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arXiv 2024年

作者： Bu, Fanchen Jo, Hyeonsoo Lee, Soo Yong Ahn, Sungsoo Shin, Kijung School of Electrical Engineering KAIST Daejeon Korea Republic of Kim Jaechul Graduate School of Artificial Intelligence KAIST Seoul Korea Republic of Graduate School of Artificial Intelligence POSTECH Pohang Korea Republic of Department of Computer Science and Engineering Pohang Korea Republic of

Combinatorial optimization (CO) is naturally discrete, making machine learning based on differentiable optimization inapplicable. Karalias & Loukas (2020) adapted the probabilistic method to incorporate CO into differentiable optimization. Their work ignited the research on unsupervised learning for CO, composed of two main components: probabilistic objectives and derandomization. However, each component confronts unique challenges. First, deriving objectives under various conditions (e.g., cardinality constraints and minimum) is nontrivial. Second, the derandomization process is underexplored, and the existing derandomization methods are either random sampling or naive rounding. In this work, we aim to tackle prevalent (i.e., commonly involved) conditions in unsupervised CO. First, we concretize the targets for objective construction and derandomization with theoretical justification. Then, for various conditions commonly involved in different CO problems, we derive nontrivial objectives and derandomization to meet the targets. Finally, we apply the derivations to various CO problems. Via extensive experiments on synthetic and real-world graphs, we validate the correctness of our derivations and show our empirical superiority w.r.t. both optimization quality and speed. © 2024, CC BY.

关键词： Combinatorial optimization

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Optical Wireless Integrated Sensing and Communication Based on Optical Phased Array: Performance Metric and Optimal Beamforming

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IEEE Transactions on Wireless Communications 2025年

作者： Wen, Yunfeng Yang, Fang Song, Jian Han, Zhu Tsinghua University Department of Electronic Engineering Beijing100084 China State Key Laboratory of Widegap Semiconductor Optoelectronic Materials and Technologies Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Optical wireless integrated sensing and communication (OW-ISAC) is emerging as a crucial technology to complement and augment its radio-frequency counterpart. In this paper, we propose an optical phased array (OPA)-based OW-ISAC framework to enable concurrent multi-user communication and environment imaging. The optical beamforming and atmospheric propagation are first elaborated to introduce the principles of OPA-based OW-ISAC. In addition, the investigation into the multi-beam property, direct detection scheme, and sensing task of imaging for OW-ISAC yields dedicated signal-to-interference-plus-noise ratio and contrast metrics for communication and sensing sub-systems, respectively. Moreover, the precoding matrices and photodiode orientations are jointly optimized to achieve optimal beamforming. Subsequently, numerical simulations illustrate the relationships between communication and sensing performance metrics. Furthermore, the proposed OW-ISAC scheme is substantiated in a realistic scenario with the optimized beamforming. The demonstrated high-precision sensing and reliable communication capabilities of OPA-based OW-ISAC can serve plentiful future applications in the era of connection and intelligence. © 2002-2012 IEEE.

关键词： Optical communication

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Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models 9

Digital Forensics Investigation and Incident Response in Int...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Ahdan, Syaiful Zaki Hamidi, Eki Ahmad Riskiono, Sampurna Dadi Negara, Ridha Muldina Mayasari, Ratna Ramadona, Suci Nurhayati, Ade Sucipto, Adi Jupriyadi Nurkahfi, Galih Nugraha Farahiyah, Dzata Naseer, Muchammad Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia Uin Sunan Gunung Djati Bandung Electrical Engineering Department Bandung40614 Indonesia School of Electrical Engineering Telkom University Bandung40257 Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau28265 Indonesia Institut Teknologi Telkom Jakarta Faculty of Engineering Jakarta11710 Indonesia Bandung40135 Indonesia Universitas Islam Indonesia Yogyakarta Faculty of Industrial Technology Yogyakarta55584 Indonesia Sekolah Tinggi Teknologi Bandung Informatics Department Bandung40235 Indonesia

ISBN: (纸本)9798350305029

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article. © 2023 IEEE.

关键词： Internet of things

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Preprocessing Techniques for Enhancing Vision-Based Detection System for Tire Sidewall Extraction 7

Preprocessing Techniques for Enhancing Vision-Based Detectio...

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7th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2024

作者： Loo, Jia Hao Jauw, Veronica Lestari Lim, Chin Seong Sarmin, Khairul-Rijal Qomariyah, Nunung Nurul Fajar, Ahmad Nurul University of Nottingham Malaysia Department of Mechanical Materials and Manufacturing Engineering Malaysia Continental Tyre Technology Centre Malaysia Petaling Jaya Malaysia Bina Nusantara University School of Computing and Creative Arts Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Information System Management Department Jakarta Indonesia

ISBN: (纸本)9798331519643

This study aims to develop a system for extracting crucial information from tire sidewalls using Optical Character Recognition (OCR). Initially, images of tire were captured manually by smartphone cameras, including Redmi 9T, iPhone 11, and Galaxy S23 Ultra. The captured images are then transferred to a computer for storage. Subsequently, these images were cropped according to the boundaries identified by Hough Circle Transform (HCT). The cropped images were then further pre-processed. During the pre-processing phase, geometrical transformation and image sharpening techniques are applied to enhance the clarity and readability of the text images. The text is then extracted using Google Vision, with the extracted text categorized by size, DOT, brand and pattern. The results indicated that the effectiveness of image pre-processing was constrained by the accuracy of circle detection, which reached a maximum rate of 87.1%. This causes parts of the text to be cut out inaccurately, leading to a suboptimal extraction accuracy of 55.65%. It is also observed that the Redmi 9T camera produced inconsistent results compared to other devices. Specifically, the iPhone 11 and Samsung Galaxy S23 Ultra demonstrated superior extraction accuracies of 69.71% and 66.37%, respectively, whereas the Redmi 9T achieved a lower extraction accuracy of 37.76%. © 2024 IEEE.

关键词： OCR text extraction text identification tire handling tire sidewalls information

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UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes

UpCycling: Semi-supervised 3D Object Detection without Shari...

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International Conference on computer Vision (ICCV)

作者： Sunwook Hwang Youngseok Kim Seongwon Kim Saewoong Bahk Hyung-Sin Kim Department of Electrical and Computer Engineering Seoul National University SK Telecom Seoul Korea Graduate School of Data Science Seoul National University

Semi-supervised Learning (SSL) has received increasing attention in autonomous driving to reduce the enormous burden of 3D annotation. In this paper, we propose UpCycling, a novel SSL framework for 3D object detection with zero additional raw-level point cloud: learning from unlabeled de-identified intermediate features (i.e., "smashed" data) to preserve privacy. Since these intermediate features are naturally produced by the inference pipeline, no additional computation is required on autonomous vehicles. However, generating effective consistency loss for unlabeled feature-level scene turns out to be a critical challenge. The latest SSL frameworks for 3D object detection that enforce consistency regularization between different augmentations of an unlabeled raw-point scene become detrimental when applied to intermediate features. To solve the problem, we introduce a novel combination of hybrid pseudo labels and feature-level Ground Truth sampling (F-GT), which safely augments unlabeled multi-type 3D scene features and provides high-quality supervision. We implement UpCycling on two representative 3D object detection models: SECOND-IoU and PV-RCNN. Experiments on widely-used datasets (Waymo, KITTI, and Lyft) verify that UpCycling outperforms other augmentation methods applied at the feature level. In addition, while preserving privacy, UpCycling performs better or comparably to the state-of-the-art methods that utilize raw-level unlabeled data in both domain adaptation and partial-label scenarios.

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Self-polarized RGB device realized by semipolar micro-LEDs and perovskite-in-polymer films for backlight applications

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Opto-Electronic Advances 2024年第3期7卷 35-49页

作者： Tingwei Lu Yue Lin Tianqi Zhang Yue Huang Xiaotong Fan Shouqiang Lai Yijun Lu Hao-Chung Kuo Zhong Chen Tingzhu Wu Rong Zhang School of Electronic Science and Engineering Fujian Engineering Research Center for Solid-State LightingXiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China Department of Photonics and Graduate Institute of Electro-Optical Engineering College of Electrical and Computer EngineeringYang Ming Chiao Tung UniversityHsinchu 30010China Semiconductor Research Center Hon Hai Research InstituteTaipei 11492China.

In backlighting systems for liquid crystal displays,conventional red,green,and blue(RGB)light sources that lack polarization properties can result in a significant optical loss of up to 50%when passing through a *** address this inefficiency and optimize energy utilization,this study presents a high-performance device designed for RGB polarized *** device employs an array of semipolar blueμLEDs with inherent polarization capabilities,coupled with mechanically stretched films of green-emitting CsPbBr3 nanorods and red-emitting CsPbI3-Cs4PbI6 hybrid *** CsPbBr3 nanorods in the polymer film offer intrinsic polarization emission,while the aligned-wire structures formed by the stable CsPbI3-Cs4PbI6 hybrid nanocrystals contribute to substantial anisotropic emissions,due to their high dielectric *** resulting device achieved RGB polarization degrees of 0.26,0.48,and 0.38,respectively,and exhibited a broad color gamut,reaching 137.2%of the NTSC standard and 102.5%of the Rec.2020 *** compared to a device utilizing c-plane LEDs for excitation,the current approach increased the intensity of light transmitted through the polarizer by 73.6%.This novel fabrication approach for polarized devices containing RGB components holds considerable promise for advancing next-generation display technologies.

关键词： halide perovskite light-emitting-diodes polarized emission nanocrystals stability

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Provably Efficient Algorithm for Nonstationary Low-Rank MDPs

arXiv

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arXiv 2023年

作者： Cheng, Yuan Yang, Jing Liang, Yingbin Integrative Sciences and Engineering Programme NUS Graduate School Singapore School of Electrical Engineering and Computer Science The Pennsylvania State University University ParkPA16802 United States Department of Electrical and Computer Engineering The Ohio State University OH43210 United States

Reinforcement learning (RL) under changing environment models many real-world applications via nonstationary Markov Decision Processes (MDPs), and hence gains considerable interest. However, theoretical studies on nonstationary MDPs in the literature have mainly focused on tabular and linear (mixture) MDPs, which do not capture the nature of unknown representation in deep RL. In this paper, we make the first effort to investigate nonstationary RL under episodic low-rank MDPs, where both transition kernels and rewards may vary over time, and the low-rank model contains unknown representation in addition to the linear state embedding function. We first propose a parameter-dependent policy optimization algorithm called PORTAL, and further improve PORTAL to its parameter-free version of Ada-PORTAL, which is able to tune its hyper-parameters adaptively without any prior knowledge of nonstationarity. For both algorithms, we provide upper bounds on the average dynamic suboptimality gap, which show that as long as the nonstationarity is not significantly large, PORTAL and Ada-PORTAL are sample-efficient and can achieve arbitrarily small average dynamic suboptimality gap with polynomial sample complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Markov processes

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Hybrid Full-Bridge Phase-Shift and Half-Bridge LLC Resonant Converter Based on Dual Transformers

Hybrid Full-Bridge Phase-Shift and Half-Bridge LLC Resonant ...

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International Conference on Applied System Innovation (ICASI)

作者： Chih-Chiang Hua Ching-Chun Chuang Min-Rui Hong Jian-Min Wang Department of Electrical Engineering National Yunlin University of Science and Technology Douliou Taiwan R.O.C. Department of Electrical Engineering National Kaohaiung University of Science and Technology Kaohsiung City Taiwan Computer Science and Information Engineering National Formosa University Taiwan Graduate Institute of Vehicle Engineering National Formosa University Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

This paper proposes a hybrid full-bridge phase-shift and half-bridge LLC resonant converter based on dual transformers with different output voltages. In the proposed LLC resonant circuit, the power switches can achieve zero-voltage switching, which reduces power losses caused by traditional hard switching. Additionally, the converter continuously operates at the resonant frequency, enabling zero-current switching for the rectifier diodes and enhancing overall converter efficiency. The prototype circuit operates at an input voltage of 400V and fixed frequency with a constant duty ratio. By adjusting the phase shift between PWM square waves to change the output power, the proposed converter achieves a wide range of output voltages from 250V to 450V and a rated capacity of 1kW. The experimental results show that the proposed converter achieves a maximum conversion efficiency of 92.01% at an output voltage of 250V and a maximum conversion efficiency of 93.78% at an output voltage of 450V.

关键词： Legged locomotion Technological innovation Resonant frequency Rectifiers RLC circuits Switches Resonant converters

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Synthetic Batik Pattern Generator Using Wasserstein Generative Adversarial Network with Gradient Penalty

Synthetic Batik Pattern Generator Using Wasserstein Generati...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Kus Andriadi Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large.

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization

Cloud-Native Mobile Application Applied for Law and Regulati...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Muhammad Juan Al Qausar Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process.

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