Smart Computing and Systems Engineering - 2018 (SCSE 2018)

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/18937

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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.
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%.
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.
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.
Identification of water stressed leaves using Artificial Intelligence: The case of eggplant
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Senanayake, P.A.; de Silva, R.
Identification of water stress of leaves from the photos taken has a long history. Researchers have defined a parameter called Leaf Water Content (LWC) to quantify the dryness of leaves. However, in the case of automatic watering of plants, such high accuracy of LWC is not needed as a decision to water or not alone is sufficient. Furthermore, the agricultural industry cannot use methods of remote sensing that are required to find LWC as they are complex and costly. In the current practice, farmers use their knowledge and experience together with the appearance of plants to estimate the water stress and watering time point of plants. The approach presented in this paper is easily implemented and requires only a series of photos taken by a smartphone or a camera and a software app. In this paper, a method s introduced using Artificial Intelligence (AI) where the images of leaves are directly used to determine whether the leaves are water stressed. We could identify the water stressed leaves accurately using this method. Once an app based on our method is developed, it could easily be used by farmers to automatically identify whether the eggplants are water stressed and need watering.
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.
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.
Determinants of successful implementation of Green Supply Chain Management: From literature review perspective
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Thushanthani, T.; Rupasinghe, T.D.
The purpose of this study is to identify the Green Supply Chain Management (GSCM) best practices and explore the factors influencing the succesful adoption of green supply chain management practices. The authors have used a systematic review of literature approach to collate 27 articles ranging from automobile, beverages, construction, electrical, hospitality, power generating and, general industries. The findings are revealed under five categories namely; green procurement, green design, green packaging, green operations, green manufacturing and reverse logistics incorporating 48 critical success factors under five themes, namely; Organizational Commitment (OC), Knowledge Base (K), Operational Dynamics (OD) , Market Pressure (MP) and Exogenous (E).
A cross-functional collaborative model for supplier evaluation for the sustainability of a firm
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Jayarathne, K.; Wijayanayake, A.; Weerabahu, S.
Business organizations have emphasized the importance of sustainability in their business processes. Sustainability of a firm can be measured on social, environmental and economic benefit indicators known as “triple bottom line”. Supplier selection process is one of the critical issues of sustainability activities faced by supply chain managers to maintain a strategically competitive position in the industry and supplier selection can significantly affect in achieving the triple bottom line. Given the current context, technological factors immensely affect the sustainability of a firm. Communication and web based systems related technology is a vital factor to build sustainable supply chain relationships. Thus, technological aspects can be taken into consideration under different sustainable criteria for supplier selection, though it has not been considered yet as a major factor. Analytical Network Process (ANP) has been incorporated to compute the supplier evaluated score that was computed by each department against each supplier. Then an Integer Linear Programming (ILP) model has been used to integrate the judgments of the multiple decision-makers. This research addresses the supplier selection decisions by groups of experts, which improves the quality and accuracy of the decisions made. In this model, both subjective and objective factors related to supplier selection are incorporated in order to optimize the procurement process aligning to the sustainability of the firm.
Data mining model for identifying high-quality journals
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Jayaneththi, J.K.D.B.G.; Kumara, B.T.G.S.
The focus in local universities over the last decade, have shifted from teaching at undergraduate and postgraduate levels to conducting research and publishing in reputed local and international journals. Such publications will enhance the reputation on the individual and the university. The last two decades has seen a rapid rise in open access journals. This has led to quality issues and hence chossing journals for publication has become an issue. Most of these journals focus on the monetary aspect and will publish articles that previously may not have been accepted. Some of the issues include design of the study, methodology and the rigor of the analysis. This has great consequences as some of these papers are cited and used as a basis for further studies. Another cause for concern is that, the honest researchers are sometimes duped, into believing that journals are legitimate and may end up by publishing good material in them. In addition, at present, it is very difficult to identify the fake journals from the legitimate ones. Therefore, the objective of the research was to introduce a data mining model which helps the publishers to identify the highest quality and most suitable journals to publish their research findings. The study focused on the journals in the field of Computer Science. Journal Impact Factor, H-index, Scientific Journal Rankings, Eigen factor Score, Article Influence Score and Source Normalized Impact per Paper journal metrics were used for building this data mining model. Journals were clustered into five clusters using K-Means clustering algorithm and the clusters were interpreted as excellent, good, fair, poor and very poor based on the results.
Street attractiveness enables change to a city structure
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Kurahashi, S.; Nagai, H.
The study proposes an agent-based model for urban dynamics, combining locating of a facility for stopping off and measures to promote street attractiveness. The model expresses simplified urban dynamics. It also enables to verify how policies affect the daily travel of urban residents and indirectly change an urban structure towards a desirable formation. As a result, the model clarified that the policy of street attractiveness affected compactification of an urban structure physically and a significant decrease of car users along with CO2 reduction. Use of this model, reveals significant differences of improvement effects on an urban structure depending on the locations of the facility, the implementation scale of each promotional measure around the facility, and demonstrates the synergy effects of the policy on transportation.
Applicability of crowdsourcing for traffic-less travelling in Sri Lankan context
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Senanayake, J.M.D.; Wijayanayake, J.
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using crowdsourcing together with data mining techniques, data related to user mobility were collected and studied and based on the observations, an algorithm has been developed to overcome the problem. By using developed techniques, the best transportation method can be predicted. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. The algorithm correctly predict the best traffic-less traveling method for the studied area of each given day & the given time. Throughout this research it has been proven that to determine the best transportation method in Sri Lankan context, data mining concepts together with crowdsourcing can be applied. Based on a thorough analysis by extending the data set of the collection stage, it was shown that this research can be extended to predict the best transportation method with consideration of existing traffic in all the areas.
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.
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.
Agent based modeling for unordered traffic in Sri Lanka – An investigation into pedestrian behavior
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Rathnayaka, K.R.K.S.
Rising traffic congestion is an inescapable condition in large and growing metropolitan areas across the world. Main entities of a traffic scenario are pedestrians and vehicles. Police make different rules to control the traffic congestions and from an infrastructure development perspective, authorities take actions to construct underground and overhead pedestrian bridges, fences along pavements, islands, etc. However, most of these initiatives end up with unexpected results, mostly since traffic congestion is an emerging macro-level pattern of complex micro-level behaviors of pedestrians and drivers. The study proposes Agent-Based Modeling and Simulation (ABMS) approach, which applies computational methods to study the issues in complex systems. When considering a simulation environment, software agents interact with each other similar to the way real world vehicles and pedestrians behave. This lets us study traffic congestion emerging as a macro-level pattern. Identifying the overall impact of behaviors of drivers and pedestrians to the congestion by extending the previous work, is the aim of this research. The research uses ABMS environment called NetLogo to develop the simulator and Kiribathgoda junction in Western Province, Sri Lanka as the testbed. Coming up with an effective traffic simulator for the unordered traffic conditions in Sri Lanka, which could be used by policy makers to analyze different traffic congestion scenarios and test different solutions to reduce traffic, is the main objective of this research.
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.
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.
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.
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.
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.