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Proposal of a novel peeling of nano-particle (PNP) process for localized material removal on a hard material surface by controllable magnetic fields 22

Proposal of a novel peeling of nano-particle (PNP) process f...

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22nd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2022

作者： Permpatdechakul, Thitipat Khajornrungruang, Panart Suzuki, Keisuke Kutomi, Shotaro Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Avanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

This article proposes a novel Peeling of Nano-Particle (PNP) process to locally remove material on a hard material surface using controllable magnetic fields. Fe3O4 particles in the size range of 50-100 nm in aqueous solution (pH value 11 adjusted by KOH) were magnetically controlled to adhere and remove from a 4H-SiC surface by two electromagnetic coils, which were sandwiched between the substrate. The particle controlling phenomenon on the surface was experimentally observed and verified by our developed apparatus applying an evanescent field. According to the results, particles could be controlled to approach and remove from the substrate surface with 12mT of magnetic field at the selective area on the substrate surface to realise the proposed PNP process. © European Society for Precision engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Magnetic fields

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A Web-Based Vaccine Distribution system for Covid-19 Using Vaxallot 4th

A Web-Based Vaccine Distribution System for Covid-19 Using V...

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4th EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2023

作者： Valarmathi, B. Srinivasa Gupta, N. Prakash, G. BarathyKolappan, A. Padmavathy, N. Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Database Systems School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Systems Engineer Tata Consultancy Services Tamil Nadu Chennai India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031488900

Vaxallot seeks to implement a system to distribute vaccines across high-risk groups accounting for various parameters and prove to be superior to what conventional systems are capable of today. It is a Python flask-based tool backed by infrastructure and data resources from the Covid India central repository;all it needs is a single channel input and a single parameter of the value produced, and the algorithm will take care of the rest. Since it’s Python-based and has an active integration with google sheets, live value updating could be possible for the real-time output of the distribution. The novelty of the proposed mechanism is the unique priority index, a score that accounts for an array of factors associated with the pandemic and is computed for regions in question here;this makes way for better distribution of vaccines. The application has an exclusive segment centered on handling excess units, if any. Moreover, since the application is developed to suit the needs of dynamic demographics, any region can roll out this application for purposes they desire to serve the masses. Since it isn’t bound by a coronavirus, it can be used by the healthcare industry as they deem fit. © 2024, ICST institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Coronavirus

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Quantum Remote State Preparation Based on Quantum Network Coding

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computers, Materials & Continua 2022年第10期73卷 119-132页

作者： Zhen-Zhen Li Zi-Chen Li Yi-Ru Sun Haseeb Ahmad Gang Xu Xiu-Bo Chen School of Information Engineering Beijing Institute of Graphic CommunicationBeijing102600China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Information Security Center State key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Department of Computer Science National Textile UniversityFaisalabad37610Pakistan School of Information Science and Technology North China University of TechnologyBeijing100144China Advanced Cryptography and System Security Key Laboratory of Sichuan Province China

As an innovative theory and technology,quantum network coding has become the research hotspot in quantum network *** this paper,a quantum remote state preparation scheme based on quantum network coding is *** with the general quantum remote state preparation schemes,our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network,by designing the appropriate encoding and decoding steps for quantum network *** is worth mentioning,from the network model,this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck network—butterfly ***,it can be treated as an efficient quantum network preparation scheme due to the characteristics of network coding,and it also makes the proposed scheme more applicable to the large-scale quantum *** addition,the fact of an arbitrary unknown quantum state remotely prepared means that the senders do not need to know the desired quantum ***,the security of the proposed scheme is ***,this scheme can always achieve the success probability of 1 and 1-max flow of value ***,the communication efficiency of the proposed scheme is ***,the proposed scheme turns out to be practicable,secure and efficient,which helps to effectively enrich the theory of quantum remote state preparation.

关键词： Quantum remote state preparation quantum network coding quantum k-pair network

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Ubi-Care: An Elderly Life Support Healthcare Framework Based on Ubiquitous Personal Online Data Stores

Ubi-Care: An Elderly Life Support Healthcare Framework Based...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Chen, Hong Zhou, Tao Wu, Bo Graduate School of Human Sciences Waseda University Saitama359-1192 Japan Daiichi Institute of Technology Department of Information and Electronics System Engineering Taito Tokyo110-0005 Japan School of Computer Science Tokyo University of Technology Hachioji Tokyo192-0982 Japan

ISBN: (纸本)9781665410205

In recent years, the global aging population has intensified, leading to a sharp increase in social security benefits and caregiving costs. The elderly face greater health risks, and their behaviors often indicate signs of crises and illnesses. The rapid development of IoT technology offers new solutions for detecting abnormal signs, thereby promoting healthy aging, independent living, and social participation for the elderly. However, the diversity of IoT devices has led to the phenomenon of personal data silos. When the elderly leave their usual IoT environment, the issue of continuity in healthcare services becomes more pronounced. To address this issue, this study proposes a decentralized Ubi-Care framework. The framework aims to achieve complete separation of data and applications. It is based on the ActivityPub protocol and integrates various data from wearable devices, smart home sensors, and social networks, storing this data in a ubiquitous personal online data store (UPOD) and assigning different roles based on data type. UPOD applications support bidirectional following, allowing users to access data associated with relevant roles, addressing issues related to data categorization, sharing, privacy, and security. Additionally, this study proposes a method for utilizing complete UPOD data to perform anomaly detection based on the hidden Markov model (HMM). By effectively integrating IoT data into UPOD and enhancing data interoperability. The data-sharing model proposed in this study also facilitates elderly individuals and their family members in sharing relevant data as needed, while ensuring privacy protection. The methods proposed in this study will help prevent accidental injuries and enable early diagnosis of diseases, providing strong technical support for elderly healthcare. © 2024 IEEE.

关键词： Electronic health record

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Research and Innovation in Next Generation Security and Privacy in Industry 5.0 Iot 6

Research and Innovation in Next Generation Security and Priv...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Navale, Geeta S. Madala, Ravikiran Managuli, Manjunath Jayalakshmi, N. Kadiravan, G. Rawat, Ruchira Sinhgad Institute of Technology and Science Department of Computer Engineering Maharashtra Pune India Ph.D Information Technology Network and Data Center Engineer University of Cumberlands DurhamNC United States KLS Gogte Institute of Technology Department of Electronics and Communication Engineering Karnataka Belagavi India PSNA College of Engineering and Technology Master of Computer Applications Tamilnadu Dindigul India KL Deemed to Be University Department of Computer Science and Information Technology Andhra Pradsh India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

The objective of the newest manufacturing paradigm, known as 'Industry 5.0,'is to combine human intelligence with cutting-edge technology like the Internet of Things (IoT), artificial intelligence (AI), and robots to develop production systems that are incredibly effective and adaptable. But as we rely more on these technologies, we face additional privacy and security issues that might affect how dependable and trustworthy these systems are. In this report, we examine the most recent advancements in security and privacy for Industry 5.0 IoT and pinpoint the newest trends, obstacles, and possibilities. We also cover how these changes may affect manufacturing in the future and provide advice to scholars, practitioners, and policymakers. © 2023 IEEE.

关键词： artificial intelligence cyber-physical systems human-machine collaboration Industry 5.0 Internet of Things IoT manufacturing privacy robotics security

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A Framework for Deepfake Detection using Convolutional Neural Network and Deep Features

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Procedia computer Science 2025年 258卷 3640-3648页

作者： Soundarya B C Gururaj H L Naveen Kumar C M Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of Computer Science and Business System Malnad College of Engineering Hassan India

With the advancement of Artificial Intelligence, facial recognition has become a crucial biometric feature. Deepfake technology leverages AI and can create hyper-realistic digitally manipulated videos of people appearing to say or do things that never occurred. The emergence of Generative Adversarial Networks (GANs) has further enabled the creation of fake visual content with astonishing realism. This technology has diverse applications, such as in the film industry, where it allows for video recreation without reshooting, creating awareness videos, restoring the voices of those who have lost them, and updating movie scenes at low cost. However, this rapid advancement also presents significant challenges. The proliferation of synthetic images raises severe concerns about their societal impact, particularly in terms of potential misuse for harassment and blackmail. Therefore, developing robust deepfake detection models is imperative. This study evaluates the performance of a proposed ResNet34 model in deepfake detection. We utilize the FaceForensics++ dataset to train and assess the model, incorporating images generated by four popular deepfake techniques. Our experimental results demonstrate that integrating linear ternary patterns (LTP) and edge detection-based features with the modified ResNet34 model achieves superior performance, attaining 97.5% accuracy and surpassing other approaches.

关键词： Deepfake Artificial intelligence Deep learning

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Planning Software Release and Testing Stop Time under Budgetary and Reliability Constraints 18

Planning Software Release and Testing Stop Time under Budget...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Singh, Veenu Kumar, Vijay Singh, V.B. Amity University Amity Institute of Information Technology Uttar Pradesh Noida India Amity University Aias Department of Applied Mathematics Uttar Pradesh Noida India Jawaharlal Nehru University School of Computer and System Sciences New Delhi India

ISBN: (纸本)9789380544519

To thrive in the competitive market, organizations are opting to release their products early, followed by an ongoing testing process to eliminate any remaining bugs through the delivery of patches. Software patches refer to small programs introduced to the users to rectify faults, introduce new features, or enhance existing functionality. After going through the literature, it is observed that researchers have worked on testing-effort based SRGM, but none have addressed the aspect of reliability and cost in the context of determining the optimal time for software release and optimal time to stop software testing while patching is considered. To bridge this gap, we have introduced a testing effort based SRGM implementing patching, with the objective of making the software cost-effective and reliable. The numerical illustration has been done using Statistical Package for Social Sciences. and Genetic Algorithm (GA). © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Generalized Modified Weibull (GMW) Genetic Algorithm (GA) Reliability Software Reliability Growth Model (SRGM) Statistical Package for Social Sciences (SPSS) Testing Cost

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Output Linearization of Single-Input Single-Output Fuzzy system to Improve Accuracy and Performance

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computers, Materials & Continua 2023年第5期75卷 2413-2427页

作者： Salah-ud-din Khokhar QinKe Peng Muhammad Yasir Noor Department of Automation Science and Technology(System Engineering Institute) School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anShaanxi710049China Department of Computer Science G.C.UniversityLahore54000PunjabPakistan Department of Physics(Electronics) G.C.UniversityLahore54000PunjabPakistan

For fuzzy systems to be implemented effectively,the fuzzy membership function(MF)is essential.A fuzzy system(FS)that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output(SISO)FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s *** a variety of non-linear techniques,a SISO FS is *** results of FS experiments conducted in comparable conditions are then *** simulated results and the results of the experimental setup agree fairly *** findings of the suggested model demonstrate that the relative error is abated to a sufficient range(≤±10%)and that the mean absolute percentage error(MPAE)is reduced by around 66.2%.The proposed strategy to reduceMAPE using an FS improves the system’s performance and control *** using the best input and output MFs protocol,the energy and financial efficiency of every SISO FS can be improved with very little tuning of *** proposed fuzzy system performed far better than other modern days approaches available in the literature.

关键词： Mean absolute percentage error membership functions relative error fuzzy system

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Automated AI Research on Cyber Attack Prediction and Security Design 6

Automated AI Research on Cyber Attack Prediction and Securit...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Madala, Ravikiran Vijayakumar, N. Nandini, N. Verma, Shanti Chandvekar, Samidha Devendra Singh, Devesh Pratap Network and Data Center Engineer Ph.D Information Technology University of Cumberlands DurhamNC United States Karpagam College of Engineering Department of Computer Science and Technology Coimbatore India Dr. Ambedkar Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru India L J University Department of Computer Application Gujarat Ahmedabad India Department of Information Technology Maharashtra New Panvel India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

A fast expanding topic of study on automated AI is focused on the prediction and prevention of cyber-attacks using machine learning algorithms. In this study, we examined the research on applying machine learning algorithms to the problems of strategic cyber defense and attack forecasting. We also provided a technique for assessing and choosing the best machine learning models for anticipating cyber-attacks. Our findings show that machine learning methods, especially random forest and neural network models, are very accurate in predicting cyber-attacks. Additionally, we discovered a number of crucial characteristics, such as source IP, packet size, and malicious traffic that are strongly associated with the likelihood of cyber-attacks. Our results imply that automated AI research on cyber-attack prediction and security planning has tremendous promise for enhancing cyber-security and averting cyber-attacks. © 2023 IEEE.

关键词： automated AI research cyber-attack prediction feature correlation machine learning neural network random forest security design

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Bat Algorithm: A Review on Theory, Modifications and Applications 3

Bat Algorithm: A Review on Theory, Modifications and Applica...

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3rd International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2023

作者： Singh, Hakam Witarsyah, Deden Misra, Alok Tiwari, Raj Gaurang Chitkara University School of Engineering and Technology Department of Computer Science and Engineering Himachal Paradesh Baddi India Telkom University School of Industrial and System Engineering Information System Departement Bandung Indonesia Lovely Professional University School of Computer Application Punjab Phagwara India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350394559

Due to its many applications in a variety of domains, including clustering, cloud computing, and power systems, metaheuristic algorithms have attracted a lot of interest from the scholarly community. By using their self-explorative and adaptive processes, these algorithms provide certain benefits over conventional methods. One well-known metaheuristic approach is effective in resolving optimization problems with constraints and without constraints. This technique was inspired by nature, notably the echolocation ability of bat species. The Bat Algorithm (BA) makes use of a powerful search mechanism to provide the best results when compared to other algorithms of the same class. The theoretical underpinnings of the BA are explored in depth in this research, along with several changes and advancements that have improved its functionality. These enhancements include adjustments to search tactics as well as other developments. The report also thoroughly examines how the BA may be used across a variety of fields, demonstrating its competence and adaptability. The BA has been effectively used in several real-world applications, from cloud computing to clustering, and each one is carefully investigated. The study also offers a thoughtful examination of the BA's possible advancements and future possibilities. It also entails investigating novel modifications and tactics that might improve its effectiveness in handling challenging optimization issues. This study seeks to direct practitioners and academics toward more effective and efficient metaheuristic algorithms, thereby stimulating improvements in optimization approaches. It does this by summarising the present state of the BA and imagining its future development. © 2023 IEEE.

关键词： Cloud computing

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