Scopus Index Publications

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This collection consists of all Scopus-indexed publications produced by SLIIT researchers. Scopus is recognized worldwide as a leading and reputable academic indexing database.

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Author: search.filters.author.Lokuliyana, S

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    Driving Innovative Culture with Emotional Intelligence
    (IEEE, 2023-06-12) Rizwi, A; Lokuliyana, S
    This research aims to examine the relationship between employee innovation and positive and negative contagion within supervising roles. Establishing an innovative culture within the organization and having managers with a high level of Emotional Intelligence are essential. As a result, this enables the study to examine the effects of these factors on employees. The study is evaluated the effects of adopting an innovation culture and working with managers who are emotionally quotient on the performance of the employees. In the corporate sector, innovation takes place under different conditions than in the private sector. Human beings experience emotions daily. An employee survey of 40 items (5-point Likert Scale) is distributed. A total of 200 surveys have been evaluated. The validity and reliability of the data were checked using SPSS, and the results were assessed using regression analysis. It involves constructing a confidence interval based on a single sample and a given level of confidence. The findings indicate that Emotional Intelligence, innovative organizational culture, and employee performance are meaningfully related. In conclusion, organizations must create innovative institution cultures and employ managers that have high levels of Emotional Intelligence to increase their employees' performance using the application of innovation.
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    Tempcache: A Database Optimization Algorithm for Real-Time Data Handling in Indoor Spatial Environments
    (IEEE, 2018-08-08) Jayakody, A; Murray, I; Hermann, J; Lokuliyana, S; Dunuwila, V. R
    The unstable arrangement of modern indoor environments has made navigation within buildings a difficult task. Hence, this paper introduces the AccessBIM framework, which is an efficient real-time indoor navigation system that facilitates in generating a real-time indoor map by crowdsourcing spatial data through the sensors available in mobile devices of navigators. The framework is equipped with a database optimization algorithm known as “Tempcache” which reduces the time and cost of searching data by examining the AccessBIM database for previously navigated paths, thus enabling faster data retrieval through efficient query processing. A simulation of a virtual environment similar to an actual indoor environment was used to test the algorithm. The significance of the algorithm was validated by comparing the total map generation time before and after the algorithm was applied for which the results demonstrated a reduction in map generation time with the use of the algorithm. The framework is also capable of capturing localization information with the support of i-Beacons which is then stored in a cloud server.
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    Location based garbage management system with iot for smart city
    (IEEE, 2018-08-08) Lokuliyana, S; Jayakody, A; Dabarera, G. S. B; Ranaweera, R. K. R; Perera, P. G. D. M; Panangala, P. A. D. V. R
    Smart cities integrate multiple ICT and IOT solutions to build a comfortable human habitation. One of these solutions is to provide an environmentally friendly, efficient and effective garbage management system. The current garbage collection system includes routine garbage trucks doing rounds daily or weekly, which not only doesn't cover every zone of the city but is a completely inefficient use of government resources. This paper proposes a cost-effective IOT based system for the government to utilize available resources to efficiently manage the overwhelming amounts of garbage collected each day, while also providing a better solution for the inconvenience of garbage disposal for the citizens. This is done by a network of smart bins which integrates cloud-based techniques to monitor and analyze data collected to provide predictive routes generated through algorithms for garbage trucks. An android app is developed for the workforce and the citizens, which primarily provides the generated routes for the workforce and finds the nearest available smart bin for citizens.