• A Multi Factor Approach of Spot Price Forecasting via Deep Learning 

  Kajamohan, K; Vathsala, T; Jananie, J; Vidanage, BVKI (2024)

  The potential cost savings and the high scalability behind the spot instances benefit the cloud customers compared to On-demand instances fit for workloads that need uninterrupted compute power. However, the termination ...

• Leveraging Natural Language Processing (NLP) to Enhance Patient Fedback Analysis and Improve Shared Antenatal Care at University Hospital KDU, Sri Lanka 

  Thihansith, GPTR; Madushanka, MKP; Wanniarachchi, WAAM; Perera, A; Vidanage, BVKI (2024)

  In Sri Lanka, approximately 94% of expectant mothers rely on public-sector health facilities for antenatal care. However, the manual collection of information on pregnant mothers using pen and paper presents significant ...

• IoT Based Assistive Smart Shoe for Disabled individuals using Kansei Engineering 

  Uththara, PVD; Pathirana, EPKH; Yasaruwan, APGBY; Vinnath, WLV; Kalansooriya, LP (2024-09)

  The challenges facing visually impaired and disabled people in accessing transportation underscore the urgent need for advanced technology solutions. To address this problem, this study proposes a specialized Smart IoT ...

• Decoding Brain Wave Patterns for Speech Recognition in Individuals with Speaking Disabilities 

  Kariyawasam, KHPKK; Ranasinghe, RALU (2024-09)

  Decoding and predicting words from brain wave patterns is an area of growing interest, with numerous methodologies and machine learning techniques being developed to achieve this. Although various tools and approaches ...

• A Data-Driven Approach to Heart Stroke Prediction using Machine Learning and Fuzzy Logic 

  Peiris, MDR; Gunasekara, ADAI (2024-09)

  Early detection of heart strokes is crucial for timely medical intervention and improved patient outcomes. This research aims to develop a reliable and accurate heart attack prediction model using machine learning ...

• Optimizing Accident Severity Prediction: A Comparative Study of LSTM, CatBoost, and CNN Models with Feature Selection 

  Gathirvelou, Thayani; Mayurathan, Barathy (2024-09)

  Road accidents have recently emerged as a significant threat, ranking as the ninth leading cause of fatalities globally. The high cost of traffic-related deaths and property damage is particularly burdensome in developing ...

• Role of Visual Elements (Color, Typography, and Layout) on User Trust in Online Payment Processes 

  Ekanayake, BMUKS; Wanniarachchi, WAAM (2024-09)

  In the rapidly changing world of digital transactions, trust is the key to seamless online payment experiences. This research dives into the intriguing world of user trust within online payment processes, exploring how ...

• Data Science Driven Solution to Predict Employee Attrition: A Systematic Review 

  Kosgahakumbura, PK; Hettiarachchi, YB; Peiris, DR; Hewage, RP; Hewaarchchi, ST; Madhubhashani, KD; Lakmali, SMM; Gunathilake, HRWP (2024-09)

  Employee attrition refers to leaving employees from the organization due to various reasons. Understanding and predicting employee attrition is crucial for organizations seeking to enhance employee retention and reduce ...

• Optimizing Human-AI Collaboration in Graphic Design: Opportunities, Challenges, and Future Directions 

  Munasinghe, KDRM; Wanniarachchi, WAAM (2024-09)

  This study investigates the integration of artificial intelligence (AI) in graphic design, emphasizing its transformative effects, opportunities, and challenges. AI tools are increasingly used for automating routine ...

• AQUAFINA: Streamlining Collaboration, Meet Management, and Performance Prediction in Swimming 

  Munasinghe, KDRM; Kawya, MVT (2024-09)

  Swimming, is a prominent sport in Sri Lanka with a significant number of school, university, and open- level swimmers participating in competitions. However, the management of these events faces critical challenges, ...

• Early Detection and Identification of Blister Blight Disease in Tea Plantations Using Deep Learning and Real-Time Environmental Data 

  Gunathilaka, KKDSR; Hettige, B (2024-09)

  Tea, one of the world's most widely consumed beverages, faces significant threats from Blister Blight disease, particularly in hot and humid regions. This disease, caused by the fungus Exobasidium vexans, leads to ...

• OptiLens AI: Empowering Patients with Advanced Cataract Diagnosis and Personalized Eye Care 

  Ruwanpathirana, RPKL; Wanniarachchi, WAAM (2024-09)

  Globally, cataracts are among the major causes of blindness. Previously, ophthalmologists used objective lens examination and visual acuity tests, to diagnose cataracts. In general, this method of manual diagnosis ...

• A Comprehensive Review of Automated ICD -10 Categorization Model: Methodologies, Challenges, and Future Directions 

  Chinthika, AHS; Dissanayake, DMKS; Kaumal, WMS; Madhubashitha, WNNA; Sandamali, ERC (2024-09)

  In healthcare systems worldwide, the manual assignment of ICD-10 (International Classification of Diseases, 10th Revision) codes presents significant challenges, including resource constraints, lengthy processing times, ...

• Attribute Selection and Verification for Effective Hockey Player Ranking in the Sri Lankan Context 

  Hettiarachchi, HAYB; Lakmali, SMM; Pradeep, RMM (2024-09)

  Sri Lanka's hockey domain has been hindered by the lack of a standardized dataset and the absence of a well-defined set of attributes for player performance assessment, limiting the application of advanced AI technologies. ...

• Data-Driven optimization strategies for Resource Allocation in Small Businesses 

  Maddumarachchi, NCG; Wijesinghe, PRD; Sandamali, ERC (2024-09)

  Small businesses are critical drivers of economic growth and innovation globally. However, in Sri Lanka, these businesses face significant challenges related to resource management, including inefficient allocation ...

• Enhancing On-Device learning in IoT Systems through Meta-Learning Techniques: A Comprehensive review 

  Dissanayake, GASSA (2024-09)

  The incorporation of meta-learning approaches to on-device learning for IoT systems has emerged as one of the effective ways of developing intelligent and never-stopping devices capable of learning and adapting on their ...

• A Review of Machine Learning Algorithms and Weather Forecasting Integration for Enhancing Flood Prediction in the Nilwala River Basin 

  Sewwandini, HT; Kalansooriya, Pradeep; Vidanagama, DU Vidanagama1 (2024-09)

  In Sri Lanka, the Nilwala River Basin is very vulnerable to severe flooding that often places local lives, property, and livelihoods at risk. The current review evaluates the integration of complex machine learning models ...

• Piloting Data-Driven Real Estate Decisions in Colombo: A Prototype Dashboard for Informed Stakeholder Engagement 

  Ranasinghe, HI; Abeysinghe, DVDS (2024-09)

  The real estate sector in Colombo is challenged by fragmented data repositories and a lack of integrated analytical tools, resulting in inefficiencies and suboptimal decision-making by stakeholders. To address ...

• A Comprehensive Review of Dynamic Pricing Strategies: Optimizing Market Competitiveness and Consumer Satisfaction for Sri Lankan Consumer Brands 

  Diwyanjalee, UDAN; Fonseka, CIM; Ranaweera, DN; Senadeera, GAT; Ilmini, WMKS; Madhubhashani, KD (2024-09)

  Dynamic pricing has been widely successful in enhancing customer satisfaction and maximizing revenue across global markets. This paper aims to delve into creating dynamic pricing models specifically designed for Sri ...

• Using a Study Planner with Predictive Analytics: Exploring the Effects on Academic Performance and Time Management: A Systematic Review 

  Wijesinghe, TD; Abeysinghe, DVDS (2024-09)

  This study examines the impact of a data driven study planner with predictive analytics on students' academic performance and time management to find out the effect of the innovation. The research aims to determine the ...

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