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2023 International Technical Conference on Circuits/Systems, computers, and Communications, ITC-CSCC 2023

作者： Tham, Mau-Luen Tay, Bee-Sim Khor, Kok-Chin Phon-Amnuaisuk, Somnuk Universiti Tunku Abdul Rahman Lee Kong Chian Faculty of Engineering and Science Department of Electrical and Electronic Engineering Malaysia Department of Internet Engineering and Computer Science Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Malaysia School of Computing and Informatics Universiti Teknologi Brunei Brunei

ISBN: (纸本)9798350326413

Stop-skipping strategy can benefit both bus operators and passengers if the control is intelligent enough to adapt to the changes in passenger demands and traffic conditions. This is possible via deep reinforcement learning (DRL), where an agent can learn the optimal policy by continuously interacting with the dynamic bus operating environment. In this paper, one express bus lane followed by one no-skip flow is treated as one episode for bus route optimization. The objective is to maximize the passenger satisfaction level while minimizing the bus operator expenditures. To this end, a reward function is formulated as a function of passenger waiting time, passenger in-vehicle time, and total bus travel time. By training an agent of a double deep Q-network (DDQN), simulation results show that the agent can intelligently skip the stations and outperform the noskip method, under different passenger distribution patterns. © 2023 IEEE.

关键词： Reinforcement learning

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Toward a Low-Cost Perception System in Autonomous Vehicles: A Spectrum Learning Approach

arXiv

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arXiv 2025年

作者： Alsakabi, Mohammed Erickson, Aidan Dolan, John M. Tonguz, Ozan K. Department of Electrical and Computer Engineering College of Engineering The Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA United States

We present a cost-effective new approach for generating denser depth maps for Autonomous Driving (AD) and Autonomous Vehicles (AVs) by integrating the images obtained from deep neural network (DNN) 4D radar detectors with conventional camera RGB images. Our approach introduces a novel pixel positional encoding algorithm inspired by Bartlett’s spatial spectrum estimation technique. This algorithm transforms both radar depth maps and RGB images into a unified pixel image subspace called the Spatial Spectrum, facilitating effective learning based on their similarities and differences. Our method effectively leverages high-resolution camera images to train radar depth map generative models, addressing the limitations of conventional radar detectors in complex vehicular environments, thus sharpening the radar output. We develop spectrum estimation algorithms tailored for radar depth maps and RGB images, a comprehensive training framework for data-driven generative models, and a camera-radar deployment scheme for AV operation. Our results demonstrate that our approach also outperforms the state-of-the-art (SOTA) by 27.95% in terms of Unidirectional Chamfer Distance (UCD). © 2025, CC BY-NC-ND.

关键词： Radar imaging

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Low-threshold lasing with a stationary inflection point in a three-coupled-waveguide structure

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Physical Review A 2023年第6期108卷 063504-063504页

作者： Kessem Zamir-Abramovich Nathaniel Furman Albert Herrero-Parareda Filippo Capolino Jacob Scheuer School of Electrical Engineering Tel-Aviv University Tel-Aviv Israel Department of Electrical Engineering and Computer Science University of California Irvine California 92697 USA

The frozen mode regime is a unique slow-light scenario in periodic structures, where the flat bands (zero group velocity) are associated with the formation of high-order stationary points (also known as exceptional points). The formation of exceptional points is accompanied by enhancement of various optical properties such as gain, Q factor, and absorption, which are key properties for the realization of a wide variety of devices such as switches, modulators, and lasers. Here we present and study an integrated optical periodic structure consisting of three waveguides coupled via microcavities and a directional coupler. We study this design theoretically, demonstrating that a proper choice of parameters yields a third-order stationary inflection point (SIP). We also show that the structure can be designed to exhibit two almost overlapping SIPs at the center of the Brillouin zone. We study the transmission and reflection of light propagating through realistic devices composed of a finite number of unit cells and investigate their spectral properties in the vicinity of the stationary points. Finally, we analyze the lasing frequencies and threshold level of a finite structure (as a function of the number of unit cells) and show that it outperforms conventional lasers utilizing regular band-edge lasing (such as distributed-feedback lasers).

关键词： Evanescent waves Gain properties of lasers Integrated optics Laser applications Laser-system design Lasers Light stopping & storage Waveguide arrays

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Modified Chaotic Grey Wolf Optimization Algorithm for Energy Aware in WSN

Modified Chaotic Grey Wolf Optimization Algorithm for Energy...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Joseph, L. M. I. Leo Deepika, Gubbala Jahnavi Dinesh, P.S. Vijayashaarathi, S. Samanvita, N. Sr University School of Engineering Department of Ece Warangal India Malla Reddy Engineering College for Women Autonomous India Bannari Amman Institute of Technology Department of Computer Science and Engineering Sathyamangalam India Sona College of Technology Department of Ece Salem India Nitte Meenakshi Institute of Technology Department of Electrical & Electronics Engineering Bengaluru India

ISBN: (纸本)9798350313413

Wireless Sensor Network (WSN) is group of spatially distributed sensors which monitors environmental exchanges that data with each other over wireless channels. Energy aware in WSN are referred to as saving or balancing energy between nodes in WSN. Energy saving protocols are utilized to minimize energy consumed through WSN. Energy balancing protocols effectively distribute energy consumption throughout network. In this research, the Modified Chaotic Grey Wolf Optimization (MCGWO) algorithm is proposed for the effective energy aware in WSN. The optimal cluster head and route paths are selected by utilizing the proposed optimization algorithm. the developed MCGWO algorithm minimizes the nodes' energy utilization while increasing the data transmission in WSN. The performance of proposed technique is estimated by utilizing performance measure of throughput, packet delivery ratio, delay and energy consumption. The proposed method attained high packet delivery ratio of 94.4%, 93.7%, 92.1% and 90.9% for 50, 100, 150 and 200 nodes which is comparatively higher than other existing algorithms like Cuckoo Search Algorithm (CSA), Ant Colony Optimization (ACO), Firefly Optimization Algorithm (FOA) and Grey Wolf Optimization (GWO). © 2023 IEEE.

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Cloud-Enabled Predictive Vehicle Health Monitoring and Maintenance with LSTM Networks for Time-Series Analysis 1

Cloud-Enabled Predictive Vehicle Health Monitoring and Maint...

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1st International Conference on Innovations in Communications, electrical and computer engineering, ICICEC 2024

作者： Vinya, Viyyapu Lokeshwari Manivannan, K.K. Manivannan, S.K. Sathiyamoorthy, C. Jagadeeswaran, M. Meenakshi, B. SRM Institute of Science and Technology Department of Computing Technologies School of Computing Kattankulathur Tamil Nadu Chennai India Easwari Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Vit Bhopal University Department of Physics School of Advanced Sciences and Languages Madhya Pradesh Bhopal India J.J College of Engineering and Technology Department of Information Technology Tamil Nadu Tiruchirappalli India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376517

Maximizing operational efficiency and customer satisfaction in the automobile sector depends on maintaining vehicle health and avoiding maintenance downtime. Vehicle Internet of Things (IoT) devices capture massive volumes of sensor data, enabling predictive maintenance. This research offers cloud-based predictive vehicle health monitoring and maintenance systems using Long Short-Term Memory (LSTM) networks for time-series analysis. System architecture uses IoT sensors in automobiles to gather real-time data on engine temperature, oil pressure, and vibration. This data is stored, analyzed, and predicted on clouds. To assess time-series sensor data and forecast failures or maintenance requirements, LSTM networks, a form of recurrent neural network, are used. The proposed system uses data preprocessing to manage missing values and outliers, feature extraction to find significant sensor data patterns, and LSTM-based predictive modeling to predict vehicle health conditions. Technology may predict future faults by continually monitoring and evaluating the vehicle's state, allowing proactive maintenance to avoid expensive breakdowns and downtime. The cloud-based architecture is scalable and flexible, providing smooth connection with fleet management systems and remote vehicle health monitoring across scattered sites. The suggested method optimizes maintenance schedules and resource allocation using predictive insights from real-time sensor data to improve operational efficiency and save costs. It may improve predictive vehicle health monitoring and maintenance in the automobile sector, improving dependability, safety, and cost. © 2024 IEEE.

关键词： Customer satisfaction

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A Resource-Rational Process Model of Violation of Cumulative Independence 44

A Resource-Rational Process Model of Violation of Cumulative...

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44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022

作者： Cao, Yiwei Nobandegani, Ardavan S. Shultz, Thomas R. Department of Psychology McGill University Canada School of Computer Science McGill University Canada Department of Electrical & Computer Engineering McGill University Canada

Human decision-making is filled with numerous paradoxes and violations of rationality principles. A particularly notable example is violation of cumulative independence (VoCI). Recently, there has been a surge of interest in theorizing and developing a resource-rational foundation for many such phenomena. Here we ask whether VoCI could be given a resource-rational basis too. To what extent could VoCI be explained in terms of the optimal use of limited cognitive resources? In this work, we look at VoCI through the lens of modern psychological theories of bounded rationality, presenting the first resource-rational account of VoCI. We discuss the implications of our work for risky decision-making, and more broadly, human rationality. © 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY)

关键词： Decision making

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Boosting Monolayer Transition Metal Dichalcogenides Growth by Hydrogen-Free Ramping during Chemical Vapor Deposition

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Nano Letters 2024年第27期24卷 8277-8286页

作者： Liu, Hongwei Zhang, Tianyi Wu, Peng Lee, Hae Won Liu, Zhenjing Tang, Tsz Wing Tang, Shin-Yi Kang, Ting Park, Ji-Hoon Wang, Jun Zhang, Kenan Zheng, Xudong Peng, Yu-Ren Chueh, Yu-Lun Liu, Yuan Palacios, Tomás Kong, Jing Luo, Zhengtang Department of Chemical and Biological Engineering Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction The Hong Kong University of Science and Technology Kowloon999077 Hong Kong Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National Tsing-Hua University Hsinchu30013 Taiwan Department of Materials Science and Engineering Korea University Seoul02841 Korea Republic of Key Laboratory for Micro-Nano Optoelectronic Devices of Ministry of Education School of Physics and Electronics Hunan University Changsha410082 China

The controlled vapor-phase synthesis of two-dimensional (2D) transition metal dichalcogenides (TMDs) is essential for functional applications. While chemical vapor deposition (CVD) techniques have been successful for transition metal sulfides, extending these methods to selenides and tellurides often faces challenges due to uncertain roles of hydrogen (H2) in their synthesis. Using CVD growth of MoSe2 as an example, this study illustrates the role of a H2-free environment during temperature ramping in suppressing the reduction of MoO3, which promotes effective vaporization and selenization of the Mo precursor to form MoSe2 monolayers with excellent crystal quality. As-synthesized MoSe2 monolayer-based field-effect transistors show excellent carrier mobility of up to 20.9 cm2/(V·s) with an on-off ratio of 7 × 107. This approach can be extended to other TMDs, such as WSe2, MoTe2, and MoSe2/WSe2 in-plane heterostructures. Our work provides a rational and facile approach to reproducibly synthesize high-quality TMD monolayers, facilitating their translation from laboratory to manufacturing. © 2024 American Chemical Society.

关键词： Monolayers

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A novel multi-frequency in-situ clamp-on method for tower grounding resistance

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Measurement: Journal of the International Measurement Confederation 2025年 253卷

作者： Dan, Yihua Bu, Siqi Zhang, Zhanlong Wong, Chak-Nam Lin, Peiyu The School of Mechatronics and Vehicle Engineering Chongqing Jiaotong University Nan'an District Chongqing China Hong Kong The Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong The School of Electrical Engineering Chongqing University Shaping Ba District Chongqing China

The accurate measurement of tower grounding resistance is important for avoiding major electrical accidents caused by insufficient grounding performance. Existing methods for measuring tower grounding resistance mainly include the fall-of-potential method (3-probe method, multi-probe method) and the classical clamp-on method. However, in practical cases, the existing fall-of-potential method has low efficiency for numerous towers because it requires disconnecting all ground lead conductors for each tower. At the same time, the classical clamp-on method still has a low-efficiency problem because it requires disconnecting some ground lead conductors and maintaining only 1 ground lead conductor connected. Besides, the classical clamp-on method lacks detail considering the influence of overhead ground wires, and is easily affected by the environment, which is often inaccurate. To solve the above problem, this paper proposes a novel multi-frequency in-situ clamp-on method for measuring tower grounding resistance. The basic theory and features of the classical clamp-on method are analyzed, and then a novel multi-frequency in-situ clamp-on method (MICM) is proposed based on the classical clamp-on method. Finally, the case study and verification are carried out. The results show that the proposed MICM can accurately and efficiently measure the tower grounding resistance without disconnecting any ground lead conductor, avoid the disadvantage of the classical clamp-on method, significantly increase the measurement efficiency, and provide a theoretical basis for maintaining transmission lines. © 2025

关键词： Surveying

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The Null Motion for Singularity Avoidance of Adaptive-Skew Single Gimbal Control Momentum Gyroscopes 42

The Null Motion for Singularity Avoidance of Adaptive-Skew S...

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42nd Chinese Control Conference, CCC 2023

作者： Liu, Feng Wang, Dongping Lyu, Kedong Ding, Xiaojun School of Electrical Information Engineering North Minzu University Yinchuan750030 China College of Computer and Information Engineering Tianjin Agricultural University Tianjin300392 China Tianjin Electronic Information Technician College Department of Automation Engineering Tianjin300350 China

ISBN: (纸本)9789887581543

The adaptive-skew of the single gimbal control moment gyroscopes (ASGCMG) has been proposed. The effectiveness of the singularity avoidance with varying variable skew angle in ASGCMG is not clear. In this paper, the singularity of ASGCMG is analyzed based on Binet-Cauchy identity, and the singular gimbal angles are given, so the characteristics of the ASGCMG system can be used for designing logic. The mechanism of the singularity avoidance with assisting of the varying skew angle is revealed. Based on convex optimization theory, the new steering law with null motion is designed. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Convex optimization

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Efficient Feature Matching for Large-scale Images based on Cascade Hash and Local Geometric Constraint

Efficient Feature Matching for Large-scale Images based on C...

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2024 ISPRS Technical Commission I Mid-term Symposium on Intelligent Sensing and Remote Sensing Application

作者： You, Kan Jiang, San Li, Yaxin Jiang, Wanshou Huang, Xiangxiang School of Computer Science China University of Geosciences Wuhan430074 China Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic University 999077 Hong Kong State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430072 China School of Computer and Information Anhui Polytechnic University Wuhu241000 China

Feature matching plays a crucial role in 3D reconstruction to provide correspondences between overlapped images. The accuracy and efficiency of feature matching significantly impact the performance of 3D reconstruction. The widely used framework with the exhaustive nearest neighbor searching (NNS) between descriptors and RANSAC-based geometric estimation is, however, low-efficient and unreliable for large-scale UAV images. Inspired by indexing-based NNS, this paper implements an efficient feature matching method for large-scale images based on Cascade Hashing and local geometric constraints. Our proposed method improves upon traditional feature matching approaches by introducing a combination of image retrieval, data scheduling, and GPU-accelerated Cascade Hashing. Besides, it utilizes a local geometric constraint to filter matching results within a matching framework. On the one hand, the GPU-accelerated Cascade Hashing technique generates compact and discriminative hash codes based on image features, facilitating the rapid completion of the initial matching process, and significantly reducing the search space and time complexity. On the other hand, after the initial matching is completed, the method employs a local geometric constraint to filter the initial matching results, enhancing the accuracy of the matching results. This forms a three-tier framework based on data scheduling, GPU-accelerated Cascade Hashing, and local geometric constraints. We conducted experiments using two sets of large-scale UAV image data, comparing our method with SIFTGPU to evaluate its performance in initial matching, outlier rejection, and 3D reconstruction. The results demonstrate that our method achieves a feature matching speed 2.0 times that of SIFTGPU while maintaining matching accuracy and producing comparable reconstruction results. This suggests that our method holds promise for efficiently addressing large-scale image matching. © 2024 Kan You et al.

关键词： Hash functions

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