IRSPAS 2016
Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/15651
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Item Impact of teamwork quality on software development project success: Sri Lankan context(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Kumari, P.D.R.S.; Wijayanayake, W.M.J.I.Software has become a very crucial in all facets of modern world by the growth of technology. A software development project (SDP) can be viewed as a set of activities performed by a set of developers. Software development is a complex activity that requires teamwork effectively. Teamwork is a dynamic process of working collaboratively with a group of people in order to achieve a goal. According to the literature, Software project success can be measured using four indicators namely, cost, quality, time and scope and there is a significant relationship between teamwork quality (TWQ) and SDPs success. Most of researchers have done their research works on teamwork for German and Dutch SDPs. However we cannot apply these findings direct to Sri Lankan context. As found literature of social and cultural factors can be effect to performance of software development project. The main objective of this research is to come up with a framework to explain impact of TWQ for SDPs success. To achieve that objective, conceptual model was developed as mention in the figure. The model was derived from different models which are found in literature. Then the indicators which are used to measure TWQ factors and the SDPs success are identified. This study focuses on Qualitative Research approach and questionnaire is used as the technique of data collection. Participation selection is done through snowball sampling, making use of our network to make contact with organizations to ask for their willingness to participate. TWQ on SDP success is gaining an increasing interest within both academia and industry. The reasons for making this kind of research supporting strategic and operational management of SDPs to organize teams more efficiently and effectively. Our research work has ability to solve actual delay incurred by a software project due to lack of TWQ due to lower performance of team members. This is useful for Sri Lankan software industry to build and manage teams more constructively and adjust their management activities to improve team collaborations and team performance.Item Effect of information system resources and capabilities on firm performance: Evidence from apparel industry(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Udawaththa, P.; Wijayanayake, W.M.J.I.Information systems (IS) play a vital role in almost every organization compared with all other resources in a firm. Organizations mostly rely on information systems to carry out and manage their operations, interact with their customers and suppliers and compete in the marketplace. So examining the contribution of IS resources to firm performance is critical in the current environment. In apparel industry, Information Technology (IT) with IS has become an integral part. Like service industries, few departments of the apparel industry are fully depended on IT or Enterprise Resource Planning (ERP) Systems. There are so many recent cases in the world which provides us better evidence on how critical IT is in an apparel industry. Since the apparel industry being the no one leading contributor to the export revenue , understanding whether and how IS resources have affected the firm performance in apparel industry is an important research area to carry out a study, as it allows the management to know the value of their IS investments. Some research studies that have been carried out so far posit a direct relationship between IS resources/capabilities with firm performance, while others have questioned the direct-effect argument and emphasized that IS resources/capabilities are likely to affect firm performance only when they are deployed to create unique complementarities with other firm resources. So the main objective of the research is to identify the effects of IS resources and capabilities on firm performance in apparel industry. An empirical test will be performed on a selected sample with reference to the apparel industry in Sri Lanka in-order to achieve the objective mentioned in the research. As an initial step, existing information system resources and the capabilities in each selected firm will be identified. Then the extent to which IS resources are deployed in the firm will be identified. A quantitative methodology will be employed. Data will be collected through surveys using questionnaires on a five-point Likert scale, interviews with IS specialists, system analysts and data administrators relevant to each firm. The conceptual model that has been developed referring to literature will be tested by the questionnaire for applicability. Questionnaires will be based on the variables and their indicators identified from the literature. Questionnaire will be tested with a sample for validity and will be based on self-assessed scaled items. Data collected through descriptive methods will be analyzed using descriptive statistic techniques to find out the relationships with the independent and dependent variables. The partial least squares multivariate technique will be used to analyze the data. The empirical results will be then analyzed to develop the implications for Sri Lankan business managers.Item Study on knowledge management practices in software development industry in Sri Lanka(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Gunawardhana, A.; Wijayanayake, W.M.J.I.In the information age with expanded global market, many organizations compete for higher profit margins. As a result, using previous knowledge for redesigning and integrating business processes to increase operational efficiencies has become a necessity. Furthermore, organizations can improve quality of products and services by collective body of knowledge offered by employees of these organizations. Software development process is a knowledge-intensive process. Therefore, with the increased complexity of Software Engineering (SE) project work, knowledge processes have led to a greater dependency upon solving problems. Software organizations gain local experience with the time by completing lots of SE project works, careful measurement of planned software activities, trial and error, feedback from customers and from the environment in general. However, for better implementation of Knowledge Management (KM) practices, organizations need to be supported by right kind of people, process and technology. Organization’s people, processes and technology will at all times are either enablers of, or barriers to, effective knowledge management. Therefore, it is very important to identify the barriers and remove them and build enablers which support the effective KM practice within the organization. This study is built around this people, process and technology model. Therefore, people, process, technology are independent variables and effectiveness of KM is the dependent variable. This study was undertaken to analyze key factors affecting to the effectiveness of KM, finding out the percentages of each people, process, and technology factors impact to the KM in software industry and as the main objective, study the current KM practices in Sri Lankan software development industry and find out the best KM practices. The study is descriptive in nature. Stratified sampling technique under probability sampling design will be used to select the samples. Primary data will be collected from the samples by administering a structured questionnaire. The data will be collected from small to large KM practicing companies. Correlation and coefficient analysis, multiple regression analysis and ANOVA will be carried out on the collected data to derive the findings. With the time by working on different projects, employees gather unique knowledge from their experience. The results of this study will help managers to facilitate adoption of KM and prioritizes its practices.Item Predicting landslides in hill country of Sri Lanka using data mining techniques(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Karunanayake, K.B.A.A.M.; Wijayanayake, W.M.J.I.A landslide is the movement of rock, debris or earth down a slope. They result from the failure of the materials which make up the hill slope and are driven by the force of gravity. When it refers to Sri Lankan context landslide is the major natural disaster in hill country of Sri Lanka, creating economical and ecological damage while endangering human lives. Therefore, the fast detection plays an important role in avoiding or minimizing the hazards. Currently in Sri Lanka National Building Research Organization (NBRO) under the Ministry of Disaster Management in Sri Lanka issue landslide early warning messages based on Landslide Hazard Zonation Map and readings of auto meter rain gauging. However, a map is only covering a specific point in time, and do not take current weather and geographical conditions into account. Though they collect current rainfall using auto meter rain gauging this facility is not established in everywhere. As the hill country is a rapidly developing area some causative factors can be changed time to time due to human intervention or natural incidents. Therefore, it is understood that there has a problem in predicting landslide depending on current situation. On the other hand, to deal with the current approach there must have an expert. The main objective of this study is to develop a model which can be embedded to develop an user friendly and efficient computer program which is usable by any ordinary person who is living in a landslide prone area to determine “am I safe in the current place with regards to current geological and weather condition?” by dealing with data of current situation rather than living blindly until NBRO issue warnings. Most of the time landslides often occur at specific location under certain topographic and geologic conditions within the country and it is important to utilize existing data to predict landsides. Data mining techniques can be used to develop prediction models using existing data. Plan-Do-Check-Act data mining methodology has been selected for this study. Initially, study is limited to homogeneous areas of Badulla and Nuwara-Eliya districts which are already identified as landslide prone areas. Based on the homogeneity of these areas models will be developed by incorporating only three causative factors, slope, surface overburden, land use which are varying due to human intervention and natural incidents and triggering factor, rain fall. The historical data are collected using the contours, map of land use, map of overburden and map of landslides. The decision tree algorithm and the neural network technique will be used to develop prediction models out of predictive analysis data mining techniques. The cross validation evaluation technique will be used to test the models and ultimately select the best model out of decision tree algorithm model and neural network model.Item An online news crawling framework for an aggregated news site(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Wagawaththa, W.A.I.K.; Wijayanayake, W.M.J.I.The internet has become one of the most widespread platforms for information exchange and retrieval as the number of news websites is increasing rapidly. During the last decade, most of the major newspapers have developed web sites providing news and other information. In addition, web-only newspapers have also appeared. News aggregator is a good substitute for news sites like BBC news. Because news aggregators can index not just the content of the BBC news but all other news sites, giving it a huge advantage in coverage. On the other hand, news aggregators may complement online news sites. Because news consumers incur costs (time and effort) in searching for news that are important to them and also they will compare the expected benefit from visiting a news site to the expected search cost, where that cost includes becoming aware of the existence of the site and finding how to navigate it. There are few news aggregators like Google News, News Look Up, Fark which provide news aggregation facilities, but they are proprietary and there are privacy concerns about the user along with the biasness of these aggregators. In order to benefit more from the available information, the objective of the research is to develop a technical framework, gathering online news and approach to recognize most important latest news and display the recognized news items that society is interested in without any bias. Presenting crawled news items in a way that it displays the trending topics in society will increase the awareness of the reader. In order to do that news classification and ranking is a needed. News items for the framework will be gathered through (RSS) feeds. Gathered news feeds will be stored and will be preprocessed. Keywords will be extracted from an algorithm that can be worked with any language that has basic Morphological tools for language processing. Category classification of the news items will be done using a method that is based on the keyword extraction algorithm. Topic detection and classification of the news items will be done to the category classified news items using an algorithm that requires no corpus for statistics or training data. The ranking of the news article, topic and source will be done using an approach which is based on the virtual graph model. In the ranking process, similarity between articles are calculated manually and it will be automated using the cosine similarity.Item Analysing mobility patterns of people to determine the best transportation method(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Senanayake, J.M.D.; Wijayanayake, W.M.J.I.With the technological enhancements related to Internet, Wireless Communication, Big Data Analytics, Sensor-based Data, and Machine Learning; new paradigms are enabled for processing large amount of data which are collected from various sources. In the past decades, both coarse and fine-grained sensor data had been used to perform location-driven activity inference. In recent years, GPS phone and GPS enabled PDA become prevalent in people’s daily lives. With such devices people become more capable than ever of tracing their outdoor mobility and using locationbased applications. Based on the collected data from these GPS enabled devices with the help of IoT related to user mobility lots of research areas are opened. In this research the data related to user locations when users do any outdoor movements is collected using the mobile devices that are connected to the Internet and is mined using data mining techniques and come up with an algorithm to model & analyse those big data to identify mobility pattern, traffic prediction, transportation method satisfaction etc. The data for this research will be collected using a mobile application which has to be installed in smart devices like smart phones, tablet PCs etc. In this application the user has to enter the activity that he or she currently doing and the method of transportation & the users' opinion on the transportation method if he is doing some sort of travelling. The GPS coordinates (longitude & latitude) as GPS trajectories along with the time stamp and the date will be automatically acquired from the users' IoT device. A cloud based storage will be used to store collected data. Since the dataset is going to be a huge one, there can be data which contains outlier values due to the uncertainty of the mobile network coverage and the GPS coverage of the devices. Therefore, these data should be properly cleaned when doing data mining activities otherwise these data will lead to incorrect results such as wrong traffic prediction in certain places if several users are stuck in the same GPS coordinates for a while. Not only that but also when it comes to the user satisfaction, it might lead to generate incorrect outcome if the users in the sample will not enter their satisfaction accurately. This can be avoided by comparing cluster wise users with the consideration of the location and the transportation method. We can get the average opinion of the users and take it as the satisfaction of the transportation method in that cluster. Using the final results of this research the government can also be benefited if we selected the sample users well with mixing all the types of people and by providing necessary information for planning smart cities.