Browsing by Author "Ahangama, S"

Now showing 1 - 13 of 13

item: Article-Full-text
Acceptance of health information systems in Sri Lanka using fuzzy set qualitative comparative analysis
(Faculty of Graduate Studies, 2024) Senthilrajah, T; Ahangama, S
The global doctor-patient ratio is 17 per 1000 population, however, it is 1.23 per 1000 population in Sri Lanka [1]. As it is far behind the expected numbers, the Sri Lankan public health sector is facing challenges in providing efficient services to citizens free of charge, including surgeries and cancer treatments. Looking at Nordic countries adoption of HIS has reached 95%-100% and the health sector has been digitalized using powerful Health Information Systems (HIS) in the form of Electronic Health Records (EHR), Personal Health Records (PHR), and Electronic Medical Records (EMR). The Government of Sri Lanka (GoSL) has launched various initiatives to digi-talize the public health sector and trailed Hospital Health Management Information Systems (HHMIS). However, it is noted that the acceptance of HIS is low among healthcare stakeholders. The empirical findings suggest the main reasons for low acceptance could be issues relating to usability. Therefore, this study is focused on identifying the factors impacting the acceptance of HIS by doctors and nurses in the public health sector.
item: Article-Full-text
A comparative study of the characteristics of hate speech propagators and their behaviours over Twitter social media platform
(Elsevier, 2023) Perera, S; Meedin, N; Caldera, M; Perera, I; Ahangama, S
The internet and social media have facilitated diverse communication genres, enabling widespread and rapid opinions-sharing. However, hate speech imposes a contemporary challenge on individuals and communities, given the user anonymity, freedom, and inadequate regulation. Therefore, it is imperative to identify the perpetrators responsible for spreading hate content and examine their behaviour to prevent and mitigate the negative impact. This study aimed to compare the characteristics of hate speech propagators and their behaviour with non-hate users on Twitter for the first time in Sri Lanka. The intrinsic and extrinsic profile features were extensively analyzed, employing Sinhala and English text analysis techniques. A corpus of 102882 posts from 530 hate and non-hate Twitter user profiles was selected for the study. This study investigates the unique characteristics of hate speech propagators and non-hate users by examining their profile self-presentation, conducting social network analysis, and analyzing sentiment and emotion through linguistic analysis. Hate users often refrained from expression, with infrequent account verification and geotagging. They tend to have a higher follower and following counts and more favourites, group memberships, and statuses than non-hate users. However, general Twitter user engagement with hate users was significantly low, with fewer likes, retweets, and replies. The limited involvement of normal users with hate content indicates that audiences can be effectively utilized to combat hate speech. The sentiment analysis between languages showed polarisation of negative tweets towards Sinhala, with the synergistic effect of English language users using positive sentiment to spread hate content. The novel findings shed light on the characteristics of hate users, facilitating their early detection and moderation of hate speech and aiding in developing algorithms to rank and categorize hate users using artificial intelligence. Moreover, it can be used for policy reforms, awareness programmes, and building social cohesion while combating hate speech.
item: Conference-Abstract
Hardware implementation of motion blur removal
(2011) Chandrapala, T; Cabral, A; Sameera, T; Ahangama, S; Samarawickrama, J
Motion Blur due to the relative motion between the camera and object can seriously degrade image quality. We present an FPGA based blur detection and correction algorithm which is implemented on lop of a configurable soft-processor based architecture. The system consists of two main modules. The blur detection module identifies the blur length and angle, and the restoration module uses regularized inverse filtering to remove the blur. The Processing algorithms are implemented as separate cores on the FPGA fabric where the soft processor core is only used for managing system configuration. The system can achieve a frame rate of 15fps for a 720p HD video strea
item: Conference-Full-text
Heuristics-based sql query generation engine
(Faculty of Information Technology, University of Moratuwa., 2021-12) Sugandhika, C; Ahangama, S; Ganegoda, GU; Mahadewa, KT
A database is one of the prime media to store data. Most of the time, relational databases are preferred over other databases due to their ability to represent complex relationships between data. Languages like Structured Query Language (SQL) are used to retrieve data stored in relational databases. Information stored in these databases is often accessed by naïve users who do not possess high competencies in technical database querying. Therefore, Natural Language Interfaces to Databases (NLIDB) are being developed to translate natural language into SQL queries and retrieve the corresponding database results. This paper proposes a novel NLIDB called SQL Query Generation Engine which has been developed using a heuristics-based approach. The system was tested with more than 200 natural language queries and has shown an overall accuracy of 93%.
item: Article-Full-text
The Impact of ICT regulations and internet filtering on ICT diffusion and quality of life
(Faculty of Graduate Studies, 2024) Ahangama, S
ICT has transformed human life in a multitude of ways and continues to do so, by the creation, sharing, communication, storing, and management of information. However, it also opened the door for new cybersecurity risks, and if these privacy and security risks are not adequately addressed, ICT use will be restricted by the users. Thus, this cross-country level study (with 106 countries) aims to identify the relationship between ICT regulations on ICT diffusion and the quality of life of citizens while exploring the moderating effect of the use of internet filtering by the government (Figure 1). ICT diffusion refers to the spread and adoption of ICT by various communities and organisations. According to the National Cyber Security Alliance (NCSA), USA, 74% of American internet users have reduced their online activities due to privacy concerns. Similar findings are drawn from other studies too [1]. Thus, to improve ICT diffusion, it is important to set up a matured ICT-related regulatory environment (H1). As virtual social networks become increasingly popular, online bullying, hate speech, and the spread of fake news have emerged as major problems. Some of the incidents have led to suicides as well as community-level violence. The platform providers are therefore under pressure to restrict this kind of internet content. For example, in January 2024 at the USA Senate, CEOs of social media companies were urged to draw attention to how they had failed to safeguard children. On the other hand, there is growing concern about the involvement of the government in content filtering and censoring highlighting the fact that it could impact the freedom of speech and be biased.
item: Conference-Full-text
An integrated approach to esg index construction with machine learning
(IEEE, 2023-12-09) Gamlath, M; Gunathilaka, C; Wijesinghe, A; Ahangama, S; Perera, I; Sivaneasharajah, L; Abeysooriya, R; Adikariwattage, V; Hemachandra, K
This paper presents an integrated approach to the automated generation of Environmental, Social and Governance (ESG) ratings of companies from financial and textual data. Three different research avenues on ESG relationships are investigated, each presenting a machine learning model which approaches the ESG calculation from a different aspect. The first model generates annual ESG ratings, the second uses historical data to predict the ESG rating of the immediate next quarter, and the third predicts whether the ESG rating would rise, fall or remain stable year-on-year. The combination of these models provides a foundation for the construction of a fully automated ESG rating system.
item: Conference-Full-text
Machine learning-based automated tool to detect Sinhala hate speech in images
(Faculty of Information Technology, University of Moratuwa., 2021-12) Silva, E; Nandathilaka, M; Dalugoda, S; Amarasinghe, T; Ahangama, S; Weerasuriya, GT; Ganegoda, GU; Mahadewa, KT
Social media platforms have emerged rapidly with technological advancements. Facebook, the most widely used social media platform has been the primary reason for the spread of hatred in Sri Lanka in the recent past. When a post with Sinhala hate content is reported on Facebook, it is translated to the English language before the review of the moderators. In most instances, the translated content has a different context compared to the original post. This results in concluding that the reported post does not violate the established policies and guidelines concerning hate content. Hence, an effective approach needs to be in place to address the aforementioned problem. This research project proposes a solution through an automated tool that is capable of detecting hate content presented in Sinhala phrases extracted from Facebook posts/memes. The tool accepts an image that contains Sinhala texts, extracts the text using a Convolutional Neural Network (CNN) model, preprocesses the text using Natural Language Processing (NLP) techniques, analyzes the preprocessed text to identify hate intensity level and finally classifies the text into four main domains named Political, Race, Religion and Gender using a text classification model.
item: Conference-Full-text
Predictive maintenance and performance optimisation in aircrafts using data analytics
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2018) Weerasinghe, S; Ahangama, S; Wijesiriwardana, CP
Airline industry has provided a significantly conventional, faster and reliable mode of transportation for passengers and freight over the decades in which the industry has been in service despite the pressure being applied especially in maintaining operational affordability. The study critically reviews the techniques and tools, infrastructure and general application architecture for discussing the applicability of data analytics based on both batch processing and real time stream data in general aviation for health monitoring and predictive analysis in order to predict maintenance and optimize the performance of aircrafts. In this respect, the study further evaluates the significant capability in addressing contemporary problems which are uniquely addressed by data analytics system.
item: Article-Full-text
Relating social media diffusion, education level and cyber security protection mechanisms to E‑participation initiatives: insights from a cross‑country analysis
(Springer, 2023-04-17) Ahangama, S
collaboration, and decision making. VSN based e-participation tools allow many-to-many communication and collaboration near real-time with users who might be in geographically dispersed locations. It provides a platform to voice opinions and perspectives and share them with others in new and innovative ways. Cybersecurity is a key area that needs to be considered for the success and continuous use of e-participation systems as it protects user privacy and helps to avoid scams, harassment, and misinformation. The intervening effect of cybersecurity protection mechanisms and citizens’ education level on the relationship between VSN diffusion and e-participation initiatives is explored in the proposed research model presented in this paper. Moreover, this research model is explored for different stages of e-participation (e-information, e-consultation, and e-decision making) and the five dimensions of cybersecurity (legal, technical, organizational, capacity building, and cooperation). The findings indicate that improved VSN usage has increased e-participation (especially in e-consultation and e-decision making) as a result of improved cybersecurity protection and public education, highlighting the varying importance of different cybersecurity protection measures for three stages of e-participation. Thus, considering the recent problems like platform manipulation, misinformation and data breaches associated with the use of VSN for e-participation, this study emphasizes the importance of regulations, policies, partnerships, technical frameworks, and research to ensure cybersecurity, as well as the importance of education to enable the public to interact productively in e-participation activities. This study is performed using publicly available data from 115 countries and the research model is developed, drawing theoretical basis from the Protection Motivation Theory, Structuration Theory, and Endogenous Growth Theory. This paper recognizes the theoretical and practical implications, and limitations while recommending future research directions.
item: Conference-Full-text
A review of query optimization techniques for complex event processing
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Perera, KPD; Ahangama, S; Sudantha, BH
Complex Event Processing (CEP) Systems is a technology that is used in many modern fields of application such as finance and business analysis. It tracks and analyses data from large information streams pertaining to a string of related or non-related events in order to identify patterns and relations that could be used to derive useful connections among seemingly unrelated factors within its applications. CEP systems make use of pattern queries to match identified events within an event stream. However, due to the generalized nature of CEP query languages and the lack of general structure and semantics, it is difficult to write queries that function optimally to deliver the expected results within the required time frames. This issue is particularly of importance as CEP systems often deal with time sensitive data and hence require rapid processing in order to output useful information and hence, defines the importance and requirement for query optimization techniques that may be applied to CEP systems. This paper focuses on research publications related to the four main pattern query optimization techniques, namely, Multi-Query Optimization, Join Query Optimization, Nested Query Processing techniques and Query Rewriting as well as their applications within modern CEP systems. This study further aims to identify possible limitations within the four techniques mentioned previously and advise on possible measures that may be taken to further improve these techniques in order to offer greater efficiency and stability to pattern query processing within CEP systems.
item: Conference-Full-text
A rule-based lemmatizing approach for sinhala language
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2018) Nandathilaka, M; Ahangama, S; Weerasuriya, GT; Wijesiriwardana, CP
Speech recognition, natural language processing, language translation and deep learning researches are bridging the communication gap between humans as well as between humans and machines. Sinhala is a native language in Sri Lanka which is being used by 19 million people approximately. The growth of Sinhala natural language processing tools is less when compared to European and other Asian Languages. A lemmatizer for Sinhala can be used for the morphological analysis and is an essential module in Sinhala language processing mechanisms. Lemmatizing is a complex process in morphological analyzing where base/root of words are derived. There is not much work published focusing on lemmatizer approaches for Sinhala. This paper presents a rule based lemmatizing approach which can be used to determine the base form of Sinhala words with an accuracy of 77.3%. It differs from similar works because the data used in the research are extracted from social media.
item: Article-Full-text
A systematic mapping of introductory programming languages for novice learners
(IEEE, 2021) Perera, P.; Tennakoon, G; Ahangama, S; Panditharathna, R; Chathuranga, B
Delivery of core programming principles to novices is a challenging task and many introductory programming languages and platforms have been designed to support this process. Educational programming languages generally focus on alleviating the syntax overhead enforced on novice learners by designing languages with simple and concise keywords. Furthermore, only the most basic programming concepts and principles are incorporated and many languages follow unique methods to provide more simplified learning environments. However, considering the way programs are authored using these platforms, two common contrasting approaches to program representation are identified as text-based and block-based representations. Additionally, a hybrid approach of dual-modality interfaces, which combines the best of both techniques has gained traction as a current trend in the development of educational programming platforms. However, despite these extensive features, not all introductory programming languages can cater to the exact requirements of novice learners and a dearth of comprehensive studies and literature reviews have been conducted to investigate this context. This paper explores and presents a comprehensive review of how different elements of educational programming languages and platforms contribute towards learning by novices under the Technology Acceptance Model (TAM). The review is conducted under two main constructs of TAM as (1) Perceived Usefulness (PU) and (2) Perceived Ease of Use (PEOU) and external factors regarding the programming environment, language design, included programming concepts and supporting features such as the target audience group, language extensibility, and availability of learning materials are thoroughly investigated considering the typical behavioral patterns of novices concerning computer programming education.
item: Article-Full-text
A systematic review of introductory programming languages for novice learners
(IEEE, 2021) Perera, P; Tennakoon, G; Ahangama, S; Panditharathna, R; Chathuranga, B
Delivery of core programming principles to novices is a challenging task and many introductory programming languages and platforms have been designed to support this process. Educational programming languages generally focus on alleviating the syntax overhead enforced on novice learners by designing languages with simple and concise keywords. Furthermore, only the most basic programming concepts and principles are incorporated and many languages follow unique methods to provide more simplified learning environments. However, considering the way programs are authored using these platforms, two common contrasting approaches to program representation are identified as text-based and block-based representations. Additionally, a hybrid approach of dual-modality interfaces, which combines the best of both techniques has gained traction as a current trend in the development of educational programming platforms. However, despite these extensive features, not all introductory programming languages can cater to the exact requirements of novice learners and a dearth of comprehensive studies and literature reviews have been conducted to investigate this context. This paper explores and presents a comprehensive review of how different elements of educational programming languages and platforms contribute towards learning by novices under the Technology Acceptance Model (TAM). The review is conducted under two main constructs of TAM as (1) Perceived Usefulness (PU) and (2) Perceived Ease of Use (PEOU) and external factors regarding the programming environment, language design, included programming concepts and supporting features such as the target audience group, language extensibility, and availability of learning materials are thoroughly investigated considering the typical behavioral patterns of novices concerning computer programming education.