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5th international conference on Smart Computing and Informatics, SCI 2021

5th International Conference on Smart Computing and Informat...

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5th international conference on Smart Computing and Informatics, SCI 2021

ISBN: (纸本)9789811696688

the proceedings contain 58 papers. the special focus in this conference is on Smart Computing and Informatics. the topics include: QCA-Based Error Detection Circuit for Nanocommunication Network;evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine;minimum Simplex Nonlinear Nonnegative Matrix Factorization for Hyperspectral Unmixing;prediction and Analysis of Vitamin D Deficiency Using Machine Learning algorithms;student Performance Prediction Using Classification Models;estimating Driver Attentiveness through Head Pose Using Hybrid Geometric-Based Method;IIWSCOA-Based DCNN: Improved Invasive Weed Sine Cosine Optimization Algorithm for Early Detection of Myocardial Infarction Using Deep Convolution Neural Network;intrusion Detection Using Support Vector Machine and Artificial Neural Network;student’s Academic Performance Prediction Using Ensemble Methods through Educational Data Mining;A Flexible Accession on Brain Tumour Detection and Classification Using VGG16 Model;check Certificate—A Certificate Verification Platform for Students and Organizations;secure Cluster-Based Routing Using Modified Spider Monkey Optimization for Wireless Sensor Networks;ChefAI Text to Instructional Visualization Using Amazon Web Services;Identification of Predominant Genes that Causes Autism Using MLP;Detecting Impersonators in Examination Halls Using AI;telugu Text Classification Using Supervised Machine Learning Algorithm;Application of Hybrid MLP-GWO for Monthly Rainfall Forecasting in Cachar, Assam: A Case Study;Temperature Prediction Using Hybrid MLP-GOA Algorithm in Keonjhar, Odisha: A Case Study;development of Different Word Vectors and Testing Using Text Classification algorithms for Telugu;addressing Longtail Problem using Adaptive Clustering for Music Recommendation System;A Proficient GK-KMA Based Segmentation and Lung Nodule Detection in CT Images Using PTRNN;framework for Diabetic Retinopathy Classification.

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Securing Blockchain Using Propagation Chain Learning 5th

Securing Blockchain Using Propagation Chain Learning

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5th international conference on Blockchain and Trustworthy Systems, BlockSys 2023

作者： Jin, Shifeng Zhai, Yijun Zhong, Yuxuan Cui, Jifu Xu, Lei Sun, Hongxia Lei, Yan School of Big Data and Software Engineering Chongqing University Chongqing400044 China College of Computer Science Chongqing University Chongqing400044 China School of Pre-school Education Chongqing College of International Business and Economics Chongqing401520 China Qingdao Penghai Software Co. Ltd. Qingdao266000 China Haier Smart Home Co. Ltd. Qingdao266000 China Qingdao Haidacheng Purchasing Service Co. Ltd. Qingdao266000 China

ISBN: (纸本)9789819981007

Smart contract vulnerabilities are the most common and severe type of blockchain vulnerability, which may result in very serious economic and property losses. Vulnerability detection and repair are necessary to ensure the security of the blockchain. Currently, the-state-of-art smart contract vulnerability detection methods (e.g. Oyente and Securify) use heuristics based on human-designed algorithms, which have certain shortcomings in different application scenarios. therefore, this paper proposes a smart contract vulnerability detection method, i.e. CuVuD, which uses Propagation Chain Learning to solve the current vulnerability detection problem. this method first parses the source code, then obtains and trims the propagation chain of smart contracts, and finally detects vulnerabilities in smart contracts. To verify the effectiveness of CuVuD, this paper compares the CuVuD method with seven the-state-of-art smart contract vulnerability detection methods on a large-scale smart contract dataset based on the Solidity language. the experimental results show that CuVuD’s effectiveness in detecting smart contract vulnerabilities is significantly higher than seven the-state-of-art smart contract vulnerability detection methods, significantly improving the ability to detect vulnerabilities. © 2024, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smart contract

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5th international conference on Advanced Informatics for Computing Research, ICAICR 2021

5th International Conference on Advanced Informatics for Com...

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5th international conference on Advanced Informatics for Computing Research, ICAICR 2021

ISBN: (纸本)9783031094682

the proceedings contain 23 papers. the special focus in this conference is on Advanced Informatics for Computing Research. the topics include: Efficient Entity Resolution for Bibliographic Data Using MapReduce;securing of Identification System Data Transmission Using Deep Autoencoders and Data Hiding;a Hybrid Filter/Wrapper Machine Learning Model for Classification Cancer Dataset;edge-Assisted IoT Architecture: A Case of Air Pollution Monitoring Frameworks;optimized Analysis Using Feature Selection Techniques for Drug Discovery Detection;crop Identification and Disease Detection by Using Convolutional Neural Networks;an Efficient Novel Approach for Detection of Handwritten Numericals Using Machine Learning Paradigms;multiclass Classification in Machine Learning algorithms for Disease Prediction;CREA-Components Reusability Evaluation and Assessment: An Algorithmic Perspective;capsule Network Based Speech Emotion Recognition for Efficient Capturing of Spatial Features;a Survey and Analysis on the Distraction Patterns of the Students in E-Learning and M-Learning Environments;relationships Among Human Genome Graph Elements Using Clusters Detection;transfer Learning Architecture Approach for Smart Transportation System;preface;a Blockchain-Based Solution for Electronic Medical Records System in Healthcare;analysing Sentiments of People Over Vaccines in Reddit Posts Using Natural Language Processing;segmentation of Tumor Region from Mammogram Images Using Deep Learning Approach;review on IoT Based Real-Time Healthcare Monitoring System;application of IoT in 5G Wireless Communication: A Detailed Review;enhanced Service Point Approach for Microservices Based Applications Using Machine Learning Techniques;Worldwide Vaccination Report for COVID-19 Analysis and Visualization Using Deep Learning.

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Application of Machine Learning algorithms to Path Loss Modeling: A Review 5

Application of Machine Learning Algorithms to Path Loss Mode...

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5th international conference on Information Technology for Education and Development, ITED 2022

作者： Abdulkarim, Abubakar Faruk, Nasir Alozie, Emmanuel Sowande, Olugbenga. A. Olayinka, Imam-Fulani Yusuf Usman, Aliyu D. Adewole, Kayode S. Oloyede, Abdulkarim A. Chiroma, Haruna Garba, Salisu Imoize, Agbotiname Lucky Musa, Abdulwaheed Taura, Lawan S. Ahmadu Bello University Department of Electrical Engineering Nigeria Kampala International University Department of Electrical Telecommunications Computer Engineering Uganda Sule Lamido University Department of Physics Nigeria Directorate of ICT Sule Lamido University Nigeria University of Ilorin Department of Telecommunication Science Nigeria Ahmadu Bello University Department of Electronics and Telecommunication Engineering Nigeria University of Ilorin Department of Computer Science Nigeria College of Computer Science and Engineering University of Hafr Al Batin Saudi Arabia Sule Lamido University Department of Computer Science Nigeria University of Lagos Department of Electrical and Electronics Engineering Nigeria Kwara State University Department of Electrical and Computer Engineering Nigeria

ISBN: (纸本)9781509064229

the demand for high-speed internet services is increasing due to emerging needs such as e-commerce, e-health, education, and other high-technology applications. Wireless communication networks have now become a necessity, especially with the introduction of the 5G networks which have the potential to provide extraordinary data rates with extremely low latency. the deployment and operation of 5G and beyond networks in built-up environments would require a complex and reliable radio propagation model that guides network engineers to achieve effective coverage estimation and appropriate base station placements. the inefficiency, and sometimes inconsistencies of deterministic and empirical path loss models necessitated the need to integrate machine learning models. Recently, different machine learning-based pathloss models have been developed to overcome drawbacks associated with conventional pathloss models due to their significant learning and prediction abilities. this paper aims to review path loss models relative to machine learning-based algorithms with a focus on models developed in the last 21 years (2000 to 2021) to study their network parameters and architectures, designs, and applicability, and proffer further research directions. © 2022 IEEE.

关键词： 5G mobile communication systems

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Interconnected through Robotic System in English Foreign Language Education 5th

Interconnected Through Robotic System in English Foreign Lan...

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5th international conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Muthmainnah, M. de Barros Cardoso, Luís Miguel Oliveira Kaur, Dalwinder Burhamzah, Muftihaturrahmah Aeni, Nur Al Yakin, Ahmad Sharma, Aditi Teacher Training and Education Faculty Indonesian Language Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Portugal Department of Languages and Communication Sciences Polytechnic Institute of Portalegre Portalegre Portugal Manipal Globalnxt University Kuala Lumpur Malaysia English Study Program Universitas Negeri Makassar Makassar Indonesia Teacher Training and Education Faculty Civic Education Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Department of Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International [Deemed University Pune India

ISBN: (纸本)9789819761050

Robots have become increasingly important in a variety of life domains as a result of the rapid advancement of technology. Additionally, robots are employed in education as teaching assistants in science, art, and language courses. this research aims to explore the potential of robotic systems as a multipurpose tool for increasing cultural awareness, language proficiency, and communicative competence in the GenAI era. Language games, conversation simulations, and real-time feedback mechanisms are just a few examples of interactive scenarios enabled by virtual robot systems or tutor robots that enable immersive language experiences that go beyond the limitations of conventional schooling. this research contributes knowledge that explores how AI can be used to personalize language teaching according to the needs and learning styles of each student in higher education. the total population of undergraduate students involved in this research was 350 for the 2023 academic year, with 24 students selected purposefully based on sample characteristics from this group who were exposed to using AI for one semester. the research method used is a mix method with quantitative analysis of the results of surveys and interviews with students who are known to have given positive responses and proposes a comprehensive strategy for using AI robot technology in EFL classrooms, which can significantly improve effective learning outcomes. the survey results also show that if educators have a solid understanding of the relationship between linguistic acquisition and technological advances, they will be better prepared to design engaging, individualized lessons that prepare their students to use the language effectively in real-world contexts. the robot-assisted language learning (RALL) approach used in this study, with the integration of robots in the classroom, has the potential to change the way people learn languages to make it more interesting, fun, and motivating, increase engagement

关键词： Students

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5th international conference on Mechanical Engineering, ICOME 2021

5th International Conference on Mechanical Engineering, ICOM...

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5th international conference on Mechanical Engineering, ICOME 2021

ISBN: (纸本)9789811915802

the proceedings contain 42 papers presendted at a virtual meeting. the special focus in this conference is on Mechanical Engineering. the topics include: Investigation of the Runner Blade Arrangements on a 3-Blade Kaplan Turbine Against Turbine Power;analysis Study of Performance and Reliability Impact in Boiler through Differential Coal Calorific Value (Case Study: Pelabuhan Ratu Coal-Fired Power Plant);Effect of the Oxide Scale on Tube Boiler Remaining Life of a 600 MW Coal Power Plant;Numerical Study of the Generator Lubricant Cooler Air-Side Flow to Increase the Reliability of GTG#1.3 PLTGU Muara Karang;Optimization of Coal Blending with Backpropagation Neural Networks (BPNN) and Genetic algorithms (GA) in Tangential In-Furnace Blending Boilers;exergy Analysis in Gas Turbine Power Plant with Different Offline Compressor Washing Methods;swappable Battery Innovation as a Drone Frame Structure with Purpose to Increasing the Flight Time Duration;Changes the Governor Valve Operation Mode to Improve Efficiency HP Turbine;energy Absorption Analysis on Crash-Module Shape and Configuration of Medium-Speed Train;fuel Cell Power Pack with Integrated Metal Hydride Hydrogen Storage for Powering Electric Forklift;numerical Study Air Preheat Coil as Porous Medium to Analyse Flow Characteristics and Improve Productivity in Muara Karang Unit 4 Steam Power Plant;Numerical Study for the Modified Cooler of SAF Motor at Power Plant;numerical Study of the Effect of Cooling Air on Low-Pressure Air Cooler in a Two-Stage Reciprocating Compressor;numerical Study of Fin Height Effects with the Staggered Arrangement in Annular-finned Tube Heat Exchangers;Performance Assessment of Drying Machine Using CFD.

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Green Communication Systems: Towards Sustainable Networking

Green Communication Systems: Towards Sustainable Networking

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Information Science, Parallel and Distributed Systems (ISPDS), international conference on

作者： Wai Yie Leong Yuan Zhi Leong Wai San Leong Persiaran Perdana BBN Putra Nilai INTI International University Nilai Negeri Sembilan Malaysia Schneider Electric Singapore Kallang Singapore

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

this paper provides a comprehensive examination of Green Communication Systems, focusing on strategies, technologies, and practices aimed at minimizing energy consumption and environmental impact in communication networks. through an exploration of energy-efficient networking, renewable energy integration, optimization techniques, and policy considerations, this paper highlights the importance of sustainability in the telecommunications industry. Case studies and future directions are also discussed to offer insights into practical implementations and emerging trends.

关键词： Industries Wireless communication Renewable energy sources Energy consumption Heuristic algorithms Green products Energy efficiency

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Machine Learning based Slow Learner Prediction in Educational Sector 5

Machine Learning based Slow Learner Prediction in Educationa...

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5th international conference on Trends in Electronics and Informatics, ICOEI 2021

作者： Ela, Nurun Nahar Jahan, Nusrat Computer Science and Engineering Daffodil International Univarsity Dhaka Bangladesh

ISBN: (纸本)9781665415712

the educational sector has been proved to be a major sector where improvement measures are a must to develop the system and the curriculum which changes in every few years. Students state that in order to cope with the changing curriculum every now and then, Education is said to be the backbone of a nation. If the students are falling behind that means the nation is falling behind. therefore, it is necessary to guide student for their betterment which will help us to achieve a strong backbone. Our purpose of the study is to predict the slow learner among the university level learners which is the crucial stage of their study life and the step where they must acquire skills to face the professional life. the proposed study has collected data from the computer science and engineering department students. In order to achieve the better outcome, machine learning algorithms have been applied and finally 98% accuracy has been obtained. © 2021 IEEE.

关键词： Decision trees

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Deep Learning Based Speculative Analysis of Diverse Nature Inspired Optimization algorithms in Agriculture

Deep Learning Based Speculative Analysis of Diverse Nature I...

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international conference on Inventive Research in Computing Applications (ICIRCA)

作者： M. Chandraprabha Rajesh Kumar Dhanaraj School of Computing Science and Engineering Galgotias University Greater Noida U.P. India Galgotias College of Engineering and Technology Greater Noida U.P. India Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) Pune India

the main process involved in Deep learning is the optimization as it helps to select the best from the different available alternatives such as weights and learning rates. Deep Neural Networks (DNNs) have shown a great potential in a variety of fields. However, as neural networks get deeper and datasets become larger, optimizing these networks becomes increasingly challenging. In a deep learning model, there are some functions that are highly responsible for making accurate predictions. they are objective function, activation function, and loss function. Deep learning model training includes learning the parameters to fulfill the objective function. Typically, the goal is to decrease the loss experienced throughout the learning process. To increase the accuracy of the model, an optimisation process is performed repeatedly until it achieves a good level of convergence. In this research study, diverse optimization algorithms ranging from behavioral patterns of animals or birds such as FFO, PSO, HOA, ALO, WOA, LWBA, FOA and CSOA are reviewed and the evaluation has been done based on the following performance metrics like accuracy, precision, f1 score, and recall. Among all these algorithms, WOA outperformed and produced an accuracy of about 99% with less error rate.

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Design of Optimized low-power GPS-Yagi Antenna using Machine Learning techniques 5

Design of Optimized low-power GPS-Yagi Antenna using Machine...

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5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Jessintha, D. Sobirovich, Kenjaev Sanjar Ananth, Christo Kumar, T. Ananth Electronics and Communication Engineering Easwari Engineering College Chennai India Samarkand State University Faculty of International Education Programs Uzbekistan Samarkand State University Department of Natural and Exact Sciences Uzbekistan Computer Science and Engineering IFET College of Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350398267

the time-consuming process of developing analytical models can be accelerated with the help of machine learning, which is a technique for data processing. Using machine learning, antenna designers can quickly and intelligently optimize their physical antenna designs. this is achieved by developing trained models of the designers' designs. Consequently, antenna designers can create more efficient antennas. Due to this, antenna designers can continue developing new designs despite the increasing complexity of antennas. When discussing this specific type of antenna, 'Yagi' is frequently used as an abbreviation for 'Yagi-Uda' the full name of the antenna. the length of the 'driven dipole' may be equal to or shorter than the length of the 'directors.' the ability to rapidly execute a diverse set of optimization algorithms and objectives, made possible by the trained models, makes it easier to conduct rapid comparisons and a diverse set of studies (including stochastic analysis for tolerance studies, etc.). While the device was operating at a frequency of ten gigahertz, the concept of two parasitic directors was conceived, and these parasitic directors were designed and optimized to improve the device's directivity further. this antenna offers numerous advantages, one of which is its simplicity of manufacture. this antenna can be manufactured relatively easily due to its diminutive size and uncomplicated overall layout. the stochastic global search and optimization method known as simulated annealing (SA) is extraordinarily effective. this method is implemented instead of more conventional ones to achieve optimal element spacing. © 2022 IEEE.

关键词： Machine learning

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