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International Conference on Advanced Robotics (ICAR)

作者： Murad Mebrahtu Awet Araia Abiel Ghebreslasie Jorge Dias Majid Khonji Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi UAE Center for Autonomous Robotic Systems (KUCARS) Abu Dhabi UAE

ISBN: (数字)9798350342291

ISBN: (纸本)9798350342307

Over the past decade, the field of assisted and autonomous driving has experienced significant advancements. However, autonomous driving systems are still challenged by the complexities of dynamic urban environments, especially when it comes to predicting and responding to the often stochastic behavior of pedestrians. Current approaches largely concentrate on most likely predictions but tend to ignore their inherent probabilistic nature. Our research introduces a novel Transformer-based multimodal probabilistic prediction model that utilizes a Gaussian Mixture Model (GMM). This approach is simpler than its predecessors, yet it maintains competitive performance, capable of inferring prediction uncertainties using GMM parameters. Additionally, we demonstrate how our prediction model can be incorporated into a risk-aware behavior planner, based on the Chance-Constrained Stochastic Shortest Path (CC-SSP) framework. This planner uses probabilistic trajectory predictions as a Markov transition function to modulate the speed of the autonomous vehicle, effectively keeping the probability of collision below a defined threshold. Our implementation is available at https://***/Murdism/Probabilistic_Pedestrian_Trajectory_***.

关键词： Pedestrians Stochastic processes Predictive models Probabilistic logic Transformers Behavioral sciences Autonomous vehicles

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Heart Arrhythmia Classification Using Deep Learning: A Comparative Study 6

Heart Arrhythmia Classification Using Deep Learning: A Compa...

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6th Iraqi International Conference on engineering Technology and its Applications, IICETA 2023

作者： Radi, Omar Alslatie, Mohammad Mustafa, Wan Azani Alquran, Hiam Badarneh, Alaa Mohammed, F.F. Alkhayyat, Ahmed Jordan University of Science and Technology Department of Biomedical Engineering Irbid Jordan The Institute of Biomedical Technology King Hussein Medical Center Royal Jordanian Medical Service Amman11855 Jordan Faculty of Electrical Engineering Technology Perlis Arau Malaysia Yarmouk University Biomedical Systems and Medical Informatics Engineering Irbid Jordan Al-Zahraa University for Women Karbala Iraq The Islamic University Faculty of Engineering Najaf Iraq

ISBN: (纸本)9798350303339

Heart arrhythmia is an irregular heartbeat that causes heart problems. It can be classified by their seriousness into serious and non-serious arrhythmia. Mainly to diagnose heart arrhythmias, we use Electrocardiogram (ECG). In this paper, the authors compared three different models of classifiers: Convolutional Neural Network, Dense Neural Network and Long Short-Term Memory to classify cardiac arrhythmia into two types normal and abnormal, using the MIT-BIH database. The results show that CNN and DNN have the best result of the models with 99% accuracy while LSTM shows 60 accuracy percent. © 2023 IEEE.

关键词： Diseases

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Anisotropy of two-dimensional ReS_(2)and advances in its device application

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Rare Metals 2021年第12期40卷 3357-3374页

作者： Ya-Di Cao Ying-Hui Sun Su-Fei Shi Rong-Ming Wang Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface ScienceSchool of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing100083China Department of Chemical and Biological Engineering Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic InstituteTroyNY 12180USA

Two-dimensional(2D)transition metal dichalcogenides(TMDCs)have attracted growing interest regarding their potential applications in next-generation electronic and optoelectronic *** to their atomic thickness and tunable bandgap,they exhibit unique mechanical,electrical,and optical *** a specific member of the TMDC family,rhenium disulfide(ReS_(2))has stimulated intensive interest due to its anisotropic crystal structure,weak inter-layer coupling,and anisotropic electrical and optical *** this review,we summarize the distinct crystal structure and intrinsic anisotropic properties of ReS_(2),followed by an introduction to its synthesis *** current applications of ReS_(2)and its heterojunctions are presented based on its anisotropic *** review not only provides a timely summary of the current applications of ReS_(2)and its heterojunctions,but also inspires new approaches to develop other innovative devices based on 2D materials with a low lattice symmetry.

关键词： Transition metal dichalcogenides(TMDCs) Rhenium disulfide Anisotropic property Heterojunction Functional device

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Gbps key rate passive-state-preparation continuous-variable quantum key distribution within an access-network area

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Photonics Research 2024年第7期12卷 1485-1493页

作者： FEIYU JI PENG HUANG TAO WANG XUEQIN JIANG GUIHUA ZENG State Key Laboratory of Advanced Optical Communication Systems and Networks Center for Quantum Sensing and Information ProcessingSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Shanghai Research Center for Quantum Sciences Shanghai 201315China Hefei National Laboratory Hefei 230088China College of Information Science and Technology Donghua UniversityShanghai 201620China

The conventional Gaussian-modulated coherent-state quantum key distribution(QKD) protocol requires the sender to perform active modulations based on a true random number generator. Compared with it, the passive-state-preparation(PSP) continuous-variable quantum key distribution(CVQKD) equivalently performs modulations passively by exploring the intrinsic field fluctuations of a thermal source, which offers the prospect of chip integration QKD with low cost. In this paper, we propose and experimentally demonstrate a high-rate PSP-CVQKD scheme within an access-network area using high-bandwidth detectors in a continuous wave encoding and decoding way. By proposing effective methods for suppressing the noises during the PSP process and polarization multiplexing to decrease the photon leakage noises, we realize the high-intensity local oscillator transmission, thereby achieving coherent detection with high efficiency, low noise, and high bandwidth. The secure key rates over transmission distance of 5.005 km with and without consideration of the finite-size effect are 273.25 Mbps and 1.09 Gbps. The use of the PSP method boosts the asymptotic secret key rate of CVQKD to Gbps level for the first time, to our knowledge, within the range of the access network, which provides an effective and secure key distribution strategy for high-speed quantum cryptography access communication.

关键词： passive network distribution

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L-Band Tunable Mode-Locked Fiber Laser Achieving up to 19 kHz Wavelength Sweeping Rate

L-Band Tunable Mode-Locked Fiber Laser Achieving up to 19 kH...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Guanyu Ye Kin Kee Chow Bowen Liu Yifan Ma Maolin Dai Takuma Shirahata Shinji Yamashita Sze Yun Set Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan Department of Engineering Manchester Metropolitan University Manchester United Kingdom

For the first time, we introduce a rapid wavelength-swept L-band tunable mode-locked fiber laser, boasting an exceptional wavelength sweeping rate of up to 19 kHz, enabled by external modulation of the pump current.

ISBN: (纸本)9798350369311

关键词： Laser mode locking Modulation Lasers and electrooptics Laser excitation Laser tuning Reliability Laser applications Pump lasers L-band Fiber lasers

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Implementation and Evaluation of 0.6 µm CMOS Complex RCPF for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2025年第1期145卷 25-37页

作者： Sato, Lina Fukagawa, Kanta Shouno, Kazuhiro Tanimoto, Hiroshi Muto, Cosy Moriyama, Seijiro Takahashi, Chikau Yoshino, Michitaka Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan Anagix Corporation 3-22-27 Numama Kanagawa Zushi249-0004 Japan Takamori Corporation Japan Research Center for Micro-Nano Technology Hosei University 3-11-15 Midori-cho Koganei Tokyo184-0003 Japan

This paper describes the implementation and evaluation of an RC polyphase filter (RCPF) and circuitry for measuring its frequency characteristics. The integrated circuit is fabricated on a 0.6 µm CMOS process and its supply voltage is 5 V. The integrated circuit includes a filter under test (FUT), a four-phase square wave generator, several analog switches and differential amplifiers to amplify the high-impedance signals of the RCPF. This FUT is a third-order complex RCPF whose passband is 8 − 40 MHz. This paper describes the design of these circuits in detail. This integrated circuit can select two measurement methods by means of external control signals. The first method uses a four-phase square wave. The frequency characteristics are measured by using an on-chip four-phase square wave generator driven by an external clock generator and by a spectrum analyzer tuned to the fundamental frequency. The second method uses an external network analyzer. Furthermore, this integrated circuit is equipped with a calibration circuit to measure the frequency characteristics of the circuitry except FUT by passing through the input / output signals of the FUT. As a result, the frequency characteristics of the FUT itself can be accurately measured. The effectiveness is confirmed through evaluation of the fabricated integrated circuit. © 2025 The Institute of electrical Engineers of Japan.

关键词： Differential amplifiers

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation 11

A Genetic Algorithm to Optimize Cargo Stability in Container...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Hsieh, Chi-Jung Wu, Kuang-Sung Wu, Tin-Yu Tey, Fu Jie Chen, Yi-Kai Ho, Jye Yi National Ilan University Department of Computer Science and Information Engineering Ilan County Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Pingtung County Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9781665492324

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method. © 2022 IEEE.

关键词： Genetic algorithms

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Optimal Placement of Electric Vehicle Charging Stations: A Case Study in Jordan

Optimal Placement of Electric Vehicle Charging Stations: A C...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Ahmad Bashaireh Duaa Obeidat Abdullah A. Almehizia Laith Shalalfeh Electrical Engineering Department Jordan University of Science and Technology Irbid Jordan National Center for Electrical Systems and Cooling King Abdulaziz City for Science and Technology Riyadh Saudi Arabia Energy Engineering Department German Jordanian University Amman Jordan

Several economic factors have contributed to an increased adoption of electric vehicles (EVs) in Jordan. Charging EVs constitutes a considerable electrical load, and hence, the rise in the number of EVs has a major effect on the electric distribution network. To address this, the charging infrastructure should be carefully studied, and an optimal implementation that minimizes the negative impact is crucial. In this paper, we develop a framework for optimal placement of EV charging stations using Particle Swarm optimization (PSO). The optimization problem maximizes the total EV charging capacity while minimizing transmission line and transformer loading and total power losses. This framework is implemented in MATLAB and DIgSILENT PowerFactory and applied to two cases in Jordan’s distribution network: an industrial area and a small town.

关键词： Power transmission lines Limiting Loading Distribution networks Transformers Propagation losses Electric vehicle charging

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Design and Development of a Fixed-Wing Tail-Sitter Tethered VTOL Drone with Custom Autopilot and Robust Control Techniques 16th

Design and Development of a Fixed-Wing Tail-Sitter Tether...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Safaee, Ahmad Aguiar, A. Pedro Santos, Filipe Neves Moreira, Antonio Paulo SYSTEC-ARISE Research Center for Systems and Technologies Faculty of Engineering University of Porto Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering Technology and Science CRIIS-Centre for Robotics in Industry and Intelligent Systems Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering and DEEC/FEUP - Department of Electrical and Computer Engineering Faculty of Engineering of the University of Porto Porto4200-465 Portugal

ISBN: (纸本)9783031817236

The need for aerial platforms capable of sustained operation is critical in fields such as surveillance, agricultural monitoring, disaster response, and temporary telecommunication systems. Traditional unmanned aerial vehicles (UAVs) are hampered by limited battery capacity and inefficient energy utilization. This paper introduces an autonomous vertical flight drone tethered to a ground-based platform, which overcomes these limitations. The drone is designed to optimize its position and energy usage by harnessing wind currents, functioning similarly to a kite when conditions permit. This is enabled by a custom-designed autopilot system comprising both hardware and software tailored for this application. We detail the model identification process for three vertical take-off and landing (VTOL) drone systems, employing authentic data that measures lateral positional errors from the tether. Robust mixed sensitivity controllers are developed and implemented. The effectiveness of these controllers is validated through simulations showing their capability to handle uncertainties. Furthermore, the practical application and robust performance of the system are confirmed by a real-world case study, highlighting its potential in real operational environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： VTOL/STOL aircraft

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Prediction Aided by Surrogate Training

arXiv

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arXiv 2024年

作者： Xia, Eric Wainwright, Martin J. Laboratory for Information and Decision Systems Statistics and Data Science Center Department of Electrical Engineering & Computer Sciences Massachusetts Institute of Technology CambridgeMA United States Laboratory for Information and Decision Systems Statistics and Data Science Center Department of Mathematics Massachusetts Institute of Technology CambridgeMA United States

We study a class of prediction problems in which relatively few observations have associated responses, but all observations include both standard covariates as well as additional "helper" covariates. While the end goal is to make high-quality predictions using only the standard covariates, helper covariates can be exploited during training to improve prediction. Helper covariates arise in many applications, including forecasting in time series;incorporation of biased or mis-calibrated predictions from foundation models;and sharing information in transfer learning. We propose "prediction aided by surrogate training" (PAST), a class of methods that exploit labeled data to construct a response estimator based on both the standard and helper covariates;and then use the full dataset with pseudo-responses to train a predictor based only on standard covariates. We establish guarantees on the prediction error of this procedure, with the response estimator allowed to be constructed in an arbitrary way, and the final predictor fit by empirical risk minimization over an arbitrary function class. These upper bounds involve the risk associated with the oracle data set (all responses available), plus an overhead that measures the accuracy of the pseudo-responses. This theory characterizes both regimes in which PAST accuracy is comparable to the oracle accuracy, as well as more challenging regimes where it behaves poorly. We demonstrate its empirical performance across a range of applications, including forecasting of societal ills over time with future covariates as helpers;prediction of cardiovascular risk after heart attacks with prescription data as helpers;and diagnosing pneumonia from chest X-rays using machine-generated predictions as helpers. © 2024, CC BY.

关键词： Prediction models

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