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3rd International Informatics and software engineering Conference, IISEC 2022

作者： Wijendra, D. De Silva, D.I. Gunawardhena, N.M. Wijayarathna, S.M. Aluthwaththage, J.H. Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Garbage disposal and collection is an ongoing global crisis amplified by the increasing world population, lack of funds and public awareness, and recently because of the Covid-19 pandemic. information Technology can be utilized as a solution for the existing garbage collection methods that are old-fashioned, time-consuming, and energy-consuming due to the lack of a unified and consistent system that incorporates all the parties involved in garbage production and collection. A mobile-based garbage collection system is proposed to overcome the issues aforementioned through route and schedule optimization, AI chatbot, and optimized GPS tracking. The route and schedule optimization is achieved through vehicle routing problem with time windows(VRPTW) with synchronization and precedence that was optimized using LNS;the total travel cost went from 172 minutes to 144 minutes. The AI chatbot feature facilitates reporting garbage collection issues and complaints and enquiring about waste management tips (reduce, recycle, and reuse tips) to be used at home. The most prominent role of developing this AI chatbot is replacing the manual process of reporting garbage collection issues in Sri Lanka with an efficient and interactive way. The chatbot has waste management tips Q and A. In Optimized GPS Tracking, the user can use the map to find the nearest garbage disposal place based on the type of rubbish they generate. The truck driver can find the optimal path to the closest current garbage disposal centres and public trash bins and view the location of Homeowners on the map. The optimized path between two points is displayed based on distance, time, and fuel consumption. The main goal of the component is to show the location of garbage disposal bins and the optimal paths for truck drivers using Linear regression and the Node2vec algorithm. © 2022 IEEE.

关键词： Machine learning

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An energy-aware routing scheme based on a virtual relay tunnel in flying ad hoc networks

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Alexandria engineering Journal 2024年 91卷 249-260页

作者： Hosseinzadeh, Mehdi Ali, Saqib Mohammed, Adil Hussein Lansky, Jan Mildeova, Stanislava Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Hassan Ahmed, Omed Rahmani, Amir Masoud Mehmood, Asif Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Computer Science and Mathematics Faculty of Economic Studies University of Finance and Administration Prague Czech Republic Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Biomedical Engineering Gachon University Gyeonggi-do Seongnam-si13120 Korea Republic of

Flying ad hoc networks (FANETs) tackle diverse challenges, for example, dynamic topological structure, high mobility of nodes, low density, and energy restrictions. These challenges make problems in designing reliable and stable routing in FANETs. Hence, the design of a routing algorithm is essential for transferring data between drones. In this paper, an energy-aware routing scheme based on a virtual relay tunnel (EARVRT) is proposed in flying ad hoc networks. EARVRT includes a virtual relay tunnel (VRT) that manages relay nodes in the route discovery process and lowers network overhead. Moreover, three metrics, namely route energy, hop counts, and a new metric called path correlation are regarded in the path selection operation. Note that correlation is defined with regard to two scales, including the cosine similarity of two nodes and their distance. EARVRT is evaluated according to delay, network longevity, consumed energy, and packet delivery rate. Then, our scheme is compared with three methods, namely LoCaL, O-LAR, and PSO-GLFR. These results show the superiority and success of EARVRT in comparison with other algorithms. © 2024 The Author(s)

关键词： Drones

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Parkinson’s Detection Using RNN-Graph-LSTM with Optimization Based on Speech Signals

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computers, Materials & Continua 2022年第7期72卷 871-886页

作者： Ahmed S.Almasoud Taiseer Abdalla Elfadil Eisa Fahd N.Al-Wesabi Abubakar Elsafi Mesfer Al Duhayyim Ishfaq Yaseen Manar Ahmed Hamza Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityMahayil62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Science and Artsat MahayilKing Khalid UniversityMahayil62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityMahayil62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj62529Saudi Arabia

Early detection of Parkinson’s Disease(PD)using the PD patients’voice changes would avoid the intervention before the identification of physical *** machine learning algorithms were developed to detect PD ***,these ML methods are lack in generalization and reduced classification performance due to subject *** overcome these issues,this proposed work apply graph long short term memory(GLSTM)model to classify the dynamic features of the PD patient speech *** proposed classification model has been further improved by implementing the recurrent neural network(RNN)in batch normalization layer of GLSTM and optimized with adaptive moment estimation(ADAM)on network hidden *** consider the importance of feature engineering,this proposed system use Linear Discriminant analysis(LDA)for dimensionality reduction and SparseAuto-Encoder(SAE)for extracting the dynamic speech *** on the computation of energy content transited from unvoiced to voice(onset)and voice to voiceless(offset),dynamic features are *** PD datasets is evaluated under 10 fold cross validation without sample *** proposed smart PD detection method called RNN-GLSTM-ADAM is numerically experimented with persistent phonations in terms of accuracy,sensitivity,and specificity andMatthew correlation *** evaluated result of RNN-GLSTM-ADAM extremely improves the PD detection accuracy than static feature based conventional ML and DL approaches.

关键词： Dimensionality reduction LDA feature extraction auto encoder classification recurrent neural network LSTM and optimization

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Advanced Security Approach for Building Secure Containerized Manufacturing Digital Twins

Advanced Security Approach for Building Secure Containerized...

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2024 IET International Conference on engineering Technologies and Applications, ICETA 2024

作者： Lin, Yu-Chuan Chiu, Po-Kai Suryajaya, Benny Department of Computer Science and Information Engineering Chinese Culture University Taipei Taiwan Institute of Manufacturing Information and Systems National Cheng Kung University Tainan Taiwan Intelligent Manufacturing Research Center National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9781837242672

In the era of digital transformation, containerized systems and digital twins are vital technologies in intelligent manufacturing. Our previous research, the Implementation Framework of Digital Twins for Intelligent Manufacturing (IF-DTiM), lacks comprehensive security features[1]. To address this critical gap, we propose the Advanced Security Approach for Building Secure Containerized Manufacturing Digital Twins (ASABS-CMDT), integrating automated tools for detecting vulnerabilities, container image creation, and secure digital signing, all within DevSecOps practices. Case studies show that ASABS-CMDT significantly enhances system security and reduces development time, offering valuable insights for practitioners in intelligent manufacturing. © The Institution of engineering & Technology 2024.

关键词： Smart manufacturing

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ELIZA: Smart Monitoring and Reporting Toast Master System 4

ELIZA: Smart Monitoring and Reporting Toast Master System

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Nizer, F.S.A. Iksudha Bhargavi, R. Agalyah, P. Raveendran, M. Kuruppu, Anuththara Rupasinghe, Shalini Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

Public speaking is the most common form of fear, and everyone feels uneasy with it. Fear of speaking in public is commonly called "glossophobia, " where people are discouraged from speaking in front of people due to embarrassment and rejection. Public speaking anxiety (PSA) is one of the most universal subtypes of anxiety where people fear, lose their confidence, and become uncomfortable physically and mentally. But public speaking is considered important in the educational sector and workplaces, where people get higher opportunities. Therefore, clubs like Toastmasters help people overcome their fear of public speaking and improve their confidence. We are launching the idea of a Smart Monitoring and Reporting Toastmasters System for people to improve their public speaking so they do not need a supervisor or mentor to train them. This smart monitoring system recognizes the candidate through image processing and deep learning. Moreover, this will analyze some features from the candidates' speeches, such as facial emotion recognition, speech recognition, hand and body gesture recognition, and the candidates' attire and appearance separately. This system will identify their mistakes and flaws and provide overall feedback to the users on the speech provided by the candidate. By implementing this web application, users can train themselves without a supervisor, and they can improve themselves and gain the confidence to participate in a Toastmasters competition as perfect candidates. © 2022 IEEE.

关键词： Speech recognition

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Adaptivo: A Personalized Adaptive E-Learning System based on Learning Styles and Prior Knowledge 7

Adaptivo: A Personalized Adaptive E-Learning System based on...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Rishard, M.A.M. Jayasekara, S.L. Ekanayake, E.M.P.U. Wickramathilake, K.M.J.S. Reyal, Shyam Manathunga, Kalpani Wickramarathne, Jagath Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350345711

The rapid advancement of technology and the internet has resulted in an increase in the number of learners seeking e-learning. Though E-Learning is widely used most e-learning systems provide the same set of learning resources and learning paths to each student, regardless of their personal preferences. In recent years there has been increasing attention towards the characteristics of learners such as the learning styles and the knowledge level of the learner. This research paper proposes a personalized adaptive E-learning system called 'Adaptivo' that provides a personalized learning experience to the learners based on their learning style and knowledge level. To make the learning process more efficient and engaging, Adaptivo takes into account the specific differences between learners in terms of time, online interactions and learning duration. It then builds a personalized learning path depending on each learner's learning style and knowledge level. The main aim of this study is to investigate the impact of the proposed adaptive learning approach on learners. The results show that the students appreciate the approach, are highly satisfied, and performed better when content is personalized according to their learning style and prior knowledge. © 2022 IEEE.

关键词： E-learning

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Comparative Analysis of Movie Recommendation systems Using Filtering Techniques on IMDB and Rotten Tomatoes 15

Comparative Analysis of Movie Recommendation Systems Using F...

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15th International Conference on information, Intelligence, systems and Applications, IISA 2024

作者： Majhi, Santosh Kumar Sahani, Preetipadma Pradhan, Rosy Acharya, Biswaranjan Grivokostopoulou, Foteini Kanavos, Andreas Gerogiannis, Vassilis C. Department of Computer Science and Information Technology Bilaspur India Veer Surendra Sai University of Technology Department of Computer Science and Engineering Odisha Burla India Veer Surendra Sai University of Technology Department of Electrical Engineering Odisha Burla India Marwadi University Department of Computer Engineering Ai Rajkot India Computer Technology Institute and Press 'Diophantus' Patras Greece Ionian University Department of Informatics Corfu Greece University of Thessaly Department of Digital Systems Larissa Greece

ISBN: (纸本)9798350368833

Recommendation systems are pivotal in industries like entertainment, where competitiveness is intense. This study enhances movie recommendations by utilizing rich datasets from IMDB and Rotten Tomatoes, incorporating movie ratings, user profiles, audience scores, and critics' reviews. These elements were subjected to sentiment analysis to refine the data quality. We explored three filtering techniques: content-based, which analyzes movie features;collaborative, which processes user behavior patterns;and hybrid, combining both to leverage their strengths. The effectiveness of these methods was assessed using Mean Average Precision at k (MAP-k) and Root Mean Square Error (RMSE), with our results showing notable improvements in recommendation accuracy. For instance, the hybrid method achieved a MAP ©k of 0.271 and an RMSE of 0.634, indicating enhanced precision and reliability of the recommendations. These findings suggest significant potential for improving user satisfaction and retention in digital platforms, demonstrating the benefit of integrating diverse data sources and analytical techniques in recommendation systems.

关键词： Collaborative filtering

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Elegant Fit-On - Virtual Fitting Room on Handheld Devices 4

Elegant Fit-On - Virtual Fitting Room on Handheld Devices

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Galagoda, R.R.N.P.A.B.W.M.S.R. Gunarathne, E.H.N.L. Maheshi Purnima, K.A.D. Wickramarathna, H.P.C.S. Reyal, Shyam Siriwardana, Samanthi Department of Computer Science & Software Engineering Sri Lanka Institute of Information Technology Colombo Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Colombo Sri Lanka

ISBN: (纸本)9798350398090

Clothing has been one of the basic human needs since ancient times. It is a common thing to try on clothes and consider certain features when buying clothes. With the current pandemic situation, it is risky to wear and buy clothes by physical shopping. Consequently, people do online shopping. Those existing shopping websites are not user-friendly and less reliable as the customers will not have the privilege to purchase the exactly fitting outfit. Therefore, the customer satisfaction level is low with the clothes they have bought through online platforms. Therefore, the aim is to utilize technology to provide a virtual fitting room experience on handheld devices. The objective is to create a customized 3D avatar that represents the customer's unique body shapes and features, which allows to try on clothes. This avatar is 360 degrees rotatable with pre-defined poses to check what the fit-on looks like. This solution shows whether the clothes are too fit or loose for the customer by showing live wrinkles. The text and voice feedback are generated at the end, which would be helpful for differently-abled people, especially those with vision issues. © 2022 IEEE.

关键词： Three dimensional computer graphics

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COVID-Tracker: Surveillance of Potential Clusters Using a Wristband and Location-based Data 7

COVID-Tracker: Surveillance of Potential Clusters Using a Wr...

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7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Mandara, A.P. Manjari Randula, H.K. Kisal Priyadarshana, H.L.Y. Uyanahewa, J.J. Manathunga, Kalpani Reyal, Shyam Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9781665421683

COVID-19 is a global pandemic that has threatened the survival of humans and other living beings. COVID-19 causes illnesses varying from the very mild cold to serious health complications resulting in death. Most information Technology based solutions have been implemented to prevent the COVID-19 pandemic while raising awareness in the public. However, there is a limited number of reliable and real-time applications of self-awareness on COVID-19. Currently, the globe is dealing with the COVID-19 epidemic, particularly in pursuit of economic growth in each country. Therefore, an accurate, efficient automatic method to raise self-awareness by avoiding risky contacts is useful for human survival. This paper describes the automatic detection of temperature using a wearable device and an automatic alerting mechanism to inform the users of potentially risky contacts with higher temperatures nearby within a considerable time frame. COVID-Tracker produces results with high accuracy and efficiency, this is beneficial to improve self-awareness among users, to visualize potential covid clusters, and also to improve the mental health of self-isolated people. The developed application consists of four main components namely: temperature measuring band, mobile application, prediction model-based visualization dashboard and an AI bot. Based on the results reported here, developed methods can help people to achieve self-awareness of COVID-19 by avoiding risk factors early and accurately. © 2022 IEEE.

关键词： COVID-19

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Realty Scout - Smart System for Real Estate Analysis & Forecasting with Interactive User Interface 7

Realty Scout - Smart System for Real Estate Analysis & Forec...

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7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Hapuarachchi, H.A.V.P.U. Manoratne, M.D. Gamlath, K.G.B.K. Vithane, S.G.G. Sriyaratna, Disni Supunya, N. H. P. Ravi Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9781665421683

The real estate industry is one of the highest income generating sources in the country. As the country moves toward a highly diversified economy, the role of real estate has become a more important part of the country's economy. However, the state of the local real estate industry is yet to improve and is currently lagging the technology curve. As a result of this issue, useful information is not made available to the end-users. Therefore, the real estate industry needs to improve its adoption of ongoing technologies to move from traditional to smart real estate industry. Therefore, we developed a Smart Real estate system called "Realty Scout"which can analyze and forecast real estate information accurately. The "Realty Scout"is implemented with a highly interactive view of the properties with a given virtual tour for the users to enhance the user experience. This smart real estate system also collects data on property values, in addition to a trained data set, to forecast future property values. Certain machine learning algorithms are used in the backend to generate future values. An accurate and fast prediction of the real estate value is important to buyers, sellers, and other stakeholders. Furthermore, by gathering users' personal information and tracking their search history through the system, the system recommends properties to users based on collected data. As potential users of the system, they can gain an advantage from this feature by finding their desired property without spending more time. In addition, this system aimed to give advanced property filtrations options to the user. Building up a smart system for the real estate industry would be an advantage for all stakeholders who are actively engaged with the real estate industry. © 2022 IEEE.

关键词： Forecasting

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