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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Mendonca, Vanessa Santos, Mikael Munoz, Daniel M. Humberto Llanos, Carlos Federal Institute of Brasilia Department of Computer Science Brazil Mechatronics Graduate Program Department of Mechanical Engineering Brazil Federal Institute of Brasilia Department of Agronomy Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Technological advancements are increasingly evident across various sectors, including automobiles, industry, and healthcare. In precision agriculture, significant progress has been made, with AgroTICs and Smart Agriculture gaining substantial traction in the market. However, a gap remains between cutting-edge technology and family farming, presenting a challenge from both social and applied research perspectives. However, there is still a gap between cutting-edge technology and family farming, which creates a challenge from a social and applied research point of view. In this context, this paper proposes a monitoring model based on Fuzzy Logic and sensor automation applied to estimate the health of a corn crop. The proposed Fuzzy inference system involves calculating an indicator of nutrients as well as the average color and area of corn plants. The nutrient indicator is automatically computed by an ESP32 microcontroller using sensor readings, while the average color and area inputs are manually entered via a mobile application. Additionally, the Fuzzy inference is integrated into the ESP32. The model underwent experimental validation on the health of the plantation, and the results were evaluated in four areas: one was designated for testing, and three were for validation. The model achieved an accuracy of 97.5% in Scenario 3, categorized as 'Very Favorable', and an accuracy of 65% in Scenarios 2 and 4, categorized as 'Unfavorable'. The implications of this research contribute to the advancement of AgroTICs among small producers, with the potential to enhance and automate the monitoring of their harvest production. © 2024 IEEE.

关键词： Agribusiness

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BookChain: A Secure Library Book Storing and Sharing in Academic Institutions using Blockchain Technology

BookChain: A Secure Library Book Storing and Sharing in Acad...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Chinnasamy, P. Elumalai, Anupriya Ayyasamy, Ramesh Kumar Kavya, S.P. Dhanasekaran, S. Kiran, Ajmeera MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India VIT - AP University School of Computer Science and Engineering India Faculty of Information and Communication Technology Kampar Malaysia KPR Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India Deemed to Be University Kalasalingam Academy of Research and Education Department of Information Technology Tamilnadu Srivilliputtur India

ISBN: (纸本)9798350348217

By exploiting wireless operators, contemporary bookcrossing allows people to share books conveniently and hastens the spread of knowledge. Nevertheless, the widespread use of smartphone bookcrossing has been seriously hampered by the lack of tracking, resulting in missing and disappearance of textbooks, additionally, it leads to organizational inefficiency. Hence, we suggest using the emerging blockchain technology to exploit the advantages of its immutability and encrypted smart contract in order to overcome these difficulties. In this research, we propose a BookChain, a blockchain-based intra-campus book-sharing system that is verifiable and effective. BookChain securely records all of the book's interacting entities on blockchain because every consumer could retrace the book's renting activity, hence lowering the risk of a book being misplaced. Additionally, BookChain promotes the use of smart contracts to streamline the distribution of books with very little human interference, maximizing productivity. The experimental findings demonstrate the efficiency and affordability of the suggested system even with a large number of concurrent participants. © 2023 IEEE.

关键词： Smart contract

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Deep Reinforcement Learning-Based Robust Design for an IRS-Assisted MISO-NOMA System

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 424-441页

作者： Waraiet, Abdulhamed Cumanan, Kanapathippillai Ding, Zhiguo Dobre, Octavia A. University of York School of Physics Engineering and Technology YorkYO10 5DD United Kingdom Khalifa University Department of Computer and Communication Engineering Abu Dhabi United Arab Emirates Memorial University Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada

In this paper, we propose a robust design for an intelligent reflecting surface (IRS)-assisted multiple-input single output non-orthogonal multiple access (NOMA) system. By considering channel uncertainties, the original robust design problem is formulated as a sum-rate maximization problem under a set of constraints. In particular, the uncertainties associated with reflected channels through IRS elements and direct channels are taken into account in the design and they are modelled as bounded errors. However, the original robust problem is not jointly convex in terms of beamformers at the base station and phase shifts of IRS elements. Therefore, we reformulate the original robust design as a reinforcement learning problem and develop an algorithm based on the twin-delayed deep deterministic policy gradient agent (also known as TD3). In particular, the proposed algorithm solves the original problem by jointly designing the beamformers and the phase shifts, which is not possible with conventional optimization techniques. Numerical results are provided to validate the effectiveness and evaluate the performance of the proposed robust design. In particular, the results demonstrate the competitive and promising capabilities of the proposed robust algorithm, which achieves significant gains in terms of robustness and system sum-rates over the baseline deep deterministic policy gradient agent. In addition, the algorithm has the ability to deal with fixed and dynamic channels, which gives deep reinforcement learning methods an edge over hand-crafted convex optimization-based algorithms. © 2023 CCBY.

关键词： Heuristic algorithms

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Blockchain Solution For SMEs Cybersecurity Threats In E-Commerce 1

Blockchain Solution For SMEs Cybersecurity Threats In E-Comm...

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1st International Conference on computer science and Emerging Technologies, CSET 2023

作者： Zawaideh, Firas H. Abu-Ulbeh, Waheeb Mjlae, Salameh A. El-Ebiary, Yousef A. Baker Al Moaiad, Yazeed Das, Sunanda Irbid National University Faculty of Science and Informaiton Technology Department of Cyber Security Irbid Jordan Al-Istiqlal University Faculty of Administrative Sciences and Informatics Cybersecurity Department Palestine Palestine Prince Abdullah Bin Ghazi Faculty of Information Technology Cs Department Jordan UniSZA Faculty of Informatics and Computing Malaysia Mediu Faculty of Computer and Information Technology Malaysia School of Computer Science and Engineering Jain University Bangalore India

ISBN: (纸本)9798350341737

The rapid growth of electronic commerce (e-commerce) has revolutionized the way Small and Medium-sized Enterprises (SMEs) conduct business, enabling them to reach global markets and unlock new growth opportunities. However, this digital transformation has also exposed SMEs to an escalating array of cybersecurity threats that could compromise their data, financial integrity, and reputation. Blockchain technology, known for its decentralized and immutable nature, has emerged as a potential solution to enhance the security and resilience of e-commerce operations for SMEs. This research paper aims to investigate the current state of cybersecurity preparedness among SMEs engaged in e-commerce and identify the prevalent threats they face in the digital landscape. To achieve this goal, the study incorporates systematic literature review (SLR) method to examine the best technological solution to address the cybersecurity issues faced by e-commerce organizations in this paper of SMEs operating in e-commerce to gather data on their security practices, incident history, and perceptions of cybersecurity risks. In the context of this research, blockchain technology will be explored as a potential mechanism to enhance the security of e-commerce operations for SMEs. The inherent features of blockchain, such as decentralization, transparency, and immutability, could help protect sensitive data and thwart cyberattacks. By exploring the integration of blockchain into e-commerce systems, the research aims to shed light on the potential benefits and challenges associated with its adoption by SMEs. The research findings will not only shed light on the prevailing cybersecurity practices within SMEs and highlight their vulnerabilities but will also explore how blockchain technology can be leveraged to address these challenges. By understanding these patterns and exploring the feasibility of blockchain integration, the research aims to provide comprehensive recommendations for enhancing cy

关键词： Cybersecurity

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Multiple Knowledge Graphs Semantic Interaction based on Graph Embedding and Matching Processing 9

Multiple Knowledge Graphs Semantic Interaction based on Grap...

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9th IEEE International Conference on Data science in Cyberspace, DSC 2024

作者： Wang, Ling Hao, Haoyu Yan, Xue Wang, Xiwei Zhou, Tie Hua Ryu, Keun Ho Northeast Electric Power University School of Computer Science Jilin China Ton Duc Thang University Faculty of Information Technology Ho Chi Minh City Viet Nam Chungbuk National University College of Electrical and Computer Engineering Cheongju Korea Republic of

ISBN: (纸本)9798350391367

With the rapid development of natural language processing technology, various fields are constructing domain knowledge graphs and trying to integrate multi-domain knowledge graphs to better grasp the information of each domain. Aiming at this trend, we proposed the GE-CSM model, which is a novel model that combines graph embedding and context semantic matching. By combining entity-relationship graph embedding and context semantic matching, the model is able to understand the relationships between entities more accurately and provide more semantic information based on the context. Finally, through experimental validation, the effectiveness of the model in performing multiple knowledge graph integration is demonstrated, and the response time and semantic richness of the downstream Q&A task are improved, proving its potential in enhancing semantic interaction performance. © 2024 IEEE.

关键词： Knowledge graph

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Smart Energy Management System Using IoT for Real-Time Monitoring and Theft Detection

Smart Energy Management System Using IoT for Real-Time Monit...

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Information Technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Rajermani Thinakaran Somasekar Jalari Vikram Neerugatti Ravindra Raman Cholla K Nagendra Rao Faculty of Data Science and Information Technology INTI International University Malaysia Department of Computer Science and Engineering Faculty of Engineering and technology Jain (Deemed-to-be University) Bangalore India Department of Computer Science and Engineering S V College of Engineering Tirupati Andhra Pradesh India

ISBN: (数字)9798331510732

ISBN: (纸本)9798331510749

The internet of things technology has developed almost all the sectors including energy management. In traditional energy management system meters are used to recording the number of units and electricity used but they are unable to provide the real time information or updates or any theft of electricity. By focusing this problem, we have developed a system which is able to overcome all the problems in traditional electric management system. It monitors the energy usage and real time theft detection of electricity as it cost lot of money. In our system we have used a current sensor which continuously checks the electricity flow. The microcontroller measures the actual energy usage as well as expected values. It compares both the values. If a big difference found, then it could mean the theft of electricity. So, the GSM module is used to send the alert to the user hence they can take required action. The Wi-Fi module sends the data over the cloud for data analytics. Also, user can see the real time data from the cloud platform. Hence user can track the energy usage and get timely alerts so that user can be aware of energy consumption or energy theft. The system is developed by setting up hardware parts as well as integration with software. The system can be operated or monitored from remote place, as Wi-Fi module connects the system with the internet. System can detect the unusual activities like theft of electricity by analyzing the data. Using the IoT technology for energy management, it can become cost effective as well as smart solution of energy management to avoid any theft. Hence it can overcome the loss.

关键词： Meters GSM Energy consumption Renewable energy sources Costs Electricity Real-time systems Recording Monitoring Wireless fidelity

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An Intelligent System for Furfural Estimation in the Power Transformers 2nd

An Intelligent System for Furfural Estimation in the Power T...

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2nd International Conference on Renewable Power, ICRP 2023

作者： Nezami, Md. Manzar Hashem, Hythem Equbal, Md. Danish Khan, Mohammad Junaid Ansari, Md. Fahim Mustafa, Elfatih Elmubarak Department of Electronics and Communication Engineering GLA University Mathura281406 India Department of Computer Science Faculty of Science and Arts at Belqarn University of Bisha Sabt-Al-Alaya61985 Saudi Arabia Department of Electrical Engineering Galgotias College of Engineering and Technology Greater Noida India Haryana Nuh India Department of Electrical Engineering Graphic Era University Dehradun India

ISBN: (纸本)9789819967483

Power transformers are supposed to be an expensive and critical component of a power system and so its schedule maintenance is an important aspect near the utilities. The cellulose paper used as the solid insulating material of the transformer deteriorates regularly due to progressive aging. As a result, it produces several degradation by-products of cellulose insulation into the transformer oil. Furfurals are among the major by-product of cellulose and are exploited to estimate the physical state of the transformer’s dielectric and the electrical insulation directly and noninvasively. In the present work, an intelligent system is proposed and developed that predicts the level of furfural in the transformer oil. The system makes predictions using easily quantifiable parameters, enabling utilities to avoid suffering financial losses. The proposed system employs the Adaptive Neuro Fuzzy Inference System (ANFIS) technique with temperature and moisture as the input and 2-Furfuraldehyde (2-FAL) as the output. An optimum arrangement of the developed model to find accurate outputs has been achieved by the suitable selection of number and types of the membership functions of the network. Also, an exhaustive study is made to optimize the training data points to achieve the accurate predictions at minimum iterations. The proposed system is validated with nine test conditions of temperature and moisture, and the output thus obtained is verified through existing life models in the literature. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Power transformers

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A Systematic Review of Federated Learning Mechanism for The Internet of Medical Things

A Systematic Review of Federated Learning Mechanism for The ...

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Computing, sciences and Communications (ICCSC), International Conference on

作者： Aravind P M Asha Jerlin Ganesh Gopal Devarajan Senthil Murugan Nagarajan School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Ghaziabad Uttar Pradesh India Department of Mathematics Faculty of Science Technology Medicine University of Luxembourg Luxembourg

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353655

The rapid evolution of healthcare technology, no-tably the integration of the Internet of Medical Things (loMT), has revolutionized patient care, diagnosis, and treatment method-ologies. However, this progress introduces substantial challenges, primarily concerning the security, privacy, and interoperability of sensitive medical data. Federated Learning, a decentralized ma-chine learning approach, emerges as a possible solution to address these difficulties since it allows for collaborative model training without requiring raw patient data exchange. This systematic review explores and evaluates various FL mechanisms tailored for 10MT applications. The review examines existing literature, encompassing the amalgamation of loT and healthcare, the challenges faced in traditional health care systems, and the role of FL in mitigating these challenges. It highlights applications, privacy-preserving techniques, security measures, advantages, limitations, and potential enhancements in utilizing FL within 10MT environments. The review also presents a structured methodology for evaluating FL paradigms, encompassing performance metrics, privacy/security analysis, advantages/limitations assessment, and comparative analysis. Moreover, the paper pro-poses an innovative framework for federated learning in 10MT, detailing its architecture, modules, algorithms, functionalities, ethical considerations, and expected impact. Through a comprehensive analysis and synthesis of existing literature and proposed strategies, this review aims to provide insights for health care stakeholders in selecting and implementing optimal FL strategies for collaborative medical advancements while upholding stringent data privacy and security standards in 10MT.

关键词： Ethics Data privacy Federated learning Collaboration Medical services Internet of Medical Things Security Medical diagnostic imaging Interoperability Systematic literature review

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Network Management devices in an SDN environment 24

Network Management devices in an SDN environment

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24th International Conference on Control Systems and computer science, CSCS 2023

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Soran Technical College Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

ISBN: (纸本)9798350313390

Network optimization and continued availability depend on a number of capabilities that are part of network management. The Maintenance, operating and also offering a safeguarded interaction network is very complicated. It calls for the network operators to grapple with low-level vendor particular arrangements to execute the high degree network policies which are complicated. A method for monitoring networks with OpenFlow controller is presented in this paper in two separate functions for the same networks. Bandwidth utilization, Meter values, charts and statistics are provided by the method to extend controller monitoring capabilities. The method architecture and implementation will be introduced in order to present the feature set. Additionally, softswitches are used as a switch and Mininet to evaluate a virtualized network. This analysis shows whether Meters or ports value is better for network management. © 2023 IEEE.

关键词： Network management

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A systematic approach for data acquisition for tool modelling and analysis of wear-dependent tool deflections during milling Inconel 718 17

A systematic approach for data acquisition for tool modellin...

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17th CIRP Conference on Intelligent Computation in Manufacturing engineering, CIRP ICME 2023

作者： Potthoff, Nils Neumann, Louisa Wiederkehr, Petra Virtual Machining Computer Science XIV TU Dortmund University Otto-Hahn-Str. 12 Dortmund44227 Germany Faculty of Mechanical Engineering TU Dortmund University Dortmund44227 Germany

Nickel-based superalloys are commonly used for components in the aerospace industry. Due to their favorable mechanical properties, such as high strength and corrosion resistance, these materials are suitable for use under extreme temperature conditions. However, the poor machinability results in high process forces and high tool wear, and, therefore, large tool displacements, so that high manufacturing tolerances are often difficult to achieve. Simulation systems can be used to optimize the process. The data acquisition for the development of the models required is challenging. In the following, a method for in-situ digitization of the tool is presented. Furthermore, the occurring tool deflections during the machining of Inconel718 are analyzed for different wear conditions to serve as basis for the parameterization of simulation models. © 2024 Elsevier B.V.. All rights reserved.

关键词： Corrosion resistance

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