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Prediction of Crack Propagation Rate Due to Stress Corrosion Cracking in AISI 4340 Steel in 0–5 N NaCl Solution Using Artificial Neural Network 5th

Prediction of Crack Propagation Rate Due to Stress Corrosion...

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5th international conference on Emerging Trends in Mechanical and Industrial engineering, ICETMIE 2022

作者： Chandola, Nitin Maharishi, Subhash Tewari, Vinay Kumar Shukla, Animesh Department of Mechanical Engineering Graphic Era University Dehradun Clement Town India

ISBN: (纸本)9789811969447

Prior studies on the aluminum-based fatigue crack prediction show the advancement and introduction of the machine learning-based prediction system to the stress corrosion cracking (SCC)-based crack propagation prediction. In this study, we have focused on making an optimized model and methodology of predicting the crack propagation rate of AISI 4340 under the influence of 0–5 N of NaCl solution. this study shows the performance of prediction of crack propagation rate when the applied potential is taken as the attribute variable along with the crack length and stress intensity. the prime objectives of the study were to create an optimized model based on machine learning for the prediction of crack propagation rate. In the current study, we achieved an accuracy of 94% in predicting the crack rate (R2 = 0.887) with only three attributes. the relations were extracted from the data using data science and statistical techniques like k-nearest neighbors and polynomial regression. the independent attributes like applied potential show better trends in the accuracy of the test data. the model is not optimized for big data, as there is the possibility of overfitting if the batch size is increased during training. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Stress corrosion cracking

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Enhancing data leakage tracing: A novel digital watermarking method for document files 5

Enhancing data leakage tracing: A novel digital watermarking...

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5th international conference on Computer Communication and Network Security, CCNS 2024

作者： Kong, Tong Zhou, Hao Qu, Haikuo Chen, Jie Wang, Chonghua Li, Jun China Industrial Control Systems Cyber Emergency Response Team Beijing China Department of Cyberspace Security Beijing Electronic Science and Technology Institute Beijing China

ISBN: (纸本)9781510681842

With the development of informatization, the value of data is rapidly escalating. the security and controllability of data have become increasingly important. Digital watermarking is an effective method for data tracing and copyright protection. However, most digital watermarking methods focus on images, audio, and video files, with few applications dedicated to document file protection. therefore, we present an imperceptible and cryptographic digital watermarking method for document files, inspired by the image digital watermarking based on the Least Significant Bit (LSB). Firstly, the watermark information is divided into segments which will be encrypted into ciphertexts separately. then, these ciphertexts are converted into a binary byte stream and embedded into the LSB of the characters' color information in document files. Finally, we design an algorithm combined with the chaos theory to execute the embedding process, ensuring its controllability and randomness. Meanwhile, we design a watermark extraction method with a voting mechanism to restore and verify the watermark information. this method can resist the destruction of document files (such as adding, deleting, or modifying some characters) and enhance the stability and traceability of watermark information. the results demonstrate that the accuracy of information extraction is still nearly 80%, even when up to 40% of the document's characters are deleted, enabling quick verification of document copyrights and rapid tracing of the data source. © 2024 SPIE.

关键词： Information leakage

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Design of equipment intelligent management system based on Internet of things technology 5

Design of equipment intelligent management system based on I...

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5th international conference on Internet of things, Automation and Artificial Intelligence, IoTAAI 2023

作者： Li, Mingyue He, Xiaoran Zhang, Yuhao Liu, Chuanliu Cheng, Jiaqi Yang, Tianliang Yu, Yuerong Chen, Jiabao Zhao, Jiaqi Li, Pengtao School of Artificial Intelligence Tianjin University of Science and Technology Tianjin China School of Economics and Management Tianjin University of Science and Technology Tianjin China School of Chemical Engineering and Materials Tianjin University of Science and Technology Tianjin China

ISBN: (纸本)9798400716485

With the continuous improvement of the level of industrialization, the demand for intelligent control in the industrial production process is becoming more and more prominent. the use of Internet of things technology can quickly obtain a large amount of information, facilitate information processing, and improve industrial intelligence. Our team proposes to build an intelligent management system for large and medium-sized equipment based on Internet of things technology. Based on the Internet of things technology, we collect the use of all kinds of large and medium-sized equipment to determine the purchase situation of the next quarter, reduce the idle situation of equipment, improve the utilization rate of resources, and realize the reasonable allocation of resources. the product transmits the collected data to the cloud server through the wifi module of esp8266. the data is processed and analyzed, and the data results are visualized. At the same time, we have developed a corresponding applet, so that users can view the use of equipment and equipment utilization in real time. this product through the test equipment detection, real-time display data, the follow-up will continue to process and improve. the product performance is excellent, has the larger promotion and the application value. © 2023 ACM.

关键词： Information management

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SafeCuff: An Automated Cuff Pressure Monitoring and Control System for Enhanced Patient Safety 5

SafeCuff: An Automated Cuff Pressure Monitoring and Control ...

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5th IEEE international conference on Advances in Electronics, Computers and Communications, ICAECC 2023

作者： Gangula, Yaswanth Manoj Kumar, Nelavelli Sai Mohanty, Aparna Anitha, R. School of Electronics Engineering Vellore Institute of Technology Vellore India Systems Engineer Tata Consultancy Services Hyderabad India

ISBN: (纸本)9798350305449

Endotracheal cuff pressure monitoring and control are crucial for ensuring patient safety and optimizing mechanical ventilation. Proper maintenance of cuff pressure is vital to establishing a reliable seal between the endotracheal tube and the tracheal wall, effectively preventing air leakage and minimizing the risk of aspiration. Inappropriate cuff inflation can lead to detrimental outcomes such as tracheal mucosa damage, necrosis, increased aspiration risk, and compromised ventilation effectiveness. Regular monitoring and adjustment of cuff pressure by healthcare providers are essential to minimize complications, improve patient outcomes, and enhance overall ventilation efficacy. this research paper recognizes the significance of periodic pressure monitoring and introduces an IoT-based automated system specifically designed to monitor and control cuff pressure. the primary objective of this system is to safeguard patients by mitigating risks associated with suboptimal cuff pressure management. the system incorporates advanced Internet of things technology, utilizing sensors for real-time monitoring and feedback. It enables healthcare providers to promptly identify any deviations in cuff pressure and make the necessary adjustments. the system further offers the convenience of both automatic control at the edge and remote control through a dedicated mobile application. this allows healthcare providers to maintain optimal cuff pressure levels efficiently and effectively. By implementing such an automated system, the potential exists to protect patients from harm and associated hazards. In situations like the pandemic, where mechanical ventilation is frequently needed, this could be helpful. Adequate endotracheal cuff pressure management facilitated by this system can contribute to improved patient safety, mitigation of risks, and optimized mechanical ventilation outcomes. © 2023 IEEE.

关键词： Remote control

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Enhancing Security in SDN Environments through Multi-Layer Authentication and Machine Learning-Based threat Mitigation 5

Enhancing Security in SDN Environments Through Multi-Layer A...

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5th international conference on Advancements in Computing, ICAC 2023

作者： Ilangarathna, D.N. Dilshan, D.R.G.K.B. Dharmakeerthi, Uditha Senarathne, Amila Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

the revolutionary nature of Software-defined networking(SDN) in network management is accompanied by new and more difficult security concerns. this study provides a full security architecture and a robust SDN setup. It combines north and southbound APIs' multi-factor authentication with machine learning-based threat detection. We implement a strict two-factor authentication scheme for the northbound API space using the Ryu SDN framework. SSL/TLS encryption and MongoDB for credentials allow for the authentication of users and applications. this prevents Man-in-the-Middle attacks by verifying user credentials and app IDs in a safe environment. the research uses machine learning to prevent malicious injections when utilizing southbound API. By learning from network traffic data, models like k-nearest neighbours (KNN), Decision Trees(DT), and Random Forests(RF) may distinguish between genuine and malicious packets. By quickly identifying dangerous network behaviours, this method employs malicious packet detection and alert generation. Numerous experiments prove the structure effectively counters security risks. It protects software-defined networks, making sure they stay online and secure. this study contributes to the ongoing conversation about SDN security by providing a comprehensive method for dealing with the complex challenges posed by the rapid evolution of cyber threats in the software-defined networking sector. © 2023 IEEE.

关键词： Authentication

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Predictive Intelligence Enhanced Fuzzy Model for Underwater Network Optimization 5th

Predictive Intelligence Enhanced Fuzzy Model for Underwater ...

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Praveena, K.N. Mishra, Awakash Kamalraj, R. Belwal, S. Ankit School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Information Technology Jain University Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India

ISBN: (纸本)9789819780426

this paper gives a predictive intelligence-enhanced fuzzy version for underwater network optimization. It combines predictive intelligence technology with fuzzy common sense, which can lessen the functionality gap of underwater community optimization. this proposed version is implemented in an underwater cooperative tracking community. With the proposed model, objectives can be tracked with sensors within the network, and their national statistics can also be appropriately anticipated. Similarly, the version has excessive scalability and robustness because of the mixing of predictive intelligence. In the end, simulation experiments suggest that the proposed model correctly improves the precision of tracking challenges and improves the scalability of the network. the Predictive Intelligence superior Fuzzy model (PIE-FUZMO) for underwater network optimization is a singular method developed to cope with the complex optimization issues confronted through underwater networks. the PIE-FUZMO uses a couple of laptops with imaginative and prescient sample recognition techniques and fuzzy good judgment to enhance the underwater community performance while decreasing the running fee. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scalability

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Research on the Early Warning System of College Students' Mental Health Based on big data Analysis 5

Research on the Early Warning System of College Students' Me...

引用

5th international conference on Computer Network, Electronic and Automation, ICCNEA 2022

作者： Wei, Huimei Wang, Lijuan He, Dandan Li, Yao Dalian Institute of Science and Technology School of Information Science and Technology Dalian China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

With the continuous improvement of education quality, the importance of College Students' mental health is more and more obvious in college education. For the mental health management of college students, we should not only establish a system database to store data sources, but should reasonably apply the data sources to upgrade the data to an objective, visual and predictable level, so as to prepare for a rainy day. this study applies big data related technologies to the field of College Students' mental health, and carries out early warning and intervention on College Students' mental health through data thinking and methods. the system provides an intelligent solution based on data thinking for preventing college students' mental diseases, enhancing college students' management ability and improving students' physical and mental health. © 2022 IEEE.

关键词： Students

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StutterAI: Virtual Assistant for Stutter Detection and Analysis through Machine Learning and Natural Language Processing Approaches 5

StutterAI: Virtual Assistant for Stutter Detection and Analy...

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5th international conference on Advancements in Computing, ICAC 2023

作者： Arachchi, B.A.T.P. Benthota Sanjeewa, J.M.I.P. Wijesooriya, H.M.A.H. Chandrasena, M.C. Kishara, Jenny Kelegama, thamali Rajapakse, V.M. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka Ltd Nugegoda Sri Lanka

ISBN: (纸本)9798350358131

Stutter AI is an innovative research project that focuses on the development of a web application designed to detect and provide personalized treatments for individuals with varying degrees of stuttering severity. Stuttering, characterized by disruptions in speech flow, can significantly impact communication and confidence. the Stutter AI web app utilizes advanced voice analysis techniques, natural language processing, and machine learning algorithms to analyze speech patterns, identify stuttering types, and assess severity at the phrase and syllable levels of patients aged between eighteen to forty-five. Based on this analysis, the app generates tailored treatment suggestions, incorporating evidence-based techniques to support individuals in managing and improving their fluency. through its user-friendly interface and comprehensive approach, Stutter AI aims to empower individuals who stutter, while also providing valuable insights to speech-language therapists and researchers in the field of stuttering therapy. © 2023 IEEE.

关键词： Learning algorithms

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the State and Optimization of VR technology in Real Estate: A big data and Visualization Approach 24

The State and Optimization of VR Technology in Real Estate: ...

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2024 5th international conference on big data Economy and Information Management, BDEIM 2024

作者： Sun, Xiliang Wu, Mingze International College Beijing China Agricultural University Beijing China

ISBN: (纸本)9798400711862

With the rapid development of global information technology, Virtual Reality (VR) has started to deeply affect the operations and market ecosystems of China’s real estate sector. Research has shown that incorporating VR into the property sales and marketing, and presentation processes can enhance the operational performance and engagement of customers. Using both personal study and existing literature, this paper applies the SWOT analysis framework and incorporates big data methods to analyze China’s VR real estate market from four aspects: strengths, weaknesses, opportunities, and threats. the findings show that VR can offer a very realistic virtual view and thus speed up the decision-making process, however, it is still faced with issues of technical failures and privacy concerns. In addition, the paper explores how VR can be integrated with artificial intelligence (AI), and applied to the commercial real estate and rental markets. Ahead, suppose real estate companies are able to harness big data platforms for user behavior analytics and targeted advertising. In that case, VR in China’s property sector is likely to continue to develop strongly. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Digital transformation Property marketing chain Real estate technology Virtual reality

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REncoder: A Space-Time Efficient Range Filter with Local Encoder 39

REncoder: A Space-Time Efficient Range Filter with Local Enc...

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39th IEEE international conference on data engineering, ICDE 2023

作者： Wang, Ziwei Zhong, Zheng Guo, Jiarui Wu, Yuhan Li, Haoyu Yang, Tong Tu, Yaofeng Zhang, Huanchen Cui, Bin Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peng Cheng Laboratory Shenzhen China Zte Corporation Beijing China Tsinghua University Beijing China

ISBN: (纸本)9798350322279

A range filter is a data structure to answer range membership queries. Range queries are common in modern applications, and range filters have gained rising attention for improving the performance of range queries by ruling out empty range queries. However, state-of-the-art range filters, such as SuRF and Rosetta, suffer either high false positive rate or low throughput. In this paper, we propose a novel range filter, called REncoder. It organizes all prefixes of keys into a segment tree, and locally encodes the segment tree into a Bloom filter to accelerate queries. REncoder supports diverse workloads by adaptively choosing how many levels of the segment tree to store. We theoretically prove that the error of REncoder is bounded and derive the asymptotic space complexity under the bounded error. We conduct extensive experiments on both synthetic datasets and real datasets. the experimental results show that REncoder outperforms all state-of-the-art range filters. © 2023 IEEE.

关键词： data structures

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