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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

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

ISBN: (纸本)9798350364637

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. © 2024 IEEE.

关键词： Quantum computers

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Introduction to Quantum Multi-Agent Reinforcement Learning: Concepts and Applications 15

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

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

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

ISBN: (纸本)9798350364637

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. © 2024 IEEE.

关键词： Quantum computers

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"There is a Damn Hello on the Social Media!" Insights into Public Risk Communication in the Digital Age 18th

"There is a Damn Hello on the Social Media!" Insights into P...

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18th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2024

作者： Große, Christine Division of Computer Science Electrical and Space Engineering Department of Digital Services and Systems Luleå University of Technology Luleå971 87 Sweden

ISBN: (纸本)9783031725586

The ability to handle threats, such as disinformation, manipulation of public opinion, and disruption of critical supplies, is becoming increasingly important, thus, necessitating, among other strategies, efforts to establish a proper risk communication to the public. This paper addresses the need for more empirical research in this area to contribute to the development of an in-depth understanding of public risk communication that includes information-related threats and cyber issues. The study involves officials of three public organizations entrusted with safety and security in society: the police, the rescue service, and the county administrative board of a county in the middle of Sweden. The results detail the recognition of risks to be communicated, the organization of the communication process, the messages that these actors seek to bring forth, and to whom as well as challenges of public risk communication in the digital era. The findings indicate that information-related and cyber risks are increasingly essential to consider as an additional layer of public communication. Two implications emerged as particularly important: (1) all communication about risks and crises must consider the systemic risk of mis- and disinformation, and (2) tailored communication about the risks interrelated with disinformation should use human-centered, dialogue-based, and moderated approaches. Further research can focus on associated challenges, considering the distribution of responsibilities, inter-organizational information sharing and cooperation, and the possibly stochastic effects on critical (information) infrastructures and, ultimately, societal values. © IFIP International Federation for Information Processing 2025.

关键词： Stochastic systems

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A Discontinuous Galerkin Time-Domain Method to Simulate Metasurfaces using Generalized Sheet Transition Conditions

A Discontinuous Galerkin Time-Domain Method to Simulate Meta...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Chen, Liang Ozakin, Mehmet Burak Zhao, Ran Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

The generalized sheet transition conditions (GSTCs) are incorporated into a discontinuous Galerkin time-domain (DGTD) method to efficiently simulate metasurfaces. The numerical flux for GSTCs is derived for the first time using the Rankine-Hugoniot jump conditions. This numerical flux includes time derivatives of fields and therefore explicit time integration schemes that are traditionally used with DGTD do not yield a stable time marching method. To alleviate this bottleneck, a new time marching scheme, which solves a local matrix system for the unknowns of the elements touching the same GSTC face, is developed. Numerical results, which validate the accuracy of the proposed method against analytical solutions and demonstrate its applicability to the simulation of curved and space/time-varying metasurfaces, are presented. © 2022 IEEE.

关键词： Numerical methods

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Multiphysics Analysis of Screening Effects on Terahertz Photoconductive Devices

Multiphysics Analysis of Screening Effects on Terahertz Phot...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Chen, Liang Dong, Ming Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

Output saturation observed for high power levels of input optical pump is a well-known bottleneck in the operation of terahertz photoconductive devices (PCDs). This saturation is a result of various screening effects that stem from the interactions between electromagnetic fields and semiconductor charge carriers. To simulate these effects, this work uses a time-domain multiphysics approach that solves a coupled system of the Maxwell and the drift-diffusion equations to rigorously take into account the two-way nonlinear coupling between fields and carriers. Furthermore, an optical absorption-based model is used to correctly compute the carrier generation rate. The resulting multiphysics solver is used to simulate realistic PCDs, and excellent agreement is observed between the simulation and experimental results. © 2022 IEEE.

关键词： Multiphysics

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A Discontinuous Galerkin Scheme for Transient Multiphysics Simulation of Organic Electrochemical Transistors

A Discontinuous Galerkin Scheme for Transient Multiphysics S...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Dong, Ming Chen, Liang Bagci, Hakan Computer Electrical and Mathematical Science and Engineering Division Electrical and Computer Engineering Program Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

A time domain discontinuous Galerkin (DGTD)-based framework is developed to analyze three-dimensional organic electrochemical transistors (OECTs). The proposed framework uses a local DG scheme to discretize the (non-linearly) coupled system of the Poisson equation (in electric potential) and the drift-diffusion (DD) equations (in charge densities) in space. To reduce the computational requirements, a dual-mesh scheme, which uses a dense mesh for the DD equations and a much coarser mesh for the Poisson equation, is used. Furthermore, an implicit-explicit time integration scheme, which allows for a significantly larger time-step size, is utilized to efficiently account for the extremely long response time of OECTs. Numerical results are provided to demonstrate the applicability and accuracy of the proposed solver. © 2022 IEEE.

关键词： Poisson equation

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An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

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computer Modeling in engineering & Sciences 2024年第3期138卷 2029-2059页

作者： Sheetal Sharma Kamali Gupta DeepaliGupta Shalli Rani Gaurav Dhiman Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India PG Department of Information Technology Goswami Ganesh Dutta Sanatan Dharma CollegeChandigarh160030India Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India Division of Research and Development Lovely Professional UniversityPunjab144001India

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart *** address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed *** analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

关键词： Error fault detection techniques sensor faults outliers Internet of Things

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Machine Learning and Deep Learning Approach for Predicting Neonatal Mortality in Indonesia 10

Machine Learning and Deep Learning Approach for Predicting N...

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10th International Conference on Applied System Innovation, ICASI 2024

作者： Hamid, Nur Rumiati, Fidya Prayogo, Rizal Dwi Nambo, Hidetaka Kanazawa University Division of Electrical Engineering and Computer Science Japan Universitas Indonesia Faculty of Public Health Department of Epidemiology Indonesia

ISBN: (纸本)9798350394924

This research explores machine learning approaches to determine the most significant features related to neonatal mortality in Indonesia. We create prediction tasks with deep learning models including MLP, LSTM, and CNN. We found that low birth weight and early breastfeeding becomes the most significant features related to neonatal mortality in Indonesia. For prediction task, implementing feature importance task as feature selection can improve prediction performance and reduce algorithm complexity. LSTM and CNN achieved the best prediction model with 90.91% accuracy. © 2024 IEEE.

关键词： Forecasting

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Near-sensor computing-assisted simultaneous viral antigen and antibody detection via integrated label-free biosensors with microfluidics

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InfoMat 2023年第10期5卷 80-95页

作者： Byungjoon Bae Yongmin Baek Jeongyong Yang Heesung Lee Charana S.S.Sonnadara Sangeun Jung Minseong Park Doeon Lee Sihwan Kim Gaurav Giri Sahil Shah Geonwook Yoo William APetri Kyusang Lee Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVirginiaUSA School of Electronic Engineering Soongsil UniversitySeoulRepublic of Korea Department of Electrical and Computer Engineering University of MarylandCollege ParkMarylandUSA Department of Chemical Engineering University of VirginiaCharlottesvilleVirginiaUSA Division of Infectious Diseases and International Health Department of MedicineSchool of MedicineUniversity of VirginiaCharlottesvilleVirginiaUSA Department of Material Science and Engineering University of VirginiaCharlottesvilleVirginiaUSA Department of Intelligent Semiconductors Soongsil UniversitySeoulRepublic of Korea

Precise diagnosis and immunity to viruses,such as severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)and Middle East respiratory syndrome coronavirus(MERS-CoV)is achieved by the detection of the viral antigens and/or corresponding antibodies,***,a widely used antigen detection methods,such as polymerase chain reaction(PCR),are complex,expensive,and time-consuming Furthermore,the antibody test that detects an asymptomatic infection and immunity is usually performed separately and exhibits relatively low *** achieve a simplified,rapid,and accurate diagnosis,we have demonstrated an indium gallium zinc oxide(IGZO)-based biosensor field-effect transistor(bio-FET)that can simultaneously detect spike proteins and antibodies with a limit of detection(LOD)of 1 pg mL–1 and 200 ng mL–1,respectively using a single assay in less than 20 min by integrat-ing microfluidic channels and artificial neural networks(ANNs).The near-sensor ANN-aided classification provides high diagnosis accuracy(>93%)with significantly reduced processing time(0.62%)and energy consumption(5.64%)compared to the software-based *** believe that the development of rapid and accurate diagnosis system for the viral antigens and antibodies detec-tion will play a crucial role in preventing global viral outbreaks.

关键词： artificial intelligence biosensor edge-computing integration microfluidic

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Performance-Guaranteed Solutions for Multi-Agent Optimal Coverage Problems using Submodularity, Curvature, and Greedy Algorithms 63

Performance-Guaranteed Solutions for Multi-Agent Optimal Cov...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Welikala, Shirantha Cassandras, Christos G. Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States Boston University Division of Systems Engineering and Center for Information and Systems Engineering BrooklineMA02446 United States

ISBN: (纸本)9798350316339

We consider a class of multi-agent optimal coverage problems in which the goal is to determine the optimal placement of a group of agents in a given mission space so that they maximize a coverage objective that represents a blend of individual and collaborative event detection capabilities. This class of problems is extremely challenging due to the non-convex nature of the mission space and of the coverage objective. With this motivation, greedy algorithms are often used as means of getting feasible coverage solutions efficiently. Even though such greedy solutions are suboptimal, the submodularity (diminishing returns) property of the coverage objective can be exploited to provide performance bound guarantees. Moreover, we show that improved performance bound guarantees (beyond the standard (1-1 / e) performance bound) can be established using various curvature measures of the coverage problem. In particular, we provide a brief review of all existing popular applicable curvature measures, including a recent curvature measure that we proposed, and discuss their effectiveness and computational complexity, in the context of optimal coverage problems. We also propose novel computationally efficient techniques to estimate some curvature measures. Finally, we provide several numerical results to support our findings and propose several potential future research directions. © 2024 IEEE.

关键词： Optimal detection

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