ICACT–2021

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/24483

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Advancements in Environmental Technologies for Sustainable Urban Regeneration: A Comparative Assessment
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Edirisinghe, Ruwan Danuka
The present study aims to appraise advancements in environmental technologies applicable to urban regeneration, with a special focus on urban brownfield redevelopment. The rapid literature review technique was employed as the research strategy, in the mixed method research design. Technological solutions proposed in the selected articles were comparatively assessed their practicality in an urban setting, in terms of cost, efficacy, physical space required and potential harm to the neighboring environment, by using a five-point scale scoring system. In this study, nanoremediation, thermal remediation methods (i.e. electrical resistance heating, thermal conduction heating and steam enhanced extraction), non-thermal physical remediation methods (electrokinetic remediation, non-thermal plasma technologies, air sparging, soil washing and replacement and passive treatment technologies such as permeable reactive barriers), chemical oxidation (advanced chemical oxidation and Fenton process), and naturebased solutions or bioremediation or gentle remediation technologies (biodegradation processes methods such as bioaugmentation, bioventing, bioprecipitation, biostimulation, landfarming, and phytoremediation methods such as phytostabilization, phytovolatilization and phytoextraction or phytomining and monitored natural attenuation) are presented. Each environmental restoration strategies provided has its own set of limitations, application possibilities and future development potential, as evidenced by this study. Nanoremediation, bioremediation and radio frequency heating in the current state of the art are found to be feasible for an urban area. Property developers and urban authorities could consider the application potential of these technologies in urban brownfield redevelopment in urban regeneration. An integrated approach for addressing the limitations of these technologies may be worth considering in research and developments in the urban sector.
Agricultural Call Centres: An Overview Of 1920 Agricultural Advisory Service Usage, Sri Lanka
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Rathnayake, Sanduni; Kamiss, T.A.; Dissanayeke, U.I.; Alahakoon, P.C.B.; Rizwan, M.F.M.
The 1920 Agricultural Advisory Service (AAS) was introduced in 2006, as an ICT initiative of agricultural extension in Sri Lanka. There are no studies assessing the long-term usage of AAS by the community. Therefore, secondary research was carried out to identify the trends and patterns in 1920 AAS usage. Data were collected from internal databases, records, seasonal reports of National Agriculture Information and Communication Centre (NAICC), journal articles and web sources. Results revealed an increasing trend of receiving queries from 2006 to 2012 and, from 2016 to 2018. The trend was decreasing from 2012 to 2015. By the end of 2018, AAS has received 546,473 queries since its inception. Queries on fruits, vegetables and subject specific matters have been highest for several years. The highest number of queries was regarding ‘cultivation’ matters and queries from Colombo district was the highest in every year. There was no seasonal variation of the total number of queries received. Peak hours of AAS were from 8.00 am to 10.00 am where it served 31.6% of the total queries received per month. This study revealed several avenues for primary research. A detailed field level studies on the parameters claimed for the highest number of queries will be helpful to plan tailor-made extension programs. Mapping of queries received by AAS will provide a valuable information source for the policy makers in designing field extension programmes in Sri Lanka.
An Approach to Detect Fileless Malware that Maintains Persistence in Windows Environment
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Atapattu, Malmi; Jayawardena, Buddhika
The rapid enhancement of the Internet in the past few years has increasingly impacted the general public’s work and life. As a drawback, this enhancement has also led to a major increase in malicious software on the internet causing great security threats to the consumers of the internet. Currently, a new type of malware class called Fileless malware has come into action causing more destructive damages. As the name Fileless suggests, these types of malware programs are not files or executables, but a malicious activity that runs entirely in the memory, leaving the slightest evidence on the targeted host machine. Microsoft Windows is one of the most widely used operating systems both in personal desktop computers and enterprise computer systems and is highly targeted by Fileless malware. This paper provides an approach to detect fileless malware that maintains persistence in the Windows environment using Fileless malware behavioural data and deep learningbased classification models.
Aspect Based Multi-Class Sentiment Dataset for Bilingual eWOM of Commercial Food Products
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Edirisuriya, Binguni; Asanka, Dinesh; Wijayanayake, Janaka
Aspect-Based Sentiment Analysis for product review opinion analysis is commonly utilized by the commercial food products manufacturing businesses to drive decisions regarding products. However, the general consumers are not facilitated with decision making ready end-user applications which generates insights to arrive at the purchase decision at the time of purchase due to the unavailability of products’ attribute-wise analysis-ready data. Although Electronic Word of Mouth (eWOM) platforms are comprised of opinions with a diversity of languages and expression formats, themselves do not generate any value to make comparable decision making. Hence, there is an existing gap of impactful information retrieval by the consumer to aid the purchase. Therefore, creating a publicly available analysis-ready dataset for the commercial food product domain contributes significantly to the Sri Lankan consumers and Government organizations. Through our research work, a manually annotated bilingual eWOM opinion text dataset for selected commercial food products categories has been delivered in which the opinions expressed in the Sinhala language have been translated into English language and each opinion has been manually rated into five levels by two domain experts. Two product attributes, “Price of the product”, “Safeness of product” have been considered as aspects to conduct the Aspect-Based Sentiment Analysis. This study describes the sub-tasks performed to conduct the Aspect- Based Sentiment Analysis on the dataset along with the basic statistical evaluation of the dataset. We have presented results on the performance of the dataset by utilizing an existing Long Short-Term Memory Model.
Audio Steganography using LSB Technique to Embedding Data
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Shanmugaradnam, Dayanantha; Weerasinghe, Hesiri Dhammika
Data protection is a major concern on the internet medium. Data needs to be protected from intrusion, penetration, and data theft. Audio steganography is used to hide secret messages in an audio file. This method was intended to secure the secret message. The secret message was protected using the hashing and encryption technique and the Least Significant Bit substitution was performed to hide the data. The Stego audio files were analyzed by Signal-to- Noise Ratio and Mean Opinion Score. The Stego audio files had an 80dB average Signal-to-Noise Ratio and the overall Mean Opinion Score was 4.4 out of 5. It proves that this method helped to improve the robustness and imperceptibility. Using the proposed method higher security can be achieved.
Challenges of Adopting Blockchain Technology to Pharmaceutical Supply Chain – A Case Study from Sri Lankan Health Sector
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Paththinige, Pavani Wasana; Rajapakse, Chathura
Ensuring the transparency of pharmaceutical supply chains is an important task to control the adverse health effects of counterfeit drugs. Blockchain technology has been widely recognized among supply chain researchers as a useful emerging technology to enhance transparency and security of various supply chains. However, the adoption of the blockchain technology in pharmaceutical supply chains is still in its infancy with only a handful of research reported to date. This paper presents the details of a conceptual model developed to explore the challenges of adopting blockchain technology to manage pharmaceutical supply chain while combatting against the flow of counterfeit drugs. The proposed conceptual model, which is based on a comprehensive review of literature, encapsulates the complex linkages between seven influencing factors namely 1) Relative advantage 2) Upper management support 3) Human Resource 4) Compatibility 5) Cost 6) Complexity, and 7) Technological Infrastructure and Architecture. The factors evaluated in the framework interact and impact one another. The proposed framework can be utilized as a starting point for implementing blockchain applications in the pharmaceutical supply chain as well as by academics to develop, refine, and assess blockchain based research. As factors have been identified, practitioners will be able to develop a strategy for implementing blockchain in the pharmaceutical supply chain
A Consortium Blockchain Model to Overcome Issues in the Global Patent Authentication and Management Process
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Gunasekara, Prageeth Thilina; Rajapakse, Chathura
Patent authentication and management is an important activity to protect the intellectual property rights of individuals and organizations globally. As the patents are territorial and the data management related to patent applications mostly happens with local intellectual property (IP) offices, the patent authentication and management (PAM) process is significantly inefficient and time-consuming on the global scale. Moreover, the data management issues in the patent process often lead to conflicts and legal actions among competing parties. Blockchain technology is widely recognized for its potential use in creating decentralized, secure, and transparent systems with immutable records. It hence seems to be a useful technology to overcome the issues in the patent domain. This paper explores the adaptability of blockchain technology in the patent domain. It presents the design of a consortium blockchain system, which is proposed as a solution to numerous issues stemming from inefficient data management. The proposed consortium blockchain design is based on the Ethereum architecture and is equipped with smart contracts to ensure the reliability of patent data as well as the real-time update of records. This paper further discusses the potential testing and validation strategies for the proposed model.
Convolutional Neural Network for Classification and Value Estimation of Selected Gemstones in Sri Lanka
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Amarasekara, Samali; Meegama, Ravinda
Gemstone classification and value estimation are considered to be tedious tasks encountered in the gem industry all over the world. This happens due to colour variations found in the same gem type which is often difficult to detect with the naked eye. This paper presents a machine learning approach to automatically classify the gem type by using an image and also to estimate the value of the stone using a few measurements. The proposed technique uses a microscopic image of a gemstone which is taken using a gemological microscope. A Convolutional Neural Network (CNN) is trained to classify gem type while features such as type, colour palette, shape and weight are used to estimate the value of the. This work creates a system that is capable of classifying and estimating the value of four types of gemstones, namely, Blue Sapphire, Yellow Sapphire, Amethyst and Cat’s eye. The results indicate that the proposed technique managed to classify the gemstones with the highest accuracy of 87% for yellow sapphires and 77% for blue sapphires. The yellow sapphires produced the highest accuracy in colour categorization which can be attributed to the high contrast of the images vailable. As such, it can be concluded that the quality of the original image is important in correctly identifying the exact colour of a gemstone.
Database Management System Deployment on Docker Containerization for Distributed Systems
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Kithulwatta, W.M.C.J.T.; Jayasena, K.P.N.; Kumara, B.T.G.S.; Rathnayaka, R.M.K.T.
Containerization is a novel technology that brings an alternative for virtualization. Due to the most infrastructure-based features, most computer system administration engineers use Docker as the infrastructure level platform. On the Docker containers, any such kind of software service can be deployed. This study aims to evaluate Docker container based relational database management system container behavior. Currently, most scholarly research articles are existing for the database engine performance evaluation under different metrics and measurements of the database management systems. Therefore, without repeating them: this study evaluated the data storage mechanisms, security approaches, container resource usages and container features on the launching mechanism. According to the observed features and factors on the containerized database management systems, containerized database management systems are presenting more value-added features. Hence containerized database management system Docker containers can be recommended for the distributed computer systems for getting the benefit of effectiveness and efficiency.
A Deep Neural Network Approach for Analysis of Firewall Log Data
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Lillmond, Chandesh; Suddul, Geerish
In this paper, we propose an intelligent approach for the classification of incoming and outgoing firewall traffic packets. A firewall is a quintessential tool that ensures the control of traffic over machines’ communication over a network. It uses a set of specific rules to define the traffic and thus assists in avoiding cyber-attacks which can be very costly to an organization. Our intelligent approach is mainly through the application of the Deep Neural Network (DNN) Machine Learning algorithm so that packets going through the firewall can be automatically classified as either allow, deny or drop. Our experiments demonstrate a classification accuracy of around 94%, which is higher when compared with other approaches.
Development of an Autonomous Agricultural Drone and Real - Time Monitoring Interface for Aerial Seeding
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Mohamed, M.R.; Priyankara, D.M.T; Kaluwandara, C.N.; Bandara, S.
Applications of Unmanned Aerial Vehicles (UAVs) or commonly known as drones, have been considerably growing during the past few decades in various fields such as agriculture, aerial mapping, surveillance, disaster management, and military applications. Drones are used in agriculture to monitor, harvest, and apply pesticides and fertilizers [1]. An autonomous agricultural drone (quadrotor) was developed for aerial seeding and a web interface using IoT technology with a raspberry pi microcontroller. A lowcost and open-source flight controller was used [2]. The real-time unmanned aerial vehicle monitoring system was developed using PHP/MySQL as the backend technologies on the website and Bootstrap, AJAX, JQuery for the frontend and to communicate with the Pixhawk and Raspberry Pi, Python was used. To enhance the continuous flying time with load, proper weight calculations were done before it flies with the load. CAD software was used to design the drone from the top, bottom, right and left views with exact calculations [3]. The design calculations, along with thrust values, also calculated for payload.
Drone Technology for Rice Agriculture at the Fertilizer Spraying Process
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Amarasinghe, Akarshani; Jayaratne, Lakshman; Wijesuriya, Viraj B.
This paper presents a drone simulator to spray fertilizer for rice farmland with minimum human intervention. The proposed drone simulator is capable of suggesting the optimal path to spray fertilizer, indicating the current altitude and the current battery level of the drone at flight. The obtained results at the evaluation stage show that the proposed path planning algorithm outputs the optimal path for given farmland with minimum execution time. This solution will cherish the use of drone technology for rice agriculture while supporting the economic growth of a country.
Evaluation of Cooling Techniques for Personal Cooling Garments in Hot and Humid Climates
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Fernando, D.O.D.P.; Ahmad, A. N.; Nandasiri, Gayani K.; Nissanka, Indrajith D.
Personal cooling garments have become a major requirement to cater thermal discomfort, caused mainly due to the rise in global temperatures. Various cooling techniques have been used for specific applications, mainly focused on thermal protection than thermal comfort. Thermoelectric cooling, phase change materials, and evaporative cooling techniques were selected and further analyzed through mathematical modeling to assess their suitability for personal cooling garments. Phase change materials can provide 2 hours of cooling using 46 capsules, while evaporative cooling can provide cooling for 36.1 minutes and thermoelectric cooling can provide continuous cooling. The study concluded that a combination of thermoelectric cooling with phase change materials could remove required heat from the top part of the body which is emitted during medium level activities. Two circuits, each with three Peltier modules of the TEC1-127 series supplied with a direct current of 1.5A and supplied voltage of 9V could provide efficient heat pumping ability, with the coefficient of performance of 1.17 each. The macro capsules with eicosane as the core material act as the heat sink when used in combination with thermoelectric modules. Hence, it concludes that a combination of thermoelectric modules with phase change materials integrated into a personal cooling garment could effectively provide the required thermal comfort.
Field Testing of Highway Bridges Enhanced by Assumptions of Composite Action
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Lu, Renxiang; Judd, Johnn
A load rating procedure that involves field testing and composite action considerations for girders affected by external effects is presented in this paper. In the proposed procedure, the critical vehicle sequence for the bridge is determined and the actual response of the bridge is measured using a series of runs by driving a vehicle of calibrated weight. To replace the data readings affected by external effects, the position of the neutral axis corresponding to a fully composite action is assumed. After applying this correction, the actual load rating is discretized and compared with the analytical load rating so that different contributions to the loading capacity are quantified. A three-span non-composite steel girder highway bridge was used to illustrate the procedure. Results indicate that although the unintended composite action was the dominant contribution, the contribution was unreliable for loads beyond the linear elastic regime. It was observed that corrections made based on composite action assumptions improve the understanding of the case study because the contributions due to additional stiffness lateral and longitudinal distribution would have been unrealistic otherwise.
Heart Disease Prediction Using Machine Learning Techniques: A Comparative Analysis
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Gamage, L.
In today's world, heart disease is one of the leading causes of death. In clinical data analysis, predicting heart disease is a difficult task. Machine Learning (ML) helps assist with the decision-making and prediction of large volumes of data generated by the healthcare industry. The main goal of this study is to find the best performance model and compare machine learning algorithms for predicting heart disease. This work applies supervised machine learning algorithms, namely Logistic Regression, Support Vector Machine, KNearest Neighbor, and Random Forest, to the Cleveland Heart Disease dataset to predict heart disease. Our experimental analysis using preprocessing steps and model hyperparameter tuning, Logistic Regression, Support Vector Machine, K- Nearest Neighbor and Random Forest achieved 90.16%, 86.89%,86.89%, and 85.25%, accuracies respectively. As a result, Logistic Regression classification outperforms other machine learning algorithms in predicting heart disease.
Hybrid Movie Recommendation System
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Punitharasa, Sinthujan; Selvanajagam, Kirisanthi; Ramakrishnan, Thamilini; Chelvarajah, Amalraj; Weerasinghe, W.M.R.M.
Movie recommendations play a great part in the aspects of our social life. Such a system allows users to recommend a group of films based on their interests or the popularity of the movies. This research was conducted to study different approaches to movie recommendation and discusses a hybrid approach that combines a content-based filter, a collaborative-memory-based filter, and a collaborative-model-based filter. The proposed system aims to reduce the issues with existing movie recommendation systems by enhancing performance. The content-based filter is based on a TF-IDF classifier with cosine similarity. The collaborative-memory-based filter is based on truncated SVD with Pearson correlation. A collaborative model-based filter is based on improved SVD matrix factorization.
Impact of ZnO NPs on In Vitro Germination and Growth Characteristics of Rice (Oryza sativa)
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Perera, Sujani; Rupasinghe, Thilini; Wijenayaka, Lahiru
A key feature of contemporary nanotechnology is the successful utilization of nanotechnological concepts in agriculture, for applications such as enhancement of the efficiency of crop production through improved seed germination & growth, smart fertilizers, smart pesticides etc. Effect of different nanoparticles (NPs) such as TiO2, Ag, Si, Au, Cu, Zn and ZnO on seed germination have been studied in literature for crops such as canola, mung beans, onions, fenugreek and watermelon. Current study focuses on investigating the impact of ZnO NPs on the seed germination and growth of rice (Oryza Sativa). ZnO is a non-toxic NP and has the potential to boost the yield and growth of food crops. According to literature, ZnO NPs have been used to enhance the seed germination in different plants such as mung beans, peanut and black gram. Herein, ZnO NPs were synthesized by a wet chemical method by mixing ethanolic solutions of NaOH and Zn (CH3COO)2·2H2O.The morphology of the synthesized ZnO NPs was studied using Scanning Electron Microscopy (SEM) and synthesized ZnO NPs exhibited a spherical shape with a diameter ranging from 65 nm to 95 nm, with an average diameter of (73±2) nm. The impact of ZnO NPs on germination and growth of rice was studied under different NP concentrations (0- 2000 mg/L) for Sudu samba and traditional rice varieties, Suwandel and Madathawalu. Further, the growth characteristics were investigated by measuring the root length and the shoot length of rice seeds. A significant enhancement of seed germination was observed in all three rice varieties after treating with ZnO NPs. Sudu Samba seeds showed a 7.3 % enhancement of seed germination (at 500 mg/L ZnO) while Suwandel and Madathawalu showed an enhancement of 20 % and 17% respectively. This can be attributed to the ability of ZnO NPs to penetrate through the cell wall and release targeting genes to specific cellular organelles to boost the cell division. As Zinc is an enzymatic component, it has the ability to influence secretion of indole acetic acid (IAA) which important to regulate plant growth and when the level of IAA is increased, it causes an effective response in seed germination. Interestingly, no significant difference in root length and shoot length was observed for Madathawalu while, a negative effect was observed for Sudu samba and Suwandel at 7 days. Further investigations with varying ZnO concentrations and other types of traditional Sri Lankan rice varieties are currently ongoing to gain more insight into the phenomena observed above.
M-LMS Adoption Intention; Empirical Evidence from Postgraduates in Developing Context
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Chandradasa, Isuru
Mobile learning is a widely used teaching and learning method and a Mobile learning management system is a part of the mobile learning process. During the pandemic period, the demand for mobile learning raised rapidly and is continuing to rise. After the pandemic if academic institutions hope to continue this trend, it is important to know about students’ intention to use this Mobile learning management system in the future. Without knowing this continuing this application in the future is a risk for the organization as well as a negative factor for users’ satisfaction. The evidence from past literature in this regard is lacking. Therefore, the objective of this study is to examine the continued intention of Sri Lankan postgraduate's mobile learning management system use in the future. The variables that might influence their continued intention of using this Mobile learning management system are identified from previous literature and based on that conceptual framework and hypothesis of the study developed. This study used quantitative techniques and data collected from 119 postgraduate students of one of the reputed state university in Sri Lanka by employing a convenience sampling technique. The data was analyzed using SPSS 25 statistical software package. The results of the study showed that direct utilization, ease of use, mobility value, academic relevance, and university management support will have a significant impact on the post-graduates' intent on the mobile learning management system in their future academic pursuits. This study provides theoretical and practical insights for researchers and practitioners about M-LMS usage and future implications. The data included postgraduates only from one state university which is the major limitation of this study.
Model for Integration of Technology in Authentic Education-An interpretation of a literature Review
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Manjaree, Bhagya; Liyanage, Laalitha S.I.; Rupasinghe, Thilini P.; Tillekaratne, Aashani; de Silva, K.M.N.
This literature review is conducted to identify, appraise and synthesize empirical evidence of a filtered list of recent literature regarding methods in which technology could be integrated to facilitate authentic learning pedagogy. A protocol was developed to carry out a search for screening[1]. iDiscover search engine of University of Cambridge library was used for selection and filtering of the articles for their appropriateness. Critical appraisal was performed and data was extracted to map, conceptualize and synthesize the proposed tripod model for integration of technology in authentic education. This model depicts the findings in three zones namely, foundational layer, operational layer and the stage which is the platform for authentic education. Understanding the landscape of the tripod model for integration of technology in authentic education could be quite decisive in selecting the best-fit technological tool. This article argues about how technological interventions could enhance the outcomes of authentic education and the need of an appropriate pedagogical strategy to align such interventions to the elements of authentic education.
Modeling the Relationship between Profitability and Market Share of Licensed Commercial Banks in Sri Lanka
(Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka, 2021) Hettiarachchi, Imesha; Ekanayake, Piyal; Aponsu, Lakshan
Sri Lankan banking industry comprises of two major types of establishments viz. Licensed Commercial Banks (LCB) and Licensed Specialized Banks of which the profitability of the former being determined by the size of the firm, indicated by total assets held by the bank. In this study, the relationship between market share and profitability of LCBs was investigated using Multiple Linear Regression (MLR) analysis and considering the variables unique to the Sri Lankan banking industry. Quarterly data were obtained from the Central Bank of Sri Lanka from 2008 to 2020. In addition to MLR, analysis of variance and time-series analysis was also carried out to ensure the reliance of the results and conclusions. It was found that the market share represented by Deposit Customers and Loan Customers have a positive relationship with the profitability measured by Profit After Tax (PAT). Further, market share explained a substantial 96.5% of the variability in profitability. The model predicted that a unit increase in deposits and loans lead to an increase in profitability by 6.1% and 10.7% respectively. Finally, it could be concluded that the loans granted to bank customers accounted for increasing the profitability of LCBs in Sri Lanka than the deposits made by the customers. Accordingly, the LCBs can review their strategies to optimize profitability based on the loans granted to and deposits received from the customers.