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7th International Conference on Informatics and Computing, ICIC 2022

作者： Syahidi, Aulia Akhrian Supianto, Ahmad Afif Hirashima, Tsukasa Watanobe, Yutaka Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin City Indonesia Research Center for Data and Information Sciences Bandung City Indonesia Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Learning Engineering Laboratory Higashihiroshima Japan University of Aizu Division of Information Systems Department of Computer Science and Engineering Fukushima AizuWakamatsu Japan

ISBN: (纸本)9798350345711

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the 'if-then' rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process. © 2022 IEEE.

关键词： Data mining

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Compartment-specific estimation of T2 and T2* with diffusion-PEPTIDE MRI

arXiv

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arXiv 2024年

作者： Gong, Ting Fair, Merlin J. Setsompop, Kawin Zhang, Hui Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom Radiological Sciences Laboratory Department of Radiology Stanford University StanfordCA United States Department of Electrical Engineering Stanford University StanfordCA United States

We present a microstructure imaging technique for estimating compartment-specific T2 and T2* simultaneously in the human brain. Microstructure imaging with diffusion MRI (dMRI) has enabled the modelling of intra-neurite and extra-neurite diffusion signals separately allowing for the estimation of compartment-specific tissue properties. These compartment-specific properties have been widely used in clinical studies. However, conventional dMRI cannot disentangle differences in relaxations between tissue compartments, causing biased estimates of diffusion measures which also change with TE. To solve the problem, combined relaxometry-diffusion imaging methods have been developed in recent years, providing compartmental T2-diffusion or T2*-diffusion imaging respectively, but not T2 and T2* together. As they provide complementary information, a technique that can estimate both jointly with diffusion is appealing to neuroimaging studies. The aim of this work is to develop a method to map compartmental T2-T2*-diffusion simultaneously. Using an advanced MRI acquisition called diffusion-PEPTIDE, a novel microstructure model is proposed and a multi-step fitting method is developed to estimate parameters of interest. We demonstrate for the first time that compartmental T2, T2* can be estimated simultaneously from in vivo data. we further show the accuracy and precision of parameter estimation with simulation. Copyright © 2024, The Authors. All rights reserved.

关键词： Tissue

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Low-latency machine learning FPGA accelerator for multi-qubit-state discrimination

arXiv

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arXiv 2024年

作者： Gautam, Pradeep Kumar Kalipatnapu, Shantharam Shankaranarayanan, H. Singhal, Ujjawal Lienhard, Benjamin Singh, Vibhor Thakur, Chetan Singh Department of Electronic Systems Engineering Indian Institute of Science Bangalore560012 India Defence Research and Development Organisation Bangalore560093 India Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States The Department of Physics Indian Institute of Science Bangalore560012 India

Measuring a qubit state is a fundamental yet error-prone operation in quantum computing. These errors can arise from various sources, such as crosstalk, spontaneous state transitions, and excitations caused by the readout pulse. Here, we utilize an integrated approach to deploy neural networks onto field-programmable gate arrays (FPGA). We demonstrate that implementing a fully connected neural network accelerator for multi-qubit readout is advantageous, balancing computational complexity with low latency requirements without significant loss in accuracy. The neural network is implemented by quantizing weights, activation functions, and inputs. The hardware accelerator performs frequency-multiplexed readout of five superconducting qubits in less than 50 ns on a radio frequency system on chip (RFSoC) ZCU111 FPGA, marking the advent of RFSoC-based low-latency multi-qubit readout using neural networks. These modules can be implemented and integrated into existing quantum control and readout platforms, making the RFSoC ZCU111 ready for experimental deployment. © 2024, CC BY.

关键词： System-on-chip

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Age-of-Information and Energy Optimization in Digital Twin Edge Networks

Age-of-Information and Energy Optimization in Digital Twin E...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yongna Guo Yaru Fu Yan Zhang Tony Q. S. Quek School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden School of Science and Technology Hong Kong Metropolitan University China Department of Informatics University of Oslo Oslo Norway Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing the two performance metrics Age of Information (AoI) and energy efficiency. We jointly consider the problems of edge association, power allocation, and digital twin deployment. However, the inherent randomness of the problem presents a significant challenge in identifying an optimal solution. To address this, we first analyze the feasibility conditions of the optimization problem. We then examine a specific scenario involving a static channel and propose a cyclic scheduling scheme. This enables us to derive the sum AoI in closed form. As a result, the joint optimization problem of edge association and power control is solved optimally by finding a minimum weight perfect matching. Moreover, we examine the one-shot optimization problem in the contexts of both frequent digital twin migrations and fixed digital twin deployments, and propose an efficient online algorithm to address the general optimization problem. This algorithm effectively reduces system costs by balancing frequent migrations and fixed deployments. Numerical results demonstrate the effectiveness of our proposed scheme in terms of low cost and high efficiency.

关键词： Measurement Multi-access edge computing Costs Numerical analysis Power control Information age Digital twins Synchronization Resource management Optimization

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Edit Temporal-Consistent Videos with Image Diffusion Model

arXiv

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arXiv 2023年

作者： Wang, Yuanzhi Li, Yong Zhang, Xiaoya Liu, Xin Dai, Anbo Chan, Antoni B. Cui, Zhen The PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China SeetaCloud Nanjing210094 China The Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong

Large-scale text-to-image (T2I) diffusion models have been extended for text-guided video editing, yielding impressive zero-shot video editing performance. Nonetheless, the generated videos usually show spatial irregularities and temporal inconsistencies as the temporal characteristics of videos have not been faithfully modeled. In this paper, we propose an elegant yet effective Temporal-Consistent Video Editing (TCVE) method to mitigate the temporal inconsistency challenge for robust text-guided video editing. In addition to the utilization of a pretrained T2I 2D Unet for spatial content manipulation, we establish a dedicated temporal Unet architecture to faithfully capture the temporal coherence of the input video sequences. Furthermore, to establish coherence and interrelation between the spatial-focused and temporal-focused components, a cohesive spatial-temporal modeling unit is formulated. This unit effectively interconnects the temporal Unet with the pretrained 2D Unet, thereby enhancing the temporal consistency of the generated videos while preserving the capacity for video content manipulation. Quantitative experimental results and visualization results demonstrate that TCVE achieves state-of-the-art performance in both video temporal consistency and video editing capability, surpassing existing benchmarks in the field. © 2023, CC BY.

关键词： Benchmarking

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Synchronized Optimization With Prescribed Performance for High-order Strict-feedback System

Synchronized Optimization With Prescribed Performance for Hi...

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IEEE Conference on Decision and Control

作者： Yuxiang Zhang Xiaoling Liang Dongyu Li Shuzhi Sam Ge Tong Heng Lee Department of Electrical and Computer Engineering National University of Singapore Singapore School of Cyber Science and Technology Beihang University Beijing China Tianmushan Laboratory Hangzhou P. R. China

This paper investigates synchronized optimization with prescribed performance for the strict-feedback system with time-synchronized convergence property, which is the highly essential performance desired in various real-world high-precision control applications. The prescribed performance is considered to keep the state-variables within a predefined region during the control period to meet the required system performance. To consider optimization performance while also concurrently attaining the time-synchronized properties simultaneously of each backstepping subsystem, optimized backstepping is utilized to establish the learning framework; wherein the normnormalized sign function is appropriately incorporated in each backstepping subsystem, which generates the decomposition of the optimal system control and gradient term of the cost function with appropriate time-synchronized control items and unknown independently learning parts to be approximated with neural networks. With this decomposition design, the learning objective is transformed to adaptively explore the optimal control parameter in the admissible policy region. By additionally employing the adaptive dynamic programming technique, actor-critic method, and gradient-constrained method, the solution of the Hamilton-Jacobi-Bellman equation is iteratively approximated while the learnable parameter stays within the predefined region. The work here has the outcome of time-synchronized convergence which surpasses the usual typical developments in this class of problems considered. The proposed method is verified with the vehicle platoon problem to show its effectiveness in that the system preserves special properties of time-synchronized stability and control while optimizing the overall system control.

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Double-RIS Aided Multi-user MIMO Communications: Common Reflection Pattern and Joint Beamforming Design

arXiv

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arXiv 2023年

作者： Zhang, Pingping Gong, Shiqi Ma, Shaodan State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China

Reconfigurable intelligent surface (RIS) has entered the public consciousness as a promising technology for enhancing the performance of future wireless communication systems by dynamically constructing the wireless channels. In this letter, we study a double-RIS aided downlink multi-user multiple-input multiple-output (MIMO) communication system. We investigate the mean-square-error (MSE) minimization problem by jointly optimizing the active transmit beamforming, the receive equalizer and the passive beamforming at each RIS. Different from prior works, for the sake of reducing both communication overhead and signal processing complexity, we assume that the two RISs utilize the common reflection pattern. Under this assumption, the coupling of the variables becomes tighter, thereby making the optimization problem more challenging to solve. To effectively address this issue, we propose a majorization-minimization (MM)-based alternating optimization (AO) algorithm. Numerical results show that in high signal-to-noise ratio (SNR) region, the double-RIS with common reflection pattern can achieve nearly the same performance as that with separate reflection pattern whereas the complexity is only half of the latter. Thus, our proposed design enables an effective tradeoff between the performance and the implementation complexity of the considered system. Copyright © 2023, The Authors. All rights reserved.

关键词： Mean square error

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Molecular Communication for Quorum Sensing Inspired Cooperative Drug Delivery

arXiv

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arXiv 2023年

作者： Fang, Yuting Johnston, Stuart T. Faria, Matt Huang, Xinyu Eckford, Andrew W. Evans, Jamie Department of Electrical and Electronic Engineering School of Mathematics and Statistics and Systems Biology Laboratory Department of Biomedical Engineering Department of Biomedical Engineering ARC Centre of Excellence in Covergent Bio-Nano Science and Technology The University of Melbourne ParkvilleVIC3010 Australia School of Engineering Australian National University CanberraACT2600 Australia Department of Electrical Engineering and Computer Science York University TorontoONM3J 1P3 Canada

A cooperative drug delivery system is proposed, where quorum sensing (QS), a density-dependent bacterial behavior coordination mechanism, is employed by synthetic bacterium-based nanomachines (B-NMs) for controllable drug delivery. In our proposed system, drug delivery is only triggered when there are enough QS molecules, which in turn only happens when there are enough B-NMs. This makes the proposed system can be used to achieve a high release rate of drug molecules from a high number of B-NMs when the population density of B-NMs may not be known. Analytical expressions for i) the expected activation probability of the B-NM due to randomly-distributed B-NMs and ii) the expected aggregate absorption rate of drug molecules due to randomly-distributed QS activated B-NMs are derived. Analytical results are verified by particle-based simulations. The derived results can help to predict and control the impact of environmental factors (e.g. diffusion coefficient and degradation rate) on the absorption rate of drug molecules since rigorous diffusion-based molecular channels are considered. Our results show that the activation probability at the B-NM increases as this B-NM is located closer to the center of the B-NM population and the aggregate absorption rate of the drug molecules non-linearly increases as the population density increases. © 2023, CC BY.

关键词： Aggregates

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Movable Antenna-Enhanced Wireless Communications: General Architectures and Implementation Methods

arXiv

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arXiv 2024年

作者： Ning, Boyu Yang, Songjie Wu, Yafei Wang, Peilan Mei, Weidong Yuen, Chau Björnson, Emil The National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China The EHF Key Laboratory of Fundamental Science School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China The School of Electrical and Electronics Engineering Nanyang Technological University 639798 Singapore Department of Computer Science KTH Royal Institute of Technology Stockholm Sweden

Movable antennas (MAs), traditionally explored in antenna design, have recently garnered significant attention in wireless communications due to their ability to dynamically adjust the antenna positions to changes in the propagation environment. However, previous research has primarily focused on characterizing the performance limits of various MA-assisted wireless communication systems, with less emphasis on their practical implementation. To address this gap, in this article, we propose several general MA architectures that extend existing designs by varying several key aspects to cater to different application scenarios and tradeoffs between cost and performance. Additionally, we draw from fields such as antenna design and mechanical control to provide an overview of candidate implementation methods for the proposed MA architectures, utilizing either direct mechanical or equivalent electronic control. Simulation results are finally presented to support our discussion. Copyright © 2024, The Authors. All rights reserved.

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H∞optimal control design of static var compensator coupling hybrid active power filter based on harmonic state-space modeling

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CPSS Transactions on Power Electronics and Applications 2021年第3期6卷 227-234页

作者： Gong, Cheng Sou, Wai-Kit Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macao 999078 China also with the Institute of Microelectronics University of Macau Macao 999078 China and also with the Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao 999078 China

Compared with the conventional active power filter (APF), the static var compensator coupling hybrid active power filter (SVC-HAPF) has distinct characteristics of low DC-link operating voltage, which can lower the system and operational costs. It also has a wider operational range than the conventional hybrid active power filter (HAPF). In this paper, a harmonic state-space (HSS) modeling is firstly proposed to address the nonlinearity issue of the SVC-HAPF. The HSS based SVC-HAPF model is linear time-invariant (LTI), which enables the optimal control techniques. Then, the linear matrix inequality (LMI) based H∞ optimal control design is proposed, which finds the optimal controller parameters via convex optimization algorithm. The proposed controller for the SVC-HAPF achieves high steady-state accuracy, fast transient response, and fixed switching frequency simultaneously. Finally, simulation and experimental results are also provided to verify the effectiveness and performance of the optimal controller for the SVC-HAPF in comparison with the recent developed state-of-the-art multi-quasi-proportional-resonant (MQPR) controller, which shows superior control performances. © 2017 CPSS.

关键词： State space methods

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