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International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Sungjoon Lee Gyu Seon Kim Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9783903176652

ISBN: (纸本)9798331508722

Airports are critical hubs for international travel, managing increasing passenger numbers and dynamic flight schedules. Efficient air traffic management (ATM) is essential for ensuring safety, minimizing delays, and optimizing airport capacity. Traditional methods like Dijkstra's algorithm are limited in dynamic environments due to their static nature and high computational requirements. This paper proposes using multi-agent reinforcement learning (MARL) algorithms, specifically communication network (CommNet), to address these challenges. CommNet enables information sharing among agents and co-ordinated actions, leading to efficient and safe aircraft routing. Our study leverages CommNet's centralized training and decentralized execution (CTDE) to demonstrate MARL flexibility, adaptability, and efficiency. Evaluated in a simulated environment modeled after Incheon International Airport (ICN), CommNet's performance is compared with other reinforcement learning (RL) algorithms lacking inter-agent communication. Results show CommNet significantly reduces aircraft delay times, optimizes taxiing energy consumption, and maintains safety standards, using approximately 10.1% less energy than independent MARL (I-MARL). These findings highlight CommNet's potential to enhance next-generation ATM systems through improved coordination and decision-making.

关键词： Training Heuristic algorithms Atmospheric modeling Wireless networks Reinforcement learning Airports Safety Delays Air traffic control Aircraft

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Trends in One-Shot Neural Architecture Search

Trends in One-Shot Neural Architecture Search

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Seok Bin Son Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Recent advances in neural architecture search (NAS) techniques have provided effective solutions for managing high-dimensional data. These methods algorithmically automate the design process of NAS, aiming to identify an optimized structure that meets target performance criteria with reduced time and resource expenditure. This paper introduces the One-shot NAS method, which offers a computationally efficient approach to exploring NAS while minimizing the associated computational costs.

关键词： High dimensional data Market research Neural architecture search Computational efficiency Information and communication technology Convergence

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Trends in Transfer Learning on Reinforcement Learning for Mobility Control

Trends in Transfer Learning on Reinforcement Learning for Mo...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Sungjoon Lee Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper provides an in-depth analysis of recent trends and advancements in applying Transfer Learning (TL) techniques to RL for vehicle control. We particularly focus on applications in autonomous driving and unmanned systems. The integration of TL with RL has demonstrated significant potential in overcoming key challenges such as Sim2Real transfer, multi-agent collaboration, and scalability in real-time applications.

关键词： Scalability Transfer learning Collaboration Reinforcement learning Market research Real-time systems Information and communication technology Autonomous vehicles Convergence

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Introduction to Quantum Multi-Agent Reinforcement Learning: Concepts and Applications

Introduction to Quantum Multi-Agent Reinforcement Learning: ...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Yeryeong Cho Seok Bin Son Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Advancements in quantum computer hardware and software have paved the way for the application of quantum computing across various fields. With the development of computers with thousands of qubits, the power of quantum is increasing. Because of efficiency in high action dimensions, quantum computing has advantages in multi-agent fields where the amount of data is huge. At the same time, reinforcement learning (RL) has gained prominence for its potential in unknown environments. Consequently, the integration of quantum computing and multi-agent reinforcement learning (MARL), known as quantum multi-agent reinforcement learning (QMARL), is proposed. This paper introduces the overall concept and applications of quantum computing, MARL, and QMARL. It also shows the current technology trends depending on the application. In conclusion, the paper presents challenges and future research directions for QMARL and shows that QMARL can be utilized in various applications for excellent performance.

关键词： Quantum computing Qubit Reinforcement learning Market research Software Hardware Information and communication technology Convergence

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Real-me Nonlnear Pulse Evolution Dynamics n a Tm-doped Fiber Laser

Real-me Nonlnear Pulse Evolution Dynamics n a Tm-doped Fiber...

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CLEO: science and Innovations, CLEO:S and I 2023 - Part of Conference on Lasers and Electro-Optics 2023

作者： Xu, Shutao Zeng, Junje Sander, Michelle Y. Deparment of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BrooklineMA02446 United States Department of Biomedical Engering Boston University BostonMA02215 United States

We investigate the nonlinear pules evolution dynamics in a Tm-doped fiber laser in real-time with a modified dispersive Fourier trasform technique. Coherence degradation and recovery proceses are analyzed with spectra... 详细信息

ISBN: (纸本)9781957171258

关键词： Fiber lasers

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Quantum Reinforcement Learning: An Overview

Quantum Reinforcement Learning: An Overview

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Gyu Seon Kim Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Recent research in quantum computing has gained significant momentum, promising transformative advances across various fields, including artificial intelligence (AI). This paper focuses on quantum reinforcement learning (QRL), which utilizes quantum neural network (QNN) to address the inherent chal-lenges in conventional reinforcement learning (RL) frameworks. For a comprehensive examination of QRL, in this paper, the structure of QNN is explored in-depth, including the functional roles of key quantum circuit gates such as the unitary, rotation, controlled-X, and Hadamard gates. This paper also discusses the primary components of QNN, namely state encoding, parameterized quantum circuits (PQC), and measurement processes. Furthermore, the application of IBM qiskit for the visualization of quantum states and circuits is highlighted, providing practical insights into the deployment of quantum principles in RL. Consequently, this paper encapsulates the potential of QRL to revolutionize AI, positioning it as a pivotal area of future research and development in quantum computing.

关键词： Visualization Neural networks Reinforcement learning Logic gates Quantum state Encoding Information and communication technology Artificial intelligence Quantum circuit Research and development

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Quantum Teleportation: A Premier Quantum Communication Protocol

Quantum Teleportation: A Premier Quantum Communication Proto...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Chaemoon Im Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Communication is one of the fields that adopts quantum characteristics to improve its potential. In particular, quantum teleportation (QT) is considered a fundamental tool for enabling quantum networks. This paper focuses on the concept of QT and how it is applied in conjunction with additional technologies such as entanglement purification, entanglement swapping, and quantum error correction.

关键词： Privacy Protocols Quantum entanglement Purification Teleportation Information and communication technology Error correction Quantum networks Convergence

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Trends in Reinforcement Learning Methods for Stock Prediction

Trends in Reinforcement Learning Methods for Stock Predictio...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Jaehyun Chung Hyunseok Choi Seokhyeon Min Soohyun Park Joongheon Kim Department of Electrical and Computer Engineering Korea University Seoul Republic of Korea Division of Computer Science Sookmyung Women's University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

A popular and lucrative area of research has al-ways been stock prediction. Stock prediction using traditional deep learning has been proven to provide better accuracy and returns. However, as artificial intelligence developed, the idea of reinforcement learning (RL) emerged. The rise of RL in the financial markets is fueled by a number of benefits that are specific to this area of artificial intelligence (AI). RL, in particular, enables the combination of the “prediction” and “portfolio construction” activities into a single integrated step, allowing machine learning challenges to be precisely customized to investors' objectives. Conveniently, significant limitations like transaction costs, market liquidity, and investor risk aversion can be considered simultaneously. Despite the fact that supervised learning techniques continue to receive the majority of attention, the RL research community has achieved great strides in the financial field during the previous several years. This paper introduces the overall concepts and applications of RL and stock prediction. Additionally, current technology trends are presented based on several application domains. In summary, this paper explores RL-based research trends in the field of stock prediction and makes suggestions for future research avenues.

关键词： Costs Accuracy Supervised learning Reinforcement learning Predictive models Parallel processing Prediction algorithms Market research Real-time systems Portfolios

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Procrustean entanglement concentration for quantum-classical coexistence

Procrustean entanglement concentration for quantum-classical...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Lu, Hsuan-Hao Alshowkan, Muneer Alnas, Jude Lukens, Joseph M. Peters, Nicholas A. Quantum Information Science Section Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States School of Electrical and Computer Engineering Duke University DurhamNC27708 United States Research Technology Office and Quantum Collaborative Arizona State University TempeAZ85287 United States

We present a theoretical framework for Procrustean entanglement concentration tailored for polarization-entangled states infiltrated by polarized classical crosstalk, and experimentally validate its efficacy in a depl... 详细信息

ISBN: (纸本)9781957171395

关键词： Polarization

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Organic-inorganic hybrid piezotronic bipolar junction transistor for pressure sensing

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Microsystems & Nanoengineering 2024年第3期10卷 229-244页

作者： Emad Iranmanesh Zihao Liang Weiwei Li Congwei Liao Shunyu Jin Chuan Liu Kai Wang Shengdong Zhang Charalampos Doumanidis Gehan A.J.Amaratunga Hang Zhou Guangdong Provincial Key Laboratory of In-Memory Computing Chips School of Electronic and Computer EngineeringPeking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Mechanical Engineering Guangdong Technion-Israel Institute of TechnologyShantou 515063P.R.China State Key Laboratory of Microelectronics Device and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029P.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000PR China School of Electronics and Information Technology Sun Yat-sen UniversityNo.132 East Waihuan RoadGuangzhou 510006P.R.China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of South AlabamaShelby Hall3128MobileAL 36688USA Electrical Engineering Division Department of EngineeringUniversity of Cambridge9 JJ Thomson AvenueCambridge CB30FAUnited Kingdom Zhejiang University International CampusHainingChina

With the rapid development of the Internet of Things(IoTs),wearable sensors are playing an increasingly important role in daily monitoring of personal health and *** signal-to-noise-ratio has become the most critical performance factor to *** enhance it,on the one hand,good sensing materials/devices have been employed;on the other hand,signal amplification and noise reduction circuits have been ***,most of these devices and circuits work in an active sampling mode,requiring frequent data acquisition and hence,entailing high-power *** this scenario,a flexible and wearable event-triggered sensor with embedded signal amplification without an external power supply is of great ***,we report a flexible two-terminal piezotronic n-p-n bipolar junction transistor(PBJT)that acts as an autonomous and highly sensitive,current-and/or voltage-mediated pressure *** PBJT is formed by two back-to-back piezotronic diodes which are defined as emitter-base and collectorbase *** force exertion on the emitter side,as a result of the piezoelectric effect,the emitter-base diode is forward biased while the collector-base diode is reverse *** to the inherent BJT amplification effect,the PBJT achieves record-high sensitivities of 139.7 kPa^(-1)(current-based)and 88.66 kPa^(-1)(voltage-based)in sensing *** PBJT also has a fast response time of<110 ms under exertion of dynamic stimuli ranging from a flying butterfly to a gentle finger ***,the PBJT advances the state of the art not only in terms of sensitivity but also in regard to being self-driven and autonomous,making it promising for pressure sensing and other IoT applications.

关键词： bipolar transistor IoT

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