ICACT 2018

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Security and Privacy Implications of Biometric Authentication: a Survey
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Wijenayake, D.S.
In today’s world, biometric authentication is used by a wide range of gadgets and systems to verify user identification and access control. Even though biometric authentication is more secure when compared to traditional authentication methods, it itself is not completely hack–proof as any technology can always be hacked and exposed. Protecting user biometric data is a key security challenge in this field. In case a hacker steals any biometric information such as fingerprints, voice waves, etc. from a user, the hacker can effortlessly access all the systems that the original user has access to, which is a serious security concern. Biometric information is unique and it is even impossible to change as passwords, to block someone using it. This is the most vital drawback of biometric authentication. Therefore, the aims of this paper, are to find, understand and propose remedies to the security and privacy shortcomings of the latest biometric authentication methods. The outcome of the critical evaluation taken place in this research, results that several limitations are there in the recent researches. The lack of generalizations (testbeds and participants of the studies were limited to selected geographical areas when compared to the whole populations of the testbeds/users of the world), fewer experiments, and lack of usability/privacy requirements are among them. The paper suggests solutions/future research directions for the many of aforementioned limitations, such as, implementing indicators which depict the strength of biometric authentication methods’ security, rehashing of the studies with different populations via the internet, improving current research-based biometric authentication applications to support multimodal (using of two or more biometrics to authenticate)/continuous authentication, ensuring trust and privacy of users, etc. In conclusion, with the competition among major players in the electronic device market, research-based biometric authentication methods will be rapidly implemented in the real world. To ensure the protection of sensitive data, mobile interfaces should be improved, researchers are highly encouraged to reproduce and critically evaluate others’ researches, and the security and privacy of biometric authentication should be maintained without compromising usability. Then only it would be a challenge to hackers to exploit the biometrics.
Hybrid Gene Selection with Information Gain and Multi-Objective Evolutionary Algorithm for Leukemia Classification
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Fajila, M.N.F.
Leukemia is a bone marrow cancer with various subtypes such as Acute Myeloid Leukemia and Acute Lymphoblastic Leukemia which require expertise to be identified. Morphological and histological appearances can be used to identify diseases. Yet, precise identification of subtypes is a difficult task. Therefore, subtype detection is a crucial part in prognosis. In this study, a hybrid gene selection approach Information Gain-Multi-Objective Evolutionary Algorithm (IG-MOEA) is proposed to identify Leukemia subtypes. Microarray data consists of thousands of genes where all are not corresponding to disease. Irrelevant and redundant genes have high impact on worst classification performance. Hence, IG is initially applied to preprocess the original datasets to remove irrelevant and redundant genes. Then, further MOEA is used to select a smaller subset of genes for perfect classification of new instances. Gene subset selection highly influences the classification. Further, the subsets selected intern is influenced by the algorithm used for gene selection. Moreover, informative subset of genes can be used efficiently for perfect prediction. Thus, selecting the appropriate algorithm for subset selection is important. Hence, MOEA is used in the proposed study for subset selection. The performance of proposed IG-MOEA is compared against the Information Gain-Genetic Algorithm (IGGA) and Information Gain-Evolutionary Algorithm (IG-EA). Three Leukemia microarray datasets were used to evaluate the performance of the denoted approach. Remarkably, 100% classification was achieved for all the three datasets only with few informative genes using the proposed approach.
Voltage Sag Compensation using Dynamic Voltage Restorers: A Performance Analysis
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Senevirathne, K.M.P.C.B.; Ariyawansa, K.A.; Abeynayake, P.G.; Dampage, U.
Voltage sags are considered to be one of the most severe and frequent power disturbances occurring in the power system. The electronic devices used today are very sensitive to power quality, any disturbance in the power supply will negatively affect end user equipment. In order to overcome these voltage sags, implementation of a dynamic voltage restorer (DVR) has been proposed to compensate for voltage sags. Hence this technology can provide power regulation as well as power quality improvement. Electric vehicle (EV) batteries, connected in a vehicle-to-grid (V2G) system, act as the power source to the DVR, offering feasibility as well as mobility in delivering energy, thereby making it an ideal choice for energy storage used for improving power quality. This paper presents a simulation, using MATLAB, on the performance of a Dynamic Voltage Restorer (DVR) which utilizes energy from the batteries of Electric Vehicles (EV) as its power source.
Finite Element Method based Triangular Mesh Generation for Aircraft-Lightning Interaction Simulation
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Vinotha, K.; Thirukumaran, S.
Lightning is a natural electrical discharge process. Most common lightning strike is Cloud-to-Ground. It occurs when the negative charges accumulated at the bottom of the thundercloud traverse towards the ground to neutralize its charges with the positive earth charges induced due to the thundercloud and electrons travels along the lightning channel. The statistics shows that the commercial aircrafts directly struck by lightning strikes that are under the thundercloud once a year on average. The study of electromagnetic threat due to lightning strikes is important for flight safety and restructuring the aircraft design to mitigate direct lightning effects on the physical material of the aircraft causing damages and indirect effects on the navigation systems in it.The prime objective of this paper is to find the electric field distribution around the aircraft conductor in free space conditions under lightning scenario. For the simulation, the flash of the cloud-to-ground lightning is represented as a wave equation. Finite element method is applied to solve the wave equation for identifying potential distribution and exclusively to electric field calculations. Each of the triangular finite elements are considered and the potential at any nodes within a typical element are obtained. The equation 𝐸 = −𝛻𝑉 represents the relationship between electric potential and electric field which is used to determine the electric field distribution around the aircraft surface by a numerical derivative evaluation technique from the electric potential distribution already obtained. This paper presents an aircraft-lightning interaction simulation under the thundercloud and above the ground by generating two dimensional triangular mesh using finite element method. Significant electric field distribution is observed at the sharp end points of the aircraft. Due to higher radiated electric field, the aircraft-lightning interaction may result in an adverse impact on the aircraft navigation systems and cause damage to its structures. The simulation results would be very useful for studying lightning impact on the aerial vehicles struck by the cloud-to-ground lightning. During the simulation, it was assumed that an aircraft surface is a good conductor and the effects of material properties are left for future studies.
Technology Enabled Formative Assessment in Medical Education
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Youhasan, P.; Sanooz, A.R.M.
Technology enabled assessment is a novel pedagogical approach which has emerged into Medical educational practice. The main aim of formative assessment is to drive learning through constructive feedback. Kahoot is a free, real-time, game based, Web2.0 learning platform which is widely accepted to conduct formative assessment. The aim of this study was to explore the students’ perception on using Kahoot as a formative assessment tool at Eastern University Sri Lanka. A total number of 61 third year medical students participated in this cross sectional descriptive study following a pharmacology formative assessment conducted via Kahoot. The student perceptions on Kahoot experience was evaluated by a selfadministered questionnaire which consisted 10 perception statements. The participants asked to rate the statements by using 5-point Likert scale, ranging from 1 (Strongly disagree) to 5 (Strongly agree). Descriptive statistics was computed to present students’ perception. This study revealed that most of the students (83.6%) felt happy with Kahoot experience in conducting the formative assessment and (95.1%) of them recommended Kahoot for formative assessment in future. Majority of the participants (>90%) agreed or strongly agreed that Kahoot increases the focus on subjects, provides fun during learning, motivates to learn and is an effective method for active learning and providing feedback. The general outcome shown in this study derived from the students gives Kahoot a place as a tool to enhance the learning and to provide feedback. The free availability, feasibility, the technical simplicity and the enjoyable attitude from the students towards this application make this as a practical tool in Technology Enabled Assessment.
Finite Element Method based Triangular Mesh Generation for Aircraft-Lightning Interaction Simulation
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Vinotha, K.; Thirukumaran, S.
Lightning is a natural electrical discharge process. Most common lightning strike is Cloud-to-Ground. It occurs when the negative charges accumulated at the bottom of the thundercloud traverse towards the ground to neutralize its charges with the positive earth charges induced due to the thundercloud and electrons travels along the lightning channel. The statistics shows that the commercial aircrafts directly struck by lightning strikes that are under the thundercloud once a year on average. The study of electromagnetic threat due to lightning strikes is important for flight safety and restructuring the aircraft design to mitigate direct lightning effects on the physical material of the aircraft causing damages and indirect effects on the navigation systems in it.The prime objective of this paper is to find the electric field distribution around the aircraft conductor in free space conditions under lightning scenario. For the simulation, the flash of the cloud-to-ground lightning is represented as a wave equation. Finite element method is applied to solve the wave equation for identifying potential distribution and exclusively to electric field calculations. Each of the triangular finite elements are considered and the potential at any nodes within a typical element are obtained. The equation represents the relationship between electric potential and electric field which is used to determine the electric field distribution around the aircraft surface by a numerical derivative evaluation technique from the electric potential distribution already obtained. This paper presents an aircraft-lightning interaction simulation under the thundercloud and above the ground by generating two dimensional triangular mesh using finite element method. Significant electric field distribution is observed at the sharp end points of the aircraft. Due to higher radiated electric field, the aircraft-lightning interaction may result in an adverse impact on the aircraft navigation systems and cause damage to its structures. The simulation results would be very useful for studying lightning impact on the aerial vehicles struck by the cloud-to-ground lightning. During the simulation, it was assumed that an aircraft surface is a good conductor and the effects of material properties are left for future studies.
Mobile Biometrics: The Next Generation Authentication in CloudBased Databases
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Bhatt, C.; Liyanage, S.R.
In this period of data innovation, cell phones are generally utilized around the world for fundamental correspondences, as well as an apparatus to manage anyplace, whenever data. These situations require a high security level for individual data and protection assurance through individual distinguishing proof against un-approved use if there should be an occurrence of robbery or fake use in an organized society. At present, the most received technique is the check of Personal Identification Number (PIN), which is risky and won't not be anchored enough to meet this prerequisite. As is represented in a review (Clarke and Furnell, 2005), numerous cell phone clients view the PIN as badly arranged as a secret key that is sufficiently confounded and effortlessly overlooked and not very many clients change their PIN frequently for higher security. Subsequently, it is liked to apply biometrics for the security of cell phones and enhance dependability of remote administrations. As biometrics intends to perceive a man utilizing special highlights of human physiological or conduct attributes, for example, fingerprints, voice, confront, iris, stride and mark, this verification technique normally gives an abnormal state of security. Expectedly, biometrics works with particular gadgets, for instance, infrared camera for securing of iris pictures, increasing speed sensors for step obtaining and depends on expansive scale PC servers to perform ID calculations, which experiences a few issues including massive size, operational many-sided quality and greatly surprising expense. Adding a wireless dimension to biometric identification provides a more efficient and reliable method of identity management across criminal justice and civil markets. Yet deploying cost-effective portable devices with the ability to capture biometric identifiers – such as fingerprints and facial images – is only part of the solution. An end-to-end, standards-based approach is required to deliver operational efficiencies, optimize resources and impact the bottom line. While the use of mobile biometric solutions has evolved in step with the larger biometrics market for some time, the growing ubiquity of smartphones and the rapid and dramatic improvements in their features and performance are accelerating the trend. This is the right time to take a closer look at mobile biometrics and investigate in greater depth how they can be used to their potential. Consolidated with cutting edge detecting stages can identify physiological signals and create different signs, numerous biometric strategies could be executed on phones. This offers an extensive variety of conceivable applications. For example, individual protection assurance, versatile bank exchange benefit security, and telemedicine observation. The utilization of sensor information gathered by cell phones for biometric ID and verification is a rising boondock that must be progressively investigated. We review the state-of-the-art technologies for mobile biometrics in this research.
Altered Brain Wiring in Alzheimer’s: A Structural Network Analysis using Diffusion MR Imaging
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Mahadevan, J.; Ratnarajah, N.; Ranaweera, R.D.
Alzheimer’s disease is a chronic neurodegenerative disorder and the most common form of dementia. It is characterized by cortical atrophy and disrupted anatomical connectivity as white matter fibre tracts lose axons and myelin degenerates. Biomarker tests are crucial to identify the early stages of the disease. It is currently a key priority in Alzheimer’s research to develop neuroimaging biomarkers that can accurately identify individuals in any clinical stage of the disease. Magnetic resonance imaging (MRI) can be considered the preferred neuroimaging examination for Alzheimer’s disease because it allows for accurate measurement of the 3-dimensional volume of brain structures. Diffusion Magnetic Resonance Imaging (DMRI), one of the methods, provides insights into aspects of brain anatomy that could never previously be studied in living humans. A comprehensive study of structural brain network in Alzheimer’s has been developed using diffusion MR imaging and graph theory algorithms, that can assess the white matter connections within the brain, revealing how neural pathways damaged in Alzheimer’s disease. A range of measurements of the network properties were calculated and the pattern of the community structure and the hub regions of the network were inspected. Global measures of efficiencies, clustering coefficients and characteristic path length confirms the disrupted overall brain network connectivity of Alzheimer’s. Relatively the same pattern of hub regions is preserved in Alzheimer’s, however, non-hub regions are affected, which indicates disease alters the internal pattern of the network especially the community structure. Modular analysis confirms this alteration and produces a different modular structure and increased number of modules in Alzheimer’s. Regional connectivity measures also indicated this change and the measures demonstrated the network centrality shifted from right hemisphere to left in Alzheimer’s. The knowledge gained from this study will support to find the strong imaging biomarkers of the Alzheimer’s disease.
Study on Theory and Practice in Software Quality Assurance (With Special Reference to Information Technology Professionals in Colombo, Sri Lanka)
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Opatha, N.W.K.D.V.P.
A software product is developed or engineered by a set of professionals, and they support and maintain it over a long period of time. Software Quality Assurance (SQA) plays an imperative role in achieving high quality software. SQA process should be carried out from the inception of the project till its maintenance. This research is expected to study the gap between the theories and practical approaches related to SQA by refereeing to Information Technology (IT) professionals in software firms in Colombo, Sri Lanka. Further, it was aimed to explore the differences in SQA activities performed, and perception of IT professionals related to testing and SQA, while identifying the reasons to have/not to have a separate SQA section. The study was conducted as a descriptive study, and the selected sample size was 40. Major reasons identified for not having the SQA section were, the company being small scale with few projects (47.1%) and to reduce the cost (29.1%). The Activities that are performed by companies with a separate SQA section and without a separate SQA section are far too different. Testing programs and retesting them after correction were most popular among both types. The companies enriched with SQA section performed various other activities apart from testing. A significant proportion of the respondents (50%) were not even aware of the SQA standards, and among them, the largest proportion (82%) did not have a separate SQA section. In considering the perception of the professionals with regard to SQA and testing, there is a significant difference among both groups. Furthermore, largest proportion (39%) of the professionals agreed that more up-to-date knowledge regarding the entire process is required, which can cover all the activities and scenarios, while having the presence of SQA from the very beginning to the end of the project. Finally, having a separate SQA section would greatly benefit the companies, and it will contribute to improve the quality, with enriched set of activities. A gap truly exists in between what is emphasized in theories and the way they have been implemented practically in SQA.
Smart Iron Rack: Image Processing Approach to Iron Clothes Remotely
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Yatanwala, Y.W.T.M.; Liyanaarachchi, D.S.G.L.D.
Ironing process is a repeated manual task carried out by people daily. Conventional ironing methods always require significant amount of physical user interaction which is time consuming. As a solution, a research has been carried out to implement a smart iron rack with a mobile application that enables user to remotely perform the ironing process. As illustrated in figure below, the device connects with the mobile application through Wi-Fi and performs many tasks including hanger detection, wrinkle detection in cloths, identification of steam irons’ water levels and sending notifications to user. Iron rack consists of 5 hangers and a wide angle camera that moves along the horizontal beam to detect the clothes. When the user specifies a hanger number, the camera moves to the hanger position to check the availability of the cloth. Afterwards, the steam irons attached to the beam move vertically to iron the both sides of clothes. If the hanger number is not specified, the clothes on all five hangers will be ironed. The availability of the cloth on a particular hanger is detected using template matching algorithms in image processing. SIFT (scale-invariant feature transform) algorithm captures all interesting points of the hanger and shape of the hanger is taken as a key measure to decide the existence of the cloth. Raspberry-pi device which is mounted to micro controller, processes the images in order to determine the level of wrinkles in the outfit before and after the ironing process. “Grabcut” algorithm with localize Gaussian Mixture Model(GMM) is used to classify the foreground and background pixels in order to extract only the cloth from its background. Canny edge detection algorithm is used with (100,200) double thresholds to determine the number of wrinkle pixels in the cloth. The system was tested with 100 outfits made in cotton and silk materials. The accuracy of the system was tested in two stages. System could be able to achieve 0.80 F1 score for detecting clothes on hangers and 0.71 F1 score for detecting wrinkles in the clothes. “Smart iron rack” is a cost effective solution which is capable of remotely ironing 5 clothes at a time.
Forecasting Monthly Ad Revenue from Blogs using Machine Learning
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Dias, D.S.; Dias, N.G.J.
Blogs emerged in the late 1990s as a technology that allows Internet users to share information. Since then, blogging has evolved to become a source of living to some and a hobby to others. A blog with rich content and regular traffic could easily be monetized through a number of methods. Affiliate marketing, Google AdSense, offering courses or services, selling eBooks and paid banner advertisements are some of the methods in which a blog could be monetized. There exists, a direct relationship on the revenue that can be generated through any of the above methods and the traffic that the blog gets. Google AdSense is the leader in providing ads from publishers to website owners. All bloggers or blogging website owners who have monetized their blogs, attempt to maximize their revenue by publishing articles in hope that it will generate the targeted revenue. On the other hand, bloggers or blogging website owners that hope to monetize their blog will be greatly benefitted if there was a way to forecast the monthly ad revenue that could be generated through the blog. But there exists no tool in the market that can help the bloggers forecast their ad revenue from the blog. In this research, we are looking at the possibility of finding an appropriate machine learning technique by comparing a linear regression, neural network regression and decision forest regression approaches in order to forecast the monthly ad revenue that a blog can generate to a greater accuracy, using statistics from Google Analytics and Google AdSense. As conclusion, the Decision Forest Regression model came out as the best fit with an accuracy of over 70%
Investigation of the Impact of Clay as a Bulking Agent for Food Waste Composting at a Controlled Raised-up Temperature
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Jayawardana, M.D.S.B.; Milani, Y.; Silva, C.D.; Wijesinghe, S.
In agriculture, the nourishing and substantial quality of soil can be upgraded through transfiguring organic matter in food waste into humus like substance, which is called food waste composting. This is very important as food waste leads to cause odor and pollute the environment. The moisture content (MC), nitrogen content, C/N ratio and aeration in the compost material can be altered through various bulking agents used during the process. The usage of these bulking agents enhances the biodegradation of food waste and transformation of it into effective compost. Therefore, the entire composting process relies on the indispensable role of the bulking agents. Thus, this study was ultimately aimed to evaluate the influence of using clay as the bulking agent for food waste composting at a controlled high temperature (500C). Here a controlled raised-up temperature was used to lead rapid activation of thermophilic microbes. A consecutive five-day study was carried out to analyze the fluctuations of PH, MC and organic matter content (OMC) by preparing composting feedstock using clay as the bulking agent in four different weight percentages (0%, 5%, 10% and 25%). Using a Scanning Electron Microscope (SEM) surface morphology of the samples was analyzed at the initial stage and after five days composting. The analysis of physical parameters was evident that the organic matter was effectively converted to compost at 500C as all the parameters followed the corresponding gradual fluctuations which are presented at the quality compost production. According to the results, no effect was found from clay to control the PH of the composting process of food waste samples. With the increasing of clay percentage there was no significant change of PH was noticed compared to the blank waste sample. With the increment of the clay percentage of the composting feedstock, initial MC was dropped. Furthermore, by the increasing of the clay content of the samples MC was highly reduced. Similarly, OMC was also drastically decreased with the upswing of clay percentage. According to the observations, it can be concluded that clay has been acted as a good bulking agent to food waste composting. At this elevated temperature Food waste composting process had shown a significantly improvement. Presently, further studies are being carried out to further optimize the percentage of clay for food waste composting process at elevated temperature.
Introducing Novel Classification Methodology to Detect Kidney Disease Patterns in Sri Lanka
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Chathurangi, K.A.A.; Kapila, R.M.; Rathnayaka, T.
The healthcare sector has vast amount of medical data which are not properly analyzed and mined to discover useful information and interesting patterns. Applying data mining techniques on such domain can help medical practitioners to predict even the crucial diseases with ease. This study introduced a novel kidney disease classification methodology in Sri Lankan domain using data mining techniques. Basically there are two types of kidney diseases that can be found in Sri Lanka namely Chronic Kidney Disease (CKD) and Acute Kidney Disease (AKD). The aim of this work is building a model to predict whether a person has a risk on having a kidney disease or not and a model for CKD prediction. The data collected from 108 patients are used to train and test the models. Random Forest algorithm and a multilayered feed forward neural network were used to build the models. Result of this study is a modified Artificial Neural Network with 2 hidden layers to detect kidney disease which gives 0.80952 accuracy and a model with the combination of Random Forest algorithm and Artificial Neural Network with 3 hidden layers for CKD prediction which gives 0.81395 accuracy for testing data. The constructed models give high accuracy and minimum error rate when comparing with the other data mining algorithms.
Natural Language Processing (NLP) Techniques to Measure the Syllabus Coverage with the Final Exam Paper
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Dharmapriya, A.G.K.S.; Jayakody, J.R.K.C.
Exam questions usually play a pivotal role in the education and it is the main assessment technique to evaluate the Intended learning Outcome (ILO). The main Intention of the subject syllabus is to cover the ILO. If the syllabus is not covered effectively through the exam questions, it is a challenging task to identify whether students have acquired and enhance the necessary skills and the knowledge which are specified in the given ILO. Therefore the preparation of the exam papers and its evaluation plays an important role in education to improve the performance of the students. Having appropriate level of exam questions which covers the entire syllabus is a time consuming, tedious and challenging work for the instructors. Therefore this research work was done with the view of setting up effective question paper to measure the depth of the syllabus coverage. Further, Identification of the students’ knowledge level was an output. Natural Language Processing (NLP) techniques such as tokenization, stop word removal, non-alpha numeric word removals and tagging were used to process the contents and questions. NLP with NLTK and cosine similarity with TF-IDF (term frequency inverse document frequency), TF-IDF variations and semantic similarity algorithms were developed to generate a unique set of rules to identify the best syllabus coverage contents for exam questions. Rule based set of logics were developed to classify the exam questions under different syllabus topic. Based on the experiment output, evaluators and instructors can redesign their exam paper. 72 exam questions were used as the initial dataset. Final evaluation was done based on the total value generated from TF-IDF, TF-IDF variations, TF-IDF with cosine similarity and semantic similarity.
Solar Thermal Energy Harnessing Using a Parabolic Trough Concentrator
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Kumara, P.D.C.; Viraj, M.P.S.; Suraweera, S.K.K.; Jayaweera, H.H.E.; Muzathik, A.M.; Ariyaratne, T.R.
This paper reports the results of a study carried out in the development of a solar thermal energy harnessing plant using a parabolic trough concentrator. In the field of energy production one of the most concerned factors today is the air pollution, and it is linked with carbon and sulphur emissions from burning of fossil fuels. It is estimated that the global fossil fuel consumption will increase by 48% by 2040. In this context the Solar energy is still considered as the most prominent clean source of energy. Parabolic trough concentrator (PTC) is the most mature and commercially proven technology among the other solar thermal energy harnessing methods. The objective of this study is to design and develop a high efficiency PTC using locally available technologies and materials. The first Sri Lankan PTC thermal energy plant having dimensions of 4.5 m × 4.8 m and an aperture area of 22.3 m2 has been successfully constructed under this project and are in operation at the University of Colombo. Solar mirror films (3M 1100) pasted on stainless steel sheets are used as parabolic reflectors and they are mounted on Unplasticized Polyvinyl Chloride profiles clamped on a Galvanized Iron structure. A heat transfer fluid (Mobil Therm-605) is used to transfer the harnessed energy from PTC to the secondary energy conversion modules such as steam generator. When designing the mechanical structure, effect of the wind load was taken in to account in order to achieve the maximum stability and precision-focusing. The maximum daytime wind speed of the location of interest is around 8.3 m s-1 and the calculated maximum wind load and torque were found to be 3.19 kN and 3.64 kNm respectively for a gust factor of 1.53. The structural design was optimized using a computer simulation to bring the maximum stress below the yield point, and when stress is 23.72 MPa the total deformation was found to be 1.12 mm which does not affect the focusing significantly. The concentration ratio of the plant is 1:66 and it lies well within the range of the corresponding parameter (1:30 and 1:80) available for commercial plants. The focusing efficiency of the system is 79% which is also on par with the values available for commercial plants. However, the overall efficiency of solar thermal utilization is found to be 28.7%, hence the thermal capacity of the power plant is 5 kW. Improvements are underway to reduce the heat loss from the receiver tube. It is estimated that the overall efficiency of the system can be increased up to 65% to 70% by using evacuated glass receiver tubes.
Age and Gender Related Variations in Human EEG Signals
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Pradeep, H.B.A.C.; Meegama, R.G.N.
There is a significant amount of research focused on discovering the functional behavior inside the human brain and methods to collect brain waves with respect to age. However, due to the lack of research using data-mining and pattern extraction methodologies on such data streams, we may be losing important features from human brain wave pattern data. The proposed research is aimed at collecting different kinds of brain wave patterns from different age categories of human beings and analyzing the correlation between the wave patterns of individuals. All the EEG data were taken from publically available and trusted data sources. The data from 22 subjects, five males and 17 females, within the age range from 3 to 22 years and were recorded with 256Hz and 16-bit resolution. We used FP1 and F7 channels as our main data sources for comparing and classification purposes. In the first phase, we applied a filtering process to clean the EEG data set of young male and female subjects to extract the hidden patterns. As EEG signals are acquired as a continuous stream, we use the sliding dot product or sliding inner product of two wave forms while searching for a long signal for shorter, known feature which is referred to as cross correlation. A correlation function is a function that gives the statistical correlation between random variables. In our research, the correlation between two signal forms (data sets) was used to measure the similarity between two wave forms. Subsequently, the cross correlation between all data pairs was calculated to find hidden relationships between each data group. In the sampling process, We ignored the first 256 data samples which was captured during 1s - 2s time period to compensate for possible errors added to the main brain wave during head movements and early adjustments. Using cross correlation diagrams, we observed similarity of brain wave signals between 11 year male and 22 year female subjects having a peak value of 3.5597e.
Decision Support for Diagnosing Thyroid Diseases Using Machine Learning
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Jayamini, W.K.D.; Weerasinghe, H.D.
Diagnosis of thyroid disorders using two machine learning techniques was studied in this research. Multilayer Perceptron Neural Network with Back-propagation algorithm and Random Forest algorithm were the two algorithms used to build the models for classifying the thyroid diagnosis classes; Hyperthyroidism, Hypothyroidism, Normal. Models were developed with different structures by changing the relevant parameters and the outcomes of the developed models were compared with each other. For developing different neural networks, parameters such as the number of hidden layers, number of neurons in hidden layers and learning rates were changed. For developing different random forest models, parameters such as the number of features per tree and the number of trees in forest were changed. Those models were trained and tested using two different datasets of thyroid diagnosis (Dataset 1 and Dataset 2) which have different attributes that are related to diagnosing thyroid diseases. The models were tested using 10-fold cross-validation while the models were compared and evaluated using the measures Accuracy (%), Mean Absolute Error, Root Mean Squared Error, TP rate, FP rate, Precision and Recall. In diagnosing thyroid disease, both the algorithms performed well. Multilayer Perceptron Neural Network with Backpropagation algorithm performed well for Dataset 1 with an accuracy of 96.7442% and Random Forest algorithm performed well for the Dataset 2 with a mean accuracy level of 98.4915%.
Programmatic Approach to Evaluate Affiliate Offers
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Weerakutti, G.; Rathnayaka, K.T.
To facilitate affiliate publishers with information required to make more thoughtful decisions such as network selection, prior to start promoting an affiliate offer is significant. The present invention proposes a method to identify if an offer is a brokered offer or not and moreover if brokered, to identify how many levels that it is being brokered and who is brokering it. The proposed specification is mainly for the beneficial of the publisher. Publishers of a broker network only see cloaked URLs, rather than the actual URLs that derives from some parent network. Technically, when a user visits a URL of a brokered offer, he/she is being redirected to the offer URL of the immediate parent network. Redirection continues up until it reaches the merchant's website. Each subsidiary network in network chain will deduct an amount from the earnings payable to the publisher. Unless traced as done in the present invention, information about a network chain is not known to the publisher. So, to address the problem, the present invention takes URL to an offer as the only user input, and follows the redirects up until there is no more redirects to follow. These track URLs are then being mapped with their respective network. If the network for a track-URL is unknown, technologies such as WHOIS is being used to find a network with a domain matching the WHOIS record criteria of the track-URL. It is being concluded that, a publisher should either choose the origin or the closest preceding sibling to the origin if they are to make more revenue out of a lead. Only the specification is provided herein, but one skilled in the art is free to make an implementation out of this invention, to help publisher disclose information about an affiliate network chain.
Virtual Airplay Drum Kit based on Hand Gesture Recognition
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Dias, D.S.; Perera, M.D.R.
In the music industry, a drum kit plays a vital role in the production of masterpiece musical melodies. It is also one of the instruments that is in greatest demand by youngsters who are passionate in learning and practicing music. But acquiring a typical drum kit is become a difficult task because of its high cost as well as it requires a large storage space to hold. This research is targeted in examining the possibility of engineering a cost-effective solution to build a portable drum kit. In this approach, ultrasonic sensors are used in order to identify hand gestures. Ultrasonic sensor is used to measure the distance to an obstacle using the theories of sound reflectance. The obstacle in this scenario is the human palm. When the palm of the human is moved up and down above the ultrasonic sensor, mimicking the typical actions of playing a drum kit, the changes in distances to the palm are mapped to corresponding drum sounds using a sound generation algorithm. This algorithm is further optimized in such a way that it yields an optimal consistency in readings, regardless of the typical issues of the low cost ultrasonic sensor such as noise, low accuracy of distance readings and random loss of signal. The solution was tested with the feedback of the general audience and it yielded satisfactory results, in achieving our goal. In conclusion, this approach could be well used in reaching our goal based on over 75% of positive feedback (rated very good and good) received. But in order to improve its accuracy and efficiency, more expensive and more accurate distance sensors such as high precision ultrasonic sensors or infrared sensors could be used. The portability, the low cost of engineering, and yet the deliverance of acceptable level of quality of music, could be identified as the unique key point of this research.
Quadcopter based Surveillance System for an Industrial Environment
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Gamlath, G.B.H.; Dampage, U.; Hewawasam, H.P.M.Y.; Midigaspe, C.S.W.; Herath, H.M.S.U.
The protection of industrial infrastructure is a growing concern within industrial environments. Utilization of humans for efficient surveillance and security monitoring in a large area is inefficient since humans generally fail to maintain the concentration for longer periods of time and also due to cost involvement in employing sufficient human labor. A system architecture and design for a perimeter security system to address the aforesaid issue for large industrial facilities such as airports, seaports, logistic storage complexes and military establishments was being developed as the outcome of our research. It employs an integrated multisensory system to detect, assess and track perimeter intrusions. These sensors are integrated together into a standalone system that acquire, on processing and analyzing the probability of possible threat scenarios ignoring nuisance alarms. Upon finalizing an acquired threat, a quadcopter is autonomously dispatched to the location using an advanced location identification system, which will prioritize the locations according to the severity of threat whilst also alerting the security staff. On reaching the location, the quadcopter provides a real-time video feed while maintaining the focus on the detected target. This system is designed to operate on 24/7 in all-weather condition. A command and control center provides situational awareness to facilitate the security personnel responsible for monitoring and managing incidents. Due to the outcomes of this research, human security personnel will be provided with more relaxation in order to facilitate them to focus on tasks which demand cognitive skills. The proposed method will enhance the surveillance capacity of an installation as well as the rapid deployment capability ultimately leading to an efficient and effective security system with adequate defense in depth which is not found in conventional security systems.