• Classification of Vegetable Plant Pests using Deep Transfer Learning 

  Vijayakanthan, G.; Kokul, T.; Pakeerathan, S.; Pinidiyaarachchi, U.A.J. (IEEE, 2025)

  Sri Lankan farmers face several issues and among them crop loss due to insect pest infestation is the major hurdle. Several approaches have been proposed to detect the pest class by using computer vision and machine learning ...
• COMPARISON OF THE PREDICTIVE PERFORMANCE OF LIU-BASED ESTIMATORS. PGIS Research Congress 2023, PGIS, University of Peradeniya, Sri Lanka 

  Kayathiri, T.; Kayanan, M.; Wijekoon, P. (PGIS, University of Peradeniya, 2023)

  Logistic regression is one of the most widely used statistical methods for predicting a binary outcome by analysing the relationship between one or more existing independent variables. Although the maximum likelihood ...
• Enhancing Predictive Performance of the Logistic Two-Parameter Estimator under Multicollinearity 

  Kayathiri, T.; Kayanan, M.; Wijekoon, P. (Institute of Applied Statistics, Sri Lanka, 2024)

  This study aimed to propose a new estimator named Modified Logistic Two-Parameter Estimator (MLTPE) with the best predictive performance in logistic regression when multicollinearity exists. The performance of the proposed ...
• Improved LARS Algorithm for Adaptive LASSO in the Linear Regression Model 

  Kayanan, M.; Wijekoon, P. (Asia Pacific Publishers, 2024)

  The adaptive LASSO method has been employed for reliable variable selection as an alternative to LASSO in linear regression models. This paper introduces an adjusted LARS algorithm that integrates adaptive ...
• Weigh-in-motion using machine learning and telematics 

  Kirushanth, S.; Kabaso, B. (IEEE, 2018)

  Driving overloaded vehicle causes road infrastructural damages, accidents, air pollution by excessive fuel consumption, and unusual expenses. Measuring the gross weight of a vehicle on a particular road segment without ...
• Stochastic Restricted Modified Mixed Logistic Estimator 

  Kayathiri, T.; Kayanan, M.; Wijekoon, P. (Austrian Statistical Society, 2025)

  In this study, we introduce a new estimator named the Stochastic Restricted Modified Mixed Logistic Estimator (SRMMLE), which is specifically designed to handle multicollinearity within the framework of stochastic linear ...
• PERFORMANCE OF MODIFIED LOGISTIC REGRESSION ALGORITHM IN CLASSIFICATION 

  Tharsika, I.; Kayanan, M.; Yogarajah, B. (Eastern University, Sri Lanka, 2025)

  Logistic regression, a fundamental tool in binary classification tasks, faces challenges in real-world datasets where the assumption of predictor variable independence is often violated, leading to multicollinearity issues. ...
• SAMS: An IoT Solution for Attendance Management in Universities 

  Gopinath, S.; Nagulan, R. (IEEE, 2019-10-17)

  An autonomous and effective platform for students' attendance management is presented in this paper by using most of the advanced technologies of the IoT (Internet of Things), such as mobility, wireless network, fingerprint ...
• Generalized Stochastic Restricted LARS Algorithm 

  Kayanan, M.; Wijekoon, P. (Faculty of Science, University of Ruhuna, Sri Lanka, 2022-06-30)

  The Least Absolute Shrinkage and Selection Operator (LASSO) is used to tackle both the multicollinearity issue and the variable selection concurrently in the linear regression model. The Least Angle Regression (LARS) ...
• Enhanced Symmetric Cryptography for IoT using Novel Random Secret Key Approach 

  Gopinath, S.; Nagulan, R. (IEEE, 2020-12-10)

  The deployment of IoT devices in different domains enables technical innovations and value-added services to users but also creates multiple requirements in terms of effective communication and security. IoT devices are ...
• Some behavior of coarse structure and coarse equivalent 

  Kajan, N.; Kannan, K. (Union of researchers of Macedonia, 2022-09-05)

  I am going to introduce some properties of coarse structure. Coarse space is defined for large scale in metric space similar to the tools provided by topology for analyzing behavior at small distance, as topological property ...
• Some Results on Fuzzy metric space and some examples of fuzzy b-metric space 

  Kajan, N.; Kannan, K. (Union of researchers of Macedonia, 2020-08-24)

  The problem of constructing a satisfactory theory of fuzzy metric spaces has been investigated by several researchers from different point of view. The concept of fuzzy sets was introduced by Zadeh. Following fuzzy metric ...
• Phase Space Error Control with Variable Time-Stepping Algorithms applied to the Forward Euler method for Dynamical Systems 

  Thilaganathan, S.; Vigneswaran, R. (University of Jaffna, 2016-08-12)

  We consider a phase space stability error control for numerical simulation of dynamical systems. Tony Humphries and Vigneswaran, R., in “Phase space stability error control with variable time-stepping Runge-Kutta methods ...
• Phase space theta error control with general explicit Runge-Kutta methods for dynamical systems 

  Thilaganathan, S.; Vigneswaran, R.; Samarathunga, D.M. (PGIS, 2019-10-11)

  Variable time-stepping algorithms are often used to solve the dynamical systems, defined by autonomous initial value ordinary differential equations =f, y(0)=y0 m, where f : is a Lipschitz continuous function. Standard ...
• Phase space error control with variable time-stepping algorithms applied to the forward Euler method for autonomous dynamical systems 

  Vigneswaran, R.; Thilaganathan, S. (Advances in mathematical sciences, knowvel, 2019-03-31)

  We consider a phase space stability error control for numerical simulation of dynamical systems. Standard adaptive algorithm used to solve the linear systems perform well during the finite time of integration with fixed ...
• A Combined Error Control with Forward Euler Method for Dynamical Systems 

  Vigneswaran, R.; Thilaganathan, S. (World Academy of Science, Engineering and Technology, 2016-05-12)

  Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error ...
• Weigh-in-motion Using Machine Learning and Telematics 

  Kirushanth, S.; Kabaso, B. (IEEE, 2018-07-24)

  Driving overloaded vehicle causes road infrastructural damages, accidents, air pollution by excessive fuel consumption, and unusual expenses. Measuring the gross weight of a vehicle on a particular road segment without ...
• Extracting knowledge from Noise Information 

  Chowuraya, T.; Kirushanth, S.; Kabaso, B. (Academic Conference International (ACI), 2018-11-12)

  Information is an important part of creating knowledge. We live at a time when so much information is created. Unfortunately, much of the information is redundant. There is huge amount of online information in the form of ...
• Infoshare: A Digital Governance Community platform for Knowledge Sharing 

  Xolani, V.; Kirushanth, S.; Boniface, K. (Academic Conference International (ACI), 2018-11-12)

  With the easy availability of mobile devices and affordable bandwidth, there has been a proliferation of sharing of perceived expert information, with unreliable source, which have often not been tested in a specialized ...
• Telematics and Road Safety 

  Kirushanth, S.; Kabaso, B. (IEEE, 2018-07-24)

  Road Safety is a major concern around the world. Telematics solutions have been available for more than a decade, and several studies have been done in the use of telematics data in road safety. However, these studies are ...

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