Smart computing & Systems Engineering - (SCSE - 2019)
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Item Analysis of Factors Influencing the Virtual Learning Environment in a Sri Lankan Higher Studies Institution(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Charanya, R.; Kesavan, M.A project is commonly acknowledged as a successful project when the aim of the project is achieved positively. A system called Virtual Learning Environment (VLE) was designed among the students and university academic staff to encourage a positive approach in knowledge achievement and support active learning within the university. This study was carried out to analyze the factors influencing the VLE system and explore the relationship between the students and university academic staff on the system. The factors influencing VLE were identified through the literature review and the interviews which were conducted among the university academic staff and the industry experts. A paper-based questionnaire survey was carried out among the students and university academic staff in order to measure the severity of the factors influencing the VLE system. The respondents chosen for this study were the undergraduate students and university academic staff from Vavuniya Campus of the University of Jaffna, who used the above created VLE system. There were 120 responses from the students and 30 responses from the university academic staff. The students and university academic staff were requested to indicate their level of contribution on various factors in the survey questionnaire with a 5-point Likert scale and the Relative Importance Index (RII) was calculated for each factor. The severity of each factor was identified based on its RII value. The factors were ranked based on their severity and Spearman’s rank correlation coefficient was calculated. It was found that there was 26.9% of positive degree of agreement between the students and university academic staff on the factors influencing VLE. This paper also explores some recommendations to improve the usage of VLE systemItem An Application of Transfer Learning Techniques in Identifying Herbal Plants in Sri Lanka(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Azeez, Y.R.; Rajapakse, C.Sri Lanka has a considerable collection of plant species that have been utilized for generations as medicinal treatments. Knowledge regarding herbal plants is restricted mainly among practitioners in traditional medicine. Available systems studied; had no proper methodology to search information regarding herbal plants, which can be identified through analyzing an image of an herbal plant given. Systematic literature review was done based on herbal plants in Sri Lanka, transfer learning and plant image recognition and two open ended interviews were conducted with traditional medicine practitioners. As main objective of the study, reorganization of Information was done building a technique to enhance capability of identifying herbal plants based on deep convolutional neural networks and image processing techniques which would ultimately assist more locals with identification. Five herbal plant types were chosen to analyze further in detail and the images of the plants were acquired from web and also images photographed via 13MP camera creating a data set validated through traditional medical practitioners. Images were preprocessed and retrained on Inception-v3, Resnet, MobileNet and Inception Resenet V2 based on transfer learning. Algorithm was finetuned using image processing techniques for preprocessing and prototype was tested 5 times reaching highest average accuracy of 95.5% on Resnet for the identification of 5 different plant types. Conclusively, this study enhanced the capability of searching herbal plants by reorganizing the informationItem Automated, low-cost pedestrian crossing carriage for efficient traffic control and pedestrian safety(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Yasaswin, B.A.O.S.; Jinasena, T.M.K.K.Disorganized city planning and a huge rise in use of automobiles on the road have caused massive traffic congestion in cities across the world. Pedestrian crossing designed to facilitate movement across the road network, have unfortunately become a hindrance to movements of traffic. Though the smart zebra lines had been introduced, it has not contributed much to reduce the time that holds vehicle lines under the traffic lights. Moreover, the establishment of transfer hubs and underground crossings remain silent in local context because of their cost. Even though there are plenty of pedestrian crossing mechanisms available, they are not secure and not ideal for the disabled, elderly, children, and the sick. Considerable numbers of police officers have to spend their time on traffic controlling duties though it’s inefficient and wastage of human resources. A number of studies have focused on automated vehicles and robots as tools to ease problems of congestion. This paper, it focuses on the design of an automated guided carriage system for pedestrian transportation in an efficient and secure mannerItem A Blockchain-based decentralized system to ensure the transparency of organic food supply chain(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Basnayake, B. M. A .L.; Rajapakse, C.Low quality agricultural products are added to the market daily. Over usage of chemicals in the production process, use of uncertified chemicals and mechanisms for preservation and ripening processes, are the major issues that impact on agricultural product’s quality as well as overall health of the consumers. Mechanisms to identify the quality of the agricultural products are highly demanded due to the lack of transparency in the current process. 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 was to implement a Blockchain based solution to verify the food quality and the origin of the agricultural supply chain. A public Blockchain concept was selected instead of a private Blockchain in this study to ensure transparency by allowing any person to access the network. Instances of the smart contract were created for each physical product and deployed to Blockchain network. A Quick Response code which contained the address of the instance, was a reference to the virtual product. All the actors who are involved in the supply chain must be able to interact with the system to achieve the transparency. Each transaction and events related to a product is validated by peers of the Blockchain system. Product ownership was changed for each relevant transaction. A token-based mechanism was used to indicate the farmers’ reputation with their products. Farmers could place a certification request regarding their products and, they can gain reputation tokens for each certification done by peers. A unique Quick Response code was used to identify each product within the supply chain. The proposed system has been implemented as a prototype and validated within the studyItem Candidate Recruitment Based on Automatic Answer Evaluation Using WordNet(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kasundi, J.; Ganegoda, G.U.Any organization’s future survival in the industry mainly depends on the decisions they take today and recruiting a new employee is one of those critical decisions that an organization has to take. Recruitment process of an organization should have the capability to find the right person to the right job. Most of the organizations today, interview candidates to test their job skills but not their personality level. But recruiting the most skilled person does not work out in a good manner always. Especially for the positions like leaders, they have to consider about the personality of the employee. And also, in the industries like IT industry, employees are supposed to work in project teams but not individually. That is where personality matters the most. To work in a team, all the members should be able to corporate with each other without facing any difficulty. Therefore candidate recommendation chatbot system is suggested and it is capable of evaluating both technical skills and personality traits of the candidate and providing a final recommendation based on the scores obtained to those two sections. The system mainly contains four modules; Question Generation and Dialogue Flow Maintaining Module, Technical Answers Evaluating Module, Vocabulary Based Personality Evaluating Module and Candidate Recommendation Module. This paper will be discussing about the answer evaluation module of the system which contains an ontology to store java related technical questions and answers and has used WordNet to measure the correctness of the answersItem Communication framework for vehicular ad-hoc networks using Blockchain: Case study of Metro Manila Electric Shuttle automation project(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kulathunge, A.S.; Dayarathna, H.R.O.E.Vehicular Networks or the Vehicular Ad-hoc Networks (VANET) are experiencing revolutionary growth in research and industry, but still suffers from various breaches such as poor decentralization of communication, security vulnerabilities, scalability and trust issues in its communication as well as in its design. Major issues identified in VANET, are trust, data accuracy, and reliability of communication in the communication channel. Blockchain technology is a technology adopted by crypto currency, namely Bitcoin, which is recently used to build trust and reliability in peer-to-peer networks. This study proposes a communication framework for VANET exploring capabilities of blockchaining. Metro Manila Electric Shuttle Automation Project is used as a case study to verify the communication framework. It fulfills Vehicle-to-Vehicle (V2V) as well as Vehicle-to-Infrastructure (V2I) communication requirements of the considered project. It includes an Intelligent Toll Payment (ITP) system (V2I communication) and automated vehicular following, known as goose tracking (V2V and V2I communication), and those covering main communication requirements. Further, a simulator named SimulatorZ is implemented to model Goose Tracking which should support multi-vehicle simulation to understand data requirements of master and slave vehicles and the timing of communication. Communication framework provides trustworthiness for vehicles behavior, cashless secure transaction between two untrusted party as well as rewards and penalties for vehicles’ actions. Data communication in goose tracking is done with 10ms latency between two vehicles and 1-10-5 reliability. Slave vehicles’ movements depends on master vehicle’s speed, position, angle and the timestampItem Data Mining Approach for Identifying Suitable Sport for Beginners(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Amarasena, P.T.; Kumara, B. T. G. S.; Jointion, S.Anthropometric measurements are generally used to determine and predict achievement in different sports. An athlete’s anthropometric and physical characteristics may perform important preconditions for successful participation in any given sport. Further, anthropometric profiles indicate whether the player would be suitable for the competition at the highest level in a specific sport. Recently, more researches have been carried out on Sport Data mining. In this study, we propose an approach to identify the most suitable sport for beginners using data mining and anthropometric profiles. We propose clustering base approach. We apply a spatial clustering technique called the Spherical Associated Keyword Space which is projected clustering result from a three-dimensional sphere to a two dimensional (2D) spherical surface for 2D visualization. Empirical study of our approach has proved the effectiveness of clustering resultsItem Distribution cost optimization using Big Data Analytics, Machine Learning and Computer Simulation for FMCG Sector(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Adikari, A.M. C.; Amalan, T. P.Developments in information and communication technology has made significant impact on every sector. Unfortunately, limited research exists regarding information systems for the distribution networks in Supply Chain. This study made an effort to investigate the linkage between information systems and transportation cost optimization in FMCG (Fast Moving Consumer Goods) sector. Information systems should support the management at operational and strategic level. The study focused on the operational level implementation of information system with machine learning and big data analytics. Factors, variables and constraints affecting the cost of transportation were identified from industry experts and literature. Then a case study approach applied by analyzing the distribution network data of a Sri Lankan FMCG company. A quantitative model was developed to reflect the transport cost structure and a software model was developed considering the constraints and the cost structure, to reduce the cost of transportation by big data analytics, machine learning and computer simulation. Developed model has been compared with the existing model of transportation in the FMCG manufacturer to benchmark the optimization. In proposed model, the usage of vehicles are reduced, thereby minimizing the transportation cost by increasing the consolidation possibilities, route planning and stacking models.Item Face and Upper-Body Emotion Recognition Using Service Robot’s Eyes in a Domestic Environment(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Vithanawasam, T. M. W.; Madhusanka, B. G. D. A.The population of the elderly/disabled people of the world is increasing rapidly. Taking care of these people has become a major issue since lack of professional caregivers or family members. Hence, the only feasible solution for this is using humanoid service robots. Available care-giving service robots lack the proper human emotion recognition. Hence, they cannot communicate with people as humans do. In addition, it is not preferable to people when robots are not androids. Therefore, this paper has proposed a method to recognize a face and upper-body emotions by using service robot’s eyes. The service robot’s eyes model is able to track a particular person in a domestic environment to mimic human eyes’ behavior while providing visual feed for the system to recognize emotions. Face emotional expressions and upper-body gestures are recognized by using supervised learning methods. Finally, the results show that the trained system recognizes the emotions effectively in the domestic environment for a particular personItem Factors influencing Enterprise Information Systems adoption of Small and Medium Enterprises (SMEs): A case study on Sri Lankan manufacturing sector(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kaluarachchi, T.R.; Weerabahu, W.M.S.K.; Nanayakkara, L.D.J.F.Small and Medium Enterprises (SME) play a vital role in the Sri Lankan economy in terms of national output and employment as well as incubating innovative capabilities. In today’s highly competitive economy, small and mediumsized enterprises lack the resources and technologies to compete with large enterprises, although having a relatively high casualty rate. In order to survive in the competitive market and exploit opportunities, many small and medium-sized enterprises adopt Information Technology (IT) related applications. However, in the current context of IT Application usage, such as Enterprise Information Systems (EIS), the SME sector in Sri Lanka is lagging compared to other countries. Therefore, the need of adopting to EIS / other Information Systems related technologies is becoming a must or an urgent need in the context of establishing a competitive SME sector. Based on empirical evidence and review of literature this study captures significant factors that influence EIS adoption by SME in Sri Lankan context. The objective of this study is to recognize the real need of EIS based applications for the SME sector while identifying and defining the effectiveness of driving and hindering factors which affect the focus of SMEs adoption towards EIS based applications. Since cost based constraints was identified as a major barrier to adopting EIS based solutions, the increase of productivity and sales profitability are stated as main driving forces by the SME owners and industry experts. The results are expected to provide a practical contribution in the area of EIS adoption in the Sri Lankan Small and Medium manufacturing SMEs for better reinforcement strategies for successful implementationItem GPS guided auto-sensing system for motor vehicles(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Ranasinghe, D.C.R.; Wanniarachchi, W.K.I.L.; Anuradha, U.A.D.N.Driver errors are the most common cause of traffic accidents. Mobile phones, in-car entertainment systems, traffic volume increases, road systems becoming complicated contribute towards such driver errors. This paper introduces developing a GPS guided auto pilot system for vehicles. This system will be a driverless vehicle system. The user has to give the location of the destination to the system and then the system will automatically navigate to the given destination. These systems are currently used in aircraft, submarines and ships but not used in ground vehicles. Use of such systems in the open street is more complex than use of such systems in air or marine systems. The possible route to the destination must be selected by the vehicle after the destination coordinates are given by the user. Then the vehicle navigates through the open streets without colliding with other moving or non-moving objects. GPS sensor takes real time coordinates of the vehicle and decide the direction to be moved with respect to the given destination coordinates and pass control signals to the motor controller. While navigating, the vehicle keeps appropriate safe distance and speed with the vehicles in front of it. If the lane is not clear, the vehicle applies breaks to avoid collisions. Sonar sensors are used to detect the object in the road as they are more convenient in the outdoor applications. With further developments, this system will be able to assist drivers who drive long trips and play a vital role in minimizing road accidentsItem Green Cloud Computing: A Review on Adoption of Green-Computing attributes and Vendor Specific Implementations(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Jayalath, J.M.T.I.; Chathumali, E.J.A.P.C.; Kothalawala, K. R .M.; Kuruwitaarachchi, N.With cloud computing emerging as a trending topic, it has been a major point of discussion for the last few years. In regards to technological advancements, the associated shortcomings like environmental footprint caused by them also become an affair of high significance. Cloud computing itself is a much greener alternative to individual data centers with lesser number of servers being used and cloud data centers being far more efficient than those of traditional thereby reducing the carbon impact. Nonetheless, it cannot be neglected the fact that the data centers utilized by the cloud vendors are still a major source of carbon emissions due to the dirty energy usage. Therefore, the discussion of the paper is based on how green the foremost cloud providers are and the implementations of green IT attributes in the cloud infrastructureItem Implicit Intention and Activity Recognition of a Human Using Neural Networks for a Service Robot Eye(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Moladande, M.W.C.N.; Madhusanka, B.G.D.A.Introduction of the assistive robot concept has created numerous ways to restore vital degrees of independence for the elderly and disabled people on their Activities of Daily Living (ADL). The most important aspect of an assistive robot is to understand the user’s intentions with minimum number of interactions. Based on these facts, in this study we suggest a novel method to recognize the implicit intention of a human user, by using verbal communication, behavior recognition and motion recognition from the combination of machine learning, computer vision and voice recognition technologies. After recognizing the implicit intension of the user, the system will be able to identify the necessary objects from the domestic area that is going to help the human user and point them out to fulfil his/her intention. By far, this study is expected to simplify the human robot interaction (HRI) while consequently enhancing the adoption of assistive technologies and improving the user’s independence in ADL. These findings will certainly help to guide future designs on implicit intention recognition and activity recognition to an accurate intention inference algorithm and intuitive HRIItem Industry 4.0 maturity assessment of the Banking Sector of Sri Lanka(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Bandara, O.K.K.; Tharaka, V.K.; Wickramarachchi, A.P.R..Technological advancements have created massive changes in the way of performing businesses in this era. Whilst in creating the transition of physical world to a virtual world, industry 4.0 plays a significant role. Thus, the development of the concept of industry 4.0 revolutionize the way of conducting businesses. This concept was first limited to manufacturing sector thus with the evolvement of customer behaviour, service sector also applied these concepts to offer a better customer satisfaction. As modern customer expectations have risen with technology, Sri Lankan banking sector focussed to deliver their services strategy by enabling advanced technologies. Hence there is an essential need to define, formulate a set of guidelines in order to assess the progress of the current state of Sri Lankan banking sector in their journey of adapting industry 4.0. So, this scrutiny assesses the maturity of Sri Lankan banking sector by application of an industry 4.0 maturity model developed by the authors. The results of this study indicates that Sri Lankan banking sector is in the third maturity level of the model “Defined” as the overall maturity is 3.668.Item An Infectious Disease Medical Policy Simulation and Gaming(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kurahashi, S.This paper analyses a new type of infectious disease by an agent-based simulation and gaming model based on Ebola fever and dengue fever. The mathematical model such as SIR (Susceptible, Infected, Recovered) has been used to model these infectious diseases. Besides, a simulation and gaming model enables to represent the decision-making of each citizen on the computer, and al-so reveals the pandemic by the contact process among people in the model. The study challenges to design an infectious disease model in which some health policies are introduced including vaccine stocks, antiviral medicine stocks, medical staff and so on. Aside from the policies, a gaming simulation of a new type of infectious disease, which has not yet an effective vaccine, is also implemented in the model. We created a medical policy decision game dealing with infections using a serious game approach. As results of experiments, it has been found that preventive vaccine, antiviral medicine stocks and the number of medical staffs are crucial factors to prevent the spread. Besides, a modern city is vulnerable to dengue fever due to commuting by train. It has also been found that self-control and restraint on immigration are essential, and decision-making for vaccine reserve amount and medical support to the partner country where the infection has spread.Item Integrating Smart Transportation System for a Proposed Smart City: A Mapping Study(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Hettikankanama, H.K.S.K.; Vasanthapriyan, S.Smart transportation is playing a vital role as an important building block in smart city, providing solutions to many issues that relate to traffic on the road. This influences safety and quality of living (QoL) the main goals of smart city development. In such case, investigation of different aspects like different functionalities of smart transportation, purposes, research methods and technologies are obligatory. This study presents a literature review on existing researches on smart transportation in smart city to identify the area as well as the future research needs and gaps to be fulfilled. Here it summarizes different perspectives of smart city and smart transportation considered in studies, types of the researches performed, reported problems which are addressed in studies, purposes of deploying smart transportation, reported benefits and problems and technologies which are compatible in this research areaItem Language identification at word level in Sinhala-English code-mixed social media text(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Shanmugalingam, K.; Sumathipala, S.Automatic analyzing and extracting useful information from the noisy social media content are currently getting attention from the research community. It is common to find people easily mixing their native language along with the English language to express their thoughts in social media, using Unicode characters or the Unicode characters written in Roman Scripts. Thus these types of noisy code-mixed text are characterized by a high percentage of spelling mistakes with phonetic typing, wordplay, creative spelling, abbreviations, Meta tags, and so on. Identification of languages at word level become a necessary part for analyzing the noisy content in social media. It would be used as an intimidate language identifier for chatbot application by using the native languages. For this study we used Sinhala-English codemixed text from social media. Natural Language Processing (NLP) and Machine Learning (ML) technologies are used to identify the language tags at the word level. A novel approach proposed for this system implemented is machine learning classifier based on features such as Sinhala Unicode characters written in Roman scripts, dictionaries, and term frequency. Different machine learning classifiers such as Support Vector Machines (SVM), Naive Bayes, Logistic Regression, Random Forest and Decision Trees were used in the evaluation process. Among them, the highest accuracy of 90.5% was obtained when using Random Forest classifierItem Linguistics Analytics in Data Warehouses Using Fuzzy Techniques(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Asanka, P.P.G.D.; Perera, A.S.A data warehouse is used intensively in many industry domains to gain competitive advantage over its competitors. In modern data warehouses, linguistic analytics is an important aspect, so that it has the ability to take more precious decisions. In most of the data warehouse implementations, it is designed for crisp analysis. Crisp analysis has its own limitations and boundaries with the major assumptions that every situation belongs to one state and denial to other states. Hence, crisp data warehouse does not allow to carry out linguistic analytics. When a fuzzy data warehouse is implemented, because of the fuzzy nature of the data warehouse, linguistic analytics can be done to a certain extent. In this research, non-functional requirements such as performance and configuration are also covered so that this method can be implemented in the real worldItem Modelling & simulation of the hydration process of cement for rapid concrete constructions(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Sandaruwan, S.M.D.T.; Pallegedera, A.Hydration is series of exothermic reactions which occurs between cement and water. It is difficult to predict the exact behaviour of hydration process. It was modelled using Affinity Hydration model and was simulated using finite element approach and which was then validated with realistic parameters. Time dependent simulation has been carried out for various geometries to non-isothermal conditions inside the model. Modelling and simulation was performed in both polystyrene insulation and wooden insulation for different environmental conditions. Temperature, degree of hydration and rate of hydration was obtained using simulation and was verified with data from the realistic experimental data from literatureItem MRI based Glioma segmentation using Deep Learning algorithms(IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kaldera, H. N. T. K.; Gunasekara, S. R.; Dissanayake, M. B.Primary brain tumors can be malignant (cancerous) or benign (non-cancerous). Out of primary brain tumors, gliomas are the most common and, high grade gliomas carry a poor prognosis. In our paper, we present a technique to segment the glioma cells in Magnetic Resonance Imaging (MRI) using faster Region based Convolutional Neural Network (R-CNN) and edge detection techniques in image processing algorithms. This study identifies the region of interest that is glioma cells, with higher confidence level and localize the tumor on the MRI with the tumor mask. Further, analysis shows that with the proposed technique it is possible to achieve an average detection accuracy, sensitivity, Dice score and confidence level of 99.81%, 87.72%, 91.14% and 93.6% respectively