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Imbalanced Wafer Map Dataset Classification with Semi-Supervised Learning Method and Optimized Loss Function 18

Imbalanced Wafer Map Dataset Classification with Semi-Superv...

引用

ieee 18th International conference on automation science and engineering (ieee CASE)

作者： Huang, Jianchuan Lin, Kuo-Yi Xu, Jia Lili Tongji Univ Dept Control Sci & Engn Shanghai 201804 Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Wafer is the crucial raw material of semiconductor devices. In wafer production, impurities cannot be removed entirely, which will cause various wafer map defects. Quickly and precisely classifying wafer map defects can help engineers track failures in the semiconductor manufacturing process. However, different wafer map defect patterns occur randomly and irregularly, and labeling work is labor-intensive and time-consuming. Therefore, the wafer map dataset is usually imbalanced and consists of many unlabeled data. In this paper, we utilize unlabeled data by using semi-supervised learning methods and alleviate the imbalance problem by optimizing the loss function to increase the accuracy of wafer map classification. The performance of the proposed method is illustrated with the WM-811K dataset which consists of real-world wafer maps.

关键词： Computer aided software engineering automation Semiconductor devices Impurities Training data Production Semisupervised learning

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Evaluation of the Energy Efficiency of Software Calculations in the Design of Microcontroller Devices 17

Evaluation of the Energy Efficiency of Software Calculations...

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17th ieee International conference on Advanced Trends in Radioelectronics, Telecommunications and Computer engineering, TCSET 2024

作者： Topalov, Andrii Styslo, Taras Tkach, Vitalii Peschanenko, Volodymyr Styslo, Oksana Skrypyuk, Rostyslav Admiral Makarov National University of Shipbuilding Department of computerized control systems Mykolaiv Ukraine King Danylo University Department of IT Ivano-Frankivsk Ukraine Kherson State University Department of computer science and software engineering Ivano-Frankivsk Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of automation and computer-integrated technologies Ivano-Frankivsk Ukraine

ISBN: (纸本)9798331520564

The paper presents a study of the effectiveness of software from the point of view of minimizing the energy consumption of microprocessor devices. In this case, the programming of the microcontroller in various programming languages for arithmetic operations, as well as data output through the port, is considered. In the course of the tests, the peculiarities of the application of this or that program and their operation, taking into account the energy saving of the microcontroller, are noted. © 2024 ieee.

关键词： Microcontrollers

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Secure Face Track: A Deep Learning-Powered Attendance automation 1

Secure Face Track: A Deep Learning-Powered Attendance Automa...

引用

1st ieee International conference on Computing and Data science, ICCDS 2024

作者： Umesh, R. Sriram, K.K. Sathieshkumar, P. Velammal College of Engineering and Technology Department of Information Technology Madurai India

ISBN: (数字)9798350365337

ISBN: (纸本)9798350365337

A Deep Learning-Powered Attendance automation addresses a pressing challenge in the realm of smart attendance systems: spoofing or deception attempts by individuals seeking to manipulate the system with fake or altered facial images or videos. This project presents an intelligent anti-spoofing system, named Deep Learning-Powered Attendance automation, designed to accurately distinguish between genuine and fraudulent faces within a smart attendance context. The system's development encompasses the creation of a comprehensive dataset comprising real and fake facial images and videos. Leveraging deep learning, the project employs a robust feature extraction and classification pipeline, including the utilization of the Facenet model for facial recognition. Facenet operates across three phases: registration, training, and testing, integral to the functioning of the face recognition model. Furthermore, various data augmentation techniques, including rotation, scaling, and translation, are incorporated to enhance the system's resilience against diverse spoofing attacks. Performance metrics such as accuracy, precision, and recall are used to evaluate the system's effectiveness in detecting and preventing spoofing attempts. © 2024 ieee.

关键词： automation

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Directed Explorations During Flood Disasters Using Multi-UAV System 18

Directed Explorations During Flood Disasters Using Multi-UAV...

引用

ieee 18th International conference on automation science and engineering (ieee CASE)

作者： Garg, Armaan Jha, Shashi Shekhar Indian Inst Technol Ropar Dept Comp Sci & Engn Ropar Punjab India

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

The disaster relief operations during floods require time critical information of the flooded area to save lives. Finding critical regions of the disaster struck area in a limited time frame is crucial for effective relief planning. In this paper, we propose a multi-UAV based system with directed explorations of flooded area to gather time-critical ground information using deep reinforcement learning based controls. We learn an exploration policy for the multi-UAV system with limited battery for autonomous coverage of the flooded region. Further, we integrate D8 flow algorithm that approximates the water flow direction based on image pixel information of a sub-region in the UAVs' exploration strategy. The results show that our proposed method for multi-UAV exploration of flooded area outperforms other methods from the literature. Moreover, the learnt multi-UAV exploration policy is able to generalize to unseen flooded regions without any retraining.

关键词： Knowledge engineering Computer aided software engineering automation Reinforcement learning Robustness Batteries Planning

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Study on Steady-State Waiting Queue Length for Automatic Robotic Sorting System 6

Study on Steady-State Waiting Queue Length for Automatic Rob...

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6th International conference on Robotics, Control and automation engineering, RCAE 2023

作者： Wang, Qiang Chen, Zhangbao Qin, Guowei Hu, Haijiang College of Electronic and Electrical Engineering Bengbu University Bengbu China

ISBN: (纸本)9798350315301

The automatic sorting system is one of the important robotic systems in the field of logistics. Discrete queue theory is used to analysis the steady-state waiting queue length in automatic robotic sorting system. The automatic sorting system is modeled as a Geom/Geom/1 queuing system and the relation between the steady-state waiting queue length and system parameters which include intensity of item flow and intensity of robot service is studied. The conclusion is useful to design an automatic robotic sorting system. © 2023 ieee.

关键词： Robotics

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Energy Consumption Optimization for Two-Machine Synchronous Exponential Serial Lines 19

Energy Consumption Optimization for Two-Machine Synchronous ...

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19th ieee International conference on automation science and engineering, CASE 2023

作者： Yan, Chao-Bo Zhang, Sheng School of Automation Science and Engineering Xi'an Jiaotong University The State Key Laboratory for Manufacturing Systems Engineering Faculty of Electronic and Information Engineering Shaanxi Xi'an710049 China

ISBN: (纸本)9798350320695

Reducing the energy consumption and improving the energy efficiency of energy-intensive production systems are of significant importance. In the literature, for Bernoulli and geometric lines, the energy consumption optimization problem has been largely studied, while for more practical, e.g., exponential, reliability models, it is barely studied. This paper is intended to investigate the energy consumption optimization for two-machine synchronous exponential lines. Specifically, first, similar for the Bernoulli and geometric lines, this problem is formulated as a constrained nonlinear programming;then, two optimality equations for solving the nonlinear programming are derived;finally, based on the properties of the nonlinear optimality equations, an algorithm is designed to solve the solution of the optimality equations, which is the unique optimal solution of the energy consumption optimization problem. Extensive numerical experiments show that the algorithm is effective and computationally efficient for solving the energy consumption optimization problem. © 2023 ieee.

关键词： Nonlinear programming

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Design of City Manhole Cover Monitoring System Based on NB-IoT 7

Design of City Manhole Cover Monitoring System Based on NB-I...

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7th ieee Advanced Information Technology, Electronic and automation Control conference, IAEAC 2024

作者： Li, Jianna Qiao, Yanhua Ma, Huijuan Mao, Xiangfang Tianjin Tianshi College School of Information Science and Engineering Tianjin China

ISBN: (纸本)9798350339161

Manhole covers are prevalent in urban streets and alleys. necessitating the imperative attention to their daily maintenance and inspection. In order to meet the requirements of intelligent maintenance of manhole covers, this paper designs and implements an urban manhole cover monitoring system based on NB-IOT, which mainly uses single-chip microcomputer processing technology, sensor acquisition technology and wireless communication technology, and combines peripheral functional modules for design. The core control device of the system is STM32 single-chip microcomputer, which mainly collects water level height, combustible gas concentration and manhole cover pressure data in the well through the water level detection module, combustible gas concentration detection module and pressure detection module respectively, The GPS module collects the location data of the manhole cover, Additionally, location data of each manhole cover is collected by a GPS positioning module. The NB-IoT wireless communication module facilitates remote transmission of data while local data is periodically uploaded to the remote terminal, and the relevant data can be viewed on the mobile phone, which brings convenience to the manhole cover maintenance work and reduces the risk of accidents. © 2024 ieee.

关键词： Microcomputers

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Gesture and Voice-Based automation System for Home Surveillance 1

Gesture and Voice-Based Automation System for Home Surveilla...

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1st International conference on Advances in Computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Santhosh, B. Oli, Sanjay Jayanth, C. Suresh Kumar, M. Raj, Preetham N Kandpal, Ankit Dayananda Sagar College of Engineering Department of Electronics and Telecommunication Engineering Bangalore560078 India Dayananda Sagar College of Engineering Department of Mathematics Bangalore560078 India Dayananda Sagar College of Engineering Department of Information Science and Engineering Bangalore560078 India Bipin Tripathi Kumaon Institute of Technology Dwarahat Department of ECE Almora India

ISBN: (纸本)9798331518578

Gesture and voice-based automation innovations are being examined because of the developing interest for reliable and smart home security frameworks. In this study, a MATLAB-based home reconnaissance automation framework in light of voice and motion is created and reproduced. To perceive, interpret, and answer user developments and vocal orders, the proposed framework utilizes modern sign handling and AI calculations. Although nonverbal communication through gestures has been around for a while, gesture-based human-computer interaction (HCI) is growing in popularity in the present day. The conventional interface uses a number of tools, including markers, physical controllers, and gloves, to increase the recognition rate. This work offers a novel marker less method for capturing gestures without the use of expensive gear or any obstacles. In order to enable disabled individuals to operate household appliances using their own speech and gesture commands, we present in this paper a speech and Gesture Driven automation system for homes with a central controller. The framework joins programmed reactions with continuous observation highlights to further develop security, openness, and user solace. Framework reenactment, including control rationale, voice order handling, and motion identification, is finished with MATLAB. The accuracy, reactivity, and common sense of the innovation are shown by the recreation results. © 2025 ieee.

关键词： MATLAB

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DRL-Based Dependent Task Offloading in Collaborative Vehicular Networks 6

DRL-Based Dependent Task Offloading in Collaborative Vehicul...

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6th International conference on Internet of Things, automation and Artificial Intelligence, IoTAAI 2024

作者： Zhao, Gaoyu Cui, Haixia South China Normal University School of Electronics and Information Engineering Foshan China South China Normal University School of Electronic Science and Engineering Foshan China

ISBN: (纸本)9798350386974

Collaborative vehicular networks (CVNs) can provide the data processing and task offloading services with the seamless cooperation of edge and fog computing for user vehicles (UVs). However, intelligent task offloading in CVNs will raise numerous concerns, including the long-term quality of service (QoS) requirements and the environmental information utilization efficiency. In response to the aforementioned questions, we present a delay-energy-aware dependent task offloading algorithm (DEADTO) based on DRL to optimize the comprehensive throughput of UVs while ensuring the preservation of quality of service (QoS) stability with the utmost diligence. Compared with the existing works, our proposed algorithm demonstrates superior performance, delivering enhanced throughput, reduced latency and optimized energy consumption. © 2024 ieee.

关键词： Fog computing

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SLRNet: Shallow Convolutional Neural Network for Efficient Sign Language Recognition 3

SLRNet: Shallow Convolutional Neural Network for Efficient S...

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3rd ieee International conference on Robotics, automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Mostafa, Lamia Brishti, Faria Jerin Akther, Eishita Sultana Khaliluzzaman, M.D. Hoque, MD Jiabul Department of Computer Science and Engineering Chattogram4318 Bangladesh Department of Computer and Communication Engineering Chattogram4318 Bangladesh

ISBN: (纸本)9798331534400

In recent times, recognizing hand gestures from a sign image has become a vital research field in the areas of computer vision and human-computer interaction. Many researchers have taken advantage of various features and deep learning architectures (DLA) to update the performance of existing sign recognition systems. In small datasets such as ASL, shallow DLAs such as convolutional neural networks (CNN) work well. However, the deeper deep learning architectures are overfitted on the small datasets. To overcome this problem, in this work, two shallow CNN models, SLRNet1 and SLRNet2, are proposed. The proposed models use four convolutional layers to extract the features from the sign image and two fully connected layers to recognize the sign. The first and second models gain 98.94% and 99.14% accuracy, respectively. Both models achieve significant improvements with respect to the present state of the art. Contribution - Two regularized hand gesture recognition models, SLRNet1 and SLRNet2, were developed to work efficiently on small datasets without overfitting and perform fine-tuning to achieve better accuracy. © 2024 ieee.

关键词： Convolutional neural networks

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