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6th IEEE Symposium on Future Telecommunication Technologies, SOFTT 2022

作者： Liong, H.J. Chiong, C.W.R. Gopal, Lenin Juwono, Filbert H. Curtin University Malaysia Department of Electrical and Computer Engineering Miri Sarawak98009 Malaysia University of Southampton Malaysia Eko Galleria Department of Electrical and Electronic Engineering Nusajaya Johor79100 Malaysia University of Southampton Malaysia Eko Galleria Computer Science Program Nusajaya Johor79100 Malaysia

ISBN: (纸本)9781665455978

Intelligent reflecting surface (IRS) has recently stimulated an upsurge of research interest due to its capability of enhancing the spectral and energy efficiencies for future sixth generation (6G) wireless communication systems. This motivates the integration of IRS into simultaneous wireless information and power transfer (SWIPT) systems to improve the performance of energy harvesting and information de-coding. To unleash the full potential of IRS and achieve high sum-rate, the optimal joint transmitter precoding and reflective beamforming design is crucial yet challenging to solve. The issue has not been well investigated and the solution remains elusive. Hence, this research aims to jointly optimize the transmitter precoding and reflective beamforming matrices for IRS-Assisted multi-user multiple-input multiple-output (MIMO) SWIPT systems under quality of service (QoS) constraints. Simulation results demonstrate the effectiveness of IRS in enhancing the system performance. © 2022 IEEE.

关键词： Beamforming

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3D geometric shape assembly via efficient point cloud matching 24

3D geometric shape assembly via efficient point cloud matchi...

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Proceedings of the 41st International Conference on Machine Learning

作者： Nahyuk Lee Juhong Min Junha Lee Seungwook Kim Kanghee Lee Jaesik Park Minsu Cho Department of Computer Science and Engineering POSTECH Pohang Korea Graduate School of Artificial Intelligence POSTECH Pohang Korea Department of Computer Science and Engineering Seoul National University Seoul Korea Department of Computer Science and Engineering Seoul National University Seoul Korea and Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Department of Computer Science and Engineering POSTECH Pohang Korea and Graduate School of Artificial Intelligence POSTECH Pohang Korea

Learning to assemble geometric shapes into a larger target structure is a pivotal task in various practical applications. In this work, we tackle this problem by establishing local correspondences between point clouds of part shapes in both coarse- and fine-levels. To this end, we introduce Proxy Match Transform (PMT), an approximate high-order feature transform layer that enables reliable matching between mating surfaces of parts while incurring low costs in memory and compute. Building upon PMT, we introduce a new framework, dubbed Proxy Match TransformeR (PMTR), for the geometric assembly task. We evaluate the proposed PMTR on the large-scale 3D geometric shape assembly benchmark dataset of Breaking Bad and demonstrate its superior performance and efficiency compared to state-of-the-art methods. Project page: https://***/pmtr.

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Integrating Physical Wheelchairs and Virtual Basketball for Enhanced Access and Enjoyment in Wheelchair Basketball 6

Integrating Physical Wheelchairs and Virtual Basketball for ...

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6th IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2024

作者： Hsu, Yu-Hung Fang, Iuan-Kai Wang, Chun Chen, Jui-Chien Hu, Min-Chun National Tsing Hua University Department of Computer Science Hsinchu Taiwan National Tsing Hua University International Intercollegiate Ph.D. Program Hsinchu Taiwan National Taiwan University Department of Electrical Engineering Taipei Taiwan University of Texas at Austin School of Information United States

ISBN: (纸本)9798350372021

Wheelchair basketball for people with disabilities is a niche market with limited attention and resources due to its smaller scale. We utilize the characteristics of VR technology, combining wearable devices with physical wheelchair seating, to create a virtual and real interactive game of wheelchair basketball. This enables people with disabilities to exercise at home and allows the general public to experience the challenges of disability sports, fostering empathy and emphasizing the importance of social justice. © 2024 IEEE.

关键词： Virtual reality

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A Method for Automatic Generation of 3D Background Models Using Fractal Models and Genetic Algorithms 11

A Method for Automatic Generation of 3D Background Models Us...

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11th International Symposium on Computing and Networking Workshops, CANDARW 2023

作者： Watanabe, Kaito Nakayama, Hirotaka Shiraki, Atsushi Ito, Tomoyoshi Hirata, Katsumi Hoshikawa, Naoto National Institute of Technology Oyama College Advanced Course General Engineering Program Oyama Japan National Astronomical Observatory of Japan Center for Computational Astrophysics Mitaka Japan Chiba University Graduate School of Engineering Chiba Japan National Institute of Technology Oyama College Department of Innovative Electrical and Electronic Engineering Oyama Japan University of Tsukuba Graduate School of Science and Tecnology Tsukuba Japan

ISBN: (纸本)9798350306941

In recent years, 3DCG-related industries have grown rapidly and the demand for 3DCG content has increased. However, 3DCG production requires special skills and a lot of time. In particular, the creation of background data requires a lot of human resources at the production site because the data is huge and complex. Therefore, we propose an automatic creation system that generates 3D background data for 3DCG production. The proposed system consists of three functions: 3D model generation, generation parameter optimization, and fitness evaluation. The user inputs a landscape photograph as idea information into the system, and the system optimizes the generation parameters so that the 3D object shape approximates the input image. To evaluate the accuracy of the system's performance, we observe the optimization process and the 3D object output when a previously generated fractal image or landscape photos are input. Experimental results show that the system accurately optimizes the generation parameters and generates 3D objects that are almost identical to the shape of the fractal image. In addition, the parameters were also optimized with a certain degree of accuracy for landscape photographs for which no specific solution had been determined. © 2023 IEEE.

关键词： Genetic algorithms

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Deep Reinforcement Learning-Based LSTM Model for Traffic Flow Forecasting in Internet of Vehicles

Deep Reinforcement Learning-Based LSTM Model for Traffic Flo...

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Chinese Intelligent Automation Conference, CIAC 2021

作者： Chen, Zekuan Luo, Xiong Wang, Ting Wang, Weiping Zhao, Wenbing School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China Shunde Graduate School University of Science and Technology Beijing Foshan528399 China Department of Electrical Engineering and Computer Science Cleveland State University ClevelandOH44115 United States

ISBN: (纸本)9789811663710

Nowadays many large cities often suffer from road congestion. Then, it is necessary to improve the working efficiency of urban road network with the help of computational intelligence technologies, within the Internet of vehicles (IoV) environment. We are committed to designing traffic flow prediction methods through the use of machine learning models. In this paper, we predict the traffic flow and traffic situation of the selected road segment. Specifically, we propose a deep reinforcement learning (DRL)-based long short-term memory (LSTM) model to predict the traffic flow. On the basis of it, we characterize the traffic situation with fuzzy comprehensive evaluation (FCE)-based model. The experimental results show that the constructed DRL-based LSTM model can accurately predict the traffic flow data. Meanwhile, the traffic situation characterization model can represent the road traffic situation well. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems

arXiv

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arXiv 2025年

作者： Partohaghighi, Mohammad Marcia, Roummel Chen, YangQuan Electrical Engineering and Computer Science graduate program University of California Merced United States Department of Applied Mathematics University of California Merced MercedCA United States Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

Fractional-order stochastic gradient descent (FOSGD) leverages a fractional exponent to capture long-memory effects in optimization, yet its practical impact is often constrained by the difficulty of tuning and stabilizing this exponent. In this work, we introduce 2SED Fractional-Order Stochastic Gradient Descent (2SEDFOSGD), a novel method that synergistically combines the Two-Scale Effective Dimension (2SED) algorithm with FOSGD to automatically calibrate the fractional exponent in a data-driven manner. By continuously gauging model sensitivity and effective dimensionality, 2SED dynamically adjusts the exponent to curb erratic oscillations and enhance convergence rates. Theoretically, we demonstrate how this dimension-aware adaptation retains the benefits of fractional memory while averting the sluggish or unstable behaviors frequently observed in naive fractional SGD. Empirical evaluations across multiple benchmarks confirm that our 2SED-driven fractional exponent approach not only converges faster but also achieves more robust final performance, suggesting broad applicability for fractional-order methodologies in large-scale machine learning and related domains. © 2025, CC BY.

关键词： Convex optimization

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Lightweight Pedestrian Detection through Guided Filtering and Deep Learning 10

Lightweight Pedestrian Detection through Guided Filtering an...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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Neural Network-Based Analysis of Mammography Images for Identifying Breast Cancer Histological Subtypes

Neural Network-Based Analysis of Mammography Images for Iden...

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Future Machine Learning and Data science (FMLDS), IEEE International Conference on

作者： Muhammad Alqaaf Ahmad Kamal Nasution graduate School of science and Technology Retno Supriyanti Abu Asaduzzaman Naoaki Ono Md. Altaf-Ul-Amin Shigehiko Kanaya Graduate School of Science and Technology Nara Institute of Science and Technology Ikoma Japan Department of Electrical Engineering Jenderal Soedirman University Banyumas Indonesia Department of Electrical and Computer Engineering Wichita State University Wichita U.S.A

ISBN: (数字)9798350391213

ISBN: (纸本)9798350391220

Breast cancer (BC) is a complex disease with multiple histological subtypes that exhibits distinct biological and clinical characteristics. Accurate identification of these subtypes is crucial for the implementation of personalized treatment strategies and the improvement of patient outcomes. This study aimed to leverage the potential of neural networks and mammography data to identify specific histological subtypes of BC, with a focus on distinguishing between in situ and invasive carcinoma. We used the Digital Database for Screening Mammography (DDSM) and its curated subset, CBIS-DDSM, which provides mammography images of normal and malignant cases with verified pathological information. A convolutional neural network (CNN) architecture was designed to extract relevant features from mammography images. The model was trained using data augmentation techniques to enhance diversity and mitigate overfitting, resulting in training and validation accuracies ranging from 0.98 to 1.0. The features extracted by the trained model were then used for clustering analysis using Kmeans on PCA (KM-PCA), which identified nine well-separated clusters with minimal overlap. The clustering results were validated using a subset of mammography images with confirmed invasive carcinoma types from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Two validation approaches were incorporated to strengthen the hypothesis and further validate the results. Overall, this study demonstrates the potential of combining neural networks and mammography data to accurately identify BC histological subtypes, which could pave the way for personalized and effective treatment strategies.

关键词： Training Analytical models Accuracy Neural networks Network analyzers Feature extraction Breast cancer Data models Convolutional neural networks Principal component analysis

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Towards an ultrafast 3D imaging scanning LiDAR system:a review

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Photonics Research 2024年第8期12卷 1709-1729页

作者： ZHI LI YAQI HAN LICAN WU ZIHAN ZANG MAOLIN DAI SZE YUN SET SHINJI YAMASHITA QIAN LI H.Y.FU Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical Engineering and Information Systems The University of TokyoTokyo 113-8656Japan Research Center for Advanced Science and Technology The University of TokyoTokyo 153-8904Japan School of Electronic and Computer Engineering Peking UniversityShenzhen 518055China

Light detection and ranging(LiDAR),as a hot imaging technology in both industry and academia,has undergone rapid innovation and *** current mainstream direction is towards system miniaturization and *** are many metrics that can be used to evaluate the performance of a LiDAR system,such as lateral resolution,ranging accuracy,stability,size,and *** recently,with the continuous enrichment of LiDAR application scenarios,the pursuit of imaging speed has attracted tremendous research ***,for autonomous vehicles running on motorways or industrial automation applications,the imaging speed of LiDAR systems is a critical *** this review,we will focus on discussing the upper speed limit of the LiDAR *** on the working mechanism,the limitation of optical parts on the maximum imaging speed is *** beam scanner has the greatest impact on imaging *** provide the working principle of current popular beam scanners used in LiDAR systems and summarize the main constraints on the scanning ***,we highlight the spectral scanning LiDAR as a new paradigm of ultrafast ***,to further improve the imaging speed,we then review the parallel detection methods,which include multiple-detector schemes and multiplexing ***,we summarize the LiDAR systems with the fastest point acquisition rate reported *** the outlook,we address the current technical challenges for ultrafast LiDAR systems from different aspects and give a brief analysis of the feasibility of different approaches.

关键词： LiDAR scanner system

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Adaptive prescribed performance based on recursive nonsingular terminal sliding mode control for quad-rotor systems under uncertainty and disturbance: Real-time validation

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Aerospace science and Technology 2024年 147卷

作者： Han, Gao Mofid, Omid Mobayen, Saleh Khooban, Mohammad Hassan School of Aerospace Science and Technology Xidian University Xi'an710071 China Department of Electrical Engineering University of Zanjan Zanjan Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Department of Electrical and Computer Engineering Aarhus University Aarhus8200 Denmark

In this paper, at the aim of the fast trajectory-following control of the Unmanned Aerial Vehicle (UAV) systems subject to uncertainty and disturbance, the adaptive prescribed performance control based recursive nonsingular terminal sliding mode control is suggested. Afterward, for the fast trajectory-following control of the uncertain and perturbed quad-rotor system, a recursive nonsingular terminal sliding mode strategy is recommended. Since the better transient and steady-state response of the sliding mode surface is of the utmost importance in the design of the controller, the prescribed performance control scheme is proposed in which the transformed prescribed form of the previously proposed recursive nonsingular terminal sliding surface is obtained to prove that the recursive nonsingular terminal sliding surface can converge to a preset region. Whereas unknown bounded uncertainty and disturbance always exist in the UAV system's dynamical model which decreases its performance and efficiency, the adaptive mechanism is applied to approximate uncertain bounds of uncertainty and disturbance to advance the implementation of the UAV system. Later, quick reachability of the prescribed form switching surface is demonstrated using Lyapunov concept. Ultimately, simulation results using MATLAB/Simulink over a quad-rotor system and real-time simulation using the Speedgoat Real-Time Target Machine platform are conducted to validate the feasibility and performance of the proposed method. © 2024 Elsevier Masson SAS

关键词： Unmanned aerial vehicles (UAV)

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