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    PublicationOpen Access
    Psychological capital and personality traits in balancing work–life: a developing country perspective
    (nature.com, 2025-10-06) Pushpika, A; Jayathilaka, R; Weligodapola, M
    Achieving career aspirations while managing personal responsibilities is a global challenge for women, especially in Asian countries. Despite extensive research on work–life balance, many aspects remain unexplored. This study examines the influence of psychological capital and personality traits on work–life balance, identified as an area needing further investigation. Using a blended approach, the study integrates quantitative data from online surveys of Sri Lankan government and private bank employees and qualitative insights from online interviews. The ordered Probit regression model revealed that self-efficacy, optimism, and resilience significantly impact work–life balance, while hope does not. Among personality traits, neuroticism and conscientiousness are most influential. Thematic analysis found resilience to have the greatest impact, with personality effects varying by individual preference. Methodological triangulation was used to avoid research bias. Coping strategies for promoting work–life balance are discussed. This study is valuable for female bankers seeking work–life balance and offers insights for banking sector personnel and policymakers to develop effective strategies, contributing to the sector’s performance and economic growth.
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    PublicationEmbargo
    Human and Organizational Threat Profiling Using Machine Learning
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kumara, P.M.I.N.; Dananjaya, K.G.S.; Amarasena, N.P.N.H.; Pinto, H.M.S.; Yapa, K.; Rupasinghe, L.
    The usage of online social networking sites is increasing rapidly. But the downside is that the growth of various kinds of ongoing social media threats such as fake profiles, cyberbullying, and fake news. Many important observations can be made to increase the existing knowledge about social media threats by studying various information exchanged through public and organizations. One direction is to conduct studies on human behavior and personality traits using public user profile data and the organizational threat classifying. This research aims to build a system to predict human personality behaviors on social media profiles based on the OCEAN Model and company-based threat profiling. All the data collected relating to everyone in the consumer’s friend list is analyzed to obtain the threatening behaviors and classified according to the OCEAN to generate a threat report. Organizational network gathered log data for filtered log protection against malware. Logs received from these endpoints will be collected by collectors. Those logs will be forwarded to our filter, made of a Machine Learning Algorithm (MLA). This will be a custom MLA specially designed for this purpose. MLA will classify and categorize threats according to their severity, filtered log protection system against malware and other threats.