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Author: search.filters.author.Perera, S

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Now showing 1 - 10 of 26
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    Socio-Economic and Environmental Drivers of Food Security in Low-Income Countries: A 32-Year Cross-National Analysis for Sustainable Development
    (John Wiley and Sons Ltd, 2026-04-06) Pulle, N; Sampath, P; Wijayaweera, D; Perera, S; Jayathilaka, R; Dabare, U
    Ensuring countries meet their basic food security needs has been a long-standing challenge. Despite numerous attempts to tackle this issue, it remains unresolved. Hence, considering the broad reach of this concern, our study aims to collectively analyse how urbanisation, greenhouse gas emissions, renewable energy consumption, population growth, agricultural land, and gross domestic product per capita impact food security across countries. This study tests a stepwise panel-ordered probit model, utilising data from 17 low-income countries from 1992 to 2023. The research categorises the food production index into three categories: low, moderate, and high food security, allowing for the analysis of the likelihood of falling into a category of the food production index. The outcomes reveal that in low-income countries, urbanisation, greenhouse gas emissions, population growth, and agricultural land have a positive impact on the food production index, whereas renewable energy consumption has an insignificant negative impact. This analysis contributes distinctively to the existing body of knowledge by comparatively analysing the probabilities over the given period, together with the financial crisis and the COVID-19 pandemic, thus providing insights into both events. Furthermore, this report highlights the effectiveness of policies implemented, focusing on the efficient use of agricultural land through technological advancements, promoting modern farming techniques, encouraging youth engagement in agriculture, managing population growth, and innovating climate-resilient strategies, which are directly aligned with the research findings. These recommendations address specific challenges identified in the highlighted countries, helping improve their food security and promote sustainable development.
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    PublicationOpen Access
    Global hunger risk projections and the factors shaping future vulnerabilities
    (Elsevier B.V., 2026-06) Pulle, N; Sampath, P; Wijayaweera, D; Perera, S; Jayathilaka, R
    Hunger remains one of the most persistent barriers to human development, with progress uneven across regions and increasingly exposed to economic instability, climate pressure and structural vulnerabilities. This study investigates the key drivers of cross-country variation in hunger severity and develops forward looking projections to support evidence based global policy planning. Using a comprehensive global panel dataset covering 146 countries over the period, 1992 to 2024 the analysis identifies the socio-economic and environmental factors more strongly associated with changes in hunger outcomes over time. The results reveal that hunger severity is not shaped by a single pathway but by a combination of development related conditions, demographic pressures, and external shocks with substantial heterogeneity across country groups. Building on the estimated relationships the study generates projections from 2025 to 2029, highlighting regions where hunger risks may remain elevated or worsened in the absence of targeted interventions. The findings underscore that substantial progress in hunger reduction requires integrated methods that extend beyond food supply alone including strengthening resilience, improving social protection and supporting inverse growth by combining long run global evidence with near turn projections. This study contributes to the literature on hunger dynamics and offers timely insights for international organisations and national policymakers working towards the achievement of food security and related Sustainable Development Goals.
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    ItemOpen Access
    Towards Real-Time Market Intelligence: Event Detection and Latency Analysis in High Frequency Trading Dashboards
    (Faculty of Humanities and Sciences, SLIIT, 2024-10-18) de Silva, U; Perera, S; Liyanage, U.P; Erandi, H
    High Frequency Trading (HFT) relies on millisecond level decisions, where market responsiveness and system latency directly determine profitability. Traditional dashboards offer real-time visualizations but often fail to detect abrupt market shifts or quantify the delays in system reactions. This paper presents an AI-aided Market Pulse and Latency Panel that integrates candlestick pattern recognition, statistical change point analysis, and latency measurement into a unified trader-facing dashboard. The system identifies technical patterns, detects structural regime shifts, and quantifies latency. Experimental evaluations demonstrate that the panel captures both microstructural signals and broader regime changes while exposing critical latency bottlenecks, such as API-induced delays. By combining event detection with latency analytics, the panel advances dashboards beyond descriptive visualization, providing traders with actionable insights for strategy adjustment and infrastructural optimization.
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    PublicationOpen Access
    Achieving zero hunger: A global policy lens on food security drivers and income group disparities
    (Elsevier B.V., 2026-03) Pulle, N; Sampath, P; Perera, S; Wijayaweera, D; Jayathilaka, R
    Many countries struggle to meet their daily dietary requirements despite numerous attempts to address the existing demand. Consequently, this study collectively analyses the impact of urbanisation, renewable energy, greenhouse gas emissions, population growth, gross domestic product per capita and agricultural land on food production relying on Sen's Entitlement Theory, thus providing insights to resolve the long-standing issue of food insecurity, and support the achievement of the Sustainable Development Goals. The study utilises a stepwise panel ordered Probit model on 146 countries, for the years 1993 to 2023. It further categorises the food production index into three categories of food security as; low, moderate and high, thereby enabling discussion of the likelihood of a country falling into one of the aforementioned food security categories over the years. Urbanisation, agricultural land, and the dummy variables introduced to represent the income groups have been identified to have a significant and favourable relationship with the food production index. In contrast, the greenhouse gas emissions and renewable energy variables have a significantly inverse impact on the food production index. This makes a unique contribution to the existing body of literature, especially by comparing odds over the years, across different food secure categories, countries, and their specific income levels. This study enables policymakers to gain a comprehensive historical perspective on each case. This study further promotes the Sustainable Development Goals, highlighting areas where these goals have been negatively impacted. Additionally, the study discusses optimised investment allocations, agricultural research and development, agricultural technology, climate resilient farming, and sustainable urbanisation planning as solutions for extreme cases.
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    ItemEmbargo
    Project HyperAdapt: An Agent-Based Intelligent Sandbox Design to Deceive and Analyze Sophisticated Malware
    (Institute of Electrical and Electronics Engineers Inc., 2025) Perera, S; Dias, S; Vithanage, V; Dilhara, A; Senarathne, A; Siriwardana, D; Liyanapathirana, C
    Malware increasingly employs sophisticated evasion techniques to bypass sandbox-based analysis, rendering traditional detection methods ineffective. This research presents Project HyperAdapt: Agent-Based Intelligent Sandbox, a framework that integrates both offensive and defensive machine learning models to enhance malware detection, deception, and behavioral analysis. The offensive RL model generates evasive malware samples, challenging the sandbox, while the defensive models including hybrid evasion detection, GAN-based behavior simulation, and a dynamically adapting RL agent work collectively to improve sandbox resilience. By continuously learning from evasive malware behavior, the defensive RL agent adapts in real-time, strengthening detection capabilities. Experimental results demonstrate that this approach enhances sandbox effectiveness, ensuring long-term adaptability against evolving malware threats.
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    PublicationOpen Access
    Optimizing Asset Transfer Process in ERP Using Business Process Management Technique
    (Science and Information Organization, 2025-10-30) Yasarathne, R; Ranatunga, N; Herath, V; Chalinda, L; Kahandawaarachchi, C; Perera, S; Randula, C
    Enterprise Resource Planning (ERP) systems are critical for managing enterprise-wide business processes, including asset management. Yet, many ERP platforms lack efficient mechanisms for bulk asset transfers, leading to high manual effort, increased costs, and data inconsistencies. This study applies Business Process Reengineering (BPR) techniques as the methodology to optimize ERP asset management, focusing on workflow optimization and automation, contributing both practical and methodological insights. A mixed-method approach was adopted, analyzing a financial organization with 256 branches and over 450 Oracle ERP users. Data from 51 representative branches identified inefficiencies such as manual transfer delays, approval bottlenecks, and synchronization issues. The proposed solution introduces automated bulk asset transfers, optimized approval workflows, and real-time data synchronization, along with new metrics for evaluating efficiency, compliance, risk, and asset utilization. Compared to the As-Is system, the reengineered framework achieved a 100% reduction in operational costs per user ($7,500 annual saving), an 80% reduction in compliance incidents, a 67% reduction in asset transaction errors, and a 20% improvement in asset utilization. These results demonstrate a scalable, adaptable, and effective framework that enhances ERP operational efficiency, strengthens data integrity, and advances both academic understanding and industrial practice of asset management process reengineering.
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    PublicationOpen Access
    Achieving zero hunger: A global policy lens on food security drivers and income group disparities
    (Elsevier B.V., 2026-01-19) Pulle, N; Sampath, P; Perera, S; Wijayaweera, D; Jayathilaka, R
    Many countries struggle to meet their daily dietary requirements despite numerous attempts to address the existing demand. Consequently, this study collectively analyses the impact of urbanisation, renewable energy, greenhouse gas emissions, population growth, gross domestic product per capita and agricultural land on food production relying on Sen’s Entitlement Theory, thus providing insights to resolve the long-standing issue of food insecurity, and support the achievement of the Sustainable Development Goals. The study utilises a stepwise panel ordered Probit model on 146 countries, for the years 1993 to 2023. It further categorises the food production index into three categories of food security as; low, moderate and high, thereby enabling discussion of the likelihood of a country falling into one of the aforementioned food security categories over the years. Urbanisation, agricultural land, and the dummy variables introduced to represent the income groups have been identified to have a significant and favourable relationship with the food production index. In contrast, the greenhouse gas emissions and renewable energy variables have a significantly inverse impact on the food production index. This makes a unique contribution to the existing body of literature, especially by comparing odds over the years, across different food secure categories, countries, and their specific income levels. This study enables policymakers to gain a comprehensive historical perspective on each case. This study further promotes the Sustainable Development Goals, highlighting areas where these goals have been negatively impacted. Additionally, the study discusses optimised investment allocations, agricultural research and development, agricultural technology, climate resilient farming, and sustainable urbanisation planning as solutions for extreme cases
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    PublicationOpen Access
    Event Detection and Latency Analysis in High Frequency Trading Dashboards
    (Department of Mathematics and Statistics, Faculty of Humanities and Sciences, SLIIT, 2025-10-10) de Silva, U; Perera, S; Liyanage, U.P; Erandi, H
    High frequency trading relies on millisecond-level decisions, where profitability is strongly influenced by both market responsiveness and system latency. Traditional dashboards offer real-time visualizations but fall short in detecting abrupt regime shifts or quantifying latency. This study presents an AI-aided Market Pulse and Latency Panel that integrates candlestick pattern recognition, change point detection and latency measurement into a unified dashboard. The system detects technical patterns, identifies structural market shifts, and quantifies infrastructural bottlenecks. Experimental results demonstrate that the panel enhances situational awareness by combining event detection with latency analytics, providing traders with actionable insights for strategy adjustment and infrastructural optimization.
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    PublicationOpen Access
    Unpacking how the Living Arrangements of Undergraduates Influence Quality of Life
    (School of Psychology. Faculty of Humanities and Sciences, SLIIT, 2025-10-10) Bandara, K; Abeysekara, M; Vihangi, S; Perera, S; Jayasekara, S; Samaratunge, T; Goonetilleke, N
    This study examined the connection between undergraduate students' living arrangements (private vs rented accommodation) and their Quality of Life (QoL) at the Sri Lanka Institute of Information Technology (SLIIT). All four domains of quality of life, psychological well-being, physical health, environmental factors, and social relationships were measured using an adapted version of the World Health Organisation Quality of Life: Brief Version (WHOQOL-BREF). The cross-sectional studyincluded a sample of 64 individuals obtained from the campus premises between the ages of 18-25. Multivariate Analysis of Variance (MANOVA) revealed no statistically significant differences in QoL dimensions based on accommodation type. However, the effect sizes indicate living arrangements to be a better predictor of the environmental factors as opposed to other domains of QoL. Furthermore, a chi-square test yielded a strong association between the year of study and living arrangements among students, suggesting that the year of study may have an impact on students’ choice of accommodation. These results further demonstrate the diversity of QoL and imply that, although environmental influences are worthy of consideration, living arrangements might not be a strong factor to explain students’ well-being. While the nature of the sample (i.e., small and convenient) may have hindered the statistical significance of the study, the present findings highlight the necessity for subsequent studies to accurately uncover the impact of student life, accommodation, and other related factors onthe quality of life.
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    PublicationOpen Access
    Influence of IoT on Warehouse Management Performance in the Global Context: A Critical Literature Review
    (SLIIT Business School, 2023-12-14) Perera, S; Pinto, A; Sewmini, H; Ulugalathenne, A; Thelijjagoda,S; Karunarathna,N
    This systematic research paper explores the impact of Industry 4.0 technology, specifically the Internet of Things (IoT), on Warehouse Management Performance (WMP) in the worldwide logistics sector. IoT serves as a pivotal component in the paradigm shift towards Industry 4.0, facilitating the seamless storage, packaging, and distribution of commodities. By harnessing interconnected devices and data-driven insights, warehouses have undergone significant transformations since the inception of IoT technology. This study reviews state-of-theart literature on the influence of IoT on WMP, emphasizing the vital role warehouse operations play in ensuring the smooth functioning of the supply chain management process. Warehouse operations encompass aspects ranging from planning and layout to receiving, order picking, shipping, and distribution. To optimize warehouse operations, we conduct a comprehensive literature assessment using Scopus as our primary database. The findings from this systematic review indicate that the integration of IoT technologies such as RFID, QR codes, scanners, and Warehouse Management Systems (WMS) can substantially enhance warehouse management performance. These technologies provide real-time data, predictive maintenance, and improved inventory accuracy, resulting in increased operational efficiency, reduced operational expenses, and improved customer satisfaction. Additionally, the IoT framework combines big data, blockchain, cloud computing, and wireless sensor networks to tackle key challenges related to data storage, retrieval, and utilization. This integration significantly improves the effectiveness of the warehouse management process and facilitates data-driven decision-making. Furthermore, IoT's communication capabilities enhance efficiency and reduce costs in warehouse operations. In conclusion, this systematic review underscores the transformative potential of IoT technology in the global logistics sector. It highlights the importance of technological integration, data-driven decision-making, and smart packaging solutions. Recognizing the disruptive effects of IoT on the logistics industry, it emphasizes the need for companies to adopt and leverage IoT technologies to remain competitive and agile in the evolving global supply chain landscape.