant information. A weight sharing strategy is introduced among ART blocks to mitigate computational burden. A unified implementation is introduced to avoid the need to rebuild separate synthesis models for varying source-target modality configurations. Comprehensive demonstrations are performed for synthesizing missing sequences in multi-contrast MRI, and CT images from MRI. Our results indicate superiority of ResViT against competing CNN- and transformer-based methods in terms of qualitative observations and quantitative metrics. |
5,798 | Please write an abstract with title: Sharing encountered information: digital libraries get a social life, and key words: Software libraries, Information retrieval, Consumer electronics, Collaborative work, Employment, User interfaces, Computer interfaces, Documentation, Human factors, Marketing management. Abstract: As part of a more extensive study of reading-related practices, we have explored how people share information they encounter in their everyday reading as a complement to the more traditional digital library focus on sharing intentionally retrieved materials. In twenty contextual interviews in home and workplace settings, we investigated how people encounter and save published material in the form of paper and electronic clippings. We found that sharing forms a significant use for, encountered materials. Furthermore, the function of these clippings extends far beyond a simple exchange of content to inform the recipient; in fact, the content itself may have little immediate value to the recipient. We also found the practice to be ubiquitous: all of our participants had both shared clippings with others and received them themselves. Specifically, This work reports on: (1) how sharing encountered items fits into the broader spectrum of clipping practices; (2) the function and value of the shared information; and (3) the social role of sharing the encountered information. We conclude that from a technological standpoint, we should think beyond an email model for sharing encountered information and, from a social perspective, we should attend to how sharing this sort of material contributes to the strength of social ties outside of a traditional information needs framework. |
5,799 | Please write an abstract with title: Fuzzy-Based Trustworthiness Evaluation Scheme for Privilege Management in Vehicular Ad Hoc Networks, and key words: Authentication, Vehicular ad hoc networks, Reliability, Big Data, Public key cryptography. Abstract: The vehicular ad hoc network (VANET) is a type of mobile wireless networks, where vehicles are allowed to broadcast a message to its neighbors and access data from other participants. However, how to guarantee the reliability of these broadcast messages and prevent malicious vehicles from accessing the private data of the VANETs is still an open problem to be solved. As a countermeasure, a fuzzy-based trustworthiness evaluation scheme for privilege management in VANETs is proposed in this article. In the proposed scheme, to ensure the result of trustworthiness is valid, mutual authentication with conditional anonymity between the evaluator and the vehicle to be evaluated is first employed. Then, based on the vehicle's behavioral big data, the trustworthiness of each vehicle is evaluated by utilizing the fuzzy theory. Note that the privilege of a vehicle and the reliability of the vehicle's messages are determined by its trustworthiness. Moreover, the mobility of vehicles is also considered in this article, since the location of a vehicle is not constant and the monitoring area of an road side unit is limited. The results of theoretical and experimental analyses demonstrate that the proposed scheme performs well in terms of security and efficiency. |
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