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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Artem Kudryavtsev Ivan Pavlov Violetta Zatsepina Automation and Computer Science Faculty Lipetsk State Technical University Lipetsk Russia

Cable routing for interconnection of power substation equipment is calculated considering loads caused by short-circuit, dead weight, wind, etc., but does not take into account additional conditions depending on final installation, or exclude loads such as those present in high-rise buildings. areas. seismic activity, aspects that would complement the cable deformation calculation, on the other hand, design efforts are generally not associated with 3D models, as they use only reference points and "splines" to determine Knowing the approximate deformation of the cable is important for verifying electrical distances, minimising possible inconvenience during the construction phase. This paper presents the integration of various load models for cables in a finite element representation with the SAP2000, including final installation conditions and seismic loads according to IEEE 1527, guaranteeing connection stability, electrical safe distances and equipment integrity. In addition, the deformation results are linked to an application developed in Dynamo-Python to augment the BIM model in Revit. With the proposed integration, the expected deformations are obtained for small offsets, presenting a better path correction and stress calculation, but for larger offsets representative differences in measured forces are obtained, and this aspect needs improvement.

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology 33

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Bogacki, P. Dlugosz, M. Talaska, T. Dlugosz, R. Aptiv Services Poland Kraków30-399 Poland Agh University of Science and Technology Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications Kraków30-059 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350347760

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance Systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock. © 2023 IEEE.

关键词： Pixels

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Reversing BLE Remote Control Protocols of Dual Channel LED Lamps with CCT and Illumination Control

Reversing BLE Remote Control Protocols of Dual Channel LED L...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Kandilarov, Rostislav Yordanov, Yordan University of Ruse 'Angel Kanchev' Faculty of Transport Department of Machine Science Machine Elements Engineering Graphics and Physics Ruse Bulgaria University of Ruse 'Angel Kanchev' Computer Systems and Technologies Faculty of Electrical Engeneering Electronics and Automation Ruse Bulgaria

ISBN: (纸本)9798350312911

In this paper various BLE protocols for communication between remote or Android applications and intelligent dual channel (cool and warm white) LED lamps were reverse engineered. Three protocols were fully decoded and several partially. Replay attack is tested and confirmed working. Demo C++ library was developed and a proof-of-concept firmware for esp32 based development board was used to verify the decoding and the attacks applicability. © 2023 IEEE.

关键词： Light emitting diodes

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A Suite of Division Algorithms for Posit Arithmetic

A Suite of Division Algorithms for Posit Arithmetic

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International Conference on Application Specific Systems (ASAP), Architectures and Processors

作者： Raul Murillo Alberto A. Del Barrio Guillermo Botella Dept. of Computer Architecture and Automation Faculty of Physics University of Madrid Madrid Spain Dept. of Computer Architecture and Automation Faculty of Computer Science Complutense University of Madrid Madrid Spain

Posit ™ arithmetic is a promising alternative to IEEE 754 floating-point arithmetic due to its higher accuracy, larger dynamic range, and bitwise compatibility. While posit arithmetic has been well studied for basic arithmetic operations, division has received little attention. This paper proposes multiple divider designs for posit arithmetic based on digit recurrence and iterative approximation, and evaluates their performance. ASIC synthesis results show that the proposed designs significantly reduce hardware requirements for 32-bit division units compared to previous works by 1.14 × in area, 1.11× in power, and 1.04×in datapath delay. Moreover, the paper introduces an approximate logarithmic posit division that achieves an 8.8×reduction in area and 29×reduction in energy consumption with negligible degradation of the final results, making it suitable for error-tolerant applications.

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An Efficient Model based on Machine Learning Algorithms for Virtual Machines Classification in Cloud Computing Environment 4

An Efficient Model based on Machine Learning Algorithms for ...

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4th International Conference on Innovative Research in Applied science, Engineering and Technology, IRASET 2024

作者： Amahrouch, Abdelhadi Bouhamidi, Mehdi Saadi, Youssef El Kafhali, Said Sultan Moulay Slimane University Faculty Of Sciences And Techniques Data Science For Sustainable Earth Laboratory B.P. 523 Beni Mellal23000 Morocco Polytechnic University Laboratory Of Industrial And Human Automation Mechanics And Computer Science Hauts-de-France France Hassan First University Of Settat Faculty Of Sciences And Techniques Computer Networks Modeling And Mobility Laboratory B.P. 539 Settat26000 Morocco

ISBN: (纸本)9798350309508

In cloud computing, virtual machines consolidation (VMC) techniques are commonly used to improve resource utilization and reduce energy consumption. Task scheduling in cloud systems is a crucial aspect of VMC as it involves mapping clients' requirements to the appropriate computing resources such as Virtual Machines (VMs) or Physical Machines (PMs). The cloud provider must ensure that tasks are executed efficiently using the available shared computing resources while maintaining the quality of service (QoS) and minimizing the carbon footprint. Therefore, a good VM migration based on the customer's needs and IT resource capacity is required to maintain the best performance of the cloud system. In this work, we introduce an approach that leverage machine learning-based algorithms for VMs classification based on their latency sensitivity to facilitate subsequent migration into a suitable PM for better VMC. These algorithms categorize VMs into two groups: potentially inter-active machines (exhibiting periodic behavior on a daily scale) and latency-insensitive machines (for example, batch workloads, development, and test workloads). Our model demonstrated robust performance, achieving an accuracy of around 83%, thus establishing itself as the most proficient classifier in this study. © 2024 IEEE.

关键词： Virtual machine

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SDSFusion: A Semantic-Aware Infrared and Visible Image Fusion Network for Degraded Scenes

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IEEE Transactions on Image Processing 2025年 34卷 3139-3153页

作者： Chen, Jun Yang, Liling Yu, Wei Gong, Wenping Cai, Zhanchuan Ma, Jiayi China University of Geosciences School of Automation Wuhan 430074 China Automation for Complex Systems Hubei Key Laboratory of Advanced Control and Intelligent Wuhan 430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan 430074 China China University of Geosciences Faculty of Engineering Wuhan 430074 China Macau University of Science and Technology School of Computer Science and Engineering Macau Macao Wuhan University Electronic Information School Wuhan 430072 China

A single-modal infrared or visible image offers limited representation in scenes with lighting degradation or extreme weather. We propose a multi-modal fusion framework, named SDSFusion, for all-day and all-weather infrared and visible image fusion. SDSFusion exploits the commonality in image processing to achieve enhancement, fusion, and semantic task interaction in a unified framework guided by semantic awareness and multi-scale features and losses. To address the disparity between infrared and visible images in degraded scenes, we differentiate modal features in a unified fusion model. Unlike existing joint fusion methods, we propose an adversarial generative network that refines the reconstruction of low-light images by embedding fused features. It provides feature-level brightness supplementation and image reconstruction to refine brightness and contrast. Extensive experiments in degraded scenes confirm that our approach is superior to state-of-the-art approaches in visual quality and performance, demonstrating the effectiveness of interaction improvement. © 1992-2012 IEEE.

关键词： adversarial generative network image fusion Multi-modal fusion semantic awareness

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Network Traffic Prediction with Decomposition and Multi-Scale Autocorrelation in Large-Scale Cloud Data Centers 21

Network Traffic Prediction with Decomposition and Multi-Scal...

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21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Wang, Meijia Yuan, Haitao Kuang, Zhenwei Ma, Hanbo Bi, Jing Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9798350365221

As the Internet and big data technologies advance, a tremendous amount of data is generated daily. Efficient network operations are essential for handling such data. Accurately predicting future network traffic in real-time enables prompt response from cloud infrastructure and efficient traffic scheduling and allocation, ultimately reducing costs, preventing economic losses, and optimizing the performance of downstream facilities. However, predicting network traffic in large-scale data centers is challenging due to the multidimensional, nonlinear, and high-volatility nature of the time series. Traditional prediction methods, e.g., regression algorithms, struggle to capture non-linear features effectively. Many deep learning models face issues such as gradient explosion or vanishing during their training. Current commonly used prediction methods fail to fully uncover vital information about the frequency domain features in the time series. To do so, this work proposes a novel network traffic prediction model that combines a Savitzky Golay filter, sequence decomposition, multi-scale attention, a temporal convolutional network, an autocorrelation mechanism, and bidirectional long short-term memory. It can accurately predict future network traffic by adaptively extracting important features without requiring excessive feature engineering of the original data. It performs end-to-end sequence prediction, feature selection, and automatic learning of data features and temporal dependencies to achieve accurate time series prediction and avoid redundant data processing. Experiments involving ablation studies and comparisons with advanced prediction models are performed with the Google cluster trace. Experimental results show that the proposed model improves the prediction accuracy by at least 38.52% over the state-of-the-art models. © 2024 IEEE.

关键词： Autocorrelation

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Transformer-Based Single-Cell Language Model:A Survey

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Big Data Mining and Analytics 2024年第4期7卷 1169-1186页

作者： Wei Lan Guohang He Mingyang Liu Qingfeng Chen Junyue Cao Wei Peng Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronic and InformationGuangxi UniversityNanning 530004China School of Computer and Electronic Information Guangxi UniversityNanning 530004China College of Life Science and Technology Guangxi UniversityNanning 530004China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China

The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention *** addition,increasing studies based on transformers have been proposed to model single-cell *** this review,we attempt to systematically summarize the single-cell language models and applications based on ***,we provide a detailed introduction about the structures and principles of ***,we review the single-cell language models and large language models for single-cell data ***,we explore the datasets and applications of single-cell language models in downstream tasks,such as batch correction,cell clustering,cell type annotation,gene regulatory network inference,and perturbation ***,we discuss the challenges of single-cell language models and provide promising research *** hope this review will serve as an up-to-date reference for researchers who are interested in the direction of single-cell language models.

关键词： language model transformers deep learning single-cell data

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On-Off Control Adaptive to System Disturbances 30

On-Off Control Adaptive to System Disturbances

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30th International Scientific Conference Electronics, ET 2021

作者： Nikolov, Nikola Nikolaev Alexandrova, Mariela Ivanova Faculty of Computer Science and Automation Technical University of Varna 1 Department of Automation Varna9010 Bulgaria

ISBN: (纸本)9781665445184

The present research proposes a modification of on-off control, which allows system flexibility and good control quality in the presence of variable disturbances. According to the proposed solution the control signal is divided into two, in the common case unequal parts, which further improves the overall control quality by ensuring system flexibility i.e. it will automatically select the best working regime, depending on the working conditions. The proposed solution at some extent 'imitates' adaptation of ACS to disturbances, which is due to the implementation of the second controller. Such effect, however is not observed for classic on-off control implementation, moreover it is evident that in the presence of disturbances the conditional steady-state of the control object is shifted © 2021 IEEE.

关键词： Quality control

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Indirect adaptive observer control (I-AOC) design for truck–trailer model based on T–S fuzzy system with unknown nonlinear function

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Complex and Intelligent Systems 2024年第5期10卷 7311-7331页

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Chang, Wer-Jer Yahya, Abid Badruddin, Irfan Anjum Kamangar, Sarfaraz Hussien, Mohamed Artificial Intelligence Research Institute China University of Mining and Technology Department of Automation University of Science and Technology of China Department of Marine Engineering of National Taiwan Ocean University (NTOU) Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and Technology Department of Mechanical Engineering College of Engineering King Khalid University Department of Chemistry Faculty of Science King Khalid University

Tracking is a crucial problem for nonlinear systems as it ensures stability and enables the system to accurately follow a desired reference signal. Using Takagi–Sugeno (T–S) fuzzy models, this paper addresses the problem of fuzzy observer and control design for a class of nonlinear systems. The Takagi–Sugeno (T–S) fuzzy models can represent nonlinear systems because it is a universal approximation. Firstly, the T–S fuzzy modeling is applied to get the dynamics of an observational system in order to estimate the unmeasurable states of an unknown nonlinear system. There are various kinds of nonlinear systems that can be modeled using T–S fuzzy systems by combining the input state variables linearly. Secondly, the T–S fuzzy systems can handle unknown states as well as parameters known to the indirect adaptive fuzzy observer. A simple feedback method is used to implement the proposed controller. As a result, the feedback linearization method allows for solving the singularity problem without using any additional algorithms. A fuzzy model representation of the observation system comprises parameters and a feedback gain. The Lyapunov function and Lipschitz conditions are used in constructing the adaptive law. This method is then illustrated by an illustrative example to prove its effectiveness with different kinds of nonlinear functions. A well-designed controller is effective and its performance index minimizes network utilization—this factor is particularly significant when applied to wireless communication systems. © The Author(s) 2024.

关键词： Adaptive observer control Feedback control design Indirect method Lyapunov–Krasovskii candidate T–S fuzzy models

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