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Factors influencing the resistance of bolt-connected structures to explosion shock based on explosion simulation 10

Factors influencing the resistance of bolt-connected structu...

引用

10th international conference on Mechanical engineering, Materials, and automation Technology, MMEAT 2024

作者： Zhou, Yunbo Zhang, Jun Zhang, Ming Ye, Zhibin School of Mechanical Engineering Nanjing University of Science and Technology Jiangsu Nanjing210094 China

ISBN: (纸本)9781510682634

In this paper, the explosion impact resistance of bolt-connected structures is explored, and ALE explosion simulation algorithm is used to simulate and analyze bolt-connected platforms under explosion environment, and the accuracy of the finite element model is verified by comparison with the platform explosion test. Different modeling methods were used to explore the influence of different bolt models on the simulation results. It was found that the solid bolt model had the best effect and the error was the smallest, 1.5%, compared with the experiment. The other parameters of the bolt were kept unchanged, and only the bolt strength grade was changed. The influence of different bolt strength levels on the simulation results was explored. It was found that the maximum displacement of the target plate continued to decrease with the increasing of bolt strength level, and the anti-knock performance continued to improve. The effects of different bolt models and bolt strength grades on the explosion impact resistance of bolt-connected structures are summarized and analyzed, and some theoretical basis and reference are provided for bolt-connected body design of protected vehicles. © 2024 SPIE.

关键词： Deformation Solids computer simulations Explosives Finite element methods Resistance Detection and tracking algorithms Modeling Analytical research Design

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Real-Time Sliding Mode Fault Diagnosis for a Three-Wheeled Omnidirectional Mobile Robot 18

Real-Time Sliding Mode Fault Diagnosis for a Three-Wheeled O...

引用

IEEE 18th international conference on automation Science and engineering (IEEE CASE)

作者： Lizarraga, Adrian Begovich, Ofelia Ramirez, Antonio Cinvestav Guadalajara Dept Elect Engn Zapopan 45019 Jalisco Mexico

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

This work introduces the design of a sliding mode fault diagnoser capable of diagnosing simultaneous faults in a three-wheeled omnidirectional mobile robot. The approach proposes an augmented system comprising the system states and the dynamics of the faults. Based on this, a sliding mode observer is designed to estimate both, the system state and fault magnitudes, allowing the fault diagnosis. This approach leads to light and efficient implementations, which is suitable for real-time applications. The approach has been tested in a real mobile robot showing satisfactory results.

关键词： Fault diagnosis computer aided software engineering Codes automation Observers Robot sensing systems Real-time systems

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Research on Electrospindle Vibration Prediction Model Based on Improved Whale Algorithm to Optimize Convolutional Neural Network

Research on Electrospindle Vibration Prediction Model Based ...

引用

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

作者： Jing, Hou Jianzhou, Li Jinxiang, Pian School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9798350309614

During the high-speed operation of the mechanical electric spindle, due to the uneven distribution of rotor mass and long-term wear, the rotation deviates from the axis to produce vibration, resulting in low working accuracy, so the dynamic balance method is often used to reduce the impact caused by such reasons. Aiming at the problem that it is difficult for traditional electromechanical spindles to accurately adjust the vibration amplitude of spindle rotor in a short time in a long-term complex changing environment, a mechatronic spindle vibration prediction model based on the improved whale optimization algorithm (WOA) optimization convolutional neural network (CNN) is proposed. Experimental results show that the prediction model has higher accuracy for predicting electrospindle vibration, and the convergence speed is faster and more accurate. © 2023 IEEE.

关键词： convolutional neural networks Improved whale optimization algorithm mechanical spindle vibration forecasting

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CNN-Based Image Classification for Face-Spoof Detection Using AI and ML

CNN-Based Image Classification for Face-Spoof Detection Usin...

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2023 international conference on IoT, Communication and automation Technology, ICICAT 2023

作者： Pushpanjali, Km Srivastav, Shashank Dept of Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9798350302820

With the rapid development of digital content identification in recent years, automatic image classification has become the most difficult task in computer vision. Compared to human vision, it is challenging for systems to comprehend and analyze images automatically. A few examinations have been finished to conquer issues in the existing grouping framework;however, the result was restricted exclusively to low even-out picture natives. However, these methods fail to classify images accurately. Our system employs a machine learning algorithm in this paper to produce the anticipated outcomes in computer visions. We achieved an experimental accuracy of 97.5% for grayscale image classification, demonstrating that our model can accurately classify images. © 2023 IEEE.

关键词： Image classification

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A State Graph-Based Improved Framework for Monkey GUI Testing for EDA Desktop Applications 13

A State Graph-Based Improved Framework for Monkey GUI Testin...

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13th international conference on Software Technology and engineering, ICSTE 2023

作者： Ali, Sarah Fayek, Magda Cairo University Faculty of Engineering Computer Engineering Department Giza Egypt

ISBN: (纸本)9798350371475

Monkey testing is one of the autonomous Graphical User Interface (GUI) automation testing techniques. Due to the complex GUI of Electronic Design automation (EDA) software applications, applying Monkey Testing in a timely manner is very challenging. By making use of the GUI regressions knowledge about the application we can have a faster and improved Monkey testing approach. Yet directing the improved Monkey flow to have better coverage needs enhancements so this paper addresses this by building a state graph while running to guide traversing new states using image processing and weighted random selection technique. A state is represented as an image and the improved Monkey testing flow is guided to avoid already hit windows and actions The paper proves that the state graph-based Monkey testing approach reaches higher coverage than the improved Monkey testing approach. © 2023 IEEE.

关键词： automation

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Research on Sentiment Analysis Fusion Based on Neural Network 6

Research on Sentiment Analysis Fusion Based on Neural Networ...

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6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Ma, Yuanyuan Sun, Yongyong Xu, Fei Xi'an Technological University School of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798350305388

With the aim of overcoming the limitations in feature extraction capability, OOV (out-of-vacabulary) and polysemous word in Chinese text sentiment analysis, dual attention gated recurrent neural network (AW-Att-BiGRU) with word and character information fusion was proposed. Firstly, character and word level vector are taken as input to the model to obtain semantic representation to the maximum extent. Then, characters and words with obvious emotional characteristics are given higher weights through the attention mechanism, to achieve a more comprehensive understanding of the emotional tendencies within the text and enhance the accuracy of sentiment analysis. Based on the experimental results using the Tan Songbo Hotel review dataset, the proposed model achieved an accuracy rate of 94.56%, and the accuracy rate on Weibo review dataset is 93.87%, which improves the performance compared with a single model and has certain application value. © 2023 IEEE.

关键词： Sentiment analysis

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Open Source Software Tools for Data Management and Deep Model Training automation 38

Open Source Software Tools for Data Management and Deep Mode...

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38th IEEE/ACM international conference on Automated Software engineering (ASE)

作者： Tirasoglu, Umut Turker, Abdussamet Ekici, Adnan Yigit, Hayri Bolukbasi, Yusuf Enes Akgun, Toygar ORDULU Technol Corp Artificial Intelligence Grp Ankara Turkiye TOBB Univ Econ & Technol Dept Comp Engn Ankara Turkiye

ISBN: (纸本)9798350329964

Designing and optimizing deep models require managing large datasets and conducting carefully designed controlled experiments that depend on large sets of hyper-parameters and problem dependent software/data configurations. These experiments are executed by training the model under observation with varying configurations. Since executing a typical training run can take days even on proven acceleration fabrics such as Graphics Processing Units (GPU), properly managing training data, avoiding human error in configuration preparations and securing the repeatability of the experiments are of utmost importance. In this paper, we present two open source software tools that aim to achieve these goals, namely, a Dataset Manager (DatumAid) tool and a Training automation Manager (OrchesTrain) tool. DatumAid is a software tool that integrates with computer Vision Annotation Tool (CVAT) to facilitate the management of annotated datasets. By adding additional functionality, DatumAid allows users to filter labeled data, manipulate datasets, and export datasets for training purposes. The tool adopts a simple code structure while providing flexibility to users through configuration files. OrchesTrain aims to automate model training process by facilitating rapid preparation and training of models in the desired style for the intended tasks. Users can seamlessly integrate their models prepared in the PyTorch library into the system and leverage the full capabilities of OrchesTrain. It enables the simultaneous or separate usage of Wandb, MLflow, and TensorBoard loggers. To ensure reproducibility of the conducted experiments, all configurations and codes are saved to the selected logger in an appropriate structure within a YAML file along with the serialized model files. Both software tools are publicly available on GitHub.

关键词： dataset management training automation deep model augmentation

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Evaluation of Natural Language Used to Software Engineer based on Chatbot

Evaluation of Natural Language Used to Software Engineer bas...

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

作者： Balamurugan, J. Subramanyam, Naguru Mani, D. Sharada Basi Reddy, A. St. Joseph's College of Engineering Department of Mba Chennai India Audisankara College of Engineering and Technology Department of Computer Science and Engineering Gudur India Qis College of Engineering and Technology Vengamukkapalem Department It Ongole India Mohan Babu University School of Computing Department of Computer Science and Engineering Andhra Pradesh Tirupati India

ISBN: (纸本)9798350317060

The field of natural language processing (NLP), which aims to represent and analyze human language digitally, has recently attracted much interest. Machine learning has found several uses, including translation, spam filtering, data mining, stigmatization, medicine, and answering questions online. After introducing the background and development of NLP, it breaks down into four distinct periods by describing the various stages of NLP and the building blocks of Natural Language Generation (NLG). The numerous applications of NLP, current trends, and problems are then presented, the state of the art in great depth. At the end of the paper, it explores several existing NLP datasets, models, and assessment measures. © 2023 IEEE.

关键词： Machine learning

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On the Design of Novel Attention Mechanism for Enhanced Efficiency of Transformers 24

On the Design of Novel Attention Mechanism for Enhanced Effi...

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61st ACM/IEEE Design automation conference, DAC 2024

作者： Jha, Sumit Kumar Jha, Susmit Ewetz, Rickard Velasquez, Alvaro Computer Science Department Florida International University MiamiFL United States Computer Science Laboratory Sri International Menlo ParkCA United States Electrical and Computer Engineering University of Central Florida OrlandoFL United States Department of Computer Science University of Colorado Boulder BoulderCO United States

ISBN: (纸本)9798400706011

We present a new xor-based attention function for efficient hardware implementation of transformers. While the standard attention mechanism relies on matrix multiplication between the key and the transpose of the query, we propose replacing the computation of this attention function with bitwise xor operations. We mathematically analyze the information-theoretic properties of the standard multiplication-based attention, demonstrating that it preserves input entropy, and then computationally show that the xor-based attention approximately preserves the entropy of its input despite small variations in correlations between the inputs. Across various admittedly simple tasks, including arithmetic, sorting, and text generation, we show comparable performance to baseline methods using scaled GPT models. The xor-based computation of the attention function shows substantial improvement in power consumption, latency, and circuit area compared to the corresponding multiplication-based attention function. This hardware efficiency makes xor-based attention more compelling for the deployment of transformers under tight resource constraints, opening new application domains in sustainable energy-efficient computing. Additional optimizations to the xor-based attention function can further improve efficiency of transformers. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Distribution transformers

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Advantages and Challenges of Utilizing RFID Technology 15

Advantages and Challenges of Utilizing RFID Technology

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15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dhabliya, Dharmesh Amudha, A. Kaur, Ashmeet Gayathri, C. Garg, Anvesha Vivek, V. Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Research Impact and Outcome Chitkara University Centre of Rajpura Punjab 140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350370249

Radio Frequency identity (RFID) is a rising technology that uses radio waves to become aware of and tune gadgets. With advances in hardware and software, RFID technology gives many blessings to agencies by means of growing facts accuracy, improving asset tracking, inventory management, and different procedure automation. However, no matter the diverse blessings it could provide, there are several challenges that businesses have to consider while implementing the RFID era. Those demanding situations encompass capability security and privacy worries, technical complexity, price, and interference from other RF indicators. To capitalize on the advantages of RFID, agencies must carefully weigh the advantages against the potential risks to decide the end goals and whether RFID is the most viable solution. © 2024 IEEE.

关键词： Accuracy Advantages Agencies automation Demanding Implementing Improving Indicators

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