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2024 International Conference on information and Communication technology for Development for Africa, ICT4DA 2024

作者： De Silva, D.I. Gallage, I.S. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331527792

This comprehensive review explores the pivotal role of syntax and semantics in rule-based translation, emphasizing their significance in ensuring accurate and contextually appropriate translations across different languages. The study is not focused on any specific source or target language pair but provides a general exploration of rule-based approaches that can be applied to various linguistic combinations. Despite advancements in neural machine translation techniques, rule-based methods remain crucial, particularly in domains where linguistic and cultural nuances are paramount. By synthesizing existing literature and practical insights, the review highlights the universal applicability of syntax-driven and semantics-driven techniques in translation, demonstrating how these methods contribute to high-quality translations across diverse language pairs. The implications extend to future research directions, including the development of hybrid translation approaches and the integration of contextual considerations into rule-based translation models, ultimately facilitating cross-linguistic communication and understanding. © 2024 IEEE.

关键词： Latent semantic analysis

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A Fully Featured and Optimized Object Document Mapper for the Go Programming Language 6

A Fully Featured and Optimized Object Document Mapper for th...

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6th International Conference on Advancements in computing, ICAC 2024

作者： Mohamed, Shifan Perera, Sheronie Perera, Akalanka Laksara, Yasindu Karunasena, Anuradha Siriwardana, Samanthi E.R. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

The Go programming language has seen a rise in popularity because of its straightforward nature and efficient performance. However, it still lacks a dependable and fully featured Object Document Mapper (ODM) for working with document databases like MongoDB. Many existing ODMs either miss critical features or have fallen out of active development, which can lead to messy code and added complexity. To address these issues, this study presents 'Elemental,' a robust and optimized ODM built specifically for Go. Elemental is equipped with a powerful query builder, seamless middleware integration, and advanced data aggregation tools that work across multiple database connections. Test results have shown that Elemental outperforms the official MongoDB driver in both performance and maintainability, making it a suitable choice for Go enterprise applications. The obtained benchmarks and metrics indicate that the Elemental ODM provides shorter execution times, reduces cyclomatic complexity, and has a higher maintainability index. This study concludes that Elemental ODM significantly improves the developer experience and efficiency of software development by providing a well refined set of tools. © 2024 IEEE.

关键词： Middleware

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Vision AI: Enhancing Ophthalmic Care with Advanced Detection Technologies 6

Vision AI: Enhancing Ophthalmic Care with Advanced Detection...

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6th International Conference on Advancements in computing, ICAC 2024

作者： Siriwardana, S.M.K.S. Gunasekara, S.N.W. Piyumantha, W.U. Thilakaratne, S.P. Wijendra, D.R. De Silva, D.I. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

This study presents Vision AI, an advanced diagnostic framework that utilizes hybrid deep learning models for accurate detection of eye diseases, specifically Glaucoma, Macular Hole, Central Serous Retinopathy, and Drusen. Traditional ophthalmic diagnostics often suffer from human error and inefficiencies, emphasizing the need for automated solutions. Vision AI addresses these challenges by integrating multiple model architectures, such as VGG16, ResNet, V-Net, and YOLOv8x, optimizing diagnostic accuracy and generalizability. A carefully curated dataset of retinal images was used, supported by extensive data augmentation and hyperparameter tuning to enhance model robustness. This approach significantly improved detection capabilities, achieving over 95% specificity and sensitivity across diseases. Additionally, Vision AI includes a Large Language Model for providing tailored health recommendations, making the system highly practical for clinical use. The framework is deployed in a scalable microservice-based web application, ensuring modularity, security, and real-time diagnostics, thus improving accessibility for healthcare providers. Vision AI showcases the potential of hybrid deep learning systems to transform ophthalmic care, laying a foundation for AI-assisted, patient-centered healthcare advancements. © 2024 IEEE.

关键词： Deep learning

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SmartRail - Optimized Train Management System for Sri Lanka Railways 9

SmartRail - Optimized Train Management System for Sri Lanka ...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Silva, K. R. Rasanga Dilshan, A.J.Y.J. Herath, Achini M. Senadeera, N.A.J.N. Wijendra, Dinuka R. De Silva, D.I. Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350394474

The SmartRail system is a comprehensive solution designed to address the challenges faced by the Sri Lanka Railway Department. Through its four primary subsystems, namely the Self Ticketing System and Chatbot, Timetable Management and Passenger Demand Forecasting System, Driver Management System and Fleet Management System, SmartRail aims to enhance the efficiency, convenience and security of railway operations. The Self Ticketing System and Chatbot enable passengers to book tickets and obtain real-time information through a user-friendly web application, reducing queues and improving customer satisfaction. The Timetable Management and Passenger Demand Forecasting System optimize train schedules and resource allocation based on predictive modelling, ensuring efficient utilization of resources and enhancing passenger convenience. The Driver Management System focuses on allocating drivers for train journeys while considering health conditions, previous journey information, and driver grades to improve safety and operational efficiency. The Fleet Management System utilizes blockchain technology to facilitate secure data sharing among sub-departments, ensuring data integrity and confidentiality for effective fleet management. By leveraging advanced technologies, SmartRail offers a transformative solution that has the potential to modernize and improve railway operations, resulting in enhanced efficiency, customer satisfaction, income and overall performance of the railway network. © 2024 IEEE.

关键词： Customer satisfaction

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Post-Quantum Single Sign-On Solution

Post-Quantum Single Sign-On Solution

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2024 International Conference on Computer and Applications, ICCA 2024

作者： Hassan, Meeran Nimsara, Ravindu Dharmawardhane, Rashmi Basnagoda, Vishwa Abeywardena, Kavinga Yapa Siriwardana, Deemantha Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350367560

Quantum computers pose a significant threat to widely used public-key cryptosystems, endangering current authentication and authorization systems. This paper presents a post-quantum Single Sign-On (SSO) solution that integrates Post-Quantum Cryptography (PQC) algorithms, specifically ML-DSA and ML-KEM, for authentication and authorization. The proposed system demonstrates a 90% improvement in token generation speed post-migration from traditional cryptosystems and a 331% increase in key-storage speed when storing PQC keys using a novel vector database mechanism. Additionally, an enhanced risk-based authentication model is developed, achieving a 98% accuracy in detecting risky logins, surpassing existing models. These contributions offer a comprehensive, efficient, and secure SSO system resistant to quantum attacks, addressing the limitations of current systems that do not fully integrate PQC algorithms or optimized key storage solutions. © 2024 IEEE.

关键词： Quantum computers

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EduGuard - Mobile Application for Sex Education and Sexual Harassment Reporting for Sri Lanka 6

EduGuard - Mobile Application for Sex Education and Sexual H...

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6th International Conference on Advancements in computing, ICAC 2024

作者： Udapolawatta, Sithmi Perera, Nimesha Perera, Kalya Henarath, Sajith Samarakoon, Uthpala Pandithage, Dinithi Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

The lack of comprehensive sex education for Sri Lankans and inadequate systems for reporting sexual harassment are significant problems in the current society. These issues lead to limited awareness, compromised safety, and poor health outcomes. Many individuals lack access to accurate information and resources, exacerbating the risks associated with sexual health and safety. Addressing these gaps is crucial for fostering a well-informed and secure community. In this research, we introduce Eduguard, a mobile application aimed at improving sex education and sexual harassment reporting in Sri Lanka. This comprehensive approach addresses significant gaps in education and safety, promoting awareness and health through advanced technology. Eduguard features four key components: an age-appropriate sex education platform using face recognition, a sexual harassment reporting system utilizing voice recognition for discreet reporting, a blog and questionnaire platform with Natural Language Processing (NLP) for content filtering, and a sexually transmitted disease detection module employing image processing for early diagnosis. In conclusion, Eduguard represents a pioneering solution that combines education, safety, and health through the use of advanced technology. Its impact is substantial, offering a replicable model for regions facing similar challenges. © 2024 IEEE.

关键词： Face recognition

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Intelligent Fire Detection and Response System with Dynamic Nozzle Control and Evacuation Planning 3

Intelligent Fire Detection and Response System with Dynamic ...

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3rd International Conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Manorathna, A.Y.S. Gayashan, Sachintha W.K. Tharushika, W.A.V. Rathnayaka, R.M.S.T. Weerasinghe, Lokesha De Zoysa, Revoni Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331532420

The intelligent fire detection and response system integrates three key components: Fire Type Identification, Fire Tracking, and Dynamic Nozzle Control. The Fire Identification component uses a multi-sensor setup (temperature, smoke, and gas sensors) and machine learning models to classify fire types into categories A, B, and C. The Fire Tracking component combines realtime video monitoring and temperature sensors to predict and visualize fire spread dynamically. Dynamic Nozzle Control adjusts water pressure and nozzle angles based on fire severity, ensuring precise and efficient suppression. This integrated approach enhances fire management by ensuring accurate detection and targeted suppression. © 2024 IEEE.

关键词： Fires

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Optimizing Connections:Applied Shortest Path Algorithms for MANETs

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 787-807页

作者： Ibrahim Alameri Jitka Komarkova Tawfik Al-Hadhrami Abdulsamad Ebrahim Yahya Atef Gharbi Faculty of Medical Sciences Jabir Ibn Hayyan Medical UniversityAlkufaNajaf54001Iraq Faculty of Economics and Administration University of PardubiceStudentskaPardubice53210Czech Republic Computer Science Department School of Science and TechnologyNottingham Trent UniversityNottinghamNG118NSUK Department of Information Technology College of Computing and Information TechnologyNorthern Border UniversityArar91431Saudi Arabia Department of Information System College of Computing and Information TechnologyNorthern Border UniversityArar91431Saudi Arabia

This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of *** objective was to delve into and refine the application of the Dijkstra’s algorithm in this context,a method conventionally esteemed for its efficiency in static ***,this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm,considering adaptation to the dynamic network conditions that are typical for *** paper has shown through detailed algorithmic analysis that Dijkstra’s algorithm,when adapted for dynamic updates,yields a very workable solution to the problem of real-time routing in *** results indicate that with these changes,Dijkstra’s algorithm performs much better computationally and 30%better in routing optimization than Bellman-Ford when working with configurations of sparse *** theoretical framework adapted,with the adaptation of the Dijkstra’s algorithm for dynamically changing network topologies,is novel in this work and quite different from any traditional *** adaptation should offer more efficient routing and less computational overhead,most apt in the limited resource environment of ***,from these findings,one may derive a conclusion that the proposed version of Dijkstra’s algorithm is the best and most feasible choice of the routing protocol for MANETs given all pertinent key performance and resource consumption indicators and further that the proposed method offers a marked improvement over traditional *** paper,therefore,operationalizes the theoretical model into practical scenarios and also further research with empirical simulations to understand more about its operational effectiveness.

关键词： Dijkstra’s algorithm optimization complexity analysis shortest path first comparative algorithm analysis nondeterministic polynomial(NP)-complete

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A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects

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Computers, Materials & Continua 2024年第8期80卷 2181-2197页

作者： Mofadal Alymani Mohamed Esmail Karar Hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt

Object tracking is one of the major tasks for mobile robots in many real-world ***,artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot *** contrast to previous simulation studies,this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue(RGB)colored objects in a real experimental ***,a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative(PID)schemes to achieve accurate tracking results,considering robot command delay and tolerance *** design of developed controllers implies some motion rules to mimic the knowledge of experienced *** scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot *** PID control failed to handle some tracking scenarios in this *** proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets,while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm,*** promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads.

关键词： Mobile robot autonomous systems fuzzy logic control real-time image processing

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Archimedes Optimization with Deep Learning Based Aerial Image Classification for Cybersecurity Enabled UAV Networks

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Computer Systems Science & Engineering 2023年第11期47卷 2171-2185页

作者： Faris Kateb Mahmoud Ragab Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

The recent adoption of satellite technologies,unmanned aerial vehicles(UAVs)and 5G has encouraged telecom networking to evolve into more stable service to remote areas and render higher ***,security concerns with drones were increasing as drone nodes have been striking targets for cyberattacks because of immensely weak inbuilt and growing poor security *** study presents an Archimedes Optimization with Deep Learning based Aerial Image Classification and Intrusion Detection(AODL-AICID)technique in secure UAV *** presented AODLAICID technique concentrates on two major processes:image classification and intrusion *** aerial image classification,the AODL-AICID technique encompasses MobileNetv2 feature extraction,Archimedes Optimization Algorithm(AOA)based hyperparameter optimizer,and backpropagation neural network(BPNN)based *** addition,the AODLAICID technique employs a stacked bi-directional long short-term memory(SBLSTM)model to accomplish intrusion detection for cybersecurity in UAV *** the final stage,the Nadam optimizer is utilized for parameter tuning of the SBLSTM *** experimental validation of the AODLAICID technique is tested and the obtained values reported the improved performance of the AODL-AICID technique over other models.

关键词： Aerial image classification remote sensing intrusion detection cybersecurity deep learning

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