IRSPAS 2018

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/19084

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    Investigation of effort estimation practices in small-scale agile software products
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Mahisha, J. N. N.; Gunawardana, H. M. K. T.; Rathnayaka, R. M. K. T.
    Effort estimation plays an important role in software projects and reflects on their success. The effort of a software development project is generally defined as the time consumed by the project and can be expressed as the number of person-hours, days, months or years, depending on the size of the project. The agile software development methodology which is based on iterative development, generally evolves through the collaboration between selforganizing cross-functional teams. Therefore, the most of the software development projects have been following agile software development practices today. In this research, we mainly focus on Agile Scrum methodology. First, we investigated the certain parameters identified through the systematic literature review including size measurement metrics such as lines of codes, function point, component point, as well as involvement of team members, historical data related to the previous projects and expertise involvements. Through the systematic literature review 14 different parameters of the effort estimation process, the related effort estimation models were identified. From the identified 14 parameters, the most common and applicable 4 parameters were selected to build a questionnaire and got the feedback of 50 IT professionals during the survey study. Results obtained through the systematic literature review were put on to the taxonomy by considering their effect on each selected effort estimation model. The correlation among constructs was estimated using Pearson Correlation Coefficient. The study has revealed that there is a strongest relationship between the parameters namely, expertise involvement, team member involvement, historical data and number of lines of codes to the effort of a software development. For more accurate estimates, the most influential factors are the involvement of expertise, involvement of team members and the use of historical data, respectively.
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    Image-based user fee charging system for expressway in Sri Lanka
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Kaluarachci, T. T.; Kumara, J.
    Road network development plays a vital role in national development of a county. Even though there is a broad road network in Sri Lanka, most of them were built about 50 years ago and they are not having the ability to cope with the increasing traffic volumes. Therefore, recently Sri Lanka Road Development Authority has proposed expressway system (Commonly called as highway) to amend the road network to meet the growing transport requirements of the country. All E-Grade highways in Sri Lanka are proceeded of paying user charges. But currently the process of charging user fee is handled in a manual way completely. When a vehicle enters the highway, an electronic ticket will be issued at the toll gate of the interchange which mentions the type of the vehicle and the name of the interchange entered. You have to handover the ticket received at the entering toll gate, when you are entering to the exit toll gate, and you will be informed the traveling charge based on the vehicle type. A receipt will be issued after the payment of travelling charge. Payments can be made only through cash. After finishing the payment, the toll gate barrier will be opened and can pass through the lane. Current charging system has led to the wastage of time, the delay on expressway and increase in labor cost. Motivated by this manual system, this research is proposed an automated user fee charge system using image processing concepts and distributed database management. In this system, at the entrance point, number plate of the vehicle is captured by the surveillance camera in highway which is used to mention the starting point of the journey to the database. Moreover, the driver and the front passenger are checked to use safety belts before enter the highway. At the exit point, number plate of the vehicle is again captured. Finally, vehicle number is used to get the type of the vehicle from the database and the charge for using the highway is calculated accordingly based on the entrance and exit points mentioned on the database. Seat belt detection of both driver and the front passenger was done by extending H. Guo et al.’s image-based seat belt detection study. Number plate recognition was done by applying color-based approach. A distributed database was created by interconnecting databases at each interchange in the highway. This system was implemented using C++, open computer vision library and New SQL database. The proposed system was evaluated using 100 real-time images. Accuracies of 86% and 95% were obtained for correct identification of seat belts of both driver and front passenger and number plate detection, respectively. Thus, the proposed system has a higher accuracy for the real time situation.
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    Impact of the big data technology stack in digital marketing performance
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Senarath, A. R.; Wickramarachchi, D. N.
    Digital marketing is one of the most technology consuming paradigm in successiveness in marketing world using various type of marketing platforms that are used to achieve various scenarios like achieving social concurrency using rich media contents, personalization of consumers, email marketing, real-time marketing and more. Achievement of this phenomenon has been formed through monitoring behavioral patterns and profiling of consumers, web analytics (measuring engagements, adoption, and retention), elastic server storages, real-time processing, predictive analysis, reporting, Artificial Intelligence (AI) and more digital objects. The corresponding digital objects possess some decision factors that influence the performances itself identified as handling huge volumes of data, range of data modeling, data integration concession, supporting algorithmic queries, real-time support, amount of administration overload, uptime load without disruption in the view of the technical level. Those factors are not constant in providing feasible approaches to come across various marketing strategies. Therefore, depend on a single underlying platform is rarely found in enterprises utilization which makes it difficult for the extensity in marketing processes to expand on the existing system. More marketing features denotes the higher dimensionality of data collections through dynamic streams for storage that is a matter in the integration of data, hence identifying the cardinality of a unique data set in clustering is difficult in reporting and analyzing to acquire detailed-by-customer level knowledge. When considering the bias between access paths in structured (modeled) and unstructured data in a large variety of data itself is critical which make it difficult to grasp features for further processing. When integration of data for storage, the nature of streaming data had made it difficult to join the streams in summation in performing the optimized queries on data to make them more structured. In the analytics perspective of view, the cause of complex process in analytics has driven the difficulty in user-friendly visualization and understanding of lower level results for the data scientists. The foresight of the domain can uplift by the effective use of unstructured data in real-time personalization that has the higher noise of interferences in storages that compound to pull off relevant data from a larger sink of unstructured collections for further real-time personalization. Since the objective is to improve the performance of the underlying system of extending features, the above areas are being focused to be improved. At a broader level of view, it is intended to achieve the above range of issues through an architectural model of big data technology stack. The techniques to overcome the challenges should be found before the design. The methodology is designed as mapping the lower level requirements and overlapped functionalities of identified marketing scenarios in modeled stack prioritizing key decision factors followed with the assembling the techniques found or implemented for the defined areas of challenges.
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    An application of image processing techniques in identifying herbal plants in Sri Lanka
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Azeez, Y. R.; Rajapakse, R. A. C. P.
    Sri Lanka which is a tropical country situated in South Asian region has a considerable collection of plant species have been utilized by generations as medicinal treatments for a variety of diseases. These diseases ranges from complicated situations such as diabetes, arthritis to cancer and are known to be completely cured using the traditional methods used in Ayurvedic medicines mainly extracted from herbal plants. Dissemination of knowledge regarding herbal plants is restricted mainly to very limited group of people and is passed down from generation to generation who practice traditional medicine. In this study, we therefore attempt to identify herbal plants using machine learning analysis in order to assist more locals to identify them. Among many herbal plants, 5 are chosen to analyze further in detail and the images of the plants will be acquired from social media, Institute of Ayurveda and Alternative medicine website and blogs related to Sri Lankan herbal plants creating a noisy web data set. Several existing algorithms will be analyzed in order to select the suitable algorithms to classify the selected 5 plants accurately and to suggest how they can be used for treatments as recommended by Institute of Ayurveda and Alternative medicine. The main objective of the study is to analyze the noisy image set using deep neural network architectures based on transfer learning, choose the best architecture and create a deep learning model that can be applied effectively for an application. The outcome of this study will be used by locals in identifying herbal plants accurately. The methodology includes gathering data from Institute of Ayurveda and Alternative medicine on plant details and transfer learning based on deep Convolutional Neural Networks used on noisy image set for processing them using tensorflow in a local computer. Images will be retrained on the available neural network architectures such as GoogleNet, Inception v2 and Inception v4 architectures, fine-tuned from pre-trained weights and then the best technique will be selected. The selected algorithm will be fine-tuned using data augmentation techniques on the labeled dataset and hyper-parameter tuning. Conclusively, this study will provide valuable information regarding the herbal plants and possible treatments and help to disseminate knowledge to future generations.
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    Identifying paddy diseases with image processing techniques in Sri Lankan context
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Ahamed, M. I. S.; Dimithrie, P. S.; Rajapakse, R. A. C. P.
    Agriculture is one of the main sectors in Sri Lanka for ages and rice cultivation plays a major role in Sri Lankans' economy. Currently, farmers use traditional methods and they seek the advice of regional agricultural officers to recognize any unknown paddy disease. As a result, the efforts to increase the quality and quantity of rice production are obstructed by paddy diseases especially due to the lack of resources to identify them immediately. Thus, this study attempts to identify paddy diseases using machine learning techniques in relate with Image processing. Among many rice diseases, Rice Blast, Rice Sheath Blight and Bacterial Leaf Blight are focused to analyze further in detail as they are the leading diseases for major destructions in paddy cultivation. Several existing algorithms will be analyzed to select the suitable algorithms for accurate identification of the above three diseases and to suggest better solutions to overcome them as per the recommendations of the Department of Agriculture. Thus, the main object of the study is to analyze different machine learning techniques for the classification in image processing and to get the best technique which can be used effectively for the application. Increasing the disease diagnosing rate and to decreasing the crop destruction rate from these diseases are the main objectives of the study. The outcome of this study will be used by farmers in detecting paddy diseases without depending on others. The methodology includes gathering data from Rice Research and the Development Institute in Bathalagoda (RRDI) and some more images from field visits to the farms. Then MATLAB is to use for preprocessing the datasets to get qualitative images as a data preparation step. For this purpose, we have decided to use the hybrid version of a genetic-algorithm-segmentation based selective principal component analysis method for the feature extraction and develop a featured algorithm from the literature. After the feature extraction, classification will be done by analyzing Support Vector Machine (SVM), KNearest Neighbor (KNN) and Probabilistic neural network (PNN) from the literature and the best technique will be selected. The proposed solutions is to provide precise and scalable visual cues to identify diseases. Conclusively, this study will provide valuable information regarding the reduction of crop destruction from paddy diseases for a better future.
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    A literature review on software usability and software security alignment
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Gamage, E.; Wickramaarachchi, D.
    In this 21st century, computing systems have become an integral part of day-to-day human life. Human-Computer Interaction derived into the stage with the main focused subject ‘usability’, which attempts making software well-suited for people. However, focusing on usability of software is not good enough, at the same time systems should be secure. Even though importance of usability and security of a software is evident in the literature, no proper method is available to align usability and security of a given software product. Some of the significant work available in literature includes guidelines/ recommendations to resolve the trade-off between usability and security, ontological frameworks, usability and security evaluation frameworks, and assessments frameworks for usability and security requirements. Further, Human Computer Interaction and Security (HCI-SEC) group is formed to bridge the gap between usability and security under the main goal of “Usable Security”. Regardless of all these work, no proper solution is still available to align usability and security of a software according to its requirements. Our literature review identifies following issues in the literature which need attention of future researchers. They are: usability and security aspects have not been integrated into the initial stages of the system’s development process, treating security and usability as add-ons to the system, no proper way to assess usability and security. Similarly, in requirement engineering, security and usability both considered as non-functional quality attributes which can be measured and reflected only in later stages. This lack of observance on security and usability requirements along with their interaction, generates a gap in security and usability in final software product. Moreover, in software system, usability and security has an inverse relationship and there will be a point where security or usability cannot be optimized when the other factor (security/usability) reached a level which cannot be compromised anymore. Our literature review indicates that further research is required to avoid conflicts in optimizing usability and security at the early stage of software development life cycle considering user’s requirements.
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    An expert system for legal counselling in Sri Lanka
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Dissanayake, D. M. L. M.; Rajapakse, R. A. C. P.
    According to the Human Right Commission of Sri Lanka (HRCSL) publications and their reports, lack of knowledge is the severe problem in Sri Lankan legal system. In addition to this the major reason, lack of resources, lack of awareness raising program on legal matters, lack of confidence of public on presenting their legal problems are some minor reasons. Due to these problems, most of the Sri Lankans face many legal troubles in their day today life. They do not have clear understanding about their legal matters. To reduce these legal problems, they need to have a proper and efficient legal counseling service of an expert legal officer or an expert lawyer. Legal Aid Commission (LAC) is the main legal counselling provider in Sri Lanka. LAC has expert Legal officers to provide these services. However, the commission has limited number of resources. Every counsellor has a huge work load. In addition to the LAC, Institution of human rights and National Child Protection Authority also provide legal counselling. Although there are many legal counselling institutions in Sri Lanka, a decrease of legal problems cannot be observed. Due to these problems, there is an urgent need to develop a legal expert system for the people to get advised for their legal troubles. An expert system is a computer system which is having an ability to reproduction of logical decision-making process of human experts. It consists of a knowledge base and an inference engine. The goal of this study is to develop a software system to assist the preliminary counselling process. It will provide a primary solution to start their solving process of legal problems. This context considers only about the children’s and the women’s rights violations. Extracting the knowledge of the experts in relevant field by observing their counselling process is the first step for achieving this target. Main purpose is to identify the conditions that experts mainly consider when solving legal problems. On the knowledge of legal counselling experts, a rule-based engine has been implemented. For this purpose, information about the selected scenarios are represented by a series of if-then statements. Developing an expert system with a web interface is then carried out. Finally, it is to get the expert users’ feedback to arrive conclusion. Using this system end users can get guidance to their legal problem by selecting one or more answers from a list or by entering data. The developed software system will contribute to increase the legal awareness of the Sri Lankan people by providing a primary solution to their legal matters.
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    Modeling a user authentication & verification protocol for web applications using keystroke dynamics
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Kasun, D. T. S.; Jayawardane, B.
    With the advent of new technologies which surpass their predecessors, the impact of information on the lives of people has immensely proliferated. In this challenging and dynamic environment, the need for reliable computer security steadily increases. Biometric technologies are used widely to ensure the security aspect of a system. They are divided into two categories as physical biometrics and behavioral biometrics. Physical biometrics are based on direct measurement of various parts of the human body while behavioral biometrics are related to the behavior exhibited by people. Modern systems mostly do the authentication in the user login phase. In this phase, authenticating a user with a username and a password is done. This is named as the static authentication. There are also some systems that do the authentication passively when the user is working in the session. This is called the continuous authentication. In both types of authentication processes, we can utilize keystroke dynamics for user authentication. It is a behavioral biometric which concern about the typing pattern of a user. The objective of this research is to develop a secure user authentication and verification model for web applications using keystroke dynamics based on the time dimension which includes static authentication for user authentication and continuous authentication for user verification. The time factor will be considered in building this model since the way a person types can be different in various occasions due to various circumstances. Studying the previous work done related to keystroke dynamics in the behavioral biometrics domain was completed at the beginning of this research. Various measures such as dwell time and flight time used in previous works were considered when selecting most suitable measures used in keystroke dynamics. In the second phase of the research, development of the machine learning model will be done. The incorporation of suitable measures into the model using the machine learning technique selected will be done in this stage. In the final stage of the research, validation of the construction model will be done. An optimum population for validation should be selected at the start of this stage. Through this validation, the accuracy of model developed can be assessed. This constructed model expected to be more accurate and sophisticated since it incorporates both static authentication and continuous authentication into a single system.
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    A method to determine user location distribution pattern in a Wi-Fi network through SNMP protocol
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Abeysekara, A. M. R. B.; Jayawardena, B.; Wijayasiriwardhane, T. K.
    In today’s connected world, the biggest challenge that a network manager encounters is the allocation of the bandwidth within the network in response to the user requests to increase it in different areas of the network. However, due to the limited bandwidth provided by the service provider, in most of the situations, the network manager would not be in a position to increase the bandwidth as much as the users’ request. This is because to increase the bandwidth in a particular area, it requires to decrease the bandwidth in some other area in the network in order to maintain a maximum utilization of the provided bandwidth in the entire network. On the other hand, in every network there is a pattern of user location distribution. As a result, some areas in the network require more bandwidth during a certain period of time due to the more users located in that area during that period of time whilst the other areas may not need that much of bandwidth due to the lesser number of users located. Therefore, if the pattern of user location distribution of a network can be determined, the network manager can dynamically allocate a different amount of bandwidth to the different areas of the network accordingly. In this research, we propose a novel method to determine the user location distribution data in a Wi-Fi network using Simple Network Management Protocol (SNMP protocol) and thereby to identify any pattern of user location distribution against the time. In our method is, first we get the information such as MAC addresses, IP Addresses using SNMP protocol from the routers in the network. From that information, we then get the location distribution of the users based on the router’s location. We use that information to do pattern analysis and the location distribution pattern against the time is then determined. Our aim is to provide a more rational approach for network managers to allocate different amounts of bandwidth to different areas in their network while maintaining a maximum utilization of the provided bandwidth in the entire network.
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    Blockchain based solution for Sri Lankan agricultural supply chain to ensure food security
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Basnayake, B. M. A. L.; Rajapakse, R. A. C. P.
    Low quality agricultural products are added to the market daily. Overuse of chemicals in the production process, using uncertified chemicals and mechanisms for preservation and ripening processes, are the major issues with an impact on agricultural product’s quality as well as overall health of the consumers. Mechanisms for identifying the quality of the agricultural products are highly demanded due to the lack of transparency in the current process. A crowd-based decentralized certification system is required instead of a central authority to certify the products. Blockchain technology is emerging as a decentralized and secure infrastructure which can replace involvement of a third party to verify the transactions within the system. The purpose of the research is to implement a blockchain based solution to verify the food quality and the origin of the agricultural supply chain. The data on the transactions, existing certification process, actors and their roles within the Sri Lankan agricultural supply chain context were identified and collected through self-experience and related institutes. The Agricultural department's Good Agricultural Practice certification process was studied to get data on the existing certification process. Furthermore, Hector Kobbakaduwa Agrarian Research and Training Institute’s publications were used to gather data on local food supply chain. All the actors who are engaged with the supply chain must be able to interact with the system to achieve the goal. Each transaction and events related to a product is validated by peers of the blockchain system. Product ownership is changed for each relevant transaction. A token-based mechanism is used to indicate the farmers’ reputation with their products. Farmers can place a certification request regarding their products and, they can be gained reputation tokens for each certification done by peers. A unique Quick Response (QR) code is used to identify each product container or package. In each step of the supply chain, the QR code is used to validate physical product with the virtual product. Consumers will be able to ensure the origin and the quality of each product by scanning the QR Code, with the mobile application. The proposed system will be implemented, following a systematic review of a literature as well as a series of interviews with stakeholders, as a prototype on a private blockchain and validated with the involvement of real users to arrive at conclusions.