Browsing by Author "Kalansooriya, Pradeep"
Now showing items 1-9 of 9
-
Analysis on Emotion Classification Methods
Goonewardena, IO; Kalansooriya, Pradeep (2020)Emotional intelligence is the ability to understand changing states of emotion, it is an important aspect of human interaction. With upcoming developments emotion identification is an important aspect in HCI. Ideally ... -
Conceptual Framework for a Blockchain-Based Medication Supply Chain Tracking: Enhancing Trust and Security
Amarasighe, GMT; Kalansooriya, Pradeep (2023-09)The increasing prevalence of counterfeit drugs and the complexities of the drug supply chain have highlighted the need for innovative solutions to enhance traceability, transparency, and patient safety. This concept ... -
The Effectiveness of the Cyber Security Framework of Sri Lanka Navy
Ranaweera, TC (2018) -
Impact on Human Behavior on Effective Cybersecurity Operation in Sri Lanka Navy
Lakmina, DWS (2020) -
Investigating the application of Kansei Engineering principles in Mazda car design: A Review
Caldera, HTS; Amarakoon, AMYN; Divyanjalee, HMG; Tharusha, AGLAD; Serasinghe, SMAU; Kalansooriya, Pradeep (2023-09)The integration of user emotions and preferences into vehicle design is becoming important in the current competitive automobile industry. Kansei Engineering, a theory for quantifying the psychological and emotional ... -
IoT-based Assistive Smart Shoe for Disabled Individuals Using Kansei Engineering
Uththara, PVD; Pathirana, EPKH; Yasaruwan, APGBY; WLV Vinnath, WLV; Kalansooriya, Pradeep (2025-09) -
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 (2024-09) -
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 ...