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Personalized Multimedia Recommendation Systems Using Higher-Order Tensor Singular-Value-Decomposition

IEEE Transactions on Broadcasting 2024年第1期70卷 148-160页

作者： Chang, Shih Yu Wu, Hsiao-Chun Yan, Kun Chen, Xinjia Huang, Scott Chih-Hao Wu, Yiyan San Jose State University Department of Applied Data Science San JoseCA95192 United States Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for AI Applications Chungli32003 Taiwan Guilin University of Electronic Technology Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Department of Information and Telecommunication Guilin541004 China Northwestern State University Department of Engineering Technology NatchitochesLA71497 United States National Tsing Hua University Department of Electrical Engineering Hsinchu300 Taiwan Communications Research Centre Canada OttawaK2H 8S2 Canada

Because of rapid growth of multimedia data over the Internet, the infobesity has been emerging in recent years. Many recommender systems (RSs) have been proposed using a variety of techniques, including artificial intelligence, machine learning, statistical analysis, and data mining. Nowadays, E-commerce companies such as Amazon, eBay, Netflix, etc. have applied RSs conveniently to provide better customer services than before by enabling customized multimedia-content recommendations. It is well known that classical RSs are almost all based on the user-item attribute matrices. However, this two-fold user-item relationship should be extended to the emerging many-fold relationship among an arbitrary number of attribute groups so that the corresponding new RSs may lead to better performances. Therefore, in this paper, we introduce a novel personalized multimedia recommender system (PMRS) according to our proposed new parallel higher-order tensor singular-value-decomposition (PHOTSVD) algorithm. This PHOTSVD algorithm is capable of accommodating an arbitrary number of entities such as social-media channels, users, queries, webpages, etc. in a robust RS. Furthermore, we also investigate the cold start and data bias problems critical to RSs. Finally, we compare the performances of our proposed new PMRS and three other existing tensor-based RSs over realworld data with respect to the well-adopted metric, namely normalized root-mean-square error (NRMSE). Our proposed new PMRS greatly outperforms the other three existing tensor-based RSs in terms of NRMSE. © 1963-12012 IEEE.

关键词： Singular value decomposition

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Improving Performance of Eye Movements Classification Using CNN-Transformer Model

Improving Performance of Eye Movements Classification Using ...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Ahmad Riznandi Suhari Rudy Hartanto Sunu Wibirama Department of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia Department of Electrical and Information Engineering Signal Processing Laboratory Yogyakarta Indonesia

In the past decade, eye tracking has been a crucial approach for object selection in digital assistive technology as well as touchless digital signage. Accurate object selection depends on performance of eye movements classification. Many deep learning techniques have been proposed for eye movements classification. Despite of these numerous models, previous approaches have yet to achieve high classficiation accuracy—particularly when dealing with smooth pursuit eye movement. To bridge this scientific gap and improve the effectiveness of eye movement classification, we propose a hybrid CNN-Transformer model. We also incorporated Hyperband hyperparameter tuning to obtain the best parameter values of the model. We evaluated our approach in the GazeCom dataset. This dataset was enhanced with customized annotations designed to accommodate different types of eye movements. Our method yielded F1 scores of 0.9572, 0.9273, and 0.8358 for fixation, saccade, and smooth pursuit eye movements, respectively. The proposed method achieved superior F1 scores by a margin of 1% to 12.36% compared with the state-of-the-art Temporal Convolutional Network (TCN). A significant improvement was observed in the classification of smooth pursuit eye movement. The experimental results imply that the proposed method can serve as a guide for implementing the Transformer models for eye movements classification.

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A Belief Propagation Approach for Direct Multipath-Based SLAM

A Belief Propagation Approach for Direct Multipath-Based SLA...

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Asilomar Conference on signals, Systems & computers

作者： Mingchao Liang Erik Leitinger Florian Meyer Department of Electrical and Computer Engineering University of California San Diego USA Signal Processing and Speech Communication Laboratory Graz University of Technology Austria

In this work, we develop a multipath-based simultaneous localization and mapping (SLAM) method that can directly be applied to received radio signals. In existing multipath-based SLAM approaches, a channel estimator is used as a preprocessing stage that reduces data flow and computational complexity by extracting features related to multipath components (MPCs). We aim to avoid any preprocessing stage that may lead to a loss of relevant information. The presented method relies on a new statistical model for the data generation process of the received radio signal that can be represented by a factor graph. This factor graph is the starting point for the development of an efficient belief propagation (BP) method for multipath-based SLAM that directly uses received radio signals as measurements. Simulation results in a realistic scenario with a single-input single-output (SISO) channel demonstrate that the proposed direct method for radio-based SLAM outperforms state-of-the-art methods that rely on a channel estimator.

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Fire Security Systems Analysis and Internet of Things Implications

Fire Security Systems Analysis and Internet of Things Implic...

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IEEE International Conference on Electro-Information Technology

作者： Susana Rodriguez Fuerte Xinrui Yu Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing Research Laboratory Illinois Institute of Technology Chicago IL U.S.A.

This paper presents the current use of the Internet of Things (IoT) in fire evacuation and extinction. It examines the different approaches to the problem and technologies like Building Information Modeling (BIM) and mathematical algorithms that can be used to determine the optimal evacuation route. It also evaluates existing fire security solutions such as smoke, flame, motion, and gas sensors, LED lights, buzzers, and SMS modules. Entities that specialize in Residential and Commercial Security Systems and Home Automation are also discussed, along with the services they offer. The main objective of this study is to understand current systems and resources regarding fire evacuation and extinction systems and to analyze different developments in smart buildings to create an efficient system for fire detection and evacuation.

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Multi-Quasi-Proportional-Resonant Control for Capacitive-Coupling Grid-Connect Inverter (CGCI) with Accurate Active Power Injection Technique 49

Multi-Quasi-Proportional-Resonant Control for Capacitive-Cou...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Chan, Pak-Ian Sou, Wai-Kit Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350331820

In this paper, a multi-quasi-proportional-resonant control (MQPRC) for a three-phase capacitive-coupling grid-connect inverter (CGCI) with accurate active power injection technique is proposed to mitigate the current harmonics and improve the active power injection accuracy. Then, a detail parameter design of the proposed MQPRC is provided. And the proposed accurate active power injection is verified by the simulation. Subsequently, to verify the effectiveness of the proposed MQPRC, the simulation results are presented in comparison to the quasi-proportional-resonant control (QPRC). © 2023 IEEE.

关键词： Power quality

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Smart Infant Monitoring System Using computer Vision and AI

Smart Infant Monitoring System Using Computer Vision and AI

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IEEE International Conference on Electro-Information Technology

作者： Gurpreet Singh Abhishek Raj Shekhar Xinrui Yu Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing Research Laboratory Illinois Institute of Technology Chicago IL U.S.A.

The new era of technology is being greatly influenced by the field of artificial intelligence. computer vision and deep learning have become increasingly important due to their ability to process vast amounts of data and provide insights and solutions in a variety of fields. computer vision, deep learning and signal analysis have been used in a growing number of applications and services including smart devices, image, and speech recognition, healthcare, etc., one such device is an infant monitoring system. It monitors the daily activities of the infant such as their sleeping patterns, sounds, and movements. In this paper, deep learning and computer vision libraries were used to develop algorithms to detect whether the infant was in any uncomfortable situation such as sleeping on its back, face being covered and whether the infant was awake. The smart infant monitoring system detects the infant's unsafe resting situation in real time and sent immediate alerts to the caretaker's device. This paper presents the design flow of a smart infant monitoring system consisting of a night vision camera, a Jetson Nano, and a Wi-Fi internet connection. The pose estimation and awake detection algorithms were developed and tested successfully for different infant resting/sleeping situations. The smart infant monitoring system provides significant benefits for safety and an improved understanding of infants' sleep patterns and behavior.

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Point Cloud Generation with Stereo and Monocular Depth Estimation on FPGA

Point Cloud Generation with Stereo and Monocular Depth Estim...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Perez-Vicente, Alejandro Hernandez, David Fang, Tianyang Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Department of Electrical and Computer Engineering Research Laboratory ChicagoIL60616 United States Universidad Politécnica de Madrid Etsi Industriales Madrid Spain

ISBN: (纸本)9781665480093

This research proposes a system that leverages stereo vision and monocular depth estimation to form a depth map from which a 3D point cloud scene is extracted. The emergence of competitive neural networks for depth map estimation presents an opportunity for deployment on embedded systems. Both stereo and monocular depth algorithms were tested on multiple FPGA hardware platforms. To perform acceleration on configurable hardware, a Deep Learning processing Unit (DPU) IP was used for processing AI workloads, together with a Pseudo-LiDAR reprojection for 3D reconstruction on the Arm® processor. The DPU performance configuration will depend on the logic resources the targeted board has. This paper highlights the performance, resource utilization, and bottlenecks that came across different tested combinations of both hardware and neural network architectures. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Optimizing Inductive Power Transfer Circular Pad Coils for Electric Vehicles Using Multi-Objective Particle Swarm Optimization 49

Optimizing Inductive Power Transfer Circular Pad Coils for E...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wong, Hou-Wa Ieong, Chi-Fong Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350331820

The wireless power transfer (WPT) technology has gained significant attention in recent years due to its potential to provide a convenient and efficient method to charging electronic devices without the need for physical connections. In wireless charging, the inductive coils are significantly important as they are the component that power transfer takes place. In this context, Multi-Objective Particle Swarm Optimization (MOPSO) has emerged as a promising technique for designing WPT coils with improved performance. Aiming to verify the performance of the designed coil, LCC-S compensation topology was utilized as it can provide practical battery charging specifications. © 2023 IEEE.

关键词： Inductive power transmission

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A High-Performance Three-Coil Wireless Charging System for Empowering Unmanned Surface Vehicle 49

A High-Performance Three-Coil Wireless Charging System for E...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Ieong, Chi-Fong Wong, Hou-Wa Iam, Io-Wa Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350331820

The use of unmanned surface vehicles (USVs) in oceanography research is widespread due to their ability to provide real-time data. Due to the limited battery size, recharging operations including plugging and unplugging decrease the overall utilization of the USV. To address this issue, wireless power transfer (WPT) can be implemented by installing coils at the dock and inside the USV. In this paper, a three-coil WPT system is designed for offshore USV wireless charging applications. The proposed three-coil structure is designed to ensure adequate coupling and achieve high transfer efficiency. Aiming to meet practical battery charging specifications, LCC-S-S compensation topology is analyzed with detailed parameter design to provide constant current output. Finally, simulations are conducted to verify the coupling and output characteristics of the system. © 2023 IEEE.

关键词： Energy transfer

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Review of Different Current Control Strategies for Thyristor-Controlled LC-Coupling Hybrid Active Power Filter 32

Review of Different Current Control Strategies for Thyristor...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Sou, Wai-Kit Chan, Pak-Ian Gong, Cheng Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350399714

With the characteristics of low DC-link voltage and wide operating range, thyristor-controlled LC-coupling hybrid active power filter (TCLC-HAPF) is a promising power quality compensator in the medium-voltage-level power system. This paper reviews the design and implementation of different current control strategies for the TCLC-HAPF, which are hysteresis current control (HCC), multi-quasi-proportional-resonant control (MQPRC), H∞ optimal control (HOC), finite-set model predictive control (FS-MPC), second-order sliding mode control (SOSMC) and deadbeat current control (DBCC). Also, their pros and cons are fully discussed. In order to provide a deeper understanding about the steady-state and transient performances of these control strategies, the simulation study is presented under both inductive and capacitive loads. © 2023 IEEE.

关键词： Thyristors

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