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2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

作者： Kola, Sekhar Reddy Li, Yiming Chen, Chieh-Yang Chuang, Min-Hui National Yang-Ming Chiao Tung University Electrical Engineering and Computer Science International Graduate Program Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Department of Electrical Engineering and Computer Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Parallel and Scientific Computing Laboratory Hsinchu300 Taiwan

ISBN: (纸本)9781665409230

We for the first time study characteristic fluctuation of gate-all-around silicon nanosheet MOSFETs induced by random dopants fluctuation (RDF), interface trap fluctuation (ITF), and work function fluctuation (WKF), and their combinations. The explored devices affected by the WKF and its combination result in sizeable variability. Because of enigmatical interactions among the aforementioned random factors, overestimated variabilities occur if we only consider one random source each time, compared with the statistical 3D device simulation for full RDF, ITF and WKF at the same time. Notably, 10.78% and 103% overestimations are found for the threshold voltage and off-state current fluctuations. © 2022 IEEE.

关键词： Nanosheets

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Improving Candle Direction Classification in Forex Market Using Support Vector Machine with Hyperparameters Tuning 7

Improving Candle Direction Classification in Forex Market Us...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Oetama, Raymond Sunardi Heryadi, Yaya Lukas Suparta, Wayan Computer Science Bina Nusantara University Jakarta Indonesia Binus Graduate Program Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Institut Teknologi Nasional Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned. © 2022 IEEE.

关键词： Support vector machines

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Alignment-Free Estimation of Read to Genome Distances and Its Applications 29th

Alignment-Free Estimation of Read to Genome Distances and...

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29th International Conference on Research in Computational Molecular Biology, RECOMB 2025

作者： Şapcı, Ali Osman Berk Mirarab, Siavash Bioinformatics and Systems Biology Graduate Program UC San Diego San DiegoCA92093 United States Department of Electrical and Computer Engineering UC San Diego San DiegoCA92093 United States

ISBN: (纸本)9783031902512

Searching reads from unknown origins in a reference database and finding evolutionarily similar genomes is central to many applications. Quantifying the similarity by estimating the distance between each read and matching references could further help downstream analyses such as taxonomic characterization or even placing the read on a reference phylogeny. Such distances can be computed using alignment. Since alignment becomes impractical for ultra-large reference databases, many use k-mer-based tools for downstream tasks, but these methods do not compute distances. We introduce krepp to compute the distance between a read and a genome using a maximum likelihood framework built around k-mers. We further introduce algorithms to place reads on a reference tree. Empirical evaluations show that krepp accurately estimates distances, scales well with large databases, and can place short reads coming from any part of the genome on a reference phylogeny. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Average nucleotide identity Metagenomics Phylogenetic placement

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CVIT: CONTINUOUS VISION TRANSFORMER FOR OPERATOR LEARNING

arXiv

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arXiv 2024年

作者： Wang, Sifan Seidman, Jacob H. Sankaran, Shyam Wang, Hanwen Pappas, George J. Perdikaris, Paris Institution for Foundation of Data Science Yale University United States Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania United States Department of Electrical and Systems Engineering University of Pennsylvania United States

Operator learning, which aims to approximate maps between infinite-dimensional function spaces, is an important area in scientific machine learning with applications across various physical domains. Here we introduce the Continuous Vision Transformer (CViT), a novel neural operator architecture that leverages advances in computer vision to address challenges in learning complex physical systems. CViT combines a vision transformer encoder, a novel grid-based coordinate embedding, and a query-wise cross-attention mechanism to effectively capture multi-scale dependencies. This design allows for flexible output representations and consistent evaluation at arbitrary resolutions. We demonstrate CViT’s effectiveness across a diverse range of partial differential equation (PDE) systems, including fluid dynamics, climate modeling, and reaction-diffusion processes. Our comprehensive experiments show that CViT achieves state-of-the-art performance on multiple benchmarks, often surpassing larger foundation models, even without extensive pretraining and roll-out fine-tuning. Taken together, CViT exhibits robust handling of discontinuous solutions, multi-scale features, and intricate spatio-temporal dynamics. Our contributions can be viewed as a significant step towards adapting advanced computer vision architectures for building more flexible and accurate machine learning models in the physical sciences. All data and code are publicly available at https://***/PredictiveIntelligenceLab/cvit. © 2024, CC BY-NC-SA.

关键词： Computer vision

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Joint Design of Spirograph Method and Reconfigurable Intelligent Surface for Future Communication Systems

Joint Design of Spirograph Method and Reconfigurable Intelli...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Balqis Yafis Jane-Hwa Huang Chih-Min Yu Li-Chun Wang EECS Int’l Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering National Chi Nan University Taiwan Department of Information and Computer Engineering Chung Yuan Christian University Taiwan Dept. of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Reconfigurable Intelligent Surface (RIS) is a transformative technology using the passive beamforming capabilities to create the programmable wireless environments. However, the control overhead is a challenging issue. The system needs to deliver the high-precision reflection coefficients to the RIS controller, for adjusting the phase shifts of the numerous RIS elements. Therefore, we propose a Spirograph-based discrete beamdirection strategy, which selects a set of non-uniformly distributed beam directions based on the generic patterns generated by the Spirograph (SG). We evaluate the achievable data rate and the number of controlling bits of SG-based method. We compare the SG-based method, the ideal continuous phase-shift method, and the SISO method. Simulation results show that with the properly-selected discrete beam directions, the SG-based method can achieve a comparable data rate as the ideal method, while having a lower control overhead.

关键词： Wireless communication Quantization (signal) Array signal processing Simulation Design methodology Reconfigurable intelligent surfaces Reflection coefficient Global communication

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Developing power-assisted two-wheeled luggage-carrying robot for stair-lifting using admittance control

Developing power-assisted two-wheeled luggage-carrying robot...

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2023 IEEE International Conference on Mechatronics (ICM)

作者： Kazu Nagaya Takashi Ohhira Hideki Hashimoto Graduate School of Science and Engineering Chuo University 1-13-27 Kasuga Tokyo Bunkyo Japan Department of Electrical Electronic and Communication Engineering Chuo University 1-13-27 Kasuga Tokyo Bunkyo Japan

We propose a control method for a two-wheeled robot that can carry a load in a staircase environment without increasing the burden on humans through power-assist control using admittance control. Considering that the motion of lifting the robot burdens a human in a staircase environment, it was necessary to reduce the peak value of the human force when pulling the robot upward. We evaluated the proposed, conventional, and the case without control (no control’’) methods by simulations and experiments on actual machines. Hence, the proposed method reduces the human workload to about 75% of that of the conventional method and about 50% of that without control. The proposed method can also enable the machine climb upstairs at a velocity of 1 step/s, which is about three times faster than the conventional method.

关键词： Mechatronics Force Stairs Behavioral sciences Robots Admittance control

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Traffic Video Analytic Based on Convolutional Neural Network (CNN)

Traffic Video Analytic Based on Convolutional Neural Network...

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Industrial engineering and Artificial Intelligence (IEAI), International Conference on

作者： Izzah Hazirah Hedzir Abd Kadir Mahamad Sharifah Saon Mohd Anuaruddin Bin Ahmadon Muhammad Ikhsan Setiawan Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Johor Malaysia Graduate School of Sciences and Technology for Innovation Yamaguchi University Ube Japan Department of Civil Engineering Narotama University Surabaya Indonesia

This project focuses on real-time congestion detection and tracking to improve traffic safety by enabling mechanisms to improve drivers' situational awareness. With real-time congestion detection in place, systems can be implemented to send advanced warnings to drivers approaching the solution of a traffic queue. The data may also be utilized to regulate variable speed restrictions in an attempt to enhance safety or reduce traffic congestion. Real-time characteristics are crucial in the context of traffic safety in order to provide drivers with pertinent information about current traffic conditions. However, the results and methods presented in this project could be utilized offline to provide traffic authorities with information on the congestion behavior of a road system, which could be used as a guide for the development of the road system., which could be used as guidance in the development of the road system. The project involves the processing of analyzing vehicle speed, object detection in vehicle type, and vehicle count. The objectives of this project are to design a video analytic vehicle detection that can detect vehicle speed, and count. The system can be implemented to study the behavior of the road. It also can determine the consistency for the object, count and speed detection system application by using a video taken at overpass in front of Universiti Tun Hussein Onn (UTHM) with comparison with another application to approve the system's accuracy.

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Energy-aware Model Predictive Control with Obstacle Avoidance

Energy-aware Model Predictive Control with Obstacle Avoidanc...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Santos, Marcelo A. Ferramosca, Antonio Raffo, Guilherme V. Federal University of Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte Brazil University of Bergamo Department of Management Information and Production Engineering Dalmine24044 Italy Federal University of Minas Gerais Department of Electronics Engineering Belo Horizonte Brazil

ISBN: (纸本)9780738131153

This work proposes a single-layer finite-horizon optimal control strategy to solve the autonomous navigation problem while accounting for energy efficiency and providing obstacle avoidance feature in cluttered environments with unknown obstacles. Considering the rate capacity effect of electric batteries, the nonlinear state-of-charge behavior is described and included in the optimal control problem to achieve energy-awareness. Besides, artificial potential fields are considered to obtain obstacle avoidance capabilities. The control problem is formulated inspired by the tracking model predictive control framework, and it considers the central idea of including artificial variables into the control problem to obtain a closed-loop system with an enlarged domain of attraction and with feasibility insurance. Finally, numerical results in a case study considering a quadrotor UAV are provided to corroborate the proposed strategy. © 2021 IEEE.

关键词： Energy efficiency

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A Cybertwin-Based Trading Mechanism for Personalized Transmission Services in Cloud Native Networks

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IEEE Wireless Communications Letters 2025年

作者： Zeng, Zhiyong Liang, Dandan Qin, Meng Sun, Ruijin Liang, Hui Zhang, Wei Peking University Shenzhen Graduate School School of Electronic and Computer Engineering Shenzhen518055 China Pengcheng Laboratory Shenzhen518055 China Pengcheng Laboratory Department of Strategic and Advanced Interdisciplinary Research Shenzhen518055 China Xidian University Guangzhou institute of technology Guangzhou510555 China Dongguan University of Technology School of Electrical Engineering and Intelligentization Dongguan523808 China University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2052 Australia

The Cybertwin-based cloud native network (CCNN) with a cloud-edge-end architecture is to provide personalized user services, which includes both wireless access networks and cloud networks. However, the limited availability of resources and intense user competition present significant challenges. While prior studies have contributed to this issue, they overlook the feasibility of using resources as the trading object in a user-centric approach, particularly in wireless networks. To address this gap, this letter proposes a Cybertwin-based Personalized Transmission Service Trading Mechanism (CPTSTM), employing a one-to-many concurrent bilateral negotiation model for dynamic multi-provider trading. An optimization problem is formulated to minimize user costs by modeling the negotiation as a sequential decision-making process, accounting for individual rationality and system uncertainties. Given restricted and hybrid action spaces, we introduce a Constrained Parameterized Deep Q-learning Network (CPDQN)-based negotiation strategy integrating offer evaluation, acceptance, and bidding strategies. Simulation results confirm the feasibility of the proposed mechanism and demonstrate that the CPDQN-based algorithm outperforms existing methods in terms of trade success rate (nearly 100%) and the number of negotiation rounds (reduced by 75%) while maintaining comparable user utility across various scenarios. © 2012 IEEE.

关键词： Cloud platforms

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Orthogonal Constant-Amplitude Sequence Families for System Parameter Identification in Spectrally Compact OFDM

arXiv

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arXiv 2023年

作者： Lu, Shih-Hao Chung, Char-Dir Chen, Wei-Chang Tsou, Ping-Feng The Graduate Institute of Communication Engineering National Taiwan University Taipei10617 Taiwan The Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan The Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Realtek Inc. Hsinchu30076 Taiwan

In rectangularly-pulsed orthogonal frequency division multiplexing (OFDM) systems, constant-amplitude (CA) sequences are desirable to construct preamble/pilot waveforms to facilitate system parameter identification (SPI). Orthogonal CA sequences are generally preferred in various SPI applications like random-access channel identification. However, the number of conventional orthogonal CA sequences (e.g., Zadoff-Chu sequences) that can be adopted in cellular communication without causing sequence identification ambiguity is insufficient. Such insufficiency causes heavy performance degradation for SPI requiring a large number of identification sequences. Moreover, rectangularly-pulsed OFDM preamble/pilot waveforms carrying conventional CA sequences suffer from large power spectral sidelobes and thus exhibit low spectral compactness. This paper is thus motivated to develop several order-I CA sequence families which contain more orthogonal CA sequences while endowing the corresponding OFDM preamble/pilot waveforms with fast-decaying spectral sidelobes. Since more orthogonal sequences are provided, the developed order-I CA sequence families can enhance the performance characteristics in SPI requiring a large number of identification sequences over multipath channels exhibiting short-delay channel profiles, while composing spectrally compact OFDM preamble/pilot waveforms. © 2023, CC BY.

关键词： Orthogonal frequency division multiplexing

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