Smart Computing and Systems Engineering (SCSE)
Permanent URI for this communityhttp://repository.kln.ac.lk/handle/123456789/18936
Browse
Item Isolated Sinhala handwritten character recognition using part based matching technique(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Silva, C.M.; Jayasundere, N.D.This paper presents a novel approach for Sinhala handwritten character recognition using a part based matching technique. The Sinhala character set consist of some common parts. Therefore, the characters can be split into its parts. Each part in turn, can be considered as an atomic element, which these characters are composed of. The proposed method splits the characters into their atomic parts and then conducts the recognition process. Template matching is used to compare the character parts and characters. To improve the recognition process, the global characteristics of the characters are used. Experimental results show that the proposed method gives an average accuracy of 46% where the maximum accuracy is 100% and the minimum accuracy is 11%.Item An approach to coexistence analysis between agility and ERP implementation(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Rajakaruna, R.J.P.K.; Wijayanayake, J.Business organizations tend to re-engineer their business processes by adopting Enterprise Resource Planning (ERP) systems in order to gain a competitive advantage. ERPs offer countless benefits by enabling an enterprise to operate as an integrated, process oriented and real time enterprise. But the issue is re-engineering with ERP ranks among slow-moving, costly and challenging processes of an organization. Many ERP specialists regard agile approaches positively, to mitigate the common ERP implementation challenges. Agile implementation of ERPs is still under research area. This research discusses on the need of agile approaches in ERP implementations and how agility and ERP implementations can coexist. In this case our research question is “Can the common ERP implementation challenges be solved by using agile approaches?” and if so, “How these challenges can be solved?” This study also seeking for uplift the level of awareness on the applicability of agility for ERP implementation projects and these findings can be effectively used by ERP Implementers, Vendors, Consultants, Project Managers and Researchers in their respective projects.Item Improved hierarchical role based access control model for cloud computing(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Thilakarathne, N.N.; Wickramaaarachchi, D.Cloud computing is considered as the one of the most dominant paradigms in the field of information technology which offers on demand cost effective services such as Software as a Service (SAAS), Infrastructure as a Service (IAAS) and Platform as a Service (PAAS). Promising all these services as it is, this cloud computing paradigm still associates number of challenges such as data security, abuse of cloud services, malicious insider and cyber-attacks. Among all these security requirements of cloud computing access control is the one of the fundamental requirement in order to avoid unauthorized access to a system and organizational assets. Main purpose of this research is to review the existing methods of cloud access control models and their variants pros and cons and to identify further related research directions for developing an improved access control model for public cloud data storage. The paper presents detailed access control requirement analysis for cloud computing and have identified important gaps, which are not fulfilled by conventional access control models. As the outcome of the study an improved access control model with hybrid cryptographic schema and hybrid cloud architecture and practical implementation is proposed. The study tested the model for security implications, performance, functionality and data integrity to prove the validity. It used AES and RSA cryptographic algorithms to implement the cryptographic schema and used public and private cloud to enforce our access control security and reliability. By validating and testing we have proved that the model can withstand against most of the cyber-attacks in real cloud environment. Hence, it has improved capabilities compared with other previous access control models that we have reviewed through literature.Item A reinforcement learning approach to enhance the trust level of MANETs(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Jinarajadasa, G.; Jayantha, W.; Rupasinghe, L.; Murray, I.A Mobile ad-hoc network (MANET) consists of many freely interconnected and autonomous nodes that is often composed of mobile devices. MANETs are decentralized and self-organized wireless communication systems, which are able to arrange themselves in various ways and have no fixed infrastructure. Since MANETs are mobile, the network topology is changing rapidly and unpredictably. Because of this nature of mobility of the nodes in MANETs, the main problems that occur are unreliable communications and weak security where the data can be compromised or easily misused. Therefore, a trust enhancement approach to a MANET is proposed which is RLTM (Reinforcement Learning Trust Manager), a set of algorithms, considering Ad-hoc On-demand Distance Vector (AODV) protocol as the specific protocol, via Reinforcement Learning (RL) and Deep Learning concepts. The proposed system consists of RL agent, who learns to detect and give predictions on trustworthy nodes, reputed nodes, and malicious nodes and classifies them. The identified parameters from AODV simulation using Network Simulator-3(NS-3) were given to the designed RNN (Recurrent Neural Network) model and results were evaluated.Item Vehicle type validation for highway entrances using convolutional neural networks(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Juwanwadu, L.N.W.; Jayasiri, A.Vehicle type validation for Highway entrances using convolutional neural networks is an approach taken to automate the highway toll systems of Sri Lanka. Available automated highway toll systems in the world use sensor-based validation systems to validate the vehicles that are entering the highways. Mainteneance cost of these systems is high. A vision-based validation system has not been implemented, as yet. This paper introduces a vision-based method to validate vehicles for highway systems which can reduce the cost while increasing the efficiency and safety. A Convolutional Neural Network (CNN) model was developed to achieve this objective. The CNN model employed here uses a binary classification to categorize vehicles as allowed vehicles and non-allowed vehicles for entering the highway. The model developed here showed 86.69% accuracy. The model was manually tested for different vehicle types using a GUI based application and all the test images were successfully classified into their classes.Item Developing a concept to convert LD/STL to VHDL(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Dharmarathna, G.H.R.O.A Programmable Logic Controller (PLC) is a microprocessor based solid state device which is a very significant control component unit in industrial automation systems. Ladder diagram (LD) is a form of graphical language type PLC programming. LDs and Statement Lists (STL) are used to program PLCs. Both of these programming methods represent the schematics of electrical relay circuit diagram. Since LD programs are executed in a sequential and cyclic way, the operational efficiency and performance of PLC will be limited by the length of the ladder diagram and the operational speed of the microprocessor. Field Programmable Gate Array (FPGA) is a new technology used in industrial process control systems. VHDL (VHSIC-HDL- Very High Speed Integrated Circuit - Hardware Description Language) programming is used to program FPGA devices. Because of its parallel execution system and reconfigurable hardware structure, FPGA has excellent performance. Therefore, flexible and high speed systems can be implemented using FPGA. The main aspect of this research was to develop a concept to convert LD/STL to VHDL. By using Siemens - STEP 7 Micro/WIN - version 4.0.81 and Xilinx® – ISE Design Suite version 14.6 software, this concept was developed to convert Bit Logic LDs into VHDL. After identifying the Boolean logic of the STL code, inputs and outputs are declared in the entity part and PLC to FPGA conversion logic is defined in the architecture part of the VHDL code. To overcome the performance limitations of microprocessor based PLCs, FPGA based PLC implementation is suggested as a better approach.Item Intelligent traffic controller using image processing(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Fernando, J.J.R.S.; Jayasiri, A.Traffic congestion has become significant problem in recent years with the ever increasing number of vehicles and poor management of traffic. Traffic patterns are not constant throughout the day. They are changing from time to time. Since present traffic controllers have fixed time intervals for signal lights, they could not provide a better solution. Computer vision can be used to create an intelligent traffic controller which can adapt its time intervals according to the real traffic. Several studies have been carried out based on the concept of real time image processing to manage the traffic. In current traffic controllers, wastage of effective green time is occurred, as many times fixed green time period which is assigned for a phase is larger than it actually needs. Hence the other roads at the intersection have to wait in vain, with more traffic, until that fixed green time period is over. In the proposed method real time traffic image sequences are analysed using image processing, in order to obtain actual traffic area. Then, time for green light is allocated according to that traffic area. Hence, wastage of effective green time is eliminated by the proposed method since it allocates time to green signal that is sufficient to pass the actual traffic presented on the road. Results reveals, effective green time that need to pass the traffic, is proportional to the road area covered by traffic at that time.Item Automatic smart parking system using Internet of Things (IoT)(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Rishan, U.M.Internet of Things (IoT) plays a vital role in connecting the surrounding environmental things to the network. The IoT is a system of interrelated computing devices that are provided with identifier and the ability to transfer data over a network without requiring human and computer interaction. These type of technologies are used to connect un-internet devices to the network from any remote location. With the number of vehicles on the roads climbing steeply over the last few years, motorists face problems in parking vehicles in designated slots in the city. In this paper a Smart Parking System is designed which enables the user to find the nearest parking area and provide the information about the availability of parking slot to the motorist. The system mainly focuses on reducing the time of finding the parking area and avoids unnecessary travelling through filled parking lots in a parking area. Thus it reduces fuel consumption and minimizes carbon emissions as well.Item Swarm intelligence for urban traffic simulation: Results from an Agent-based modeling and simulation study of the Sri Lankan context(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Amarasinghe, U.G.L.S.; Rajapakse, R.A.C.P.Traffic congestion is a crucial issue affecting the quality of life of individuals all over the world. In a country like Sri Lanka where the traffic is mostly heterogeneous and unorganized, traffic congestion could be largely influenced by the behaviors of pedestrians and drivers. Due to the significant impact of traffic congestion to economic growth, various measures have been taken to reduce the urban traffic congestion, such as widening the roads, expanding the road network and constructing overhead bridges. However, despite all these approaches, traffic congestion still remains as a serious issue. We are of the view that the traffic congestion in Sri Lanka is largely depending on the behaviors of the pedestrians and as well as the drivers, which is something that is not adequately investigated yet. Therefore, we propose the Agent-Based Modelling and Simulation (ABMS) approach, which is a popular computational research method based on swarm intelligence to study complex social and economic systems (O'Sullivan and Haklay, 2000), for researching the impact of driver and pedestrian behavior on traffic congestion and evaluating different traffic control strategies. We used the ABMS environment called NetLogo to develop our simulator and the data collected at the Kiribathgoda junction in Western Province, Sri Lanka was to calibrate the model with accurate parameter values. Macroscopic statistics, such as the rate of traffic flow, average speeds and queue time were used to validate the model by comparing data from real traffic situations at Kiribathgoda junction with model outputs. The ultimate objective of this research is to come up with a cost-effective decision support system for administrators and policy makers to understand various reasons behind congested unorganized traffic environments in Sri Lanka and, thereby to make better-informed decisions to control urban traffic congestion.Item A data mining approach for the analysis of undergraduate examination question papers(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Brahmana, A.; Kumara, B.T.G.S.; Liyanage, A.L.C.J.Examinations play a major role in the teaching, learning and assessment process. Questions are used to obtain information and assess knowledge and competence of students. Academics who are involved in teaching process in higher education mostly use final examination papers to assess the retention capability and application skills of students. Questions that used to evaluate different cognitive levels of students may be categorized as higher order questions, intermediate order questions and lower order questions. This research work tries to derive a suitable methodology to categorize final examination question papers based on Bloom’s Taxonomy. The analysis was performed on computer science related end semester examination papers in the Department of computing and information systems of Sabaragamuwa University of Sri Lanka. Bloom’s Taxonomy identifies six levels in the cognitive domain. The study was conducted to check whether examination questions comply with the requirements of Bloom’s Taxonomy at various cognitive levels. According to the study the appropriate category of the questions in each examination, the paper was determined. Over 900 questions which obtained from 30 question papers are allocated for the analysis. Natural language processing techniques were used to identify the significant keywords and verbs which are useful in the determination of the suitable cognitive level. A rule based approach was used to determine the level of the question paper in the light of Bloom’s Taxonomy. An effective model which enables to determine the level of examination paper can derive as the final outcome.Item A solution for reducing electricity in residential sector using image processing(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Ekanayake, D.S.; Samankula, W.G.D.M.Energy saving is a critical issue that should be addressed in a worldwide scale. In the residential sector of Sri Lanka, there are many houses. Each household on average includes four people and has diverse electronic needs to be fulfilled. This paper proposes a solution to reduce the electricity consumption of residential sector. The solution has the ability to manage the use of electricity consumption of households. It identifies each and every household electric item and connects through Wi-Fi. Each household electric item which has the ability to connect to a Wi-Fi network, will be connected to the system via the routers port forwarding function. The user has the ability to check the system and identify which electric item is wasting energy and then the user can switch it off remotely through the system. Furthermore, the proposed solution is equipped with image processing algorithms. Image processing is fast, flexible and opens a whole new world of real time computer vision. A video camera located in several places in the house is used to identify presence of humans and then automatically switch off unnecessary electronic items. The proposed detection process depends on the light condition, camera angle and the efficiency of the real time detection. Matlab’s SVM classifier people detection algorithm was used as the image processing algorithm. One thousand six hundred images were split equally into two data sets as images with humans, and images without humans. The analysis revealed a unique threshold value as 6 220 800 in images to identify humans images in it. In the future, the system is envisaged to connect to an IoT (Internet of Things) platform to derive more benefits to the end user.Item Study of machine learning algorithms for Sinhala speech recognition(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Shaminda, S.; Jayalal, S.Speech is the primary mode of communication among humans and the most natural and efficient form of exchanging information. Therefore, it is logical that the next technological development in natural language speech recognition for Human Computer Interaction is, Artificial Intelligence. Speech recognition can be defined as the process of converting speech signal to a sequence of words by an algorithm implemented using a computer program. Speech processing is one of the challenging areas of signal processing. The main objective of the study was to conduct a study on speech recognition approaches to improve the accuracy level of Sinhala speech recognition. This study was conducted in order to find the optimal algorithm for accurate Sinhala speech recognition. According to the implementation architecture of speech recognition, feature extraction and the pattern recognition phases can be varied with different algorithms. The study identified that Linear Predictive Coding (LPC) and Hidden Markov Model (HMM) gives most accurate results than other combine algorithms.Item An optimization model for planning milling quantities based on forecasting of paddy and rice prices(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Abeyweera, S.; Nanayakkara, J.Rice is considered as the staple food of Sri Lanka. The conversion of paddy in to rice is a main value creation found in the Sri Lankan agricultural industries. The paper deals with the planning concerns, in the supply chain of rice. The paper discusses various issues related to production of rice at the downstream end of the supply chain and milling management decisions. Small and Medium scale milling plants around Sri Lanka are facing problems of dissolving their businesses quickly, and they are in a need to utilize their capacity in optimal way. An efficient supply chain management framework is essential for the milling to be efficient in sourcing, processing and distribution of rice under an uncertain environment. In the study, the behaviour of the Sri Lankan paddy and rice market prices volatility has been studied qualitatively and the paper discusses the validity of applying different forecasting tools. Mainly the SARIMA and Winters model have been used for forecasting. The study identifies and proposes two price regions for forecasting, based on the macro environmental factors. In order to attain the research objectives of optimization, the researcher has used linear programming as a continuous multi period model. The research is significant for the small and medium scale milling community to enhance their livelihood by determining the right time and right quantity for procuring, processing and stocking in a volatile market environment.Item Gender recognition of Luffa flowers using machine learning(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Gunasinghe, H.N.; de Silva, R.Automatic flower gender identification could be introduced to large farmlands to help artificial pollination of imperfect flowers. Incomplete flowers contain either male or female organs but not both. In this paper, we present a computer aided system based on image processing and machine learning to identify the gender of a Luffa flower automatically. A pre-trained machine learning model is used for gender segmentation of flowers. The system is developed using Tensorflow Machine Learning Tool, which is an open-source software library for Machine Intelligence. The network was selected as the Google’s Inception model and a dataset was prepared after capturing flower images from a Sri Lankan Luffa farm. The system was tested using two datasets. The first contained the captured original images and the second was prepared by cropping each image to extract male and female floral organs, stamen and pistil respectively. The prototype system classified the flowers as either male or female at 95% accuracy level. The experimental results indicate that the proposed approach can significantly support an accurate identification of the gender of a Luffa flower with some computational effort.Item AHP integrated MILP approach to minimize transportation cost to prioritize distribution requirements(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Madushika, I.K.; Wijayanayake, A.Customer satisfaction can be considered as the most important factor for any business as it is tightly linked to revenue and determines the company’s growth and the sustainability. Further it is the leading indicator of customer repurchases and loyalty. Final outcome of the effective supply chain (SC) management is to make the customer loyal and if failed it would result to transfer the customer towards the competitor. Understanding this importance, research in supply chain management (SCM) has grown significantly in recent years. Many organizations have identified that customer satisfaction (CS) and the SC cost are linked and it is impossible to optimize both at the same time. Many studies have been done under different situations to minimize transportation cost (TC) as it ultimately reduces a tremendous amount of SC cost. The need for a reliable approach to optimize customer satisfaction while minimizing the transportation cost has been raised in many occasions as improving customer satisfaction is a goal sought by many businesses in the logistic industry. This requirement becomes critical when the distributor has to select a set of customer orders to be delivered when the supply is less than the demand. Therefore, the objective of this study was to develop a model to find a way to optimally satisfy the customer orders, while minimizing the transportation cost. As a result, a customer focused approach is presented by incorporating Analytic Hierarchy Process (AHP) and then employing a mixed integer linear programming (MILP) model to find the optimal solution. The proposed model addresses customer satisfaction while minimizing the transportation costsItem A self-configuring communication protocol stack for fog-based mobile ad-hoc networks(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Wickramarathne, I.Y.; Jayawardhana, B.; Rajapakse, R.A.C.P.This paper introduces a self-configuring communication protocol stack for fog-based mobile ad-hoc networks. The rapid development of Internet of Things (IoT) technologies have made mobile ad-hoc networks (MANETs) to become pervasive in our everyday lives. In MANETs, the nodes dynamically get connected and disconnected with other nodes of the network while maintaining the quality of service (QoS). However, when the devices have to contact frequently to cloud-based servers for various services and, as well as when the number of devices connected increases, the QoS could drop drastically due to high bandwidth consumption and the consequent latency. Fog computing (as well as edge computing) aims at shifting data processing and other services offered by cloud-based servers in a computer network towards the edge of the network to minimize the issues raised due to latency. Given these circumstances, combining ‘fog computing’ with MANETs seems a promising solution that enhances the QoS. However, the definition of fog computing is still debatable and, as well as the technologies are still being developed. Even though a reasonable foundation has been laid by the various concepts, there is a necessity for further research on different algorithms to meet the harsh requirements of node discovery, connectivity, communication and latency when combining fog computing with MANETs. The protocol stack presented in this paper addresses the issue of node discovery and peer-to-peer communication in MANETs in a fog network. The methodology involves a build and test approach in which the conceptual protocol stack has been implemented for messaging between mobile peers in a Wi-Fi network without connecting to the Internet.Item A study on classifying the store positioning from the transactional data(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Takahashi, M.; Tanaka, Y.This paper describes a customer analysis for store positioning, using data gathered from supermarkets in Japan. Among the retail industry in Japan, there are many types of reward cards used for customer retention purposes. The rewards cards or “Point Card”, is originally aimed for customer analysis purposes, but at present the full benefits have not been extracted due to issues in data analytics. This reward card has only become a method of simply distributing “virtual money” to the customer. For the efficient use of gathering data, we propose a classification method of the customer based on the objectives of visiting stores. In this study, the customers were classified into their objectives.Item Framework for embedding strategic use of simulation and optimization technologies in supply chain management(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Gunathilaka, R.; Perera, T.Simulation and optimisation technologies provide virtual environments to fine tune supply chain operations and to develop best operational configurations and strategies. However, recent review of literature and a survey of industry professionals revealed that in most instances, these technologies are typically deployed to address specific problems in isolation. Therefore, companies are failing to reap full potential of simulation and optimisation technologies. This paper presents the development of a new framework which should enable supply chain managers to embed these technologies in their decision-making processes. The proposed framework serves as a guide which helps to (a) identify missing resources (Data, Assets, Stakeholders and Processes) and make appropriate assumptions before design or re-design processes begin (b) Identify gaps against competitor business performance and develop strategies to deploy simulation and optimisation to narrow existing gaps and (c) develop necessary capabilities such as improving in-house logistics and / or out-sourcing for better ROI.Item Systems engineering approach to smart computing: From farmer empowerment to achieving sustainable development goals(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Ginige, A.Smart Computing aims to combine advances in Information and Communication Technologies to create smart systems to make human life better thus, providing a new approach to address many complex and challenging problems faced today by humanity. The study developed a solution to one such problem, uncoordinated agriculture production using Smart Computing which otherwise will lead to wide fluctuation of market prices, waste and farmers getting trapped into a poverty cycle. This was done using a bottom up approach. Using systems thinking in Systems Engineering and the insights gained from the bottom up approach the study derived a top-down approach as a way of guiding the process to solve other similar humanitarian challenges. The evolved top-down process consist of 3 broad steps; a) Root Cause analysis and development of a conceptual solution drawing on learnings from multiple disciplines, b) Development of an artefact based on Smart Computing technologies to implement the conceptual solution, and c) Development of a Closed Loop Control system to continuously monitor and manage the inputs identified in the conceptual solution using the artefact developed to achieve the desired outputs.Item An assessment of machine learning-based training tools to assist Dyslexic patients(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Sathsara, G.W.C.; Rupasinghe, T.D.; Sumanasena, S.P.Dyslexia is a language based disability, where the patients often have difficulties with reading, spelling, writing and pronouncing words. The reading speed of Dyslexics tend to be lower than their equivalents, because of slow letter and word processing. Inspite of this disorder, a dyslexic person can be trained to read in normal speed. There are manual methods and some technical improvements can be reported such as the live-scribe smart pen, Dragon Naturally Speaking, Word processors, and Video Games. This study provides an assessment about the Machine Learning (ML) based techniques used for Dyslexic patients via a systematic review of literature, and a proposed ML based algorithm that will lay foundation for future research in the areas of machine learning, augmented and healthcare training devices.