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5th International Conference on Recent Advancements in mechanical engineering, ICRAME 2024

作者： Vivekanandan, N. Rajeswari, K. Salve, Sanjay P. Kanna, N. V. Yuvraj Department of Mechanical Engineering Pimpri Chinchwad College of Engineering Pune India Department of Computer Engineering Pimpri Chinchwad College of Engineering Pune India Data Science for Business University of Stirling Stirling United Kingdom

ISBN: (纸本)9789819775347

The Electronic Nose, a compact electro-mechanical device, exhibits the capability to discern an extensive array of odors, encompassing substances such as food, human breath, and hazardous toxins. In this study, the Electronic Nose is employed to classify aromas emanating from three distinct burning materials: joss stick, mosquito coil, and instant benzoin. Utilizing the counter propagation neural network, the Electronic Nose is trained and deployed for the classification of these burning odors. The primary objective of this project is the development of an intelligent smoke detector, ensuring the precise identification of harmful burning materials. This proactive approach aims to detect potential fire hazards promptly, preventing untoward incidents effectively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electronic nose

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Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels

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IEEE Access 2025年 13卷 89542-89555页

作者： Rahiman, Wan Ghazali, Mohamad Hazwan Mohd Mahmood, Iskandar Al-Thani Universiti Sains Malaysia Engineering Campus School of Electrical and Electronic Engineering Penang Nibong Tebal14300 Malaysia Daffodil International University Daffodil Robotics Lab Department of Computer Science and Engineering Dhaka1216 Bangladesh Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Mechanical and Manufacturing Engineering Selangor Bangi43600 Malaysia PETRONAS Research Sdn Bhd Selangor Kajang43000 Malaysia

Advancement in marine vessel stabilization technologies has greatly improved the safety and comfort for crews, cargo, and passengers, while also lowering the risk of capsizing. Marine vessels operating in open waters experience disturbances from unpredictable waves and strong winds, leading to instability and potential accidents. To mitigate these risks, stabilizers are integrated into ships to maintain stability, safety, and seaworthiness. As modern vessels evolve, stabilizers play an increasingly vital role, with gyro stabilizers emerging as a highly effective solution for mitigating roll motion without external appendages. This paper provides a comprehensive review of gyro stabilizer designs and techniques, covering their historical development, mathematical modeling, advantages, limitations, and case studies. A review of current research highlights a strong emphasis on simulating gyro stabilizer control systems, demonstrating their potential in enhancing vessel stability. However, key challenges persist, including accurate wave moment prediction during the design phase and gyroscopic drift, which can impact long-term performance and efficiency. Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. By exploring the latest developments, this review serves as a valuable reference for researchers, engineers, and maritime professionals seeking to advance marine stabilization technologies. The findings underscore the potential of next-generation gyro stabilizers, including fiber optic gyros, in achieving higher precision, stability, and operational efficiency. © 2013 IEEE.

关键词： Warships

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A Case for Bayesian Grading 2024

A Case for Bayesian Grading

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1st ACM Virtual Global Computing Education Conference V. 1, SIGCSE Virtual 2024

作者： Zilles, Craig Zhao, Chenyan Chen, Yuxuan Matthews, Evan Michael West, Matthew Computer Science University of Illinois UrbanaIL United States Mechanical Science and Engineering University of Illinois UrbanaIL United States

ISBN: (纸本)9798400705984

Academic integrity continues to be an issue in education. Students' grades are often computed using a collection of evidence that varies in its trustworthiness (e.g., a proctored exam can be trusted more than an out-of-class programming project) due to practical constraints. When a student cheats, their trusted and less trustworthy scores are inconsistent, which presents instructors a choice between rewarding the cheating behavior and the burden of investigating / making cheating allegations. In this position paper, we propose that Bayesian inference might be a useful tool in assigning grades derived from trusted and less trusted evidence. Rather than compute grades by performing arithmetic on both trusted and untrusted assessments, we instead try to infer a latent variable, the student's mastery of the course material, from these observed performances and their potential for cheating. Key to this approach is that grades can be assigned that discount suspicious work without needing to explicitly make a cheating allegation. A logical conclusion of this approach is that the needed amount of trusted assessments for a given student depends on how inconsistent are their trusted and untrusted assessments. © 2024 Owner/Author.

关键词： Students

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Efficient practical Byzantine Consensus-based reputation method for IoT based electronic waste tracking and tracing system using blockchain

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Multimedia Tools and Applications 2024年第37期83卷 84639-84672页

作者： Sharma, Lokesh Gupta, Ravi Kant Lamba, Chattar Singh Kumar, Ajay Lathar, Pankaj Department of IT Manipal University Jaipur Rajasthan303007 India Department of Mechanical Engineering Manipal University Jaipur Rajasthan303007 India Department of Computer Science & amp Engineering Manipal University Jaipur Rajasthan303007 India Department of Mechatronics Engineering Manipal University Jaipur Rajasthan303007 India Department of Computer Science and Applications Delhi Skill and Entrepreneurship University Dwarka New Delhi Delhi110077 India

The utilization of smart contracts enables the integration of blockchain technology to provide incentives for the gathering of electronic trash. Traditional blockchain-based Internet of Things (IoT)-E-Waste Tracking systems have challenges such as data privacy issues, significant delays, and low transaction per second (TPS) rates. In order to tackle these difficulties, the proposed approach utilizes a blockchain-based technology called IoT-enabled Efficient Practical Byzantine Consensus-based Reputation (EPBCR). This approach effectively monitors the post-production business processes of electronic devices by using hybrid consensus and reputation optimization algorithms. As a result, it enhances transparency, traceability, and privacy. The system efficiently regulates and oversees electronic gadgets throughout its supply chain by employing smart contracts on an unchangeable distributed ledger. The methodology is supported by analyzing the gas usage of Smart contracts on the Ethereum network. This results in the creation of, efficient, and high-throughput system that assists participants in conducting economic transactions. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Smart contract

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A wake loss model asymmetry induced by the circulation of a vertical axis wind turbine

A wake loss model asymmetry induced by the circulation of a ...

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2023 International Conference on Future Energy Solutions, FES 2023

作者： Hassanian, Reza Helgadóttir, Ásdís Riedel, Morris University of Iceland The Faculty of Industrial Engineering Mechanical Engineering and Computer Science Reykjavik Iceland Juelich Supercomputing Centre Germany

ISBN: (纸本)9798350332308

The purpose of this research is to develop a theoretical method for predicting the wake region downstream of the flow from a top view of a vertical axis wind turbine (VAWT) and to examine the wake loss effects of the VAWT. Previous literature has reported that the wake region of the VAWT is not symmetric, and its downstream is similar to a circular cylinder wake street. The airflow of the VAWT is turbulent, and the inviscid incompressible flow can be applied to its range. Therefore, the current study analyzed the flow over a cylinder with circulation to investigate the velocity, pressure coefficient, and tip speed ratio and to observe the similarity between the cylinder and the VAWT. The results of this study demonstrate remarkable similarity, particularly with respect to the asymmetry of the wake region due to the distinct velocity speed in two opposite locations of the VAWT. Moreover, the pressure coefficient functionality and curvature are similar to the available measurements of the VAWT. This model can be further developed and examined under varied conditions to provide a theoretical wake loss model for VAWTs. This will lead to the expansion of VAWTs' applications in green, sustainable, and clean energy production. © 2023 IEEE.

关键词： Vertical axis wind turbine

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A computer vision based real-time warpage monitoring and detection system in fused deposition modeling

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Multimedia Tools and Applications 2024年 1-26页

作者： V S, Devesh Sundarrajan, Sridhar Venkatesan, M. Bhuvaneswari, S. School of Mechanical Engineering SASTRA Deemed University Tirumalaisamudram Tamilnadu Thanjavur613 401 India Department of Computer Science and Engineering Srinivasa Ramanujan Centre SASTRA Deemed University Tamilnadu Kumbakonam612 001 India

Additive Manufacturing (AM) manufactures a component by adding layers of material. Fused Deposition Modeling (FDM) is one such AM technique where polymer materials like ABS, and PLA are printed. The FDM method involves considerable time for printing the material. Any disruptions in the bed, power, or nozzle movements during printing will result in defective product. One of the reasons for a defective print arises due to a phenomenon called warping. These disruptions and errors pose challenges for early prevention as they are only visible gradually over time and cause warpage. In the present work, an attempt is made to predict the occurrence of warpage in FDM printed parts. In the present work, an attempt is made to avoid the adverse effect of warping by utilizing a computer vision model for real-time warpage detection. A real-time acquisition system is built to capture print layer-by-layer for a convolutional-based feature extraction process. This integration of a computer vision model aligned with continuous monitoring facilitates a timely shutdown process upon the occurrence of warpage. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Fused Deposition Modeling

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A Fault-Tolerant Mobility-Aware Caching Method in Edge Computing

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computer Modeling in engineering & sciences 2024年第7期140卷 907-927页

作者： Yong Ma Han Zhao Kunyin Guo Yunni Xia Xu Wang Xianhua Niu Dongge Zhu Yumin Dong School of Computer Information Engineering Jiangxi Normal UniversityNanchang330000China School of Digital Industry Jiangxi Normal UniversityShangrao334000China The College of Computer Science Chongqing UniversityChongqing400044China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing400030China School of Computer and Software Engineering Xihua UniversityChengdu610039China Electric Power Research Institute of State Grid Ningxia Electric Power Company Ltd. Yinchuan750002China College of Computer and Information Science Chongqing Normal UniversityChongqing401331China

Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to *** the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user ***,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource *** the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant *** response to this challenge,this paper introduces FT-MAACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance *** approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached ***,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and *** results unequivocally demonstrate that FTMAACC outperforms its peer methods in cache hit rates and transmission latency.

关键词： Mobile edge networks mobility fault tolerance cooperative caching multi-agent deep reinforcement learning content prediction

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Proactive Caching at the Wireless Edge:A Novel Predictive User Popularity-Aware Approach

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computer Modeling in engineering & sciences 2024年第8期140卷 1997-2017页

作者： Yunye Wan Peng Chen Yunni Xia Yong Ma Dongge Zhu Xu Wang Hui Liu Weiling Li Xianhua Niu Lei Xu Yumin Dong College of Computer Science Chongqing UniversityChongqing400044China School of Computer and Software Engineering Xihua UniversityChengdu610039China School of Computer and Information Engineering Jiangxi Normal UniversityNanchang330022China Electric Power Research Institute of State Grid Ningxia Electric Power Co. Ltd.Yinchuan750002China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing400030China School of Computer Science and Technology Beijing Institute of TechnologyBeijing100083China School of Computer Science and Technology Dongguan University of TechnologyDongguan523808China School of Emergency Management Xihua UniversityChengdu610039China College of Computer and Information Science Chongqing Normal UniversityChongqing401331China

Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as *** an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user ***,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of ***,techniques for caching content at the edge are becoming popular for addressing the above *** is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud ***,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity *** address this challenge,we introduce a novel method for content caching over MEC,i.e.,*** synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching *** results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.

关键词： Mobile edge computing content caching system average cost deep reinforcement learning collaborative mechanism

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AI in Medical Imaging: Enhancing Diagnostic Accuracy with Deep Convolutional Networks

AI in Medical Imaging: Enhancing Diagnostic Accuracy with De...

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2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Shrivastava, Anurag Bhadula, Shuchi Kumar, Rakesh Kaliyaperumal, Gopal Rao, Bolleddu Devananda Jain, Alok Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India GLA University Department of Computer Engineering & Applications Mathura India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India MLR Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India

ISBN: (纸本)9798331512965

The past has witnessed a time of astounding developments in AI, particularly notable deep convolutional networks, which has greatly facilitated medical imaging by opening up previously unattainable doors for both precision and effectiveness of diagnoses. This study is an investigation into how deep convolutional neural networks (CNNs) might be applied (using MRI, CT, and X-ray as examples) to medical imaging for the purposes of improving accuracy, consistency, and practicability of diagnostic procedures. Through automated feature extraction and categorization, convolutional neural networks (CNNs) enable earlier, and more accurate, detection of illnesses such as cancer, cardiovascular disease and neurological problems by detecting minor deviations that humans may miss. Here we evaluate the accuracy, sensitivity, and computing efficiency of several convolutional network (CNN) designs. ResNet and UNet are these architectures. The results indicate that CNN based models provide better performance compared to conventional diagnostic approaches with a substantial diminution in both false positives and false negatives. The article also covers combining CNNs with others AI methods such as transfer learning, ensemble methods, etc. to further improve diagnostic results. Although the encouraging outcomes, data protection, interpretability, and clinical acceptance continue to be obstacles. This study shows how AI driven technology can revolutionize medical imaging to enhance patient outcomes as well as tailored healthcare solutions. © 2025 IEEE.

关键词： Convolutional neural networks

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A Systematic Investigation of Cyber Harassment Intention Behaviors and Its Impacts on Social Media Platforms

A Systematic Investigation of Cyber Harassment Intention Beh...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Abarna, S. Sheeba, J.I. Devaneyan, S. Pradeep Puducherry Technological University Department of Computer Science and Engineering India Sri Venkateshwaraa College of Engineering and Technology Department of Mechanical Engineering Puducherry India

ISBN: (纸本)9798350348217

Several technologies have been able to fundamentally affect our lives in just a few decades by integrating themselves into our society. News and opinion are now mostly shared on social media. There are both positive and negative aspects to this. Nowadays, practically everyone has a smartphone or other internet-accessing gadget. Modern technology becomes available to kids at progressively younger ages. The majority of them use social media, which contributes to the rise of cyber harassment and the negative aspects of the internet. Due to the ease of access to these platforms, cyberbullying is prevalent on social media. Moreover, when dealing with others, the perpetrators have the ability to remain anonymous. Cyberbullying statistics for 2022 highlight the alarming incidence of harassment in the virtual world, and they are disturbing. According to these data, Cyberbullying sufferers are more than twice as likely to self-harm or entertain suicidal thoughts as a coping mechanism. Anxiety and sadness might develop in certain victims of cyberbullying. Psychologists believe that social media has contributed to an increase in stress and depression over the last decade. On the other side, the most typical targets for online bullies are young children, women, and individuals with non-traditional sexual orientations. Students are often unable to concentrate on their studies because they are afraid of the trolls. As a result, this Research Essential focuses on Cyber harassment statistics and facts in order to raise awareness among parents, students, and authorities worldwide and reveal alarming facts about virtual harassment, the intention of the harasser, its impact, the relationship between victim and harasser, and its many different shapes and forms. © 2023 IEEE.

关键词： Social networking (online)

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