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28th International Conference on automation and Computing, ICAC 2023

作者： Liu, Yefeng Yu, Longfei Zhang, Qichun School of Automation and Electrical Dept. Liaoning Key Laboratory of Information Physical Fusion and Intelligent Cnc Machine Tool Manufacturing Shenyang Institute of Technology Dept. Fushun China Shenyang Ligong University Dept. School of Automation and Electrica Engineering China University of Bradford Bradford Dept. Department of Computer Science United Kingdom

ISBN: (纸本)9798350335859

Traditional steel surface defect detection methods have issues such as low detection accuracy and efficiency. It is suggested a technique based on enhanced YOLOv5 steel surface fault identification. In order to improve the network's capacity to handle feature information, this study suggests adding SE attention mechanisms to the YOLOv5s network's Backbone, Neck, and SPPF and replacing the C3 structure at the end of the Backbone with C3TR. To achieve network model lightweight, it is proposed to replace the Neck part in the YOLOv5s model and the convolution in SPPF with Ghost convolution. Then, to improve network feature fusion, extend the improved SPPF to the Neck part. Introduce the SPD convolution in the Backbone section to reduce the information loss caused by the neural network's convolution. The tested mAP is 75.3%, which is 5.3% higher than the original model, 24.6% higher than the SSD method, and 4.6% higher than the YOLOv6 algorithm after the upgraded model has been trained on the NEU-DET dataset. The observed FPS is 81.3, which is 6.3 more than the relative literature algorithm and 18.0 more than the SSD algorithm. © 2023 IEEE.

关键词： Convolution

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PSCS4CPP: A Generative PSCS Implementation for C++ 1

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Model-Driven engineering and Software Development - 9th International Conference, MODELSWARD 2021, and 10th International Conference, MODELSWARD 2022, Revised Selected Papers

作者： Hammer, Maximilian Maschotta, Ralph Wichmann, Alexander Jungebloud, Tino Bedini, Francesco Zimmermann, Armin Systems and Software Engineering Group Computer Science and Automation Department Technische Universität Ilmenau Ilmenau Germany

ISBN: (数字)9783031388217

ISBN: (纸本)9783031388200

Since the early 2000s, Model-driven engineering has aimed to accomplish executable UML models. With fUML and PSCS, the Object Management Group (OMG) published standardized specifications of precise semantics for certain parts of UML in the form of metamodels, which form an execution environment. A certain characteristic of these environments is that static information about a model is analyzed and evaluated during runtime. With composite structures being a concept for describing structural properties of a model, the majority of execution semantics specified by PSCS concern analysis and processing of such static information about the model’s fine-grained structure. Thus, the PSCS specification appears suitable for a generative realization approach. Using Model-To-Text-Transformation to generate source code, which serves as an input for the actual execution environment, the runtime level of model executions can be relieved by outsourcing analysis and processing of static information to the level of code generation. By inserting this preprocessing step, the performance of the actual model execution at runtime can be improved. This paper introduces an implementation of the PSCS specification for C++ based on code generation using Model-to-Text-Transformation. This also includes a generative approach to realize an extension mechanism of the fUML and PSCS execution environments by introducing user-defined semantic execution strategies. The proposed PSCS implementation was developed as a part of the MDE4CPP project. Moreover, this paper presents a set of test models validating the correct functionality of the implementation as well as a performance benchmark. Finally, analysis results of an application example for the presented realization are evaluated and discussed. © 2023, Springer Nature Switzerland AG.

关键词： Specifications

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OPONeRF: One-Point-One NeRF for Robust Neural Rendering

arXiv

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arXiv 2024年

作者： Zheng, Yu Duan, Yueqi Zheng, Kangfu Yan, Hongru Lu, Jiwen Zhou, Jie Department of Automation Tsinghua University China Department of Electrical Engineering Tsinghua University China Department of Computer Science Tsinghua University China Weiyang College Tsinghua University China

In this paper, we propose a One-Point-One NeRF (OPONeRF) framework for robust scene rendering. Existing NeRFs are designed based on a key assumption that the target scene remains unchanged between the training and test time. However, small but unpredictable perturbations such as object movements, light changes and data contaminations broadly exist in real-life 3D scenes, which lead to significantly defective or failed rendering results even for the recent state-of-the-art generalizable methods. To address this, we propose a divide-and-conquer framework in OPONeRF that adaptively responds to local scene variations via personalizing appropriate point-wise parameters, instead of fitting a single set of NeRF parameters that are inactive to test-time unseen changes. Moreover, to explicitly capture the local uncertainty, we decompose the point representation into deterministic mapping and probabilistic inference. In this way, OPONeRF learns the sharable invariance and unsupervisedly models the unexpected scene variations between the training and testing scenes. To validate the effectiveness of the proposed method, we construct benchmarks from both realistic and synthetic data with diverse test-time perturbations including foreground motions, illumination variations and multi-modality noises, which are more challenging than conventional generalization and temporal reconstruction benchmarks. Experimental results show that our OPONeRF outperforms state-of-the-art NeRFs on various evaluation metrics through benchmark experiments and cross-scene evaluations. We further show the efficacy of the proposed method via experimenting on other existing generalization-based benchmarks and incorporating the idea of One-Point-One NeRF into other advanced baseline methods. Project Page: https://***/ OPONeRF/. Copyright © 2024, The Authors. All rights reserved.

关键词： Rendering (computer graphics)

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IEEE T-BIOM Editorial Board Changes

IEEE Transactions on Biometrics, Behavior, and Identity Scie...

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IEEE Transactions on Biometrics, Behavior, and Identity Science 2024年第1期7卷 1-2页

作者： Naser Damer Weihong Deng Jianjiang Feng Vishal M. Patel Ajita Rattani Mark Nixon Smart Living & Biometric Technologies Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Department of Computer Science and Engineering College of Engineering University of North Texas Denton TX USA

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A blind steganalysis-based predictive analytics of numeric image descriptors for digital forensics with Random Forest & SqueezeNet 5

A blind steganalysis-based predictive analytics of numeric i...

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5th International Conference on Information Technology for Education and Development, ITED 2022

作者： Akanji, Wasiu Okey, Ogobuchi Adelanwa, Saheed Odesanya, Oluwafunsho Olaleye, Taiwo Amusu, Mary Akinrinlola, Akinfolarin Oladejo, Abiodun Lagos State University of Science and Technology Department of Computer Science Lagos Nigeria Universidade Federal de Lavras Department of Systems Engineering and Automation MG Brazil Ladoke Akintola University of Technology Deaprtment of Electrical/Electronics Engineering Ogbomoso Nigeria

ISBN: (纸本)9781509064229

Image steganalysis have been a prominent study in digital forensics and the data science use case of artificial intelligence has been widely adopted in conceptual frameworks. In existing studies, deep learners gain prominence for intrusion detection systems while other dissimilar modules are used for feature extraction. Hence, this study rather employs deep learners as image embedding networks aimed at feature extraction for a predictive analytics of image steganalysis. The extracted numeric image descriptors trains three learner algorithms for pattern recognition using a 10 fold cross-validation system. Experimental result indicates the ensemble of Random forest algorithm and SqueezeNet image embedder as the best for steganalysis in digital forensics while the size of the training set turns out to be insignificant for the supervised machine learning study. © 2022 IEEE.

关键词： Digital forensics

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Movie sentiment analysis based on Long Short-Term Memory Network

Movie sentiment analysis based on Long Short-Term Memory Net...

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作者： Siyao Li Rui Qin Zijian Zhou College of Computer Science and Technology Harbin Engineering University Department of Automation Guangdong University of Technology Dundee International Institute Central South University

An important task in the study of Natural Language Processing(NLP) is the analysis of movie *** finishes the task of classifying movie review texts into sentiment,such as positive,negative or neutral *** works mainly follow the pipeline of LSTM(Long Short-Term Memory Network).The network model is a variant of Recurrent Neural Network(RNN) and particularly suitable for processing natural language *** existing LSTM-based works have improved the performance significantly,we argue that most of them deal with the problem of analyzing the sentiment of movie reviews while ignore analyze the model performance in different application scenarios,such as different lengths of the reviews and the frequency of sentiment adverbs in the *** alleviate the above issue,in this paper,we constructed a simple LSTM model containing an embedding layer,a batch normalization layer,a dropout layer,a one-dimensional convolutional layer,a maximal pooling layer,a bi-directional LSTM layer and a fully connected *** used the existing IMDB movie review dataset to train the model,and selected two research scenarios of movie review length and frequency of occurrence of sentiment adverbs to test the model,*** the experimental results,we proposed a model for the scenarios in which the LSTM model handles the problem of sentiment analysis with respect to the dataset construction,model stability and generalization ability,text fragment processing,data preprocessing and feature extraction,model optimization and improvement.

关键词： Sentiment Analysis LSTM Movie Review Different Application Scenarios

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Generative AI for Low-Carbon Artificial Intelligence of Things with Large Language Models

arXiv

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arXiv 2024年

作者： Wen, Jinbo Zhang, Ruichen Niyato, Dusit Kang, Jiawen Du, Hongyang Zhang, Yang Han, Zhu The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Department of Electrical and Computer Engineering University of Houston United States

By integrating Artificial Intelligence (AI) with the Internet of Things (IoT), Artificial Intelligence of Things (AIoT) has revolutionized many fields. However, AIoT is facing the challenges of energy consumption and carbon emissions due to the continuous advancement of mobile technology. Fortunately, Generative AI (GAI) holds immense potential to reduce carbon emissions of AIoT due to its excellent reasoning and generation capabilities. In this article, we explore the potential of GAI for carbon emissions reduction and propose a novel GAI-enabled solution for low-carbon AIoT. Specifically, we first study the main impacts that cause carbon emissions in AIoT, and then introduce GAI techniques and their relations to carbon emissions. We then explore the application prospects of GAI in low-carbon AIoT, focusing on how GAI can reduce carbon emissions of network components. Subsequently, we propose a Large Language Model (LLM)-enabled carbon emission optimization framework, in which we design pluggable LLM and Retrieval Augmented Generation (RAG) modules to generate more accurate and reliable optimization problems. Furthermore, we utilize Generative Diffusion Models (GDMs) to identify optimal strategies for carbon emission reduction. Numerical results demonstrate the effectiveness of the proposed framework. Finally, we insightfully provide open research directions for low-carbon AIoT. Copyright © 2024, The Authors. All rights reserved.

关键词： Low emission

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New Results in Stabilization of Uncertain Nonholonomic Systems:An Event-Triggered Control Approach

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Journal of Systems Science & Complexity 2021年第5期34卷 1953-1972页

作者： LIU Tengfei ZHANG Pengpeng WANG Mengxi JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110004China. Department of Electrical and Computer Engineering New York University370 Jay StreetBrooklynNY 11201USA

This paper reports latest developments in event-triggered and self-triggered control of uncertain nonholonomic systems in the perturbed chained *** order to tackle the effects of drift uncertain nonlinearities,nonholonomic constraints and nonsmooth aperiodic sampling in eventbased control,a novel systematic design scheme is proposed by integrating set-valued maps with stateseparation and state-scaling *** stability analysis of the closed-loop event-triggered control system is based on the cyclic-small-gain techniques that overcome the limitation of Lyapunov theory in the construction of Lyapunov functions for nonsmooth dynamical systems and enjoy inherent robustness properties due to the use of gain-based characterization of robust *** specifically,the closed-loop event-triggered control system is transformed into an interconnection of multiple input-tostate stable systems,to which the cyclic-small-gain theorem is applied for robust stability *** self-triggered mechanisms are also developed as natural extensions of the event-triggered control *** proposed event-based control design approach is new and original even when the system model is reduced to the ideal unperturbed chained ***,the proposed methodology is also applicable to a broader class of nonholonomic systems subject to state and input-dependent *** efficacy of the obtained event-triggered controllers is validated by a benchmark example of mobile robots subject to parametric uncertainties and a measurement noise such as bias in the orientation.

关键词： Event-triggered control nonholonomic systems self-triggered control stabilization

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Computing Technology Acoustic Inversion engineering Seismic Data and Its Application for Construction Purposes

Computing Technology Acoustic Inversion Engineering Seismic ...

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International Conference on Actual Problems of Electronic Instrument engineering (APEIE)

作者： Elena Yu. Goshko Sergey M. Zerkal Sergey S. Ivanov Automation and Computer Engineering Novosibirsk State Technical University Novosibirsk Russia Department of Computer Science Siberian University of Consumer Cooperation Novosibirsk Russia

The Shallow-depth engineering seismic studies are carried out in the upper part of the geological section, which is characterized by sharp vertical and horizontal variability of the physical properties of rocks. Additional difficulties in observing and recording caused by seismic vibrations of the soil are associated with the influence of unavoidable interference: ground (wind, sound noise), geological interference (noise of rock cracking during unloading of tectonic stress), man-made interference (the influence of power lines on signal reception, trembling of the soil during the work of construction or quarry mechanisms, cars, trains). The allocation of a useful signal against the background of interference requires the organization of seismic work with repeated repetition of excitations - the accumulation of signals, as well as the development of special computational algorithms and the use of new technologies for processing engineering seismic data. The article considers a computational algorithm of acoustic inversion, which transforms a wave seismic section into a discrete section of pulsed reactions of the medium - effective reflection coefficients. It has a compact discrete appearance and is easier for visual observation and further physico-geological interpretation. The computer technology of application of the acoustic inversion algorithm is implemented. The application of this technology to real engineering seismic data obtained on the territory of the construction of a high-rise building made it possible to determine the parameters of the geological foundation lying under the ground surface of the construction site, namely: the depth of occurrence, relief, areas of increased disintegration. The established properties of the geological foundation are necessary for the analysis of the strength and stability of soils during the construction and operation of a high-rise structure for its safety.

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The relevance of IT Security awareness in Renewable Energy facilities

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2022年 20卷 530-535页

作者： Lourenço, Justino Zanghi, Eric Morais, José Neves, Nelson Vasques, César Figueiredo, Fernando Department of Computer Science Engineering Instituto Superior Politécnico Gaya Avenida dos Descobrimentos 333 Vila Nova de Gaia Portugal Department of Electronics and Automation Engineering Instituto Superior Politécnico Gaya Avenida dos Descobrimentos 333 Vila Nova de Gaia Portugal Department of Mechanical Engineering ISPGAYA Instituto Superior Politécnico Gaya Avenida dos Descobrimentos 333 Vila Nova de Gaia Portugal

In recent years several efforts have being made in bringing smart network connectivity to the Renewable Energy Plant (REP) environment. On the other hand, REP is extending in scale from specialized points where the energy provider acts as a supplier to home REP (self-energy producers). This enables new important features such as: process automation, monitoring, control and optimizations. On the other hand, and in particular during and after the Covid19 pandemics the cybersecurity menace is a massive concern. The digital literacy of a worker of such an infrastructure is relevant to the correct implementation of adequate security policies. This article describes the threats and challenges on the field and conducts an enquire for perceiving the awareness of automation and Mechanics engineering students for this relevant problem, as future player in the field. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Cybersecurity

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