http://ir.lib.seu.ac.lk/handle/123456789/5397 2026-04-28T14:09:47Z http://ir.lib.seu.ac.lk/handle/123456789/5442 Web based staff management system – development for the establishment branch of university Kuleswararajan, Ushamini; Sathiyanathan, Jayanitha; Vivekanantha, Sanjeevan In this world of growing technologies everything has been computerized. With large number of work opportunities the human workforce has increased. Hence, it’s necessary to maintain the staff records in well-organized way. Many organizations specially the government institutes are still using the traditional methods which are purely paper-based to store the data of their employees. This waste the time to generate reports or search for employees’ records and loss or damage of files. Thus, there is a need of a system which can handle the data of such a large number of staff in an organization. This paper discusses the development of a computerized staff management system to the Establishment branch of Vavuniya campus, University of Jaffna. The need of staff management system was analysed through the survey and discussion with respective personnel and it was 84.9% positive response for the development of the system. The web based staff management system was developed using ASP.NET while the database designed using MYSQL to maintain the staff details, calculate the monthly salary of the staffs, forward the salary increment particulars to the financial branch, maintain reports of the work and salary of the staffs etc. This can pave way for the efficient management of the staffs of each particular department & improvement of the organizational performance. 2020-06-25T00:00:00Z http://ir.lib.seu.ac.lk/handle/123456789/5441 Payment histories in digital games – a way to more transparency Christian Lohse, Philipp This paper discusses the public acceptance of the mandatory implementation of payment histories in digital games in multiple countries. The presented data in this study was collected by an online survey in July 2019. Showing a payment history inside digital games is appreciated by the majority of survey participants. Determinants that represent the increase of transparency or fairness highly influence the appreciation for a payment history. 2020-06-25T00:00:00Z http://ir.lib.seu.ac.lk/handle/123456789/5439 Nexus between quality of smartphone online banking application and customer retention Manjula Madushani, Hewage; Rajeshwaran, Nadarajah Nexus between quality of smart phone online banking application and customer retention is still obscure as per the previous finding, particularly in Matale district. Objectives of the study have three folds, first, to identify the extent of quality of the smartphone online banking application as well as customer retention, second, to examine the impact of smartphone online banking application on customer retention and third, to examine whether quality of the smartphone online banking application varies among demographic factors of customers in selected banks. The study was undertaken by collecting the data from two hundred banking app users of selected banks in Matale via structured questionnaire (Google Form). Univariate, bivariate analysis (correlation and regression) and ANOVA and Independent Sample T test were applied to analyze the data with SPSS. Results showed that, perceived usefulness, perceived ease of use and perceived trust are very high level though the perceived risk is very low level. Further, perceived usefulness, perceived ease of use and perceived trust are positively and significantly associated with customer retention while it has a negative insignificant relationship with perceived risk. Finally, it is concluded that perceived usefulness, perceived ease of use, perceived trust positively and significantly impacts on customer retention, whereas perceived risk insignificant negative impacts on customer retention. Moreover, perceived quality of the smartphone online banking application varies among types of occupation of customers while perceived ease of use is varied among educational level. Findings of the study would be helpful to software designers and managers of banks to further enrich the applications to retain the customers. 2020-06-25T00:00:00Z http://ir.lib.seu.ac.lk/handle/123456789/5438 Training computers to recognize facial expressions of humans: a machine learning approach Mohamed Nizzad, Ahamed Rameez; Kunarakulan, Kunaratnam Humans are precise in facial expressions and recognizing them. Facial expression is a routine task of humans. Training Computers to recognize such humanly task as closed to humans can be useful in numerous ways such as offering services as per the mode of consumer or user and will enhance the phenomenon of human computer interaction. Environment and surroundings are the sources from where humans naturally learn the models of facial expressions and they have logical models in brain, and with the comparison of models, they are able to recognize the expressions of others. This research aimed to design and develop a robust facial expression recognition system by combining various techniques available in Computer Vision and Machine Learning. Hence, it was crucial to understand the human psychological aspects of facial expression in a precise manner. For the training and demonstration purposes, human volunteers were utilized along with facial expression dataset such as CK+ from internet. Local Binary Patterns (LBP) and Convolutional Neural Network (CNN) were occupied for feature extraction and optimization respectively. In addition, different kinds of AI based tools and techniques were employed to mimic the human ability of recognizing facial expressions. The outcome presents a novel approach to facial expression recognition with modified LBP and CNN. The outcome of the research suggests that further studies and optimization would lead to commercially viable solutions such as products or services as per the expression and emotions of the consumers. The researchers will continue to optimize the outcome to supersede humans in recognizing facial expressions in future 2020-06-25T00:00:00Z