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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68823 条记录，以下是1131-1140 订阅

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Collection and Storage of Technological Data in Multi-Channel CNC Processing Using a Non-Relational Database and Node-RED

Collection and Storage of Technological Data in Multi-Channe...

引用

2023 international Russian automation conference, RusAutoCon 2023

作者： Martinov, Georgi Polyakov, Kirill Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9798350345551

This article contemplates the problem of collecting and storing technological data during multichannel and multi - coordinate machining on CNC machines obtained using the OPC UA protocol and applying Node-RED open-source instrumentation. A structural model of obtaining, visualizing and storing technological data in multichannel and multi - coordinate machining is proposed in this research. The necessary nodes for Collection and storage of technological data in multi-channel CNC processing are implemented and configured. The researchers illustrated practical aspects of building a system for collecting and storing technological data in multichannel machining using the OPC UA protocol and applying Node-RED open-source tools and a non-relational MongoDB database. © 2023 IEEE.

关键词： Digital storage

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Attak Detection in RSU-OBU Communication Using Deep Neural Network 23

Attak Detection in RSU-OBU Communication Using Deep Neural N...

引用

23rd international conference on Control, automation and Systems, ICCAS 2023

作者： An, Youngwoo Eun, Yongsoon Dgist Department of Electrical Engineering & Computer Science Daegu42988 Korea Republic of

ISBN: (纸本)9788993215274

This paper proposes three types of neural network-based attack detectors for Internet of Vehicles (IoV) networks. The proposed attack detectors consist of Long Short-Term Memory (LSTM) layers. The fault detector is implemented in the Road Side Unit (RSU) that communicates with On Board Unit (OBU) installed in the autonomous vehicles. We consider the multiplicative attacks in the RSU-OBU communication messages. The training and validation data sets are generated by using an automated driving toolbox in MATLAB. Attack detector performance is evaluated using the validation data set that is not included in the training data sets. Performance comparison of the three detectors are given. © 2023 ICROS.

关键词： Autonomous vehicles

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Measuring project maturity of organizations conducting research projects using a university as an example

Measuring project maturity of organizations conducting resea...

引用

2023 international conference on ENTERprise Information Systems, CENTERIS 2023 - international conference on Project MANagement, ProjMAN 2023 - international conference on Health and Social Care Information Systems and Technologies, HCist 2023

作者： Klaus-Rosinska, Agata Bak, Agata Faculty of Management Wroclaw University of Science and Technology ul. Ignacego Lukasiewicza 5 Wroclaw50-371 Poland

The purpose of this paper is to present research related to the analysis and evaluation of the applicability of project maturity models in organizations conducting research projects, and to propose a project maturity model that could be used in such organizations. The subject of the mixed research undertaken was how to measure the project maturity of organizations conducting research projects (using university as an example). The following research steps were performed: a literature review, empirical research, and a synthesis of the obtained knowledge. © 2024 The Author(s). Published by Elsevier B.V.

关键词： Research and development management

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Integrated Webapp For Campus Placement

Integrated Webapp For Campus Placement

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Sinthuja, M. Vidhya, D. Karthik, V. Ramesh, T. M. S Ramaiah Institute of Technology Department of Information Science and Engineering Karnataka Bengaluru560064 India Hindusthan Institute of Technology Department of Computer Science and Engineering Coimbatore641032 India Presidency University Department of Computer Science and Engineering Karnataka Bengaluru560064 India

ISBN: (纸本)9798350317060

Many institutions now do not have a platform where students can view all of the offers from various firms, and they must fill out the form with their information again for each company that visits. To minimize future problems, the college placement department must check each student's information. Companies rely on the Placement department to obtain information about selected applicants for additional procedures. To solve this problem, a platform for students to register and submit their updated profiles was required. Companies can see the applications received for a specific job vacancy, admin can approve or reject the student's registration based on the database present with him, and students can see various job openings from companies at a specific time. The current system is not a proper and appropriate method of implementing Training and Placement management because it becomes difficult for the placement department to manage all of the databases, send emails regarding offers to every student, and keep track of every student, whether they received an offer or not. As a result, this study created a platform for students to register and submit their updated profiles, reducing administrative effort. Companies get immediate access to the applications submitted for a specific employment opportunity. Features are supplied to immediately generate information from existing data. This study recommended segmenting the web app into three components for design: admin, company, and student. React JS is utilized as a frontend framework for development, Node JS as a server-side script for integration and REST operations, MongoDB and Mongoose for databases and connections, Redux for state management, and Axios for requests and answers. © 2023 IEEE.

关键词： Students

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Determining UK government scope 2 and 3 computer greenhouse gas emissions 18

Determining UK government scope 2 and 3 computer greenhouse ...

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18th international conference on Future Networks and Communications (FNC) / 20th international conference on Mobile Systems and Pervasive Computing (MobiSPC) / 13th international conference on Sustainable Energy Information technology (SEIT)

作者： Sutton-Parker, J. Procter, R. Univ Warwick Comp Sci Dept Coventry CV4 7AL England Alan Turing Inst Data Sci & AI London NW1 2DB England

The objective of this research is to determine the potential of scope 3 supply chain emissions generated by end user computers within the United Kingdom government and to test current scope 2 calculation methods to improve annual reporting procedures. The supply chain analysis is accomplished by using existing asset profile data to determine the number of devices owned by computer type combined with manufacturer scope 3 product emissions data averages by type. In this example, 2.2 million computing devices are examined and found to produce emissions in excess of 623.45m kgCO(2)e. By suggesting devices are retained beyond the current 5-year periods, it is determined to be feasible that this value could be reduced by 37.5%. Additionally, by selecting devices with the lowest carbon footprint in the future when computers require replacement an estimated total reduction of 65% is achievable. The scope 2 emissions calculation compares the current methodology used to generate kWh/y values and concomitant greenhouse gas emissions to results generated by field measurement using the commercial typical energy consumption methodology. The results substantiate that the government is currently over reporting scope 2 emissions values by as much as 697% due to owned but not used devices being included in the calculation and fixed electricity consumption data used by the current methodology being too high when compared to actual use. As such, the findings are presented to the government and included as recommendations in the latest national sustainable information and communications technology strategy document.

关键词： computer carbon footprint computer energy efficiency human-computer interaction

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Human Face Mask Recognition using ResNet 152 Model 2

Human Face Mask Recognition using ResNet 152 Model

引用

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

作者： Gupta, Ashutosh Tripathi, Pradeep Singh, Bhanu Pratap Singh, Upendra Department of Computer Science Vindhya Group of Institutions VITS Satna India Department of Information Technology Shri G. S. Institute of Technology and Science Indore India

ISBN: (纸本)9798350340235

The global health crisis, and the enforcement of mask-wearing protocols has become crucial for public safety. To automate the monitoring of these protocols, this study proposes a robust human face mask recognition system utilizing the ResNet 152 model, a deep convolutional neural network known for its accuracy in image classification tasks. The system inputs an image and processes it through successive convolutional layers—Conv 1 through Conv 4—with varying filter sizes and strides to extract detailed feature maps. These layers are followed by a max pooling operation and a fully connected layer with 1000 dimensions to synthesize the extracted features into a comprehensive representation. The output is a binary classification that determines the presence or absence of a face mask. This study implemented skip connections characteristic of ResNet architectures to enable training of deeper networks without the hindrance of vanishing gradients. Preliminary results demonstrate a high accuracy rate in face mask detection, indicating that the ResNet 152 model is a promising for enhancing public health measures through automated face mask recognition. © 2023 IEEE.

关键词： CNN COVID-19 Pandemic Face Mask ResNet-152 YOLO

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Style-constrained Takagi-Sugeno-Kang Fuzzy Classifier

Style-constrained Takagi-Sugeno-Kang Fuzzy Classifier

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2023 IEEE international conference on Control, Electronics and computer technology, ICCECT 2023

作者： Gu, Suhang Shi, Hangming Zhou, Jie Jiang, Zhibin Lu, Mingli Zhu, Peiyi Changzhou University School of Mechanical Engineering and Rail Transit Changzhou China Shaoxing University Department of Computer Science and Engineering Shaoxing China Changshu Institue of Technology School of Electrical Engineering and Automation Suzhou China

ISBN: (纸本)9798350399028

Due to the excellent interpretability and classification performance, the Takagi-Sugeno-Kang fuzzy classifier (TSK-FC) has drawn great attention. However, different patterns own their respective homogeneities, and the samples from different groups present explicitly or implicitly homogenous styles, which are significantly different from the assumption that all samples from different groups are identically and independently distributed (i.i.d.). In this paper, a style-constrained Takagi-Sugeno-Kang fuzzy classifier called SC-TSK-FC is proposed by breaking the i.i.d. assumption. To explore the styles of data, a series of style matrices are embedded into the objective function of the TSK-FC. Besides, with the introduction of the regularization term corresponding to each style matrix, the nuances between different styles of data can be captured, which can help improve the classification performance of SC-TSK-FC. Particularly, five fixed fuzzy partitions with interpretable linguistic terms are adopted to along each input feature, and SC-TSK-FC outperforms TSKFC by using less fuzzy rules. These guarantee the interpretability of SC-TSK-FC. Experimental results on some benchmark datasets demonstrate the effectiveness of the proposed SC-TSK-FC. © 2023 IEEE.

关键词： Matrix algebra

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Equipment Planning for an Automated Production Line Using a Cloud System 10th

Equipment Planning for an Automated Production Line Using a ...

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10th international conference on Innovations in computer science and Engineering, ICICSE 2022

作者： Bhavana Raj, K. Webber, Julian L. Marimuthu, Divyapushpalakshmi Mehbodniya, Abolfazl Stalin David, D. Rangasamy, Rajasekar Sengan, Sudhakar Department of Management Studies Institute of Public Enterprise Hyderabad500101 India Doha Kuwait Department of Computer Science and Engineering GITAM University Karnataka Bengaluru561203 India Department Of Information Technology Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Tamil Nadu Chennai600072 India Department of Computer Science and Engineering GITAM School of Technology GITAM University Karnataka Bengaluru561203 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627152 India

ISBN: (纸本)9789811974540

Lean Manufacturing (LM), which reduces waste, maximises labour efficiency and offers lean production advantages, operational costs, and low product quality. A production line includes workstations linked via transmission and electrical control. An automated manufacturing line reduces production and labour costs, improves output quality, and minimises human error. Integration and machines automate industrial processes, so the process is computer-controlled. Adopting automated manufacturing and lean and automated Logistics Methods (LM) may enhance product quality, minimise waste, and increase agility. A survey indicates a new strategy for optimum manufacturing and distribution applications. Case studies, theoretical analysis, and real-world examples of cutting-edge technology all have an impact on the application and production processes. This suggests that LM and automation are essential in manufacturing. Practical examples are the starting point for lean and advanced automation applications that allow Lena automation System (LAS) deployment of the whole production and LM. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： automation

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Research on fault diagnosis model of computer network based on GA-BP neural network 6

Research on fault diagnosis model of computer network based ...

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6th IEEE international conference on automation, Electronics and Electrical Engineering, AUTEEE 2023

作者： Feng, Jingchao Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350305623

The popularity of the computer has prompted obvious changes in people's work and life style at this stage, providing people with quality services, but affected by a variety of factors, computer network failures occur more frequently, and then reduce its functionality, in order to ensure the healthy and stable operation of the local area network, the back propagation (BP) neural network model was optimized by genetic algorithm (GA), and the GA-BP neural network model was constructed. This paper introduces the basic model construction process and principle, and simulate computer network failures, validate models, and perform data collection and validation. The results show that the optimized model (GABP neural network) is superior to BP neural network in stability, prediction accuracy and convergence speed, and can be used in computer fault diagnosis, the nonlinear approximation and local optimization ability of BP neural network are combined with the global search characteristics of genetic algorithm. Therefore, GA-BP can predict computer network fault more scientifically and reasonably, and provide an effective implementation path and development strategy for improving the efficiency of computer fault diagnosis. © 2023 IEEE.

关键词： computer forecast GA-BP neural network model Network failure

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LoRa Agri: Agriculture automation and Intruder Detection System with IoT and LoRa technology 11

LoRa Agri: Agriculture Automation and Intruder Detection Sys...

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11th IEEE international conference on Cloud Computing in Emerging Markets, CCEM 2023

作者： Preksha, Padmaja D. Surabhi, R. Mukhopadhyay, Adwitiya Department of Computer Science Amrita School of Computing Mysuru Campus Amrita Vishwa Vidyapeetham Karnataka India

ISBN: (纸本)9798350360059

—In recent years, agriculture has undergone significant technological advancements, becoming more commercial and technology-driven. These innovations have given farmers greater control over crop cultivation, enhancing security and profitability. As a result, IoT, connected devices, and automation are increasingly used in agriculture for tasks like crop monitoring, soil moisture measurement, climate assessment, intrusion detection, and efficient irrigation. Smart farming prioritizes extensive coverage over high data volumes or rapid transmission. In rural areas, low-power long-range (LoRa) technology plays a pivotal role, connecting hundreds of sensors up to 15 km away. Compared to Wi-Fi and Bluetooth, LoRa stands out as an ideal choice for agriculture. This paper provides an overview of LoRa-based farm monitoring, including applications, advantages, and challenges. It also discusses the current landscape and future prospects for LoRa-based farm monitoring systems. This research aligns with several UN Sustainable Development Goals, including SDG 2 (Zero Hunger), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land), by promoting sustainable agriculture, technological innovation, efficient land use, climate-resilient farming, and biodiversity protection. ©2023 IEEE.

关键词： Soil moisture

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