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2023 international conference on automation Control, Algorithm, and Intelligent Bionics, ACAIB 2023

作者： Sun, Hang Li, Changsheng Zhang, He Nanjing University of Science and Technology China

ISBN: (纸本)9781510667662

In order to explore the feasibility of brain-computer interface in the weapon system application, an experience of automatic thrower model controlled by brain-computer interface is designed to compete the firing task. According to the lens of automatic thrower model fed back from the screen, the testee carries out the practical or imaginary actions, and then through the nonintrusive BCI equipment, load 6 kinds of EGG signal which are collected from the testee to the trained convolutional neural network. 9 kinds of signal controlling the actions of automatic thrower model would be output. Control the switching functions of automatic thrower model through setting to realize 9 actions including Forward, backward, left, right, turret left, right, muzzle up, down, and launch, so as to complete the firing task. The comprehensive accuracy rate of implementation is 78.83%. The result of this experience shows that the brain-computer interface has the feasibility in the military field, which is worthy of researchers to carry out deeper studies. © 2023 SPIE.

关键词： Brain computer interface

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Research on the Application of Improved LSTM Model in Time Series Problems

Research on the Application of Improved LSTM Model in Time S...

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2023 IEEE international conference on Electrical, automation and computer Engineering, ICEACE 2023

作者： Dai, Jian Liao, Maojun Guo, Xuanyu Beihang University Beijing China University of Electronic Science and Technology of China Chengdu China Beijing Normal University Hong Kong Baptist University United International College Zhuhai China

ISBN: (纸本)9798350309614

With the rapid development of deep learning technology, Recurrent neural network has made remarkable achievements in the tasks of sequence modeling and time series prediction. LSTM, as a special RNN structure, solves the long term dependence problem effectively by introducing gating mechanism, and has become one of the widely used models. In order to further improve the performance of LSTM model, this paper have improved some existing problems. The traditional LSTM model only considers the information of a time step, and ignores the context of the future moment. To solve this problem, this paper introduce a multi-step LSTM model. The multi-step LSTM model can better predict the future time series data by selecting the information of multiple time steps. The multi-step LSTM model proposed in this paper has potential application value in the field of time series prediction, and can provide reference for related research. © 2023 IEEE.

关键词： Electricity forecasting LSTM time series

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Image Recognition and Similarity Retrieval with Convolutional Neural Networks 2

Image Recognition and Similarity Retrieval with Convolutiona...

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2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Dedeepya, P. Chiranjeevi, P. Narasimha, V. Shariff, Vahiduddin Ranjith, Jinugu Ramesh, Janjhyam Venkata Naga Computer Science & Engineering PVP Siddhartha Institute of Technology Vijayawada India Computer Science & Engineering Amrita Sai Institute of Science and Technology Bathinapadu India Computer Science & Engineering CMR College of Engineering & Technology Hyderabad India Computer Science & Engineering Sir C R Reddy College of Engineering Eluru India Computer Science & Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram India

ISBN: (纸本)9798350340235

Image is a form of representation of data that is presented with visual beauty and has many patterns in it, in a database of irregular image datasets it is enough to make us humans who like structured, neat, and high readability data sets Therefore, the role of machine learning in helping to search for the same image will greatly help humans both in implementing search engines, tidying up image data structures automatically, etc. This research will focus on creating the same 5-image search system based on input from the user using the CNN algorithm & pretrained models such as ResNet with the expected results of model accuracy ranging from 80-95%. This was carried out using the CIFAR-10 dataset as a source. The CIFAR-10 dataset is a medium-scale image data set with a total of 60000 images, there are 10 categories in it, meaning each category contains 6000 images with the size of each image being 32x32. In general, a dataset has different image sizes, so this research study will first do an overview about whether the data for each image is enough with a size of 32x32. © 2023 IEEE.

关键词： Canadian Institute for Advanced Research (CIFAR) Dataset Convolutional Neural Networks (CNN) Deep Learning Deep Neural Network (DNN) Rectified Linear Units (ReLUs) Residual Neural Network (ResNet)

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Intelligent Computing technology and automation - Proceedings of the 16th international conference, ICICTA 2023

Intelligent Computing Technology and Automation - Proceeding...

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16th th international conference on Intelligent Computing technology and automation, ICICTA 2023

ISBN: (纸本)9781643684864

The proceedings contain 141 papers. The topics discussed include: power comprehensive energy optimization scheme based on improved PSO algorithm;new energy distribution network scheduling based on optimized PSO;time domain dielectric spectrum analysis of high voltage bushing insulation state based on wavelet transform;modeling and simulation of intelligent vehicle flow guidance based on agent;a video resource recommendation system based on deep learning;human motion data acquisition system of intelligent motion bracelet based on human-computer interaction;fast estimation model of green building project cost based on support vector regression machine;intelligent recommendation method for talent resources based on big data;improved human resource allocation method based on genetic algorithm;and intelligent temperature monitoring for high voltage cable with non-invasive low power consumption.

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Generalized Zero-Shot Learning via Implicit Attribute Composition

Generalized Zero-Shot Learning via Implicit Attribute Compos...

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2023 IEEE international conference on Systems, Man, and Cybernetics, SMC 2023

作者： Zhou, Lei Liu, Yang Li, Qiang School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China College of Computer Science and Technology Zhejiang University Hangzhou China Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9798350337020

Zero-shot learning (ZSL) is an important but challenging task in computer vision that aims to identify unseen classes without matching training samples. Current cutting-edge ZSL methods based on locality focus on acquiring the explicit locality of distinguishing characteristics, which could face a lack of adequate supervision at the class attribute level. This paper introduces a novel approach called IAC, which aims to learn Implicit Attribute Composition for ZSL. This method is more comprehensive compared to attribute localization that solely focuses on class-level attribute supervision. IAC utilizes subspace representations that efficiently capture the inherent structure of high-dimensional image features. Then, we learn implicit attribute composition through subspace representation learning. The superiority of the proposed IAC compared to the state-of-the-art is demonstrated through sufficient experiments conducted on three commonly used ZSL datasets, CUB, SUN, and AwA2. © 2023 IEEE.

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An Empirical Study on Quantitative Analysis of Legal Literature Based on Artificial Intelligence Algorithms

An Empirical Study on Quantitative Analysis of Legal Literat...

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computer science and automation technology (csat), international conference on

作者： Fugang Zhao Shandong University of Political Science and Law Jinan Shandong Province China

At the level of national governance, legal studies are, to a certain extent, inextricably linked to the goal of modernizing the national governance system. For the study of legal literature, the use of quantitative research methods can summarize the types of literature journals, the direction of selected topics, and the number of publications, etc. The qualitative research methods can observe the points of contention and consensus in the academic community on the construction of the legal system and the positioning of the discipline. With the continuous development of modern science and technology, there are more and more kinds of artificial intelligence algorithms, including ant colony algorithm, genetic algorithm, reinforcement learning, deep learning, logistic regression and decision tree, among which CI index is an important index. Therefore, based on the artificial intelligence algorithm, this paper selected the historical publication data of law disciplines of six universities in China's political science and law, and evaluated the influence of a single literature by using the CI index theoretical model. Based on the horizontal comparison of the overall scientific research level in terms of “quality” and “quantity” of each university's literature, some index algorithms of the model could be modified to obtain an objective picture of the current scientific research level of universities. The results show that the evaluation method based on artificial intelligence algorithms has the advantages of easy access to data, strong operability and few indicators, which is worth promoting and applying.

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Simulation of autonomous inspection robot application based on ROS 6

Simulation of autonomous inspection robot application based ...

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6th international conference on computer Information science and Application technology, CISAT 2023

作者： Zang, Entong Xiao, Yongfei Song, Bowen Institute of Automation Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Robot and Manufacturing Automation Technology Jinan China

ISBN: (纸本)9781510668546

Simultaneous localization and map construction (SLAM) is a hot research topic in mobile robotics and is a crucial technology for developing inspection robots. This paper focuses on mapping the environment by analyzing the Gmapping and Karto Slam algorithms' mapping effects and constructing a simulation environment map using the Karto Slam algorithm. To address the obstacle avoidance problem that cannot be handled by only using the Dijkstra algorithm for global path planning, an improved DWA algorithm is introduced for local path planning to optimize the real-time obstacle avoidance function of the robot. Based on the construction of a robot simulation platform, this paper studies the previous simulation of an autonomous inspection robot before actual experiments. Through simulation experiments of mapping and path planning, this study provides support for the feasibility of robot field experiments, reducing the cycle and difficulty of on-site debugging. © 2023 SPIE.

关键词： Motion planning

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Diagnosability Verification and Enforcement for Unbounded Petri Nets by Online Supervisors

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IEEE TRANSACTIONS ON automation science AND ENGINEERING 2025年 22卷 9061-9074页

作者： Hu, Shaopeng Hu, Yihui Liu, Ding Fanti, Maria Pia Li, Zhiwu Xidian Univ Sch Electromech Engn Xian 710071 Peoples R China Xian Univ Posts & Telecommun Sch Automat Xian 710121 Peoples R China Polytech Univ Bari Dept Elect & Informat Engn I-70125 Bari Italy Macau Univ Sci & Technol Inst Syst Engn Taipa Macao Peoples R China

This paper addresses the problems of diagnosability verification and enforcement of discrete event systems modeled with unbounded Petri nets. Diagnosability in such systems is critical for ensuring reliability and maintaining operational integrity, yet current methods often struggle with the complexity introduced by unboundedness and potential deadlocks. Given an unbounded labeled Petri net that may reach deadlocks, a quiescent basis coverability graph is established to verify the diagnosability of the considered system. This procedure employs a deterministic finite state automaton, called an extended verifier, derived from the proposed quiescent basis coverability graph. It is shown that an unbounded Petri net is diagnosable if and only if the verifier does not contain a class of cycles, called repetitive $F$ -cycles. This result also provides necessary and sufficient conditions for diagnosability enforcement by developing an online supervisor. Further, the designed supervisor is maximally permissive and also circumvents a plant entering deadlocks by firing non-fault sequences. Examples are presented to demonstrate the proposed method. Note to Practitioners-Fault diagnosis and diagnosability enforcement are critical for the development and operation of highly automated systems covering computer-integrated production processes, intelligent traffic, computer and communication networks, smart gird, etc. This work touches upon this problem from the perspective of discrete event systems that are modeled with unbounded labeled Petri nets. The feasibility and applicability of the reported method stem from the usage of a structurally compact representation of a considered plant such that the computational cost of a real-world system is acceptable. The graphical representation of Petri nets as well as the proposed quiescent basis coverability graph make the method easy to use and manipulate. Moreover the sufficient and necessary conditions of diagnosability enforcement can

关键词： Petri nets System recovery Fault diagnosis automation Automata Discrete-event systems Polynomials Mechanical engineering Firing Computational modeling Unbounded Petri net fault diagnosis diagnosability enforcement discrete event system

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Surround-View Road Scene Layout Estimation via IPM-Transformer for Autonomous Driving 6

Surround-View Road Scene Layout Estimation via IPM-Transform...

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6th international conference on Robotics, Control and automation Engineering, RCAE 2023

作者： Zhou, Haibin Liu, Shuo Chang, Jun Zhou, Huabing Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot Wuhan China Computer Science School Wuhan University Wuhan China

ISBN: (纸本)9798350315301

Visual perception technology is crucial for autonomous driving. It can detect dynamic and static objects around the vehicle, which is used for downstream tasks such as obstacle avoidance and navigation. LiDAR-based methods face challenges from costly sensors and extensive computational demands. In contrast, camera-based approaches are more cost-effective, but achieving a bird's-eye-view (BEV) requires perspective transformation, often leading to image distortions. To address this, we spotlight our novel contribution: The IPM-Transformer. This transformative framework integrates the mathematical geometry of Inverse-Perspective-Mapping (IPM) with data-driven deep learning, offering a robust solution to mitigate the image distortions and improve the effect of perspective transformations. We have also developed a novel framework that reconstructs a local map, showcasing both the road layout and vehicle occupancy, in the bird's-eye-view using only surround-view images. Our model achieves state-of-The-Art (SOTA) results in the vehicle occupancy category on public datasets and achieves SOTA results across all categories on our released HuanYu dataset. © 2023 IEEE.

关键词： computer vision

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Comparative Study Using IoT to Automate Your Home 7

Comparative Study Using IoT to Automate Your Home

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7th IEEE international conference on Computational Systems and Information technology for Sustainable Solutions, CSITSS 2023

作者： Neeli, Jyoti Smithu, S.B. Teja S, Ravi Layan, N. Nitte Meenakshi Instutite of Technology Department of Computer Science & Engg India

ISBN: (纸本)9798350343144

A 'home automation system' is a process that automates or adjusts routine tasks at home, such as controlling lighting and HVAC systems based on user commands. Using a portable and versatile handheld device as a user interface is an ideal approach for such systems. The increasing internet consumption and associated costs have driven the demand for home automation systems with Internet of Things (loT) capabilities. Smart home applications, where devices are intelligently connected to provide daily comfort and improve people's well-being and quality of life, have greatly benefited from loT mobile systems. © 2023 IEEE.

关键词： User interfaces

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