Browsing by Author "Perera, H"

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Embargo
Applicability of three complexity metrics
(IEEE, 2012-12-12) De Silva, D. I; Kodagoda, N; Perera, H
Over the years a number of complexity metrics have been proposed. However, there have been only a few studies conducted to compare those proposed metrics in terms of their practical applicability. The few researches that have been conducted to assess the applicability of a complexity metric have also used the five properties proposed by Briand et al. However determining whether a complexity measure satisfies some theoretical complexity properties is not a reliable method of determining the practical applicability of it. Thus, the main intent of this study was to compare three proposed code complexity metrics: McCabe's cyclomatic complexity, Halstead's software science and Shao and Wangs' cognitive functional size and identify which metric is the most suitable metric that can be used in the current state of the art with the help of thirty programmers. To conduct this empirical study ten freely available java programs were used as the base. From this study it was identified that Shao and Wangs' cognitive functional size is the best complexity metric that can be used in the real world.
Open Access
Appraisal of Satellite Rainfall Products for Malwathu, Deduru, and Kalu River Basins, Sri Lanka
(MDPI, 2022-10-20) Perera, H; Senaratne, N; Gunathilake, M. B; Mutill, N; Rathnayake, U
Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications. This evaluation is very much necessary since, it had been found that their performances vary with different areas of interest. This research looks at the three prominent river basins; Malwathu, Deduru, and Kalu of Sri Lanka and evaluates six selected SRPs, namely, IMERG, TRMM 3B42, TRMM 3B42-RT, PERSIANN, PERSIANNCCS, PERSIANN-CDR against 15+ years of observed rainfall data with the use of several indices. Four Continuous Evaluation Indices (CEI) such as Root Mean Square Error (RMSE), Percentage Bias (PBIAS), Pearson’s Correlation Coefficient (r), and Nash Sutcliffe Efficiency (NSE) were used to evaluate the accuracy of SRPs and four Categorical Indices (CI) namely, Probability of Detection (POD), Critical Success Index (CSI), False Alarm Ratio (FAR) and Proportion Correct (PC) was used to evaluate the detection and prediction accuracy of the SRPs. Then, the Mann–Kendall Test (MK test) was used to identify trends in the datasets and Theil’s and Sens Slope Estimator to quantify the trends observed. The study of categorical indicators yielded varying findings, with TRMM-3B42 performing well in the dry zone and IMERG doing well in the wet zone and intermediate zone of Sri Lanka. Regarding the CIs in the three basins, overall, IMERG was the most reliable. In general, all three basins had similar POD and PC findings. The SRPs, however, underperformed in the dry zone in terms of CSI and FAR. Similar findings were found in the CEI analysis, as IMERG gave top performance across the board for all four CEIs in the three basins. The three basins’ overall weakest performer was PERSIANN-CCS. The trend analysis revealed that there were very few significant trends in the observed data. Even when significant trends were apparent, the SRP projections seldom captured them. TRMM-3B42 RT had the best trend prediction performance. However, Sen’s slope analysis revealed that while the sense of the trend was properly anticipated, the amplitude of the prediction significantly differed from that of the observed data.
Open Access
Beneath the Sentence: A Deep Dive into Post-Homicidal Mentality and Coping Strategies on Sri Lanka’s Death Row Inmates
(School of Psychology. Faculty of Humanities and Sciences, SLIIT, 2025-10-10) Madanayake, C; Perera, H; Samarakoon, C; Athapaththu, T; Attanayaka, A; Weeramanthrie, Y; Sandupama, T; Selvaratnam, N.D; Ponnamperuma, L
This study explores the post-homicidal mentality and coping strategies of individuals convicted of homicide and sentenced to capital punishment in Sri Lanka, a context marked by stressful conditions of incarceration and cultural stigma. Using Interpretative Phenomenological Analysis (IPA), in-depth interviews were conducted with six male inmates at Welikada Prison to understand how they perceive and manage their acts (i.e., homicide) and extended detention under the threat of the death penalty. The results showed a variety of signs of psychological distress after a homicide, such as guilt, anxiety, disorientation, and emotional numbness. In order to deal with guilt, control intrusive memories, and adapt to prison life, participants used coping strategies, particularly religious surrender, creative engagement, and moral reframing. According to these findings, death row inmates face significant psychological difficulties, and the correctional system in Sri Lanka urgently needs culturally competent mental health services and rehabilitative frameworks. The study contributes to the limited qualitative literature on the inner experiences of death row prisoners, offering insights for policy development and clinical practices aimed at supporting psychological adaptation in highly punitive environments.
Embargo
Common Object Request Broker-based Publisher-Subscriber Middleware for Internet of Things - Edge Computing
(IEEE, 2022-10-04) Perera, H; Jayakody, A
The edge computing layer in IoT reduces the flow of a massive amount of data directly to the cloud by processing some data in the local network. The middleware in the layer enables this processing of data and the communication between heterogeneous devices and services in the nearby layers. CORBA, which uses as a powerful middleware technology in developing middleware solutions in enterprise-level distributed applications, has been abandoned in the current generation. The paper presents the design, and the performance evaluation of a publisher-subscriber middleware implemented using CORBA that was studied when exploring the applicability of CORBA as an IoT edge computing middleware. The evaluation was continued in two steps to analyse several parallel connections (Load test) and handle requests in a unit time (burst test) via simulating an IoT environment in a cloud environment.
Embargo
E-Learning Assistive System for Deaf and Mute Students
(IEEE, 2022-12-09) Ranasinghe, P; Akash, K; Nanayakkara, L; Perera, H; Chandrasiri, S; Kumari, S
E-learning has become a popular digital platform among both students and teachers. When using an e-learning system, deaf-mute students can get significant benefits. It allows students to better grasp their studies by providing additional details. The major problem that the deaf and mute community encounters in the e-learning environment is that they are no longer attempting to enroll in normal institutions, which do not provide many facilities for them due to a lack of resources, a lack of learning facilities, and some social disturbances. To achieve that problem this system will translate the lecturer’s voice into text, map words with pre-created sign language animations, generate subtitles for lecture videos, clearly identify the face position of the lecturer, detect difficult words, track the hand gestures, and practice sign language so that it will increase learning resources, facilities, usability and help teachers to execute their teaching process through this platform. Therefore, normal institutions can use this system as their learning management system. It will approach deaf and mute students to enroll in normal institutions and do their studies as typical students.
Open Access
Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka
(Hindawi, 2022-04) Perera, H; Fernando, S; Gunathilake, M. B; Sirisena, J; Rathnayake, U
e availability of accurate spatiotemporal rainfall data is of utmost importance for reliable predictions from hydroclimatological studies. Challenges and limitations faced due to the absence of dense rain gauge (RG) networks are seen especially in the developing countries. erefore, alternative rainfall measurements such as satellite rainfall products (SRPs) are used when RG networks are scarce or completely do not exist. Noteworthy, rainfall data retrieved from satellites also possess several uncertainties. Hence, these SRPs should essentially be validated beforehand. e Mahaweli River Basin (MRB), the largest river basin in Sri Lanka, is the heart of the country’s water resources contributing to a signi cant share of the hydropower production and agricultural sector. Given the importance of the MRB, this study explored the suitability of SRPs as an alternative for RG data for the basin. Daily rainfall data of six types of SRPs were extracted at 14 locations within the MRB. ereafter, statistical analysis was carried out using continuous and categorical evaluation indices to evaluate the accuracy of SRPs. Nonparametric tests, including the Mann-Kendall and Sen’s slope estimator tests, were used to detect the possibility of trends and the magnitude, respectively. Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) outperformed among all SRPs, while Precipitation Estimation from Remotely Sensed Information using Arti cial Neural Networks (PERSIANN) products showed dire performances. However, IMERG also demonstrated underestimations when compared to RG data. Trend analysis results showcased that the IMERG product agreed more with RG data on monthly and annual time scales while Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis–3B42 (TRMM-3B42) agreed more on the seasonal scale. Overall, IMERG turned out to be the best alternative among the SRPs analyzed for MRB. However, it was clear that these products possess signi cant errors which cannot be ignored when using them in hydrological applications. e results of the study will be valuable for many parties including river basin authorities, agriculturists, meteorologists, hydrologists, and many other stakeholders.
Open Access
Evolving Expectations of HR Professionals Amid the Covid-19 Pandemic in Sri Lanka
(researchgate.net, 2022-07) Weerarathna, R; Rathnayake, N; Perera, H; Wickramasena, D; Arambawatta, V; Kaluarachchi, R
This study explores the expectations of HR professionals in Sri Lanka in terms of their workplaces during the COVID19 pandemic. A qualitative research methodology was employed in this study with 16 semi-structured interviews of HR professionals in Sri Lanka. Results reveal that on-premise and hybrid work cultures are much preferred by HR professionals in Sri Lanka. Further, if the work culture transformation remains, their expectations are high regarding concerns in new work practices at the workplace triggered by the pandemic including worklife balance practices, crisis management practices, financial incentives, career progress and Work from Home (WFH) resources.
Open Access
Satellite Rainfall Products for analysis of Rainfall trends for Mahaweli River Basin
(SLIIT, 2022-02-11) Perera, H; Gunathilake, M. B; Rathnayakea, U
The presence of accurate and spatiotemporal data is of utmost importance in hydrological studies for river basins. However, limited ground-measured rainfall data restrict the accuracy of these analyses. Data scarcities can often be seen not only in many developing countries but also in the developed world. Therefore, much attention is given to alternative techniques to accomplish the data requirement. Precipitation data extraction from satellite precipitation products is one of the frequently used techniques in the absence of ground-measured rainfall data. The Mahaweli River Basin (MRB) is the largest river basin in Sri Lanka and it covers 1/6th of the total land area of the country. Mahaweli River is the heart of the country and the water of it is being used for many activities, including hydropower development, water supply, irrigation, etc. Therefore, analyzing rainfall trends of MRB is interesting and worthwhile for many stakeholders of the river basin. Therefore, this research investigates the suitability of Satellite Rainfall Products (SRP’s) as an alternative for Rain Gauge measured data in the MRB by performing trend analysis between the two datasets. Six precipitation products, namely PERSIANN, PERSIANNCCS, PERSIANN-CDR, GPM IMERG V06, TRMM-3B42 V7, TRMM-3B42RT V7 were extracted for 10-35 years for 14 locations of the MRB spatially distributed in the three climatic zones of the catchment. Non-parametric tests, including the Mann-Kendall test and Sen’s slope estimator tests, were used to detect the possible rainfall trends in precipitation products. Significant increasing trends were observed for both ground-measured and SRP’s in the annual scale while mixed results were observed in monthly and seasonal scales. The trends from ground-measured rainfall and SRP’s were compared and the suitability of SRP’s as an alternative technique was stated.
Embargo
Sinhala to english language translator
(IEEE, 2008-12-12) De Silva, D; Alahakoon, A; Udayangani, I; Kumara, V; Kolonnage, D; Perera, H; Thelijjagoda, S
This paper describes a machine translation system that is capable of translating a grammatically correct Sinhala sentence in to its corresponding English sentence. This is the first Sinhala to English machine translation system, which comes with features such as an inbuilt keyboard, an inbuilt dictionary, an integrated word processor based on Unicode fonts, a grammar tool, a Sinhalese grammar checker, an add word tool, and a debugging tool. With the expansion of the world, English has become an important language that people should learn, as the majority of the worldwide population understand and carry out their day-to-day work in English. In addressing this need, we thought of taking up the challenge of building, a Sinhala to English language translator. To build this system, we used the transfer-based machine translation approach, which is a rule-based approach. At present, the system has achieved a success rate of 75% with a corpus of 150 sentences.
Open Access
Statistical Evaluation and Trend Analysis of ANN Based Satellite Products (PERSIANN) for the Kelani River Basin, Sri Lanka
(Hindawi, 2022-08-31) Perera, H; Gunathilake, M. B; Panditharathne, R; Al-mahbashi, N; Rathnayake, U
Satellite-based precipitation products, (SbPPs) have piqued the interest of a number of researchers as a reliable replacement for observed rainfall data which often have limited time spans and missing days. The SbPPs possess certain uncertainties, thus, they cannot be directly used without comparing against observed rainfall data prior to use. The Kelani river basin is Sri Lanka’s fourth longest river and the main source of water for almost 5 million people. Therefore, this research study aims to identify the potential of using SbPPs as a different method to measure rain besides using a rain gauge. Furthermore, the aim of the work is to examine the trends in precipitation products in the Kelani river basin. Three SbPPs, precipitation estimation using remotely sensed information using artificial neural networks (PERSIANN), PERSIANN-cloud classification system (CCS), and PERSIANN-climate data record (CDR) and ground observed rain gauge daily rainfall data at nine locations were used for the analysis. Four continuous evaluation indices, namely, root mean square error (RMSE), (percent bias) PBias, correlation coefficient (CC), and Nash‒Sutcliffe efficiency (NSE) were used to determine the accuracy by comparing against observed rainfall data. Four categorical indices including probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and proportional constant (PC) were used to evaluate the rainfall detection capability of SbPPs. Mann‒Kendall test and Sen’s slope estimator were used to identifying whether a trend was present while the magnitudes of these were calculated by Sen’s slope. PERSIANN-CDR performed well by showing better performance in both POD and CSI. When compared to observed rainfall data, the PERSIANN product had the lowest RMSE value, while all products indicated underestimations. The CC and NSE of all three products with observed rainfall data were also low. Mixed results were obtained for the trend analysis as well. The overall results showed that all three products are not a better choice for the chosen study area.
Open Access
The usage of cash deposit machines: An empirical analysis of identifying determinant factors
(2020) Jayathilaka, R; Pathiratne, H; Jayanath, C; Perera, H; Wickremasinghe, S; Dharmasena, T
Banks in Sri Lanka have launched a new generation of machines facilitating cash deposits that are credited instantly to accounts. The purpose of this paper is to identify the factors that influence the customers’ level of cash deposit machines (CDMs) usage. The Technology Acceptance Model (TAM) was used to accomplish the purpose of the research. The study used primary data in the form of a structured questionnaire covering the variables of TAM. Correlational analysis was used to demonstrate the constructed hypotheses among the variables, and multiple linear regression was used to measure the impact of customer attitude towards the usage of CDM. Results from the analysis indicated that reliability, perceived ease of use, perceived risk and perceived usefulness were significant factors, whereas the security factor was considered less significant concerning the use of CDMs. The contribution of this research is related to the analysis from a theoretical and empirical perspective of the customer attitude towards the usage of CDM. The practical implications drawn from this study will be useful to bank managers, marketing experts and advertising executives in providing good quality services promoting CDM, whilst developing grievance settlement to build trust among customers, enabling extensive usage.