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13,500 | Please write an abstract with title: Virtual Impedance Method for Mutual Coupling Compensation, and key words: Impedance, Antenna arrays, Mutual coupling, Scattering, Dipole antennas, Array signal processing, Antenna radiation patterns. Abstract: The radiation pattern of an antenna within an array environment is modified by mutual coupling to neighboring elements, which can create unknown phase and amplitude variation on the order of 10° and 5 dB. This uncertainty in the element patterns results in beamforming errors, which can be particularly problematic for applications requiring precise pattern control. A new approach is reported to compensate for the mutual coupling of single-mode radiators using only the measured S-parameters and received signal from several far-field sources. The technique relies on the fact that dominant mode scattering from each antenna can be removed by terminating it with the proper impedance. Optimized beamforming weights are derived that compensate for mutual coupling. It is shown that implementing these optimized weights is equivalent to terminating all elements with a “virtual” impedance that cancels scattering from neighboring antenna elements (i.e., mutual coupling). Simulations of perfectly uniform and nonuniform linear dipole arrays show that compensating for mutual coupling using the proposed technique reduces the variation of the embedded element patterns by an order of magnitude compared to more conventional techniques. The proposed approach could be useful for a wide variety of antenna arrays and may even lend itself to self-calibration in the field using signals of opportunity. |
13,501 | Please write an abstract with title: Modelling and Simulation of Onboard Wire Antennas for a 3U CubeSat, and key words: Dipole antennas, Antenna radiation patterns, Solid modeling, Electromagnetics, UHF antennas. Abstract: This paper discusses the results obtained and conclusions made from modelling and simulation of the on-board antennas for a 3U CubeSat being developed by Team Anant, a group of undergraduate students at BITS Pilani. The nanosatellite features a hyperspectral camera as its primary payload. The paper initially documents the reasons for selection of a turnstile antenna for downlink in the 435 MHz band of the UHF region, and a monopole for uplink in the 144 MHz band of the VHF region. Ansys High Frequency Structural Simulator (HFSS) has been used to carry out parametric simulations for desirable network matching, radiation pattern and directivity. Further, the effect of the metallic structure of the CubeSat is examined for optimization of antenna parameters. The rationale for arriving at two particular positions for the antennas on the CubeSat is elucidated based on electromagnetic compatibility (EMC). Two different positions for the antennas are arrived at and a comparative analysis is provided. Simulations and results are also presented on the mutual interaction of the two different antennas. It is important to design, model and simulate an antenna using electromagnetic CAD tools, especially for low cost CubeSat projects. The paper is an attempt to provide nano-satellite missions with a systematic strategy for modelling and analysing wire antennas. |
13,502 | Please write an abstract with title: Training of Artificial Neural Network Using New Initialization Approach of Particle Swarm Optimization for Data Classification, and key words: Quasi-Random Sequences, QRS, Neural-Networks, Torus Sequence, TO-PSO. Abstract: Artificial neural network (ANN) has a wide variety of practice for the solution of problems in the area of data classification. Back propagation algorithm is a famous neural network (NN) traditional training approach. Hence, this classical training technique has many drawbacks like stuck in the local minima and maximum number of iterations required. Particle Swam Optimization (PSO) has been widely applied for the solutions of data classification problems. Population initialization is a vital factor in PSO algorithm, which considerably influences the diversity and convergence during the PSO's process. In this paper, the training of the ANN has been implemented with new initialization technique by using low discrepancies sequence, Torus termed as TO-PSO. In this paper, a detailed comparative performance analysis for the training of neural network is observed on nine benchmark data sets taken from UCI repository. The Results demonstrate that training of ANN with proposed initialization technique offer efficient and best substitute to traditional training approaches of the NN, which gives the solution of problems related to the data classification. Furthermore, the performance of TO-PSO has been compared with back propagation algorithm (BPA), standard PSO-NN and two other initialization approaches Sobol based PSO (SO-PSONN) and Halton based PSO (H-PSONN) for the training of ANN. The experimental results show that the proposed approach outperforms than BPA, traditional PSONN, SO-PSONN and H-PSONN in terms of converging speed and better accuracy Moreover, the outcomes of our work present a foresight that how the proposed initialization technique can be used as an efficient alternative to standard training approaches for the data classification problems. |
13,503 | Please write an abstract with title: A GaN-Based Wireless Power and Information Transmission Method Using Dual-Frequency Programmed Harmonic Modulation, and key words: Harmonic analysis, Switches, Resonant frequency, Inverters, Wireless communication, Frequency modulation. Abstract: Information transmission is often required in power transfer to implement control. In this paper, a Dual-Frequency Programmed Harmonic Modulation (DFPHM) method is proposed to transfer two frequencies carrying power and information with the single converter via a common inductive coil. The proposed method reduces the number of injection tightly coupled transformers used to transmit information, thereby simplifying the system structure and improving reliability. The performances of power and information transmission, and the method of information modulation and demodulation, as well as the principles of the control, are analyzed in detail. Then a simulation model is set up to verify the feasibility of the method. In addition, an experiment platform is established to verify that the single converter can transfer the power and information simultaneously via a common inductive coil without using tightly coupled transformers. |
13,504 | Please write an abstract with title: A Hybrid Surgical Simulator for Interactive Endoscopic Training, and key words: Training, Learning systems, Endoscopes, Biological system modeling, Instruments, Surgery, Biological systems. Abstract: Endoscopy serves as an indispensable minimally-invasive surgical procedure. Due to the limited view and non-intuitive operation of the instrument, the mastery of endoscopic manipulation requires deep medical knowledge as well as complex perception and motor skills of the surgeon. Intensive surgical training is required, and simulation-based training is of more and more importance over traditional animal- or cadaver-based approaches. Here, we developed a hybrid surgical simulator that consists of a realistic physical organ model and an artificial intelligence (AI)-driven cyber model. We built a physical model of the full urinary tract with soft materials and detailed blood vessel structures. Endourological procedures were performed to localize and treat renal calculi by a flexible endoscope. An AI algorithm detects the lesions automatically with high accuracy and provides quantitative feedback about an operator's endoscopic skills. The hybrid simulator system shows great potential as an interactive and personalized learning environment for endoscopic skills. Clinical Relevance— This work establishes a preliminary approach for realistic endoscopic training. The developed hybrid surgical simulator - with high-fidelity physical organ models and quantitative feedback - can deliver effective hands-on learning to surgeons to improve their endoscopic skills |
13,505 | Please write an abstract with title: Temporary pain relief using transcranial electrotherapy stimulation: results of a randomized, double-blind pilot study, and key words: Pain, Osteoarthritis, Electrodes, Knee, Hip, Frequency, Microprocessors, Displays, Light emitting diodes, Current measurement. Abstract: Results of a randomized, double-blind pilot study indicate that transcranial electrotherapy stimulation may be an effective treatment for the temporary reduction of pain in osteoarthritis patients. Presently, the predominant method for pain management is medication. One very different approach is the application of micro- to milliamp current applied to specific areas of the head, resulting in a release of endogenous opioids from pain management regions of the brain. For the pilot study, 64 subjects suffering from osteoarthritis of the knee and/or hip were enrolled. For two weeks prior, then during and after treatment, subject pain was self-assessed using the visual scale (VS). In addition, subjects were globally assessed by a physician. All subjects, device operators and physicians were blinded as to whether subjects were treated with an active or sham device. Data collected from the study indicate both a decrease in VS pain scores and a significant improvement (p = 0.05) in physician assessment in subjects treated with active devices compared to those treated with the sham device. |
13,506 | Please write an abstract with title: A Graph-Based Approach to Automatic Convolutional Neural Network Construction for Image Classification, and key words: Neural networks, Computer architecture, Classification algorithms, Convolutional neural networks, Task analysis, Image classification, Genetic algorithms. Abstract: Convolutional neural networks (CNNs) have achieved great success in the image classification field in recent years. Usually, human experts are needed to design the architectures of CNNs for different tasks. Evolutionary neural network architecture search could find optimal CNN architectures automatically. However, the previous representations of CNN architectures with evolutionary algorithms have many restrictions. In this paper, we propose a new flexible representation based on the directed acyclic graph to encode CNN architectures, to develop a genetic algorithm (GA) based evolutionary neural network architecture, where the depth of candidate CNNs could be variable. Furthermore, we design new crossover and mutation operators, which can be performed on individuals of different lengths. The proposed algorithm is evaluated on five widely used datasets. The experimental results show that the proposed algorithm achieves very competitive performance against its peer competitors in terms of the classification accuracy and number of parameters. |
13,507 | Please write an abstract with title: An LSTM Acceleration Engine for FPGAs Based on Caffe Framework, and key words: Field programmable gate arrays, Acceleration, Logic gates, Engines, Graphics processing units, Fixed-point arithmetic, Energy efficiency. Abstract: Recently, Long Short Term Memory (LSTM) networks have been widely used in sequence-related problem. LSTMs outperform conventional feed-forward neural networks and RNNs in many ways, since they remember patterns selectively for long durations of time. However, due to the recurrent property of LSTMs, it is hard to implement a high computing parallelism on general processors such as CPUs and GPUs. Besides, the huge energy consumption of GPU and CPU computing is a non-negligible issue for data centers. In order to solve the problems above, FPGA emerges as an ideal solution. It has the characteristics of low power and latency, which has natural advantages for the implementation of recurrent neural networks, such as LSTMs. In this paper, we propose to implement an acceleration engine for LSTM network based on FPGAs. By employing fixed-point arithmetic, systolic arrays for matrix multiplication and look up table for activate function, we optimize the LSTM on FPGA in depth. Additionally, we integrate the acceleration engine into Caffe, one of the most popular deep learning framework, to make it easier to deploy. According to the experimental results, our acceleration engine achieves 8.8X and 2.2X gains for performance, 16.9X and 9.6X gains for energy efficiency compared with CPU and GPU, respectively. |
13,508 | Please write an abstract with title: Energy-Aware Cross-Layer Offloading in Fog-RANs Using Network Coded Device Cooperation, and key words: Network coding, Scheduling, Collaboration, Receivers, Bandwidth, Radio access networks, Computer architecture. Abstract: This paper studies a Fog Radio Access Network (F-RAN) architecture that utilises the increasing storage and device-to-device communication capacities of users' smart devices (referred to as F-UEs) in order to reduce the time that the central processing unit (referred to as BBU) has to spend to serve these F-UEs and thus, increases the system's capacity. Indeed, these F-UEs can employ these capacities in cooperatively serving each other's file requests, as long as the F-UEs have the files in their storage, rather than always receiving them through the BBU. In addition, network coding (NC) can be employed to minimize the communications among the F-UEs and from the BBU to further offload the BBU resources and reduce the energy consumed in F-UEs' cooperation. This paper develops an algorithm for scheduling the file encoding and transmissions both among half-duplex F-UEs and from the BBU to minimise the consumed time-frequency resources from the BBU given constraints on the energy consumed by each F-UE for their cooperation to help preserve their battery life. The influence of the energy constraint on BBU offloading is investigated and the performance of the system under a variety of settings is evaluated through extensive simulations. The benefit of using NC is shown and the ability of the F-UEs to transmit with different power levels is also studied and shown to considerably impact the number of cooperating F-UEs and the BBU offloading. |
13,509 | Please write an abstract with title: Determination of the optimal packing configuration of a catalytic fixed-bed reactor using geometry and multi-objective optimization methods, and key words: Geometry, Shape, Utility theory, Energy dissipation, Optimization methods, Robustness, Topology. Abstract: This paper deals with the development of a geometry optimization approach to determine the optimal shape of a fixed-bed reactor where a catalytic surface reaction takes place. The investigated problem is formulated as a multi-objective optimization problem considering two antagonistic objectives: the energy dissipation in the fluid and the average concentration of reactant at the reactor outlet. The optimal solutions are subject to four constraints: (i) the process model consisting of the NavierStokes, the continuity and the convection-diffusion equations, (ii) an iso-volume constraint and (iii) two thickness constraints which allow us to take into account the manufacturability of the optimal reactors. The solution of the optimization problem is computed using the adjoint system method and the linear scalarization method which tranforms the multi-objective problem into a single-objective problem. The solution of the problem is a whole set of solutions (i.e. Pareto front) and the best optimal solution is chosen using the multi-attribute utility theory (MAUT). The best optimal shape of the reactor leads to a significant improvement of the conversion rate of 12.6% with respect to the initial shape and to an increase in energy dissipation 3.5 times higher. |
13,510 | Please write an abstract with title: Short Animation Production Using Game Engine and Motion Capture, and key words: Conferences, Virtual reality, Visualization. Abstract: Physically-Based-Rendering process and Motion Capture are adopted in this novel film based on the game engine- Unity. This film is mainly about children's problems during their growth, where the narrative method of montage is utilized. It can be viewed on streaming media platforms to promote the parents to provide their children with more companionship and caring. |
13,511 | Please write an abstract with title: Design of feedforward filters for improving tracking performances of existing feedback control systems, and key words: Filters, Feedback control, Parametric statistics, Frequency response, Frequency measurement, Size control, Frequency domain analysis, MIMO, Nanopositioning, Semiconductor device manufacture. Abstract: A design procedure for feedforward filters is proposed to improve the tracking performance of existing closed-loop systems. A parametric model is not required because it directly utilizes the frequency response of the closed-loop system, which can be measured accurately. This frequency-shaping approach enables the tradeoff between the quality of model-matching and the size of control efforts by adjusting weighting filters. Time domain specifications can be specified indirectly by approximating them in the frequency domain. The procedure is intuitively simple for SISO systems. Generalization for MIMO systems is possible by formulating convex optimization problems. A feedforward filter is designed and implemented on a nanopositioning system for semiconductor manufacturing, to improve its transient response. |
13,512 | Please write an abstract with title: A new high power efficient bit-interleaved concatenated STBC, and key words: Concatenated codes, Labeling, MIMO, Iterative decoding, Convolutional codes, Receiving antennas, Fading, Information analysis, Diversity methods, Modulation coding. Abstract: A new power efficient concatenated space-time block-code (STBC) consisting of a simple 4-states rate 1/2 convolutional code and an orthogonal STBC (oSTBC) with suitable labeling of 16QAM symbols over Rayleigh fading channel with two transmit and one receive antenna is proposed by means of extrinsic information transfer (EXIT) chart analysis. This scheme can achieve a bit error ratio (BER) below 10/sup -4/ for E/sub b//N/sub o/ = 4.4 dB at a transmission rate of 2 bits per channel use, which seems to be highly efficient w.r.t. simplicity and power efficiency. |
13,513 | Please write an abstract with title: Fault Prediction of Brightness Sensor based on BRB in Rail Vehicle Compartment LED Lighting System, and key words: Brightness, Lighting, Rails, Light emitting diodes, Temperature sensors, Predictive models, Circuit faults. Abstract: To guarantee the normal workflow and accurate brightness adjustment, it is important to predict fault of brightness sensor in rail vehicle compartment LED lighting system. In this paper, a BRB (belief rule base) based fault prediction model is proposed to accurate brightness adjustment and reliability based on the analysis of the failure mechanism of the brightness sensor in the rail vehicle compartment LED lighting system. The fault prediction model based on BRB can make full use of the system's expert prior knowledge, which can fuse the system feature quantity to achieve accurate fault prediction of the brightness sensor. In this process, the parameters of the model are updated by iterative estimation algorithm to compensate for the inaccuracy of expert knowledge. Finally, in order to verify the validity and accuracy of the proposed model, a case is studied by using the proposed prediction model for brightness sensor module in the rail vehicle compartment LED lighting system, which shows that the method can accurately predict the faults with qualitative knowledge and quantitative information. |
13,514 | Please write an abstract with title: Experimental Study on Heat Transfer Performance of Elliptical Loop Heat Pipe, and key words: fravity elliptical loop heat pipe, wind speed, vacuum degree, liquid filling rate. Abstract: Applying heat pipe to electric vehicle battery thermal management can make up for some shortcomings of liquid cooling and air cooling. A gravity elliptical loop heat pipe was made in this experiment. The effects of forced convection cooling wind speed in condensation section, internal vacuum of heat pipe and filling rate of heat pipe on performance were studied. The data illustrate that the larger the wind speed of the condensation section, the larger the heat transfer amount and the higher the thermal efficiency; the cooling wind speed of the condensation section has a greater influence on the thermal efficiency. As the increase of liquid filling rate, the heat transfer amount and thermal efficiency show a trend of increasing first and then decreasing. The experiment shows that the thermal efficiency reaches the highest as the liquid filling rate is 50%. The higher the degree of vacuum, the larger the heat transfer rate, and the higher the thermal efficiency. The equivalent thermal conductivity is up to 17620.5 W/(m·K) in the experiment. |
13,515 | Please write an abstract with title: Adoption of Virtual Reality in Cultural Heritage and Museum Exhibition, and key words: Visualization, Three-dimensional displays, Head-mounted displays, Personal digital devices, Glass, Virtual museums, User experience. Abstract: Nowadays, the acquisition of virtual reality display is crucial historical dues. Excavated component of museums provide a vital link to long-gone civilizations, allowing us to better comprehend their traditions, habits, and everyday routines. This research work presented a review of virtual cultural heritage exhibitions. Virtual Museum is created using traditional artifacts and virtual museum spaces. This paper presents the work done by various researchers in virtual museum technologies, visualization approaches, and different types of digital devices used for user interaction. Users interacted with artwork using head-mounted display devices, projectors, glasses, HD monitors, etc. This paper also includes measurable parameters, user experience, and work description, key fining and suggested some future work in the summarized table. But whenever designing a virtual museum many problems were faced by the developer, users, museum professionals, and museum creators according to the existing study. The results of archaeological excavations can be analyzed with the support of academics and practitioners from other fields, and a collection of knowledge about the related civilization can be created and disseminated to the greater community. Further to that, this article looks review on the artefacts position on museums and virtual museums. This paper also discusses the visualization technologies used for virtual cultural heritage and interactivity with users. |
13,516 | Please write an abstract with title: Bayesian blind source separation for brain imaging, and key words: Bayesian methods, Blind source separation, Brain, Time frequency analysis, Data analysis, Maximum likelihood estimation, Signal representations, Statistics, Frequency estimation, Fourier transforms. Abstract: This paper deals with the problem of blind source separation in fMRI data analysis. Our main contribution is to present a maximum likelihood based method to blindly separate the brain activations in an fMRI experiment. Choosing the time frequency domain as the signal representation space, our method relies on the second order statistics and exploits the inter-source diversity. It is efficiently implemented by the EM (expectation-maximization) algorithm where the time courses of the brain activations are considered as the hidden variables. The estimation variance of the STFT (short time Fourier transform) is reduced by averaging across time frequency sub-domains. The successful separation of the right and left visual cortex activations during a visual fMRI experiment, in a block design, and the extraction of only the relevant tasks corroborate the effectiveness of our proposed separating algorithm. |
13,517 | Please write an abstract with title: The Research on Predictive Function Control of Double-Pendulum Overhead Crane, and key words: Analytical models, State feedback, Cranes, Regulators, Simulation, Predictive models, Control systems. Abstract: When the quality of crane hook cannot be ignored, the system presents double-pendulum effect with higher underactuation, and the corresponding complexity and non-linearity increase, which makes the control of the system more difficult. In order to solve this problem, this article fully considers the error between the actual output and the predicted output, and applies the predictive function control (PFC) strategy to the positioning and anti-sway system of the double-pendulum overhead crane. According to the nonlinear mathematical model, the T-S fuzzy model is designed, and the linear quadratic regulator (LQR) is used to obtain the state feedback matrix to stabilize the controlled object, obtain the generalized controlled object, and discretize the obtained generalized controlled object. And using it as a predictive model to design a predictive function controller for a double-pendulum overhead crane. Simulation results show that the proposed method can not only realize rapid positioning, but also effectively suppress the pole swing and residual swing, and it still has good stability and robustness under the condition of adding disturbance or changing parameters. |
13,518 | Please write an abstract with title: Soft Decision Signal Detection of MIMO System Based on Deep Neural Network, and key words: Biological neural networks, Training, Neurons, Signal detection, MIMO communication, Transmitting antennas. Abstract: This paper proposes a multiple-input multiple-output (MIMO) soft decision signal detection method for a timevarying communication system. In this algorithm, the training samples, including system channel state information and received data, are input to a deep neural network (DNN), and then we employ cross-entropy loss function and root mean square propagation (RMSProp) descent algorithm to offline train and optimize the parameters of the DNN. Besides, the output layer of the DNN uses the sigmoid function as the activation function, and the negative value of the input value of the sigmoid function is the log-likelihood ratio (LLR). In this way, we can obtain the LLR value via removing the sigmoid function during the online testing without the complicated process of calculating the LLR value. Combining the DNN with the soft decision technology improves signal detection performance. Simulation results show that the proposed algorithm is better than the MMSE algorithm and similar to ML algorithm. |
13,519 | Please write an abstract with title: Partitioning Analysis in Temporal Decomposition for Security-Constrained Economic Dispatch, and key words: Economics, Processor scheduling, Conferences, Computational modeling, Loading, Parallel processing, Scheduling. Abstract: Distributed optimization algorithms are proposed to, potentially, reduce the computational time of large-scale optimization problems, such as security-constrained economic dispatch (SCED). While various geographical decomposition strategies have been presented in the literature, we proposed a temporal decomposition strategy to divide the SCED problem over the considered scheduling horizon. The proposed algorithm breaks SCED over the scheduling time and takes advantage of parallel computing using multi-core machines. In this paper, we investigate how to partition the overall time horizon. We study the effect of the number of partitions (i.e., SCED subproblems) on the overall performance of the distributed coordination algorithm and the effect of partitioning time interval on the optimal solution. In addition, the impact of system loading condition and ramp limits of the generating units on the number of iterations and solution time are analyzed. The results show that by increasing the number of subproblems, the computational burden of each subproblem is reduced, but more shared variables and constraints need to be modeled between the subproblems. This can result in increasing the total number of iterations and consequently the solution time. Moreover, since the load behavior affects the active ramping between the subproblems, the breaking hour determines the difference between shared variables. Hence, the optimal number of subproblems is problem dependent. A 3-bus and the IEEE 118-bus system are selected to analyze the effect of the number of partitions. |
13,520 | Please write an abstract with title: Gate oxide integrity issue caused by wall-related process drift in plasma etching, and key words: Plasma applications, Etching, Cleaning, Plasma sources, Plasma diagnostics, Plasma properties, Plasma measurements, Plasma materials processing, Performance loss, Production. Abstract: Different gate oxide loss in polysilicon gate etching has been found when the chamber wall condition changes, which might affect the consistency of device performance in IC production. In this work, the mechanism of wall-related process drift has been studied through etch performance evaluation and plasma diagnostics. The root cause of this issue has been identified as significant plasma property change due to the variation of surface recombination rate, of reactive free radicals with wall condition. |
13,521 | Please write an abstract with title: Teaching speech to the deaf:Can a computer help?, and key words: Education, Speech, Deafness, Auditory system, Tongue, Bridges, Fasteners, Timing, Shape control, Computer displays. Abstract: This paper describes an attempt to develop a computer-based system of speech-training aids for the deaf. Some of the problems associated with the speech of the deaf are briefly reviewed. Reasons for attempting to apply a digital computer to the problem of speech training are given. The system and its display capabilities are described. The importance of evolving such a system through a close interaction of developers and users is stressed. |
13,522 | Please write an abstract with title: Learning Spatio-Temporal Representations With Temporal Squeeze Pooling, and key words: Convolution, Neural networks, Streaming media, Data mining, Task analysis, Speech processing, Optical flow. Abstract: In this paper, we propose a new video representation learn¬ing method, named Temporal Squeeze (TS) pooling, which can extract the essential movement information from a long sequence of video frames and map it into a set of few im¬ages, named Squeezed Images. By embedding the Tempo¬ral Squeeze pooling as a layer into off-the-shelf Convolution Neural Networks (CNN), we design anew video classification model, named Temporal Squeeze Network (TeSNet). The re¬sulting Squeezed Images contain the essential movement in¬formation from the video frames, corresponding to the op¬timization of the video classification task. We evaluate our architecture on two video classification benchmarks, and the results achieved are compared to the state-of-the-art. |
13,523 | Please write an abstract with title: Integration of Data Distribution Service into Partitioned Real-time Embedded Systems, and key words: Embedded systems, Systems architecture, Quality of service, Computer architecture, Real-time systems, Unmanned aerial vehicles, Middleware. Abstract: Data Distribution Service (DDS) middleware facilitates interoperability and portability of components by building the underlying communication network in mixed-criticality systems with real-time requirements, especially those in conformity with Future Airborne Capability Environment (FACE) technical standard. Partitioning is the key technology permitting applications with different levels of criticality to execute in a same hardware on strict isolation in time and space. A system architecture is proposed to realize the integration of DDS into partitioned real-time embedded systems compliant with ARINC- 653 specification. The architecture allows communications among applications through the DDS middleware, whether they are executed in a partitioned system or not. Then an Unmanned Aerial Vehicle (UAV) combat scenario is simulated to exemplify the design feasibility. Evaluation tests show the communication stability can be obtained whether an ARINC-653 compliance system interconnect with heterogeneous systems or homogeneous systems. Based on the reliable configuration, the average communication time is stable at around 272.60μs in former situation and 281.32μs in the latter. And the specific performance difference between the two cases is further analyzed. |
13,524 | Please write an abstract with title: ASCAPE: An open AI ecosystem to support the quality of life of cancer patients, and key words: Hospitals, Conferences, Sociology, Ecosystems, Machine learning, Data models, Stakeholders. Abstract: The latest cancer statistics indicate a decrease in cancer-related mortality. However, due to the growing and ageing population, the absolute number of people living with cancer is set to keep increasing. This paper presents ASCAPE, an open AI infrastructure that takes advantage of the recent advances in Artificial Intelligence (Al) and Machine Learning (ML) to support cancer patients’ quality of life (QoL). With ASCAPE health stakeholders (e.g. hospitals) can locally process their private medical data and then share the produced knowledge (ML models) through the open AI infrastructure. |
13,525 | Please write an abstract with title: Motif discovery in upstream sequences of coordinately expressed genes, and key words: Databases, Gene expression, Computer science, Sequences, Hospitals, Genetic algorithms, Genomics, Bioinformatics, Pediatrics, Frequency estimation. Abstract: The paper presents a genetic mining approach to discover highly conserved motifs amongst upstream sequences of co-regulated genes. These motifs represent putative cis-regulatory elements that could play an important role in the co-ordinated expression of these genes. A structured genetic algorithm (St-GA) was used to evolve candidate motifs of variable length. Fitness values were assigned as a function of high scoring alignments performed with NCBI BLAST. The St-GA performed favorable with respect to existing methods on simple (l,k) insertion problems, but was unable to overcome the (l,4) insertion problem that has proved elusive to other methods. Deterministic crowding was added to the St-GA to help cope with the multimodal nature of real-world genomic data. The genetic search was performed on a set of genes selected based on their expression values as highly predictive of a subtype of pediatric ALL. Four high scoring motifs were obtained that successfully matched subsequences of cis-elements found in the TRANSFAC database. Results demonstrated that the St-GA approach to motif finding has the potential to be a competitive method for this type of problem. |
13,526 | Please write an abstract with title: Economic analysis of one type of criminal activity, and key words: Economics, Solid modeling, Analytical models, Law, Conference management, Large-scale systems. Abstract: This paper provides a formal analysis of the regularities of functioning and development of economic crimes. It was expedient to find out the conditions in which theft would not be worthwhile, i.e., supplement legal research with the economic analysis. The analysis results will help to find ways of rational crime counteraction and minimize the damage from it. |
13,527 | Please write an abstract with title: A multi-frame blocking for signal segmentation in voice command recognition, and key words: Feature extraction, Speech recognition, Distortion, Frequency-domain analysis, Information technology, Time-domain analysis, Discrete Fourier transforms. Abstract: Frame blocking segment the voice signals into overlapping frames to ensure information is maintained. Various sound features in the time domain can be extracted from the signal representation in the form of this frame. The frame blocking stage allows spectral distortion to appear at the beginning and the end of each frame, which gives rise to discontinuous signal pieces. It will appear as part of the voice feature if extracted directly in the time domain. In the frequency domain, these discontinuous signal pieces are removed using windowing techniques. However, the use of windowing techniques sometimes has an impact on changing signal information at the beginning and the end of the frame. This study proposes a multi-frame blocking method to optimize the frame blocking stage. The aim of the proposed method is to maintain the integrity of the signal information while minimizing the number of frames without losing information. In this study, the sample of the voice signal is a command signal used to control the basic movements of the robot. The absolute portion of PSD (Power Spectral Density) have used as a voice signal feature where the average values represented as grayscale images. The results of studies have shown an increase in the performance of the voice signal recognition stage by 18.29% when compared to using only conventional frame blocking methods. |
13,528 | Please write an abstract with title: Knowledge-guided Tensor Decomposition for Baselining and Anomaly Detection, and key words: Tensors, Software packages, Telecommunication traffic, Robustness, Matrix decomposition, Servers, Task analysis. Abstract: We introduce a flexible knowledge-guided penalty for incorporating known or expected patterns of activity into tensor decomposition. Our modified tensor decomposition both enables efficient identification of semantically-related patterns across data sets and provides a means for identifying anomalous patterns. Specifically, we modify the loss function for a CP tensor decomposition such that a subset of the columns of the factor matrices are guided to align with the provided knowledge. We validate the effectiveness of the method for separating baseline patterns from anomalous patterns in the context of cyber network traffic logs. After performing daily decompositions of tensors formed from network logs, we derive a set of expected components describing baseline behavior. We then decompose a new tensor, created from network logs and containing a known anomaly, providing the baseline as knowledge guidance. Notably, the anomalous behavior appears among the unguided components, resulting in drastic reduction in the search space for anomalies. Additionally, we show that our knowledge-guided decomposition is robust to incorrect knowledge in that any enforced components that are not found in the original data have low weight. Our method, implemented in the tensor software package ENSIGN, is an efficient routine that reduces the post-processing needed for an anomaly detection workflow. |
13,529 | Please write an abstract with title: Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval, and key words: Training, Costs, Adaptive systems, Conferences, Image retrieval, Reinforcement learning, Noise measurement. Abstract: Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) aims at finding a specific image from a large gallery given a query sketch. Despite the widespread applicability of FG-SBIR in many critical domains (e.g., crime activity tracking), existing approaches still suffer from a low accuracy while being sensitive to external noises such as unnecessary strokes in the sketch. The retrieval performance will further deteriorate under a more practical on-the-fly setting, where only a partially complete sketch with only a few (noisy) strokes are available to retrieve corresponding images. We propose a novel framework that leverages a uniquely designed deep reinforcement learning model that performs a dual-level exploration to deal with partial sketch training and attention region selection. By enforcing the model’s attention on the important regions of the original sketches, it remains robust to unnecessary stroke noises and improve the retrieval accuracy by a large margin. To sufficiently explore partial sketches and locate the important regions to attend, the model performs bootstrapped policy gradient for global exploration while adjusting a standard deviation term that governs a locator network for local exploration. The training process is guided by a hybrid loss that integrates a reinforcement loss and a supervised loss. A dynamic ranking reward is developed to fit the on-the-fly image retrieval process using partial sketches. The extensive experimentation performed on three public datasets shows that our proposed approach achieves the state-of-the-art performance on partial sketch based image retrieval. |
13,530 | Please write an abstract with title: Mnemonics Training: Multi-Class Incremental Learning Without Forgetting, and key words: Training, Optimization, Data models, Computational modeling, Generative adversarial networks, Gallium nitride, Training data. Abstract: Multi-Class Incremental Learning (MCIL) aims to learn new concepts by incrementally updating a model trained on previous concepts. However, there is an inherent trade-off to effectively learning new concepts without catastrophic forgetting of previous ones. To alleviate this issue, it has been proposed to keep around a few examples of the previous concepts but the effectiveness of this approach heavily depends on the representativeness of these examples. This paper proposes a novel and automatic framework we call mnemonics, where we parameterize exemplars and make them optimizable in an end-to-end manner. We train the framework through bilevel optimizations, i.e., model-level and exemplar-level. We conduct extensive experiments on three MCIL benchmarks, CIFAR-100, ImageNet-Subset and ImageNet, and show that using mnemonics exemplars can surpass the state-of-the-art by a large margin. Interestingly and quite intriguingly, the mnemonics exemplars tend to be on the boundaries between different classes. |
13,531 | Please write an abstract with title: Service-based integration of modular control components in digital manufacturing platforms, and key words: Production systems, Digital transformation, Conferences, Production facilities, Data models, Manufacturing, Complexity theory. Abstract: Due to increasing complexity on the shop floor associated with the digital transformation and growing penetration of modern production environments with smart services, the operational phase of automated production facilities is gaining additional importance. The growing range of hybrid service bundles, i.e., the combination of digital services and cyber-physical production systems (CPPS), is expanding the scope of utilization and requires the application of platform-based solutions for service integration. Efficient, scalable IT infrastructures as well as technological flexibility and independence are premises for the successful implementation of these platforms. The availability of ubiquitous communication for seamless networking of all entities also plays a central role. These prerequisites enable the vertical integration of automation components on the shop floor up to the context of strategic business processes based on continuous data and information models. This paper presents an approach for integrating CPPS elements into scalable, highly available service platforms and shows how modern control approaches can be successfully linked with smart service concepts. The exemplary use case for this is a test bench for electric drives. |
13,532 | Please write an abstract with title: SAED: A Self-Adaptive Encryption and Decryption Architecture, and key words: Hardware, Encryption, Computer architecture, Software, Acceleration, Software algorithms. Abstract: The Transport Layer Security (TLS) and Secure Socket Layer (SSL) are currently the predominant protocols to provide information security and data integrity between two communication endpoints. However, with dramatically increased network traffic, the cryptography algorithms used in SSL/TLS for encryption and decryption introduce substantial computation overhead due to the expensive CPU execution time. To accelerate the complex encryption computation, researchers have proposed novel architectures based hardware accelerators such as FPGAs, which can handle a massive amount of offloaded traffic with complex processing at very high throughput. In this paper, we study the real-world traffic workload and find that the performance of several crypto algorithms is heavily data-dependent: for small packets, software-based encryption and decryption solutions outperform hardware-based solutions, while hardwarebased solutions show higher processing speed for large packets. So there is no one-size-fits-all solution for packet processing. As a result, we propose a software-hardware co-design with quick assist technology. It combines both advantages of softwareand hardware-based approaches and be able to choose the optimal cryptography solution dynamically based on traffic status and system state. Our evaluation shows that our proposed architecture could achieve high throughput for encrypted traffic on a secured network compared to pure software or hardware solutions. |
13,533 | Please write an abstract with title: Building trust for data sourcing with the disabled community to build robust AI systems, and key words: Data privacy, Sociology, Employment, Buildings, Insurance, Machine learning, Medical services. Abstract: This research explores how to build trust between the disabled community and machine learning and AI developers. This is to encourage people with disabilities to contribute their data to build robust models that cater to a greater population. A conflicting reality exists where people with disabilities want to be accommodated in machine learning and AI systems, but they are afraid of sharing their disability status and data with AI developers. The disabled community is subjected to unfair treatment in their daily lives. Many individuals conceal their disability status to avoid being given inferior service or costly biased outcomes in healthcare, insurance premiums, and employment opportunities. When people with disabilities are not included in the data collection process, the results of the machine learning and AI systems will not cater to the needs and preferences of these minority groups. This research will examine the circumstances and privacy protection strategies will people with disabilities garner trust in contributing their data to develop inclusive AI technology solutions. The research will share the opinions of individuals from the communities with sensory disabilities and mobility issues. |
13,534 | Please write an abstract with title: Observer-Based Sliding Mode Control for Noncommensurate Fractional-order System with Mismatched Disturbances, and key words: Simulation, Observers, Numerical simulation, Robustness, Sliding mode control, Convergence. Abstract: This paper proposes a hierarchical sliding mode control strategy for a class of noncommensurate fractional-order systems with mismatched disturbances. Firstly, we design a control law based on a hierarchical terminal sliding surface. Then, based on fractional-order super-twisting algorithm, a sliding mode observer is designed to estimate the whole unknown term in control law. The proposed control method does not require information of the internal system states, but deal with mismatched disturbances effectively. Finally, numerical simulation results are shown to illustrate the effectiveness of the proposed method. |
13,535 | Please write an abstract with title: Computing Realistic Surrogate EEG for the Study of Functional Connectivity, and key words: Conferences, Estimation, Electroencephalography, Reliability, Bioinformatics. Abstract: Functional connectivity computed from electroencephalograms (EEG) can be used to better understand how the brain works. Unfortunately, estimating such connectivity is fraught with many pitfalls and can be confounded with artifacts due to volume conduction, common sources, reference scheme, etc. Devising a method to compute surrogate EEG that would be free of functional connectivity but that would reliably reproduce the effect of confounders such as volume conduction would be invaluable for statistical inference on functional connectivity. We developed such a method by simulating EEG from estimated sources and by reproducing the properties of local (but not long-range) functional connectivity in intracranial recordings. We present an example of how this approach can be used to improve the estimation of functional connectivity in EEG. |
13,536 | Please write an abstract with title: Solving dynamic tardiness problems in single machine environments, and key words: Dynamic scheduling, Processor scheduling, Dispatching, Evolutionary computation, Dynamic range, Electronic mail, Electric breakdown, Laboratories, Production. Abstract: Dynamic scheduling can be classified as partial or total. In simplest partially dynamic problems the only unknown attribute of a job is its arrival time r/sub j/. In some totally dynamic problems, other job attributes such as processing time p/sub j/, due date d/sub j/, and weights w/sub j/, are also unknown until processing. This paper proposes two approaches to face dynamic tardiness problems in single machine environments. The first approach uses, as a dispatching rule the job order provided by a total schedule S generated by an evolutionary algorithm, or by conventional heuristics for a similar static problem: same job features, processing time, due dates and weights. The second approach uses conventional heuristics and a hybrid evolutionary algorithm to reorder jobs in the waiting queue. Details of implementation of the proposed algorithms and results for a group of selected instances are discussed in this work. |
13,537 | Please write an abstract with title: Sensor Scheduling for Object Tracking with UAVs: A Comparison of Scheduling Paradigms, and key words: Adaptation models, Solid modeling, Visualization, Target tracking, Three-dimensional displays, Target recognition, Optimal scheduling. Abstract: In this paper, we consider the task of simultaneously tracking several spatially distributed ground objects (i.e., vehicles, or animals) with a single UAV equipped with an imaging sensor. The problem regarded is to actively schedule the sequence of single target observations in such a way that the kinematic state (position and velocity) of the objects to be tracked can be estimated with minimal error. The main difficulty in this task is that there is not one single optimal scheduling policy that is appropriate for all geospatial relations between the UAV and the target objects, as the quality of the target localization depends on the relative position of the object to the sensor. While many established scheduling and planning algorithms can generally be applied to this problem, their suitability varies depending on the specifics of the tracking scenario. In order to track multiple objects with only one sensor in changing situations, a trade-off has to be found between a) collecting sensor data in the right place and at the right time to achieve the lowest estimated error of a single object, and b) not focusing perception to a single object and thus neglecting observations of the others. Even if additional environment descriptors are neglected, relevant literature has proven scheduling problems akin to the one at hand to be NP-hard. We identify criteria according to which a scheduling policy can be selected and conclude with an evaluation of the procedure in simulation experiments. |
13,538 | Please write an abstract with title: Digital Twin Technologies for Measurement Virtualization Process, and key words: Graphics, Automation, Digital twin, Decision making, Process control, Production, Virtualization. Abstract: The relevance of measurement virtualization in recent years is due to the transition of processes into virtual space through the creation of digital counterparts of real physical devices. In this paper, in addition to the general provisions on digital twin technologies, an example of describing the measurement virtualization process in the LabVIEW graphical programming environment will be considered. |
13,539 | Please write an abstract with title: Towards Real-World Force-Sensitive Robotic Assembly through Deep Reinforcement Learning in Simulations, and key words: Training, Robotic assembly, Service robots, Pipelines, Training data, Reinforcement learning, Manipulators. Abstract: In manufacturing industries, vast potential exists in regards to the adaptability of automated systems through efficient robotic skill acquisition. This paper examines the use of deep reinforcement learning to automate the process of contact rich compliant assembly. Thereby, we consider an exemplary real-world use case in car assembly. To obtain training data, we use a simulated representation of the production system comprising a robotic arm which is controlled through a deep reinforcement learning agent trained with proximal policy optimization. Furthermore, we conduct a basic system analysis to improve the similarity between our physical and simulated environments. After iteratively training and evaluating different models, which distinguish through the reward design and the grade of environment variation, we validate the results on the physical hardware. We successfully obtain agents that generate expedient trajectories, which can generalize to changing environments. Success rates clearly above 90% can be achieved in simulation even with high grades of variation of the target position and the parts’ surface friction. For the transfer to the physical assembly system, we conclude that further optimization is necessary to obtain truly compliant behavior. |
13,540 | Please write an abstract with title: IoT Governance: A state of the Art and a Comparative analysis, and key words: Art, Communication systems, Internet of Things. Abstract: Governance is a complex area, yet necessary for the successful implementation of any system. In this paper, we investigate the state of art of Internet of Things governance, by studying different existing approaches and frameworks, comparing, and mapping them towards our defined IoT requirements. Our findings indicate that the existing frameworks do not fully comply with the requirements, and that there is a need for a new and generic IoT governance framework to be proposed. |
13,541 | Please write an abstract with title: The Role of Artificial Intelligence in Kinetic Targeting from the Perspective of International Humanitarian Law, and key words: Heart, Law, Weapons, Surveillance, Force, Process control, Reconnaissance. Abstract: The use of artificial intelligence (AI) in kinetic targeting is an emotive issue. Human Rights Watch (HRW) is a prominent campaigner against Lethal Autonomous Weapons Systems (LAWS) and has expressed concern these systems are fundamentally at odds with the international humanitarian law (IHL) framework for armed conflict. This framework places human control over the use of lethal force at the very heart of the targeting process. HRW asserts that the ceding of human control to AI-enabled capabilities may undermine and gradually erode the IHL framework, leaving the battlespace legally ungoverned and civilians unprotected. Concerns about the military use of AI have been exacerbated by the actions and narratives of some nations that are perceived as competing in an Al arms race. However, the debate about AI has been clouded by the fact that it focuses excessively on LAWS and human control. As a result, very little consideration is given to other potentially positive uses of AI technology in targeting. These include AI's role in Intelligence, Surveillance and Reconnaissance and Information Operations. This paper seeks to present a more nuanced examination of the role of AI in kinetic targeting and how it may affect compliance with IHL. The legal, ethical and technical arguments against and in favour of the use of AI will be examined. Finally, a way forward on this complex and emotive issue is proposed that offers a means to reinforce IHL whilst accepting that advances in technology will continue. |
13,542 | Please write an abstract with title: On Solving the On-Demand Grocery Delivery Problem, and key words: Companies, Routing, Supply chains, Industrial engineering, Data models, Computational modeling, Urban areas. Abstract: With the rise of digitalization, customer expectations, and urbanization rates in cities, on-demand commerce is proving to be very promising, because of the flexibility offered to its consumers. This flexibility reveals many challenges regarding the delivery times claimed by customers. In this work, we address a new MILP model for the on-demand grocery delivery problem that assigns time windows starting from sets of time windows filled by customers when they order their groceries, while minimizing the total routing costs. The proposed model was firstly assessed on realistic data from a hypermarket in the northern suburbs of Tunis, Tunisia. The promising results reveal outlines for future work. |
13,543 | Please write an abstract with title: Performance analysis of dynamic TDM-transport for GSM voice and GPRS/EDGE packet data services, and key words: Performance analysis, GSM, Ground penetrating radar, Wideband, Codecs, FAA, Bandwidth, Admission control, Resource management, Protection. Abstract: Today's GSM and GPRS mobile networks are based on static 16 kbps terrestrial transport on the Abis interface using E1/T1 lines. For the introduction of the high data rate GPRS coding schemes such as CS4 with up to 20 kbps, EDGE with up to 59.2 kbps and high quality wideband adaptive multirate voice codecs with up to 23.85 kbps the terrestrial Abis capacity per air interface radio channel has to be extended. With FAAS a fully dynamic allocation strategy of n/spl times/16 kbps subslots is proposed on a per site basis for both voice and data to optimally match the capacity requirements of high bandwidth radio channels. The approach includes bringing up and releasing Abis resources out of the Abis resource pool on demand. The interaction with admission control, radio resource management and link adaptation involving upgrade and downgrade procedures is taken into account. To avoid unacceptable voice blocking a new concept for voice protection is included. Detailed simulation results for different cell configurations are presented for voice only and mixed voice and GPRS/EDGE packet data scenarios at varying load, which allow the appropriate dimensioning of the Abis resource pool per site. Depending on the cell load capacity gains up to 70% (typically 30-40% for medium load) can be achieved compared to a static Abis allocation approach promising considerable cost savings for operators. |
13,544 | Please write an abstract with title: Decentralized Multi-setting Adaptive Distribution Protection Scheme for Directional Overcurrent Relays, and key words: Relays, Circuit faults, Peer-to-peer computing, Fault diagnosis, Adaptive systems, Layout, Energy resources. Abstract: Widespread integration of distributed energy resources (DERs) in the power distribution system has left the conventional protection schemes ineffective in adequately identifying and isolating a fault. Hence, modern protection schemes should be able to adapt to these variations and modify the protective device's settings to ensure effective protection coordination. Although prior works have addressed this issue using extensive communication-based methods (centralized or peer-to-peer), the actual implementation of these methods is economically less viable shortly considering the present infrastructure. However, with the advent of modern digital relays, protection schemes can be made adaptive yet keeping them decentralized and hence, easily implementable and deployable. The work proposed in this paper aspires to achieve this goal by utilizing the commonly used protective devices such as directional overcurrent relays in the power distribution systems by storing versatile setting groups enabling better observability of the relays towards fault identification and isolation in the absence of extensive communication links. |
13,545 | Please write an abstract with title: Design and Development of Portable Supervisory Unit and Programmable Automation Controller (PUSPAC), and key words: Industries, Industrial electronics, Computer languages, Automation, Protocols, Software, Picture archiving and communication systems. Abstract: This paper presents the design and development of an innovative industrial automation device named as “Portable Supervisory Unit and Programmable Automation Control (PUSP AC)” which works as a RTU (Remote Terminal Unit) and also as a PAC (Programmable Automation Controller). Typically, popular industrial automation systems like SCADA are implemented in larger industries over a robust network of various control, network, and peripheral devices. In some setups a compact standalone PLC like system ‘PAC’ is also used which includes the control, communication, and interface elements in a single device. The PUSP AC device gives the flexibility to use it with a remote MTU/computer or with implementation of local control logic through high-level programming languages. Though these automation devices are functionally similar across vendors, most of the commercial ones do not talk much about their hardware as well as software implementation. The PUSP AC is a modular platform for the students and researchers to learn and develop various industrial automation applications and protocols. The resources required for a typical automation setup is available in a single portable device along with the required software support. |
13,546 | Please write an abstract with title: Metagrating for Single Order Diffraction with High Efficiency Based on Bianisotropic Particles, and key words: Electric potential, Beam steering, Diffraction, Conferences, Reflection, Information and communication technology. Abstract: A novel metagrating is proposed to achieve single order diffraction. The proposed unit has electric and magnetic hybrid response. The unit is composed of asymmetrical patch. By introducing magnetic response, the element will break the symmetry of diffraction. One of the first order diffraction is canceled and the energy is totally reflected into the other order at 10GHz. Besides, the diffraction efficiency is higher than 80% from 9.4GHz to 11.1GHz. The simulated far field pattern shows good agreement with prediction. The proposed design provide a highly efficient method to suppress 0 and +1 order diffraction and simplify the difficulty of design, paving the way for further applications of beam steering. |
13,547 | Please write an abstract with title: Medial Spectral Coordinates for 3D Shape Analysis, and key words: Deep learning, Point cloud compression, Computer vision, Solid modeling, Three-dimensional displays, Shape, Computational modeling. Abstract: In recent years there has been a resurgence of interest in our community in the shape analysis of 3D objects repre-sented by surface meshes, their voxelized interiors, or surface point clouds. In part, this interest has been stimulated by the increased availability of RGBD cameras, and by applications of computer vision to autonomous driving, medical imaging, and robotics. In these settings, spectral co-ordinates have shown promise for shape representation due to their ability to incorporate both local and global shape properties in a manner that is qualitatively invariant to iso-metric transformations. Yet, surprisingly, such coordinates have thus far typically considered only local surface positional or derivative information. In the present article, we propose to equip spectral coordinates with medial (object width) information, so as to enrich them. The key idea is to couple surface points that share a medial ball, via the weights of the adjacency matrix. We develop a spectral feature using this idea, and the algorithms to compute it. The incorporation of object width and medial coupling has direct benefits, as illustrated by our experiments on object classification, object part segmentation, and surface point correspondence. |
13,548 | Please write an abstract with title: 900-mc PTM Over-the-Horizon Radio Link, and key words: Radio link, Bandwidth, Radio transmitters, Testing, Laboratories, Frequency, Pulse modulation, Polarization, Filters, Repeaters. Abstract: An experimental over-the-horizon radio link has been installed and tested for several months by the Federal Telecommunication Laboratories. Its chief purpose has not been to study propagation, although several interesting results may appear, nor to establish a commercially usable communication facility, but rather to study the application of this relatively unexploited type of propagation to multi-channel transmission, particularly that using ptm, pulse-time modulation. |
13,549 | Please write an abstract with title: Structurally integrated antennas for remote sensing, and key words: Remote sensing, Aircraft, Dipole antennas, Loaded antennas, Antenna arrays, Aerodynamics, Shape, Finite element methods, Automotive components, Azimuth. Abstract: This paper presents the performance of conformal, load-bearing antenna arrays embedded into the wing structure of a conceptual remote sensing joined-wing aircraft. The antenna was analyzed for a wing that was deflected due to typical aerodynamic loads. Some of the basic array theory is discussed, and the technical approach for this research is outlined. Results of this research effort indicate that wing deflections due to typical aerodynamic loads have a significant effect on the pointing accuracy of the main beam of the antenna array, and must be considered in beam steering. |
13,550 | Please write an abstract with title: Study of Backward Bent Duct Buoy, and key words: Turbines, Testing, Ducts, Navigation, Power generation, Acceleration, Shape, Petroleum, Large-scale systems, Stability. Abstract: Small wave power generators for navigation aids were used in practical in this 20 years, large wave power generator for island or land power supply is also developed in this 10 years. Backward Bent Duct Buoy (BBDB) is a new type buoy which has a Horizontal duct openning to backward. Single fuselage and twin fuselage BBDB were tested on a water tank, high electric generation, high energy conversion efficiency by wave,and low drag force by current were observed. Air pressure ratio values for both the backward facing and frontward facing are compared, and the reason of high output of BBDB (backward facing) is explained using water tank data. The floating wave power buoy can be dramatically improved by using the BBDB concept. This BBDB will be the most economical pneumatic wave energy conversion system for the island communities. |
13,551 | Please write an abstract with title: Challenges in Developing Desktop Web Apps: a Study of Stack Overflow and GitHub, and key words: Knowledge engineering, Companies, Tools, Libraries, Data mining, Open source software, Software development management. Abstract: Software companies have an interest in reaching the maximum amount of potential customers while, at the same time, providing a frictionless experience. Desktop web app frameworks are promising in this respect, allowing developers and companies to reuse existing code and knowledge of web applications to create cross-platform apps integrated with native APIs. Despite their growing popularity, existing challenges in employing these technologies have not been documented, and it is hard for individuals and companies to weigh benefits and pros against drawbacks and cons.In this paper, we address this issue by investigating the challenges that developers frequently experience when adopting desktop web app frameworks. To achieve this goal, we mine and apply topic modeling techniques to a dataset of 10,822 Stack Overflow posts related to the development of desktop web applications. Analyzing the resulting topics, we found that: i) developers often experience issues regarding the build and deployment processes for multiple platforms; ii) reusing existing libraries and development tools in the context of desktop applications is often cumbersome; iii) it is hard to solve issues that arise when interacting with native APIs. Furthermore, we confirm our finding by providing evidence that the identified issues are also present in the issue reports of 453 open-source applications publicly hosted on GitHub. |
13,552 | Please write an abstract with title: Design of oscillating system for millimeter wave generator, and key words: Argon, Helium, Millimeter wave communication, Millimeter wave technology, Microwave oscillators, Microwave technology, Organizing, IEEE catalog, Hidden Markov models, Rail to rail inputs. Abstract: The problem of creation and results of implementation of method of numerical synthesis of oscillating system for millimeter wave generator, based upon the numerical electromagnetic field analysis are discussed |
13,553 | Please write an abstract with title: Preliminary Investigation of Visual Information Influencing Driver’s Steering Control based on CNN, and key words: Visualization, Analytical models, Neural networks, Psychology, Machine learning, Optical flow, Cybernetics. Abstract: Understanding the relationship between driving behavior and visual information is an important issue in order to understand driving behavior holistically. In this study, we constructed a driver model that reproduces the driver's steering behavior from visual information based on the Convolutional Neural Network (CNN) with human physical characteristics. We obtained the driving behavior in a simulator study to train the proposed CNN model. Which region in the visual field influencing drivers' steering behavior was analyzed using the results of the feature maps generated by the trained CNN model and the driver's gaze behavior. The results indicate that the drivers perform steering action using the information within 20 degrees from the gaze point. |
13,554 | Please write an abstract with title: 3D Reconstruction with Spherical Cameras, and key words: Image reconstruction, Three-dimensional displays, Estimation, Cameras, Feature extraction, Surface reconstruction, Task analysis. Abstract: The goal of image-based 3D reconstruction is to establish a high-quality 3D expression from images. In order to achieve a high-resolution and real-time 3D model, inspired by the open source COLMAP, we propose a novel framework (3DMAP) to reconstruct 3D scenes based on spherical cameras. Unlike traditional methods which focus on building a 3D plane by Poisson distribution function, our method illustrates the key processes of 3D reconstruction: locating the camera based on global feature, estimating the scene’s relative depth from monocular panoramic images, and obtaining a high-quality 3D surface reconstruction. In the camera locating part, we use a global descriptor augmentation model to build a labeled panorama dataset GDAP, in which the images are captured by our designed spherical cameras; In the depth estimation part, we propose a new network UMDE that can estimate the depth of both indoor and outdoor scenes; Finally, in the 3D surface reconstruction section, we turn the reconstruction problem to a graph optimization problem, called GraphFit, in which, we optimize the point clouds with s-t graph and smoothing method successively. We conduct experiments on our own dataset to demonstrate the effectiveness of our proposed 3DMAP framework. Experimental results show that our 3DMAP has achieved good evaluation scores and visual effects. |
13,555 | Please write an abstract with title: Analysis of a Triple-Stator Axial-Flux Spoke-Type Permanent Magnet Vernier Machine, and key words: Torque, Stator windings, Rotors, Windings, Air gaps, Reactive power, Toroidal magnetic fields. Abstract: In this article, an axial-flux permanent-magnet (PM) Vernier machine with the triple-stator, spoke-type PM rotor, and toroidal winding wound on the innerstator is proposed. Benefited from the flux focusing spoke-type PM rotor and short end length toroidal winding, the proposed machine has a high torque density and the improved power factor. Based on the air-gap permeance function, the analytical expression of the proposed machine is derived to qualitatively analyze the machine's performance. The quasi-three-dimensional (3-D) finite element analysis (FEA) is adopted to optimize the design parameters, such as innerstator diameter, PM thickness, and slot opening width. The quasi-3-D FEA results match well with the 3-D FEA. The 3-D FEA results show the torque densities of the proposed machine reach 49.4 Nm/L and 11.4 Nm/kg, respectively, under the 232 A/cm average electrical loading. The performances, such as overload capacity, PM demagnetization, and PM and core losses, are also analyzed by 3-D FEA. The comparison with the other axial-flux PM Vernier machine is conducted, and the results reveal that the proposed machine has the great advantages of the torque density and power factor. Since the prototype is not built, in this article, the assembly scheme and thermal behavior of the proposed machine are discussed. |
13,556 | Please write an abstract with title: Classification of RSS (Ribbed Smoke Sheet) Based on Presence or Absence of Fungus using the NN (Neural Network) Perceptron Method, and key words: Fungi, Training data, Artificial neural networks, Rubber, Surface treatment, Sorting, Testing. Abstract: Indonesia is an exporter of natural rubber. One type of processed rubber used as export material is a sheet of smoked rubber or Ribbed Smoked Sheets (RSS) rubber. The quality of Ribbed Smoked Sheets greatly affects the increase in rubber exports. The quality of Ribbed Smoked Sheets has been stipulated in SNI 06-001-1987 and the International Standards of Quality and Packing for Natural Rubber Grades (The Green Book). The process of determining the quality of Ribbed Smoked Sheets is also called the sorting process. However, in some rubber plantations, the process of sorting is still done manually by observing the presence or absence of mold on the surface of the Ribbed Smoked Sheets in plain sight so as to produce inaccurate and subjective qualities. Therefore, this study is intended to carry out a classification process based on the presence of mold on the Ribbed Smoked Sheets automatically. This research uses image processing with rubber sheet image as input and classification results as output. The classification process of Ribbed Smoked Sheets uses the Neural Network Perceptron method with two classifications, namely moldy Ribbed Smoked Sheets and non-moldy Ribbed Smoked Sheets. This study uses 1000 pieces of Ribbed Smoked Sheets images as training data and 50 images of smoke rubber sheet as test data, each test has 100 pieces with an accuracy value of 96% with the best epoch value on the 4th epoch |
13,557 | Please write an abstract with title: Multi-micro-controller-based implementation of 3-phase inverters on industrial scale, and key words: Inverters, Costs, Electronics industry, Electronic components, Digital modulation, Software algorithms, Hardware, Software performance, Circuit testing, Product design. Abstract: A simple, low cost design and implementation of 3-phase industrial inverter unit has been developed by employing commonly used electronic components. The unit is based on space vector modulation principle and applies the simple scalar control algorithm constant V/F. Digital hardware circuit ideas as well as software function implementation in the proposed inverter add good features to its performance. The proposed industrial unit has been tested under different operating conditions and it proofs its outstanding features. It is planned to introduce this design as a product into industry in different sectors. |
13,558 | Please write an abstract with title: Sampling methods for improved benthic habitat maps based on reducing integrated Bernoulli variance, and key words: Adaptation models, Autonomous underwater vehicles, Closed-form solutions, Sea floor, Sampling methods, Data models, Logistics. Abstract: Oceanographic sampling to improve our knowledge about benthic habitats is common nowadays. Underwater vehicles are used to explore the seafloor to enable refined habitat maps, but considering the limited available resources during the sampling efforts, one must plan the deployments carefully. This question of effective sampling designs for underwater vehicles motivates our work. We aim to improve the sampling by using statistical models for the habitat features and to define a sampling criterion based on expected information gain. The criterion we use here is the expected integrated Bernoulli variance which we relate to the variance of presence-absence of corals in our example. Under modeling assumptions relying on a latent Gaussian model and logistic models for presence-absence data, we show partly closed form solutions for this criterion. This enables effective calculations of several possible designs, which is required in adaptive operations as is sometimes useful on for instance autonomous underwater vehicles. We illustrate the criterion in synthethic examples and in a retrospective analysis of ground truth dataset from the Trondheim fjord in Norway. |
13,559 | Please write an abstract with title: Classification of Syncope in Front-Loaded Head-Up Tilt Test with Support Vector Machine, and key words: Support vector machines, Sensitivity, Protocols, Sociology, Signal processing algorithms, Signal processing, Physiology. Abstract: Syncope describes a condition that causes a brief period of unconsciousness. It leads to a range of undesirable outcomes, including people suffering from fractures or having their bones broken. Clinically, a standard assessment protocol in syncope, head-up tilt (HUT) table test, was introduced. However, this assessment is limited with its unstable sensitivity and time consuming (40-45 minutes of tilting). Therefore, the aim of the study is to design an algorithm to classify subjects with and without syncope based on physiological signals (electrocardiography and blood pressure) acquired from front-loaded HUT test. The study selected a total of 52 people, 25 of whom were syncope negative and 27 of whom had syncope. Subject was rested in supine position for 10 minutes, followed with tilting at 70-degree on a tilt table for 20 minutes. Once the subject is tilted, an 800 micrograms of glyceryl trinitrate (GTN) was administered. A series of physiological signal processing and relevant hemodynamic parameters were computed. Then, feature selection was carried out with recursive feature elimination (RFE), to eliminate and determine the optimum number of features. A support vector machine (SVM) classifier was then used to classify the selected features via 5-fold cross-validation. Our model achieved an accuracy of 86.5%, precision of 85.7%, and recall of 88.9%. For patient evaluation, the proposed methodology is a viable strategy for determining if a patient is syncope positive or not. |
13,560 | Please write an abstract with title: Mesh Network Reliability Analysis for Ultra-Reliable Low-Latency Services, and key words: Measurement, Mesh networks, Costs, Computational modeling, Markov processes, Routing, Reliability engineering. Abstract: In a mesh network, to ensure high reliability and low latency, we can explore path diversity. In other words, a packet can be transmitted using all active links in a network to reach the destination. Here, a critical, difficult issue is to calculate the end-to-end reliability of a mesh network, given the reliability of each active link. In this paper, we derive the mesh network reliability with a new approach, which is of lower computational cost and more scalable than the state-of-the-art. Based on a Markov model, the closed-form network reliability as a polynomial expression of link reliability is obtained using the Hop-State Algorithm (HSA). Furthermore, we propose two metrics to assist in selecting the links in a network for routing to ensure performance while reducing link cost. From the analysis and simulation evaluations, exploring path diversity can effectively support Ultra-Reliable Low-Latency (URLL) services. |
13,561 | Please write an abstract with title: The use of passive radio extenders in cellular networks, and key words: Intelligent networks, Land mobile radio cellular systems, Adaptive arrays, Antenna feeds, Frequency, Coaxial cables, Testing, Gain, Microwave technology, Organizing. Abstract: Presents the results of experimental check of passive radio extender efficiency within cellular communication networks. There are several possible ways of communication assurance when mobile station (MS) is out of the coverage area of the base station (BS). The first of them offers microcell application, when two antennas are used along with the other BS equipment. The second method assumes the use of personal high-elevation direct antenna and antenna adapter, which is connected directly to the MS. In several cases passive radio extender (PRE) can be used in order to provide communication for a small local group of MS. |
13,562 | Please write an abstract with title: Local to Global Transformer for Video Based 3d Human Pose Estimation, and key words: Computer vision, Three-dimensional displays, Target tracking, Conferences, Pose estimation, Streaming media, Transformers. Abstract: Transformer-based architecture has achieved great results in sequence to sequence tasks and vision tasks including 3D human pose estimation. However, transformer based 3D human pose estimation method is not as strong as RNN and CNN in terms of local information acquisition. Additionally, local information plays a major role in obtaining 3D positional relationships. In this paper, we propose a method that combines local human body parts and global skeleton joints using a temporal transformer to finely track the temporal motion of human body parts. First, we encode positional and temporal information, then we use a local to global temporal transformer to obtain local and global information, and finally we obtain the target 3D human pose. To evaluate the effectiveness of our method, we quantitatively and qualitatively evaluated our method on two popular and standard benchmark datasets: Human3.6M and HumanEva-I. Extensive experiments demonstrated that we achieved state-of-the-art performance on Human3.6M with 2D ground truth as input. |
13,563 | Please write an abstract with title: Calculation and Experiment of Stray Inductance of PCB Double-Pulse Test Circuit Based on Three-Dimensional Simulation, and key words: Inductance, Insulated gate bipolar transistors, Solid modeling, Integrated circuit modeling, Metals, Substrates, Voltage measurement. Abstract: In high-frequency electronic equipment and power electronic devices, the dynamic performance of switching devices is one of the important indicators, and a double-pulse test circuit is usually used to test the dynamic performance of switching devices. In order to reduce the stray inductance existing in the test circuit, a double-pulse test circuit structure based on PCB is firstly proposed, and then the basic principle of using the integral calculation method to extract the PCB stray inductance is analyzed. Then the 3D model of the PCB is established, and the PCB stray inductance extraction based on 3D simulation is completed. Finally, a 1200V/100A double-pulse test experimental platform is built. By comparing the three-dimensional simulation results with the numerical calculation results using the integral method under the double-pulse test experiment, the accuracy and effectiveness of the three-dimensional simulation method proposed in this paper are verified. |
13,564 | Please write an abstract with title: Confocal Visible/NIR Photoacoustic Microscopy of Early-stage Tumor with Structural, Functional and Nanoprobe Contrasts, and key words: Optical fibers, Optical microscopy, Microscopy, Tools, Optical saturation, Lasers and electrooptics, Optical imaging. Abstract: We report fiber-based confocal visible/near-infrared optical-resolution photoacoustic microscopy that can image tumor microvasculature, oxygen saturation, and nanoprobes in a single scanning. It offers a new tool for early detection of tumors with multiple contrast modes. |
13,565 | Please write an abstract with title: Highway Modeling in Anylogic for Multi-Agent Approach to Smart City Management, and key words: Smart cities, Roads, Detectors, Computer architecture, Data models, Libraries, Proposals. Abstract: Highway management implemented to a city ring road should be indisputably integrated into Smart City strategies. It is believed that the multi-agent approach should facilitate such an integration since it is able to cover heterogeneous entities. For this reason, an agent based environment for the simulation of different control strategies to highway management was required. The software tool Anylogic was selected for this issue, since it contains built-in traffic library and allows agent based modeling. In the previous work, the architecture and the framework model for the simulation environment were defined. This paper is focused on the highway model itself. It deals with the problems which had to be overcome when modeling a highway segment in Anylogic. It includes the infrastructure with ramps and exits, loop detectors for traffic flow mapping and gantries for transmission of control actions to the drivers. The generation and the setting of traffic flow, together with its mapping and the drivers' reaction on the control measures, are also covered. The highway model was validated with real data from Prague Ring Road and, within the mentioned framework model, it is now prepared for the simulation of different scenarios. |
13,566 | Please write an abstract with title: Optimal Accuracy-Time Trade-off for Deep Learning Services in Edge Computing Systems, and key words: Deep learning, Greedy algorithms, Measurement, Numerical analysis, Heuristic algorithms, Computational modeling, Servers. Abstract: With the increasing demand for computationally intensive services like deep learning tasks, emerging distributed computing platforms such as edge computing (EC) systems are becoming more popular. Edge computing systems have shown promising results in terms of latency reduction compared to the traditional cloud systems. However, their limited processing capacity imposes a trade-off between the potential latency reduction and the achieved accuracy in computationally-intensive services such as deep learning-based services. In this paper, we focus on finding the optimal accuracy-time trade-off for running deep learning services in a three-tier EC platform where several deep learning models with different accuracy levels are available. Specifically, we cast the problem as an Integer Linear Program, where optimal task scheduling decisions are made to maximize overall user satisfaction in terms of accuracy-time trade-off. We prove that our problem is NP-hard and then provide a polynomial constant-time greedy algorithm, called GUS, that is shown to attain near-optimal results. Finally, upon vetting our algorithmic solution through numerical experiments and comparison with a set of heuristics, we deploy it on a testbed implemented to measure for real-world results. The results of both numerical analysis and real-world implementation show that GUS can outperform the baseline heuristics in terms of the average percentage of satisfied users by a factor of at least 50%. |
13,567 | Please write an abstract with title: A Multiagent Competitive Bidding Strategy in a Pool-Based Electricity Market With Price-Maker Participants of WPPs and EV Aggregators, and key words: Electricity supply industry, Generators, Production, Stochastic processes, Games, Decision making, State of charge. Abstract: Large-scale renewable energy suppliers and electric vehicles (EVs) are expected to become dominated participants in future electricity market. In this article, a competitive bidding strategy is formulated for wind power plants (WPPs) and EV aggregators in a pool-based day-ahead electricity market. A bilevel multiagent based model is proposed to study their bidding behaviors, with market clearing completion in the lower level and revenue maximization in the upper level. A stochastic framework is developed to incorporate the uncertainties in maximal power production of WPPs and EV aggregators and bid prices of other participants. The process of bidding decision is formulated as a stochastic game with incomplete information, in which electricity suppliers including WPPs and EV aggregators are considered as players of the game, their lack of information in this stochastic market environment is counterbalanced by a multiagent reinforcement learning algorithm named win or learn fast policy hill climbing (WoLF-PHC) with maximizing their own profits by self-game. The feasibility and effectiveness of the proposed model and the WoLF-PHC solution approach are successfully illustrated using a modified IEEE 6-bus system and a modified 118-bus system with different numbers of market players. |
13,568 | Please write an abstract with title: SECS/GEMsec: A Mechanism for Detection and Prevention of Cyber-Attacks on SECS/GEM Communications in Industry 4.0 Landscape, and key words: Security, Protocols, Authentication, Machine-to-machine communications, Computer security, Force, Standards. Abstract: Industry 4.0 as a driving force is making huge strides, particularly in the manufacturing sector, where all integral components involved in the production processes are getting digitally interconnected. Fused with improved automation and robotics, machine learning, artificial intelligence, big data, cloud computing, and the Internet of Things (IoT), this open network interconnectivity makes industrial systems increasingly vulnerable to cyber-attacks. While the impacts and intentions of cyber-attacks vary, they always have a detrimental effect on manufacturers, including financial losses, supply chain disruption, loss of reputation and competitiveness, and theft of corporate secrets. Semiconductor Equipment Communication Standard/Generic Equipment Model (SECS/GEM) is a legacy Machine-to-Machine (M2M) communication protocol used profoundly in the semiconductor and other manufacturing industries. It is mainly designed to be utilized in a controlled and regulated factory environment separated from external networks. Industry 4.0 has revolutionized the manufacturing industry and has brought SECS/GEM back to the limelight as it lacks security safeguards to protect against cyber-attacks. This paper proposes a digital signature-based security mechanism that offers authentication, integrity, and protection against cyber-attacks. The proposed mechanism is compared with the industry-standard SECS/GEM implementation in terms of processing time, payload overhead, and resilience against cyber-attacks. The results indicate that SECS/GEMsec effectively prevented untrusted entities from establishing communication links with legit industrial equipment while maintaining message integrity by discarding forged messages. Additionally, it protected SECS/GEM communications against Denial-of-Service (DoS) attacks, Replay attacks, and False-Data-Injection-Attack (FDIA) attacks. |
13,569 | Please write an abstract with title: Safety of Stochastic Hybrid Systems Based on Discrete Approximations, and key words: Safety, Stochastic systems, Vehicle dynamics, Uncertainty, Viscosity, Embedded system, Equations, Encoding, Optimal control, State-space methods. Abstract: Stochastic hybrid system models can be used to analyze and design complex embedded systems that operate in the presence of uncertainty and variability. Verification of safety properties of such systems is a critical problem because of the interaction between the discrete and continuous stochastic dynamics. In this paper, we propose a probabilistic method for verifying safety based on discrete approximations. We show that the safety property can be characterized as a viscosity solution of a system of coupled Hamilton-Jacobi-Bellman equations. We present a computational algorithm for computing the solution based on discrete approximations and we show that this solution converges to the one for the original system as the discretization becomes finer. Finally, we illustrate the approach with a room heater example that has been proposed as a benchmark for hybrid system verification |
13,570 | Please write an abstract with title: Undervoltage and Underfrequency Combined Load Shedding Method, and key words: Power system stability, Frequency measurement, Stability criteria, Power system dynamics, Load modeling, Real-time systems, Mathematical model. Abstract: The conventional undervoltage load shedding (UVLS) and the underfrequency load shedding (UFLS) are designed separately, lacking considerations of mutual impacts of the voltage and the frequency on load characteristics. Thus it may cause excessive or insufficient load curtailments. To deal with the problem, this paper proposes an underfrequency and undervoltage combined load shedding method. It takes account of the combined effects of frequency and voltage on load dynamic characteristic. Only the local information of loads are required to determine the load shedding strategy. Simulation results of IEEE 39-bus system have shown that this method, compared with the conventional UFLS/UVLS, can maintain the frequency stability and the voltage stability more effectively. |
13,571 | Please write an abstract with title: Analysis of Retinal Images to Diagnose Stargardt Disease, and key words: Diseases, Image edge detection, Retina, Instruments, Communication systems, Sun, Image coding. Abstract: Stargardt disease is also called Stargardt macular dystrophy, juvenile macular degeneration. The disease causes the macula to gradually weaken or degenerate, which is a small area in the center of the retina responsible for sharp, straight-ahead view. There is no remedy or treatment for this disease. Physicians, however, also recommend that people wear sun glasses in the sun and places where the light is bright. Diagnosis of this disease will take more days but we can diagnose the disease in a matter of minutes by comparing the unaffected eye to affected eye using automated algorithm and advanced histogram technique We plan to use LABVIEW tools to incorporate this technique. |
13,572 | Please write an abstract with title: Direct adaptive fuzzy controller by changing the output membership functions for nonlinear motion applications, and key words: Programmable control, Adaptive control, Fuzzy control, Motion control, Computer errors, Induction motor drives, Fuzzy logic, Tracking, Stability, Convergence. Abstract: In this paper an adaptive control speed for an induction motor drive is presented. The proposed adaptive scheme uses a Mamdani fuzzy logic controller (MFLC). The parameters, of the membership output function characterizing the linguistic terms in the fuzzy if-then rules change according the adaptation. The MFLC approximates and adaptively cancels an unknown plant non-linearity. The adaptive law is developed for the purpose of tracking a reference speed in a motion system. Based on the Lyapunov theory, the stability of the whole system and the convergence of the tracking error are also discussed. The tracking error is guaranteed to be uniformly stable and ultimately bounded with the aid of an additional supervisory term. Computer simulations show that the effect on the error of both the fuzzy approximation and the external disturbances can be attenuated by the proposed controller. Moreover, experimental results are presented to verify the effectiveness of the method. |
13,573 | Please write an abstract with title: Permission-Based Blockchain with Proof of Authority for Secured Healthcare Data Sharing, and key words: Data privacy, Smart contracts, Medical services, Blockchain, Consensus algorithm, Interoperability, Standards. Abstract: Electronic exchange of healthcare data between hospitals and institutions is limited by privacy, interoperability, and dependency on centralized data management systems. Sharing patients' data without their consent is a violation of the law and bears the risk of identity hack and misuse of healthcare data. Not all healthcare institutions follow a similar structure and semantic to store patients' data, making it almost impossible to share the data for research and better patient management. Centralized data management system is vulnerable to cyberattacks and data theft. It also creates lock-in problems for patients intending to migrate their data to any other institute. In this paper, a permissioned Blockchain with Proof of Authority (PoA) technology has been proposed that guarantees data privacy, data owner's control on sharing their sensitive information, and effective distributed management of healthcare records. It also addresses the importance of managing medical records in an interoperable manner, and the use of de facto standards such as Fast Healthcare Interoperable Resources (FHIR), which helps the meaningful exchange of healthcare records among all participants. The work is based on simulating the outcome of using PoA to understand the efficacy of this consensus algorithm when using Blockchain technology for secure data sharing. |
13,574 | Please write an abstract with title: Application of Electrodynamic Admittances in the TWT Theory, and key words: Electrodynamics, Power transmission lines, Electron beams, Conferences, Boundary conditions, Vacuum electronics. Abstract: Unlike the conventional transmission lines and waveguides, in which, as a rule, the wave propagates only in one region, in slow-wave structures (SWSs) with the electron beam (e-beam) the wave propagates or concentrates at least in three regions. Besides, in the most cases slow waves are represented by components of the E- and H-waves, each of them with different boundary conditions. This doubles the number of the boundary conditions, which achieves 16 for two regions SWSs plus 4 boundary conditions for the e-beam. |
13,575 | Please write an abstract with title: Social and economic aspects when allocating a 3.5 GHz frequency band for 5G Mobile in Indonesia, and key words: 5G mobile communication, Satellite broadcasting, Economics, Satellites, Radio spectrum management, Biological system modeling, Licenses. Abstract: The soon-to-be allocated 5G mobile technology using a 3.5 GHz frequency band has posed challenges because the spectrum of 3.5 GHz has utilized satellite services. By examining the case of Indonesia, this paper aims to investigate the social and economic aspects of two scenarios, i.e., implementing 5G using 3.5 GHz or retaining the use of the satellite for 3.5 GHz. The technological management method developed by Kano Models was used to assess the social aspect, and the net benefit was calculated to assess the economic aspect. The findings indicated that most existing services offered via satellite are in the attractive category, meaning that if such satellite services are eliminated, the market will not change significantly; however, implementing 5G at the frequency of 3.5 GHz would increase economic value due to the much higher license fee paid by the operators to the government. |
13,576 | Please write an abstract with title: Enhancing Security of Double Random Phase Encryption Schemes Based on Discrete Fractional Fourier Transforms, and key words: Encryption, Electrical engineering, Discrete Fourier transforms, Computer security, Resists. Abstract: Existing double random phase encryption (DRPE) schemes in the DFT, discrete fractional Fourier transform (DFRFT), and multiple-parameter DFRFT domains are all linear and vulnerable to the known-plaintext attack. In this brief, we first propose a random nonlinearizing block, which is then added to and nonlinearizes the encryption process of the conventional linear DRPE scheme. Besides, from computer experiments, we show the resulting random nonlinearized DRPE schemes are very sensitive to decryption key errors. Consequently, the proposed random nonlinearized DRPE schemes can resist the known-plaintext attack with enhanced security. |
13,577 | Please write an abstract with title: A Weldless Approach for Thermocouple Fabrication Through Direct Ink Writing Technique, and key words: Substrates, Ink, Silver, Temperature measurement, Carbon, Junctions, Temperature sensors. Abstract: Thermocouples are abundantly used for temperature measurement in various applications because of their availability and reliability. In this research two different materials, carbon a semiconductor and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS), an organic conductive polymer with silver as a common electrode were used to fabricate thermocouples through a weldless direct ink writing technique. Two different lengths were chosen for thermocouples to validate the effect of change in length on the performance of thermocouples. Each of the printed thermocouples is characterized and the sensitivity of thermocouples also known as the Seebeck coefficient are determined in a temperature range of up to 140°C. The Seebeck coefficients are found to be 16.6-17 μV/°C for PEDOT:PSS/Silver thermocouples and 15-17.8 μV/°C for carbon/silver thermocouples. These values are comparable to the recently reported numbers for the combination of the said materials. Furthermore, it was found that the Seebeck coefficient is not only material dependent but also influenced by the electrical properties of the printed thermocouples. Each type of printed thermocouple exhibits a stable and linear response towards the temperature change and is comparable to commercially available K-type thermocouple, however, the Seebeck coefficient reported is low when compared to K-type thermocouples due to material differences. Another key finding is the quick response and recovery time of the printed thermocouples as compared to sheath K-type thermocouples. |
13,578 | Please write an abstract with title: Characterization of low-temperature processed single-crystalline silicon thin-film transistor on glass, and key words: Silicon, Thin film transistors, Glass, Crystallization, Substrates, Wafer bonding, Plasma temperature, Semiconductor thin films, Electron mobility, Leakage current. Abstract: Single-crystalline silicon thin film on glass (cSOG) has been prepared using an "ion-cutting" based "layer-transfer" technique. Low-temperature processed thin-film transistors, fabricated both on cSOG and metal-induced laterally crystallized polycrystalline silicon, have been characterized and compared. The cSOG-based transistors performed comparatively better, exhibiting a significantly higher electron field-effect mobility (/spl sim/430 cm/sup 2//Vs), a steeper subthreshold slope and a lower leakage current that was also relatively insensitive to gate bias. |
13,579 | Please write an abstract with title: Shear wave structure of southern Sweden from precise phase-velocity measurements of ambient-noise data, and key words: Europe, Seismic interferometry, Seismic noise, Seismic tomography, Surface waves and free oscillations. Abstract: Rayleigh-wave phase-velocity tomography of southern Sweden is presented using ambient seismic noise at 36 stations (630 station pairs) of the Swedish National Seismic Network. We analyse 1 yr (2012) of continuous recordings to get the first crustal image based on the ambient-noise method in the area. Time-domain cross-correlations of the vertical component between the stations are computed. Phase-velocity dispersion curves are measured in the frequency domain by matching zero crossings of the real spectra of cross-correlations to the zero crossings of the zeroth-order Bessel function of the first kind. We analyse the effect of uneven source distributions on the phase-velocity dispersion curves and correct for the estimated velocity bias before tomography. To estimate the azimuthal source distribution to determine the bias, we perform inversions of amplitudes of cross-correlation envelopes in a number of period ranges. Then, we invert the measured and bias-corrected dispersion curves for phase-velocity maps at periods between 3 and 30 s. In addition, we investigate the effects of phase-velocity bias corrections on the inverted tomographic maps. The difference between bias-corrected and -uncorrected phase-velocity maps is small (<1.2 per cent), but the correction significantly reduces the residual data variance at long periods where the bias is biggest. To obtain a shear velocity model, we invert for a 1-D velocity profile at each geographical node. The results show some correlation with surface geology, regional seismicity and gravity anomalies in the upper crust. Below the upper crust, the results agree well with results from other seismological methods. |
13,580 | Please write an abstract with title: Short-term Load Forecasting with Deep Boosting Transfer Regression, and key words: Load forecasting, Transfer learning, Training data, Predictive models, Boosting, Data models, Reliability. Abstract: With the increasing popularity of electric vehicles and the growing trend of working from home, electricity consumption in the residential sector is expected to continue to grow rapidly over the next few years. As a consequence, short-term residential load forecasting is becoming even more vital for the reliability and sustainability of the smart grid. Although deep learning models have shown impressive success in different areas including short-term electric load forecasting, such models require a large amount of training data. For many real-world load forecasting cases, we may not have enough training data to learn a reliable forecasting model. In this paper, we address this challenge through the use of boosting-based transfer learning with multiple sources. We first train a set of deep regression models on source houses that can provide relatively abundant data. We then transfer these learned models via the boosting framework to support data-scarce target houses. The transfer process is selective and customized for each target house to minimize the potential for negative transfer. Experimental results, based on real-world residential data sets, show that the proposed method can significantly improve forecasting accuracy. |
13,581 | Please write an abstract with title: Scattering parameters measurement using magnitude and homodyne probe signals detecting, and key words: Scattering parameters, Probes, Signal detection, Reflection, Dynamic range, Microwave devices, Attenuation measurement, Signal analysis, Microwave measurements, Detectors. Abstract: The report offers an account of actual principles of operation of the microwave vector network analyzers. A new approach to increasing analyzer dynamic range based on probe signals magnitude detecting is presented taking into consideration feed mismatching. A new effective approach to microwave network parameters measurement is proposed, which combines the methods of magnitude and homodyne detecting. |
13,582 | Please write an abstract with title: Consensus-Based Formation Control of Networked Nonholonomic Vehicles With Delayed Communications, and key words: Delays, Asymptotic stability, Vehicle dynamics, Convergence, Robots, Network topology, Kinematics. Abstract: For a network of nonholonomic vehicles communicating according to an undirected connected graph, a consensus-based formation control problem is solved via a smooth time-varying, proportional-derivative, δ-persistently-exciting, controller. It is assumed that the communication among agents is affected by time-varying, nondifferentiable, communication delays and uniform global asymptotic stability is demonstrated. This goes beyond the more-often encountered property of nonuniform convergence and, what is more, for the first time in the literature, a strict Lyapunov-Krasovskii functional is provided. |
13,583 | Please write an abstract with title: Readout and control of optical alignment devices in the ATLAS Muon endcap, and key words: Optical control, Optical devices, Mesons, Spectroscopy, Particle tracking, Monitoring, Testing, Particle beams, Particle measurements, Motion detection. Abstract: Optical devices have been used to monitor the positions and deformations of the ATLAS Endcap Muon chambers in real-time during data-taking in a muon beam at CERN. A part of an octant of the ATLAS Muon endcap spectrometer has been set up in a test beam to study particle tracking precision. The scale of the ATLAS spectrometer and the high precision needed for particle momentum measurements (10% at 1000 TeV) require a continually operating optical system to track motions of the detector chambers. With alignment corrections applied the design tracking precision was achieved. |
13,584 | Please write an abstract with title: Submm-range 1 W power TWT project, and key words: Microwave technology, Organizing, IEEE catalog. Abstract: The project of compact multibeam submillimeter-range TWT is presented. Main problems and advantages of multibeam TWT design are discussed. |
13,585 | Please write an abstract with title: Design centering by yield prediction, and key words: Semiconductor device manufacture, Electrical engineering, Education, Monte Carlo methods, Fluctuations, Algorithm design and analysis, Optimization methods, Filters, Integrated circuit yield, Proposals. Abstract: Design centering is an appropriate design tool for all types of electrical circuits to determine the nominal component values by considering the component tolerances. A new approach to design centering will be presented, which starts at the initial nominal values of the circuit parameters and improves these nominal values by maximizing the circuit yield step by step with the aid of a yield prediction formula. Using a variance prediction formula additionally, the yield maximization process can be established with a few iteration steps only, whereby a compromise between the yield improvement and the decrease in statistical certainty must be made in each step. A high-quality interactive optimization method is described which allows a quantitative problem diagnosis. The yield prediction formula is an analytical approximation based on the importance sampling relation. This relation can also be used to reduce the sample size of the necessary Monte Carlo analyses. Finally the efficiency of the presented algorithm will be demonstrated on a switched-capacitor filter. |
13,586 | Please write an abstract with title: Efficient data compression methods for multi-dimensional sparse array operations, and key words: Data compression, Carbon capture and storage, Sparse matrices, Testing, Data engineering, Usability, Finite element methods, Costs. Abstract: For sparse array operations, in general, the sparse arrays are compressed by some data compression schemes in order to obtain better performance. The Compressed Row/Column Storage (CRS/CCS) schemes are the two common used data compression schemes for sparse arrays in the traditional matrix representation (TMR). When extended to higher dimensional sparse arrays, array operations using the CRS/CCS schemes usually do not perform well. We propose two data compression schemes, extended Karnaugh map representation Compressed Row/Column Storage (ECRS/ ECCS) for multi-dimensional sparse arrays based on the EKMR scheme. To evaluate the proposed schemes, both theoretical analysis and experimental tests are conducted. In theoretical analysis, we analyze CRS/CCS and ECRS/ECCS schemes in terms of the time complexity, the space complexity, and the range of their usability for practical applications. In experimental test, we compare the performance of matrix-matrix addition and matrix-matrix multiplication sparse array operations that use the CRS/CCS and ECRS/ECCS schemes. The experimental results show that sparse array operations based on the ECRS/ECCS schemes outperform those based on the CRS/CCS schemes for all test samples. |
13,587 | Please write an abstract with title: Rayleigh backscattering in a fiber gyroscope with limited coherence sources, and key words: Backscatter, Gyroscopes, Fluctuations, Coherence, Coils, Working environment noise, Frequency, Optical fiber theory, Acoustic noise, Multi-stage noise shaping. Abstract: Noise due to temporal fluctuations of Rayleigh baekscattered light in fiber-optical gyroscopes is studied experimentally with various sources whose coherence length is less than the fiber length. The reduction of the coherent fraction of backscattered light and its fluctuation frequencies with reduced source coherence is demonstrated and fit to an analytical model. Measured backscatter parameters for the fiber and sources used are presented. |
13,588 | Please write an abstract with title: A Greedy Strategy of Multiplexing uRLLC Traffic Within eMBB Services for HSR, and key words: Multiplexing, Wireless communication, Simulation, Bit error rate, Ultra reliable low latency communication, Rail transportation, Safety. Abstract: Ultra-reliable low latency communication (uRLLC) services are crucial for the safe operation of high-speed railways (HSRs). However, when multiplexing with enhanced mobile broadband (eMBB) traffics, the multiple types of uRLLC traffics pose a new challenge. To address the scheduling problem of physical resources in the coexistence of heterogeneous traffics, we divide uRLLC traffics into several levels based on the bit error rate (BER) and delay metrics. A latency margin-based physical resource multiplexing concept is proposed based on different allowable latencies of each traffics. Furthermore, we formulate an optimization problem to minimize the total power of uRLLC traffics while guaranteeing the BER and latency requirements, and a greedy strategy is proposed to solve this optimization problem efficiently. The simulation results show that our proposal can not only guarantee the BER and latency requirements but also reduce the power consumption of various uRLLC traffics significantly in the cases of poor channel status, enhancing the safety and reliability of train-ground wireless communication greatly. |
13,589 | Please write an abstract with title: Design of a Metal-Only Reflectarray for Ku-band DTH Applications, and key words: reflectarray, metal-only, phoenix element. Abstract: A metal-only reflectarray designed at a center frequency of 12.5GHz has been presented with simulation results. It avoids the use of dielectric substrate and is less susceptible to environmental conditions. A gain of 32.5dBi, aperture-efficiency of 66.2%, beam-width of 4°, and a 1dB gain-bandwidth of 13.6% are achieved at 12.5GHz. It is suitable for use in Ku band DTH reception applications with linear polarization. |
13,590 | Please write an abstract with title: An Ensembled Text-based Multi-Stacked-CNN-BILSTM for Rumor Detection on Social Media, and key words: Deep learning, COVID-19, Social networking (online), Predictive models, Feature extraction, Data models, Electronic commerce. Abstract: Social networks heave became a part of people’s life. Although there are many positive sides like eCommerce and easy communication through social networks, the existence of rumors is the negative side of social networks. With the least effort, a rumor can be quick to many users disseminated leading to unpleasant social phenomena. In the literature, there are some machine learning and deep learning approaches to automatically detect rumors. Most of the previous works fail to detect the rumors in high performance. In this paper, we present an ensembled multi-stacked-CNN-BILSTM model to detect rumors on social media. This deep learning model just considers the text of users and detects that whether a text message is a rumor or not. In the proposed model, each multi-stacked-CNN-BILSTM makes a prediction, and the label that voted maximum as predicted label is detected. We have evaluated the proposed model on the real public data set of PHEME. The proposed model achieved accuracy improvement over the ten state-of-the-art machine learning and deep learning models. |
13,591 | Please write an abstract with title: Stabilization of a Four-Dimensional Chaotic System with No Equilibria via a Novel Precise Constant-Control Approach, and key words: Bifurcation, Numerical simulation. Abstract: A problem on stabilization of a four-dimensional chaotic system is investigated. A novel precise constant-control approach is derived in this paper. A four-dimensional chaotic system with five parameters and eight terms is constructed firstly. The polynomial chaotic system is composed of four linear terms, one constant term and three quadratic nonlinear terms. The system has no any equilibrium point. A new hidden attractor can be generated from the four-dimensional polynomial system. Bifurcation diagrams of four state variables with the variation of a single parameter are depicted respectively. A novel precise constant-control approach is designed to stabilize the chaotic system. Corresponding numerical simulations verify the effectiveness of the novel approach derived in this paper. |
13,592 | Please write an abstract with title: Optimizing Computer Processing Technology Using RC Circuit, and key words: Resistance, Resistors, Program processors, Computer architecture, Voltage, Market research, Hardware. Abstract: In computer hardware, processors known as multiply-accumulate operation, MAC, compute the addition of a sum of products. MAC plays a vital role in calculating and transferring digital information. As technology advances, the computational hardware must become more efficient. As a result, this paper examined the prospect of optimizing MAC operations using RC circuits. To understand the potential of using RC circuits as architecture, this paper investigated by extrapolating the circuit formulas, errors, and dependencies of variables. In designing circuits with input variables, data were collected to interpret the effectiveness of the circuitry. Through the testing of dependence in time, voltage, or resistance, whether as fixed or changing variables, the results show a positive relationship between the number of bitlines and the number of bits representable by the circuit. The fundamentals of circuitry design are crucial to understanding and expanding modern advancements in circuit MAC operations. As a result, the basic functions of every technological processing chip are continuously upgraded using the optimal selection of fundamental variables. To help with the expanding advancement, the results from this paper hope to construct and aid more advanced research within the hardware field in the future. |
13,593 | Please write an abstract with title: Model-Based Event-Triggered Control over Lossy Networks, and key words: Uncertain systems, Protocols, Measurement uncertainty, Propagation losses, Time measurement, Communication networks. Abstract: The event-triggered control problem over lossy communication networks is addressed in this paper. Although packet dropouts have been considered in the implementation of event-triggered controllers, the assumption of protocols that employ acknowledgement messages persists. This paper provides an approach that relaxes such assumption. An event-based controller is implemented at the sensor node of the networked and uncertain system and it transmits feedback measurements to the controller node at asynchronous time instants. The transmitted packets of information are subject to dropouts by the lossy network. We show that the uncertain system can be asymptotically stabilized, that a positive minimum inter-event time exists, and that the proposed approach does not require acknowledgement messages. |
13,594 | Please write an abstract with title: On ubiquitous network security and anomaly detection, and key words: Computer networks, Computer architecture, Pervasive computing, IP networks, Information security, Monitoring, Levee, Computer security, Communications technology, Protection. Abstract: As networking trends move toward ubiquitous structuring schemes, the problem of security has taken on an increasingly important role. As a result, we must look to new security paradigms that address the new problems associated with these networks. This paper is a summary of research in progress on the Wintermute Project at Oregon State University, which was created to investigate security for ubiquitous networking schemes. |
13,595 | Please write an abstract with title: Limited wordlength and FDCT processing accuracy, and key words: Signal to noise ratio, Discrete cosine transforms, Quantization, Hardware, Arithmetic, Mathematical analysis, Guidelines, Design optimization, Additive white noise, Noise generators. Abstract: For hardware realization of the fast discrete cosine transform (FDCT) processor, as the parameters can only be specified by a finite number of binary digits (bits), the computational accuracy is governed by the precision by which the parameters are represented. To measure the effect of limited word-length, mathematical analysis is used initially to develop theoretical effects of the sensitive parameters on the processing accuracy. By simulation, the theoretical results are verified, and the results are then extended for further detailed simulation studies. Finally, the simulation results are used to develop general guidelines for optimizing the hardware design of any size FDCT or fast inverse DCT (FIDCT) processor. |
13,596 | Please write an abstract with title: Self-organizing neural networks using adaptive neurons, and key words: Adaptive systems, Neurons, Biological neural networks, Multi-layer neural network, Neural networks, Computer science, Electronic mail, Humans, Interference, Neural network hardware. Abstract: In this paper, we propose a new kind of neural network having modular structure, neural network with adaptive neurons. Each module is equivalent to an adaptive neuron, which consists of a multi-layer neural network with sigmoid neurons. We develop an algorithm by which the network can automatically adjust its complexity according to the given problem. The proposed network is compared with the project pursuit learning network (PPLN), which is a popular modular architecture. The experimental results demonstrate that the proposed network architecture outperforms the PPLN on four regression problems. |
13,597 | Please write an abstract with title: Measuring Spin Polarization of a Spin-Exchange Relaxation-Free Atomic Magnetometer at Extremely Large Optical Depths, and key words: Frequency measurement, Atomic measurements, Atom optics, Optical pumping, Optical polarization, Magnetometers, Temperature measurement. Abstract: This article presents a method for measuring the spin polarization of spin-exchange relaxation-free (SERF) atomic magnetometers at extremely large optical depths. Due to the slowing-down effect, spin polarization can be extracted by measuring the slowing-down factor extracted from the precession frequency. However, this technique is limited by a significant error in the regime of extremely large optical depths, where the pump beam intensity for achieving the optimal spin polarization of alkali atoms is significantly increased. We observed that the instantaneous precession frequency measured in the regime where the spin-exchange rate is not much larger than the Larmor frequency was no longer a constant but varied with the pump beam intensity. Thus, a method for measuring spin polarization based on the ratio of the precession frequency to the measured instantaneous precession frequency is proposed. Based on the proposed method, the spin polarization at a temperature of 473 K and an optical depth of 64 is measured. The measurement results were in accordance with theoretical analysis. The expanded uncertainties of the experimental results varied between 1.8% and 9.6%. The proposed method is also applicable to other atomic devices operated in the SERF regime with extremely large optical depths, such as co-magnetometers and atomic spin gyroscopes. |
13,598 | Please write an abstract with title: Network Service Embedding Across Multiple Resource Dimensions, and key words: Measurement, Resource management, Servers, Substrates, Optimization, Bandwidth, Virtualization. Abstract: Network Function Virtualization (NFV) poses the need for efficient embeddings of network services, usually defined in the form of service graphs, associated with resource and bandwidth demands. As the scope of NFV has been expanded in order to meet the requirements of virtualized cellular networks and emerging 5G services, the diversity of resource demands across dimensions, such as CPU, memory, and storage, increased. This requirement exacerbates the already challenging problem of network service embedding (NSE), rendering most existing NSE methods inefficient, as they commonly account for a single resource dimension (i.e., typically, the CPU). In this context, we investigate methods for NSE optimization across multiple resource dimensions. To this end, we study a range of multi-dimensional mapping efficiency metrics and assess their suitability for heuristic and exact NSE methods. Utilizing the most suitable and efficient metrics, we propose two heuristics and a mixed integer linear program (MILP) for optimized multi-dimensional NSE. In addition, we devise a virtual network function (VNF) bundling scheme that generates (resource-wise) balanced VNF bundles in order to augment VNF placement. Our evaluation results indicate notable resource efficiency gains of the proposed heuristics compared to a single-dimensional counterpart, as well as a minor degree of sub-optimality in relation to our proposed MILP. We further demonstrate how the bundling scheme affects the embedding efficiency, when coupled with our most efficient heuristic. Our study also uncovers interesting insights and potential implications from the utilization of multi-dimensional metrics within NSE methods. |
13,599 | Please write an abstract with title: Deep-Reinforcement-Learning-Based Multitarget Coverage With Connectivity Guaranteed, and key words: Robots, Optimization, Maintenance engineering, Task analysis, Informatics, Topology, Reinforcement learning. Abstract: Deriving a distributed, time-efficient, and connectivity-guaranteed coverage policy in multitarget environment poses huge challenges for a multirobot team with limited coverage and limited communication. In particular, the robot team needs to cover multiple targets while preserving connectivity. In this article, a novel deep-reinforcement-learning-based approach is proposed to take both multitarget coverage and connectivity preservation into account simultaneously, which consists of four parts: a hierarchical observation attention representation, an interaction attention representation, a two-stage policy learning, and a connectivity-guaranteed policy filtering. The hierarchical observation attention representation is designed for each robot to extract the latent features of the relations from its neighboring robots and the targets. To promote the cooperation behavior among the robots, the interaction attention representation is designed for each robot to aggregate information from its neighboring robots. Moreover, to speed up the training process and improve the performance of the learned policy, the two-stage policy learning is presented using two reward functions based on algebraic connectivity and coverage rate. Furthermore, the learned policy is filtered to strictly guarantee the connectivity based on a model of connectivity maintenance. Finally, the effectiveness of the proposed method is validated by numerous simulations. Besides, our method is further deployed to an experimental platform based on quadrotor unmanned aerial vehicles and omnidirectional vehicles. The experiments illustrate the practicability of the proposed method. |
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