KICACT 2017

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/17369

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V-Synch: Rendering Distance a No-issue with the New Feature of Video Synchronization in Existing Multimedia Platforms.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Tiwari, R.; Shakya, S.
Social media are computer mediated technologies that allow creating and sharing of information idea, career interests and other forms of expression via communities and networks. They introduce substantial and pervasive changes to communication between businesses, organizations, communities and individuals. Various features are being introduced in this field with the objective to make it more attractive to users. “V-Synch” is aimed at introducing features like video and sketch pad synchronization to develop a full- fledged app that also has the current popular features like internet call and chat. We intend to make an android application in which users can always stay connected through multiple platform synchronization (watch the video and use sketch pad in synchronized way in real time) although they are distance apart. All the devices connected to the group can take control of video playback. When any user of that group starts, pauses, or performs specific action on a video, the state of that video is synchronized to all other connected devices in real time. The elements drawn on sketch pad are also shown live in real time to everyone connected to the group. NTP algorithm is used to synchronize all participating devices to within a few milliseconds of Coordinated Universal Time (UTC). The synchronization is correct when both the incoming and outgoing routes between the client and the server have symmetrical nominal delay. V-Synch could be very much beneficial to students for group study, long distance friends to hang out together and Serve a great deal in case of tele-education.
Smart Home Automation Voice Controller.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Perera, P.V.S.P.; Weerasinghe, K.G.H.D.
Each day we are aiming for a smart living condition and make our lives more convenient and fast. The traditional wired electrical device controlling switch is an old concept now. “Voice operated device controlling” utilizes human voice commands to control electrical appliances. This research aims to design and implement a cost effective, portable, user-friendly, secure and simpler Home automation voice controller that can be operated by using Android smart phone. It also reduces the energy usage in the residential sector. This system is also designed to assist and provide support in order to fulfill the needs of elderly and disabled in the home. This research describes the way of remote controlling and monitoring electrical household appliances using Android Smart Phone Bluetooth features and wireless Bluetooth technology module depending user voice commands. The proposed system has two main components, namely voice recognition system and clicking mode facility. When automating a home load not available in the visible range, fault identification system in this design helps the user to ensure that their home appliances had gone exactly ON or OFF. The app was designed by allowing the user to add or edit the appliances. The user had the freedom to add appliances names to this app. User can select either voice mode or clicking mode. Even he/she can check the current status. Changing the language is also available in this app. As an example device name is Fan. The user has to say “Fan” to switch ON. If user wants to switch off, again, has to say “Fan”. Google voice recognition with its voice recognition and voice command features has been used to determine the voice of the user. From the commands received from an android device, the electrical appliances’ current status can be controlled. Android Phone will convert voice into a string of data using Google voice recognition feature. This string of data will be sent to Bluetooth module and then to Arduino UNO. After that, Arduino decodes and process it. The Figure 1 expresses the system architecture of the entire system. Arduino UNO is very popular, cheap product and very easy to use. Bluetooth module, relays are interfaced to the Microcontroller. The data received by the Bluetooth module from an Android smart phone is fed as input to the controller. The controller acts accordingly on the relays of the electrical appliances. The electrical appliances in the research can be made to switch on or off using the Android phone. The application shows the status of switch whether on or off. In achieving the task, the controller is loaded with a program written using Arduino language. This system facilitates features such as automation, multi-functionality, adaptability, interactivity and efficiency for home appliances controlling. As future enhancements, hope to design input voice commands in different language and hope to design smart watch with hand gestures to control in a more user friendly.
De-Identification for Privacy Protection in Audio Contents
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Induruwa, K.G.; Pallewatta, A.P.
Among different forms of audio data or information, the author wishes to limit the scope of this research to privacy protection in voice contents of speakers, because voice generally conveys intelligence such as gender, emotion and it differs from speaker to speaker. De-identification of voice may bring numerous advantages, such as preserving the privacy of speakers during communication, maintaining confidentiality of inquirers who conduct critical investigations and improve the clarity of voice signals used in airport/aviation communication by standardizing the voices of Pilots and Air Traffic Controllers. Though advanced voice encryption methods are available to deteriorate the intelligence of speech, they do not directly address the issues of speaker de-identification. This research project aims at de-identification of voice signals while preserving the intelligence of the speech during communication. Designed GUI for mono LPC spectrums of original and de-identified voice signals In this project, the de-identification process was done at three stages, where the last two processes are irreversible. First, in the frequency normalization stage, pitch of the original signal is changed and slightly de-identified the voice in frequency domain. Then 12 LPC (Linear Predictive Coding) co-efficient values of the subject-person’s original voice signal is subtracted from the 12 coefficient values of the reference sample voice signal. As a result, features are slightly moderated by the second stage. In the third stage the features are destroyed again by shuffling LPC coefficients randomly within three categories. Therefore, this whole process is expected to preserve a higher level of privacy. Based on the test carried out by using 15 samples of male and 15 samples of female voice produced a degree of 10% and 20% de-identification, which could be accepted as a very satisfactory result.
Automated Characters Recognition and Family Relationship Extraction.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Bajracharya, A.; Shrestha, S.; Upadhyaya, S.; Shrawan, B.K.; Shakya, S.
“Automated characters recognition and family relationship extraction” is an application of Natural Language Processing to identify characters from the story and determine the family relationship among them. This application is the use of specialized computer programs to identify entities, classify them and extract characters from them and determine relationship between them. This paper follows basic steps of NLP i.e. Tokenization, POS tagging, sentence parsing followed by the pronoun resolution implementing various algorithms and finally extracting entities and relations among them. Heretofore, we have successfully resolved pronoun from simple sentences by resolving Noun Phrase using the recursive algorithm for tree generation and hence extracting relation between the Noun Phrase (NP). Basic approach towards this project is to do Tokenization and POS tagging first. Then, sentence which is recursive composition of Noun phrase, verb phrase and prepositional phrase is parsed and recursive tree is generated. Then tree is traversed to determine the noun phrase which is replaced by the entity object of that particular noun phrase. Pronoun resolution is the essence of NLP and is of different type. Here, Co reference resolution has been used. After resolving the entire pronoun, then finally relationship is extracted from the story by comparing the relation ID of each Entity. Given the simple story, entities are being extracted and relationship is also determined. Understanding the approach of NLP and implementing them to showcase its use is the main theme of this project which is being done with as accurate result as possible. This paper can act as a base.
Artificial Neural Network based Emotions Recognition System for Tamil Speech.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Paranthaman, D.; Thirukumaran, S.
Emotion has become the important part in communication between human and machine, so the detection of emotions has become important part in pattern recognition through Artificial Neural Network (ANN). Human's emotions can be detected based on the physiological measurements, facial expressions and speech. Since human shows different expressions for a particular emotion when they are speaking therefore the emotions can be quantified. The English speech dataset is provided with descriptions of each emotional context available in Emotional Prosody Speech and Transcripts in the Linguistic Data Consortium (LDC). The main objective of this project describes the ANN based approach for Tamil speech emotions recognition by analyzing four basic emotions sad, angry, happy and neutral using the mid-term features. Tamil speeches are recorded with four emotions by males and females using the software “Cubase”. The time duration is set to three seconds with the sampling frequency of 44.1 kHz as it is the logical and default choice for most digital audio material. For the simulations, these recorded speech samples are categorized into different datasets and 40 samples are included in each dataset. Preprocessing includes sampling, normalization and segmentation and is performed on the speech signals. In the sampling process the analog signals are converted into digital signals then each speech sentence is normalized to ensure that all the sentences are in the same volume range. Next, the signals are separated into frames in the segmentation process. Then, the mid-term features such as speech rate, energy, pitch and Mel Frequency Cepstral Coefficients (MFCC) are extracted from the speech signals. Mean and Variance values are calculated from the extracted features. To create the classifier for the emotions, the above statistical results as an input matrix with their related emotions-target matrix are fed to train, validate and test. The neural network back propagation algorithm is executed by the classifier to recognize completely new samples of Tamil speech datasets. Each of the datasets consists of different combinations of speech sentences with different emotions. Then, the new speech samples are assigned to identify the recognition rate of the speech emotions using the confusion matrix. In conclusion, the selected mid-term features of Tamil speech signals classify the four emotions with the overall accuracy of 83.45%. Thus, the mid-term features selected are proven to be the good representations of emotions for Tamil speech signals and correctly recognize the Tamil speech emotions using ANN. The input gathered by a group of experienced drama artists who have the voice with the good emotional feelings would help to increase the accuracy of the dataset.
Four Legged Walking Robot with Smart Gravitational Stabilization
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Anthony, A.S.; Pallewatta, A.P.
There are many dangerous jobs which could be safely replaced with an adequately designed robot: bomb disposal; construction in high rise buildings; examination of radioactive environments and combat oriented police/military operations. A machine must then achieve a level of dexterity and reliability greater than that of a human worker. One of the most versatile dynamic robots that can be seen today was made by Boston Dynamics: the quadruped robot named Spot Mini is capable of handling objects, climbing stairs and operating in an office, home or outdoor environment (Bostondynamics.com, 2017). One of the main shortcomings of such robots are their size, cost and inherent need for power. Additionally, a dog inspired gait structure is not optimal for climbing. The aim addressed in this study was to design a robot that would be inconspicuous, capable of maneuvering through small environments and be able to climb inclined surfaces with minimum processing power and cost. To this end, the robot was programmed with an insect inspired gait mechanism for maximum surface area while climbing and a novel ability to maintain the center of gravity by leg movements as shown in figure 1A. Table 1 shows a direct comparison of mobility between the finished robot and an average human being. It would either walk or stabilize once instructed via Bluetooth. The newfangled placement of legs ensured bipod gait during locomotion for faster and efficient motion and monopod gait during the stabilization phase for agility. The desired positions were calculated by the use of inverse kinematics and data from the IMU. The finalized robot was able to successfully walk and proceed through various terrain including grass, sand, small stones and miscellaneous household objects such as books, bags, pencils etc. The auto balancing function worked for as steep an angle as 55°.
Challenges in Implementing ERP Systems in Small Medium Manufacturing Companies in Sri Lanka
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Yasotha, R.; Ramramanan, L.
There are numerous information systems available in the market to be selected for implementation in manufacturing organizations. When many information systems manually intergraded for management reporting for a company, there are high risks for accuracy of information. ERP is one of the information systems with inbuilt capacity to integrate many parts of the functional areas that provides meaningful information to the management. This paper describes the experiences on how a small medium size growing roof manufacturing company in Sri Lanka problem and then overcome in implementing ERP system. Small medium size manufacturing companies in Sri Lanka do not normally have electronic information system in all part of business process, whereas some processes such as production process operates outside the information system. Therefore, it is very important to predefine what level of integration to be done, who are the related parties to be consulted and what level of management information is required. The success of ERP implementation is partially depending on the selection of suitable ERP system compatible with company business process and the capability of implementation partner to map those standardized business processes into ERP by conducting BPR. This manufacturing company has many automated manufacturing plants with Programmable Logic Controllers (PLC) versions from year 1960 to 2013. When these PLCs try to integrate into ERP system, there are so many problems faced by the company that leads up to modification of plant. Finally, company decided to implement ERP by postponing the PLC integration. Well tested bugs free less customized SAP B1 system has been implemented to the company by monitoring progress by several log books. The big bang approach has been followed to implement the SAP B1 system with short term parallel run of legacy system. More importantly, top management support and motivation on change management has fuelled up the success of the SAP B1 implementation. This paper reveals the experience gained during the planning to implementation stages of SAP B1 that may occur in small medium manufacturing companies in Sri Lanka.
The Impact of a Security Culture in Small and Medium Scale Enterprise (SME) on Enterprise Information Security
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Pathirana, H.P.A.I.; Karunathilaka, J.A.M.A.
An information system is much more than computer hardware; it is the entire set of software, hardware, data, people, procedures, and networks that make possible the use of information resources in the enterprise. In current world, the information is stored in the computerised system in the form of digital data, including sensitive data, which can be extracted as needed. It is much better than maintaining hard copies in traditional manner by using physical storages. The information system security is crucially important for a business with that background. The SME introduces in many forms. Many use the number of employees, capital amount invested, turnover amount, and nature of business. In Sri Lanka, main banks use value of fixed assets as a way to introduce SME, whereas the World Bank uses number of employees as the criteria. Even though enterprises are relatively small and run with a limited budget, SMEs can now target national and international market segments, enabled by the Internet. Therefore, this complicated the business process at SMEs. The computer security represents confidentiality, integrity and availability (CIA) from the mainframe-computing era. The rise of the Internet and complex computer systems means that data is now decentralized. As such, the security measures now must extend form the CIA domain to cover additional areas, depicted in the McCumber Cube in three dimensions. This challenges SME’s to assure information security with a limited operating budget, and there are two approaches presented by the ‘Sphere of Protection’, focusing on both technology and people aspects. The technological aspect is expensive, whereas the people aspect is cost effective by introducing security culture. The policy implementation is the better tool for security culture by considering business in process level emphasizing laws to acknowledge people on the importance of assuring secure environment, and education and training are important to share the knowledge among employee. This paper explores the need for effective people based security measures for better security culture, before the implementation of technological controls is considered for SMEs.
A Simple Machine Learning Approach for Identifying Promotional Short Message Service (SMS) Messages.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Dias, D.S.; Dias, N.G.J.
Mobile phones play an integral part in the modern lives of humans. Short Message Services (SMS) Messages have become a popular mode for simple communication. Its’ simplicity, costeffectiveness and large audience has attracted the attention of advertising industry to send targeted promotional messages to mobile phones. In Sri Lanka, a survey conducted in Colombo, yielded that 3 out of 5 SMS messages received our promotional messages. Even though extensive research has been carried out in detecting junk SMS messages, the amount of research conducted on filtering promotional SMS messages is rare. The purpose of this research is to evaluate the success and accuracy of utilizing a simple machine learning algorithm to identify promotional SMS messages. Here, we have used a feed-forward neural network based on a statistical model, which was trained with a training data set consisting of promotional as well as non-promotional messages. Each test message was broken down in to individual words and filtered through by cleaning to form keywords which will have consist of a weight and probability value. With each message that is used to train, these values will be updated according to whether it is a promotional or a non-promotional message. When a message is tested through this neural network, the words of the message will be matched against the keyword’s weight and probability, which will then calculate a resultant probability. By setting a par-value, we can classify the test as a promotional or a non-promotional message. The proposed model yielded a 100% accuracy when tested within the given test data set. In order to get successful results for broader test data sets, the model has to be trained comprehensively with proper amount of promotional and non-promotional messages. Optionally, the results obtained from the feed forward neural network for incoming messages, can then be fed back in to the feed forward neural network for further training. As future work, we intend to take this solution to an android-based mobile application that extracts promotional messages from the incoming SMS messages as well as from a server, and display them to the user based on his preferences.
Introduction of a Four Stage Process of Developing Interactive Multimedia Based E-learning Materials.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Jayantha, R.H.U.; De Pasqual, M.K.; Suraweera, S.A.D.H.N.; Yatigammana, M.R.K.N.; Pathiranage, D.M.; Pallewatta, A.; Wijayarathne, P.G.
Interactive multimedia-based learning materials have been commonly used to facilitate teaching and learning. Technological tools have made the task of creating expression through multimedia more easily available. Invariably this has altered the dynamics of interactions that have traditionally constituted educational ecology of the classroom. Sri Lankan higher education sector has slightly move towards student-centered (collaborative) elearning based around construction to increase equity of access to education, to improve teaching and learning, and to promote students and academic staff in student-centred and activity-based teaching and learning. In designing pedagogically sound interactive multimedia-based e-learning materials, a high premium needs to be placed on leveraging a judicious mix of various presentation modes to cater to user’s differing learning styles and needs. This will ensure that learning is optimized which is essentially student-centred in nature in multimedia rich learning environments. However, as identified by National E-Learning Resource Center (NELRC) at University of Kelaniya, Sri Lanka, most of public higher education institutes largely use face-to-face teaching while e-learning is used as a supplementary tool. There is a lack of understanding of developing technological and pedagogical sound interactive multimedia based e- learning materials which are current problem areas seeking attention. This study used qualitative methodology which made use of qualitative method such as content analysis. This includes three distinct approaches: conventional, directed, and summative. This study used conventional content analysis where coding categories are derived directly from the text data. Based on conventional content analysis of e-learning literature which published in 2010-2016 and retrieved from EBSCO database, the four-stage process i.e. Analysis, Design, Develop,and Delivery has been developed to be used in developing technological and pedagogical sound interactive multimedia based e-learning materials in the Sri Lankan higher education system. After understanding the requirement of developing e-learning materials, the identified process start with the analysis stage which include multiple stages i.e. analyze the needs, cost, content, market, technology, and delivery method and assessment strategies. Design, develop, and delivery stages can be then carried out which also include multiple steps. This process will be useful as a guide for any e-learning centers or any teaching and learning organization for developing interactive multimedia based e-learning materials.
Facilitating an E-Learning Platform Beyond the Lectures: Digital Natives Become Active Learners.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Weerakoon, A.D.
The traditional lecturing can't inspire the digital natives towards the engagement in active learning to succeed them in the university environment and beyond in the real world context. In 2004, Romiszowski declared that e-learning presents an entirely new learning environment for students, thus requiring a different skill set to be successful. In 2008, Markus stated that e-learning is a learning process created by interaction with digitally delivered content, network-based services and tutoring support. E-learning is also called web-based learning, online learning, distributed learning, computer assisted learning, or internet based learning. This study was focused to explore the impact of a poster exhibition project on the active learning of digital natives by providing an e-learning environment. This study was carried out with Level 2 Polymer Engineering Technology students and four consecutive annual poster exhibitions has been conducted with four different batches. Each poster exhibition project was a one-month project. The students were grouped into 12 teams of 2 students in each group and each group had to prepare one poster after finalizing a theme for the poster exhibition project and the topics for the individual posters. The theme and the topics were selected to cover more than the 75% of the syllabus content of DPT 207 Polymeric Materials subject. In preparation of the posters, each group had to write a report in prior to create the rough skeletons for the poster by referring relevant articles including journal articles through the internet and each group was asked to email that report to the researcher before the given deadline. Through the constructive feedback the students had to modify the rough skeletons several times and finally came up with amazing posters. At the end of the poster exhibition project the students were given a questionnaire with both open-ended and close-ended questions. Descriptive statistical results reveal the facilitation of e-learning helps the students to learn actively, motivationally and to enhance self-monitored learning along with the collaborative learning. By enabling learners to be more active participants, a well-designed-e-learning experience can motivate them to become more engaged with the subject content and further develop them as lifelong learners.
Investigation of Efficiency of the Solid-state Dye-sensitized Solar Cells with Metal Centered Dye and Metal-free Organic Dye.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Varathaseelan, S.D.
Converting solar energy into electricity provides a much-needed solution to the energy crisis the world is facing today. With continuous research studies conducted in this field, we have come across the third generation of solar cells; the dye sensitized solar cells. Several types of dyes have been individually employed to study sensitization process of TiO2|sensitizer|p-semiconductor type solar cells. Highest efficiency has been achieved from dye-sensitized solar cells using ruthenium based metal complexes as dyes on glass substrate. However, ruthenium metal complexes cause environmental issue and they are very expensive. So we are in a need to find an alternative method. In this study metal free organic dye was used to prepare DSSCs to compare the efficiency of thesolar cell with metal centered dye. In this study, an environmental friendly dye, 1-(2- hydroxycarbonyl-phenyl)-5-(2-hydroxy-5-sulfophenyl)-3-phenylformazan (zincon) is used as a dye (sensitizer) to fabricate a solar cell. Zincon is an azo dye used as indicator for detection of metal ions. Zincon dye exhibits solvatochromic behavior due to enforcement of Van der Waals interaction between dye molecules and solvents depending on their polarity. Zincon was coated on titanium coated conducting glass substrate. Zincon dye has different surface chelating groups and making bonds easily with metal oxides. Coupling of zincon dye by COOH group with Ti4+ was confirmed by FTIR measurements. A platinum coated plastic substrate is attached to the dye coated film and the space was filed by the I-|I3 - electrolyte by capillary action. I-V characteristics were measured under light illumination. Photocurrent of 1.6 mAcm-2, photo-voltage of 395 mV, fill factor 26.5 % and efficiency of 0.2 % were observed as the best performances of the cell. Performance of this DSSC is very poor when comparing this with metal centered dye used DSSC as it gives nearly 15.3mAcm-2 photo current and having efficiency up to 3.8%.
Analysis of Road Traffic Accidents Using Data Mining
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Liyanaarachchi, K.L.P.P.; Charles, E.Y.A.
Accident happens unexpectedly and unintentionally, typically resulting in damage or injury or in fatalities. Data mining is the extraction of implicit, previously unknown, and potentially useful information from data collected for various purposes. The main objective of this research is to identify more accurate and useful patterns that would exists in the road traffic accident data using data mining techniques. It is believed that these patterns can be utilized to take measures to reduce the number of accidents or the severity of the accidents. As part of this research work, details of accidents occurred in Colombo district in the year 2015 were collected from the Traffic Headquarters, Colombo, Sri Lanka. A data set with 9487 accident incidents each detailed with 55 features was created from the collected data. This data consists four types of accidents, namely, Fatal (154), Grievous (877), Non-Grievous (2028) and Vehicle damage only (6428). There are a quite a few published studies on traffic accident analysis using data mining methods. In most of these studies, J48 classifier has produced higher accuracy than other methods. So far no such study has been reported on accidents occurred in Sri Lankan roads. A correlation analysis was performed on the data set and as a result 10 attributes were removed. In this study, the J48 decision tree classifier was usedin two ways. In the first one all four type of accidents were considered. The decision tree built with 70% of the data was able to achieve an average accuracy of 71.4687%. In the second analysis, three types Fatal, Grievous and nongrievous types were combined into one class and named as Injured. This approach was taken to reduce the effect of the vehicle damage only class, which is around 68% of the total data. The decision tree built with this merged classes was able to achieve an accuracy of 78.7288 % using a tenfold cross validation. The decision tree was converted into 20 rules, which can predict the type of accident based on the identified attribute values. The results were found to be helpful to identify the factors influencing traffic accidents and can be further analyzed to find more subtle reasons or situations that are causing accidents.
On Compression Ratio Info-leak Mass Exploitation (CRIME) Attack and Countermeasures.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Prasadi, S.; Alupotha, J.; Fawzan, M.; Alawatugoda, J.; Ragel, R.
Header compression is desirable for network applications, as it saves bandwidth. However, when data is compressed before being encrypted, the amount of compression leaks information about the amount of redundancy in the plaintext. This leads to the CRIME attack on web traffic protected by the SSL/TLS protocols. In order to mitigate the CRIME attack, compression is completely disabled in the TLS/SSL-layer. Although disabling compression completely mitigates the CRIME attack, it has a drastic impact on bandwidth usage. The attack is carried out with the assumption that the attacker has the ability to view the victim’s encrypted traffic. An attacker can accomplish this with a network protocol analyzer. It is also assumed that the attacker has the ability to make the victim client to send requests to the targeted web server. This can be accomplished by coercing the victim to visit an attacker-controlled site (which contains a JavaScript code that sends requests to the targeted server with attacker-injected values in request headers). The attacker will coerce the victim to send a small number of requests to guess the first byte of the secret cookie. The attacker then measures the size of the (compressed) request headers. With that information, the CRIME attack algorithm determines the correct value for the first character of the secret cookie. Since the attack relies on LZ77 loss-less data compression algorithm, the first byte of the target secret must be correctly guessed before the second byte is attempted. Separating secret cookies from compression is presented as a proven-secure countermeasure against CRIME attack in a previous work: (1)--separates all the secret cookies from the request header. (2)--rest of the header is compressed, while the secrets are kept uncompressed. Since the secret cookie is not compressed with the attacker-injected values, the origin of the compression leakage is shut. Thus, the proposed solution completely prevents the CRIME attack and also enables header compression. This is useful in reduction of network bandwidth usage. Figure 1 CRIME attack setup In this work we create a test environment to replicate the CRIME attack and to test countermeasures.
Coal Fly Ash as an Alternative Substrate to Replace River Sand in Cement Mortar Mixture
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Jayaweera, N.J.S.T.; De Silva, P.; Herath, H.M.P.I.K.; Jayasinghe, G.Y.
Coal is the most extensively used primary source of energy that accounts globally for 25% of total energy consumption. The global generation of coal fly ash (CFA) is estimated to be above 6x108 Mg per annum and its recycling rate is rather low (15%). Sri Lanka is also facing major economic and environmental problems of disposing CFA from Norochcholai thermal power plant and part of CFA disposal is being used as a raw material for cement production. However, CFA with high loss on ignition (LOI) values cannot be used for blending with cement and this study was designed to investigate the potential utilization of high LOI-CFA as an alternative substrate to river sand in cement mortar preparation. Compressive Strength (CS), water demand (WD), moisture content (MC), initial setting time (IST), and final setting time (FST) were examined to select the most suitable mixing ratio of CFA and river sand. Treatments were prepared in accordance with SLS ISO 1253−107: part 2−2008, with 30 replicates for LOI and MC. Treatments were defined as the percentage of added CFA into sand as T1=0 (control), T2=5%, T3=10%, T4=12%, T5=15%, T6=18%, T7=20%, and T8=25%. Four replicates per each treatment in different three ages (one day−1D, seven days−7D, and twenty-eight days−28D) were tested for CS of mortar in accordance with SLS ISO 679:2008. Initial and final setting time of cement CFA mixture was determined in accordance with SLS ISO 9597:2008(E) with 8 treatments. Results have proven that high LOI-CFA can be used as an alternative substrate to sand up to 20%. The average CS for 1D, 7D, and 28D of control treatment were 16.8 MPa, 41.3 MPa, and 51.3 MPa respectively. The highest CS for 1D (21.9 MPa) and 28D (71.1 MPa) were given by 10% CFA treatment, but the highest seven-day CS results (50.1 MPa) was given by 12% CFA treatment. Each treatment was significantly different from other treatments. Means for CS of T2, T3, T4, T5, T6 and T7 were not significantly different from the mean of control treatment, while T8 (25% CFA and 75% sand) was significantly different from the control. R2 between WD and CFA percentage obtained by regression analysis was 93.2%, which showed a strong relationship between them. R2 of IST versus WD, and FST versus WD were 97.7 % and 94.8 % respectively, which showed strong relationships with WD. Hence, it can be concluded that increasing CFA percentage up to 20, gave increased WD, IST, and FST.
A Similarity based Compression Approach for Efficient Data Processing on Cost Optimized Multi-Cloud.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Deepa, S.T.; Gejalakshmi.L.
Cloud computing provides a promising platform for flexible massive storage of data, computing and software services in a scalable manner. Massive storage sensing is prevalent in both industry and research applications where the data storage consumes volume and high velocity. There are five phases in the compression based cost effective multi cloud architecture. Pre-process phase: In this phase user is intended to upload their local files. The cloud server decides whether these files to be uploaded considering the authenticity of the user and the content priority. Deduplication process: Once the file is approved for uploading, similarity model is used for compression and clustering, Data chunks are created. Similarity model works with text data and multidimensional numerical data is contributes to the majority of the data available. Markov model is used to calculate the similarity in text data and in tree topology, similarity is determined by the number of leaf nodes. The data is checked for duplication in this step. It is done by generating signature for the data chuck, the signature stored in DDB (Deduplication DataBase) is compared with the signature of the chunk to be stored and then data chunk is stored. Upload phase: After approval for uploading and clustering, the data chunks are encrypted and uploaded into multi-cloud where the application and data are fragmented and stored in multicloud to enhance security and protection. In multi cloud architecture, no cloud provider learns the complete application logic and overall application results which leads to data and application confidentiality. Update phase: If user intend to modify, insert or delete some blocks of the existing files, then the corresponding data chunks alone is updated in the cloud. Proof of storage Phase: The user has a meta data file stored locally to identify which data chunks is available in which cloud in our multi cloud architecture. To make cloud storage cost effective, on demand resource provisioning is established and the cost is calculated depending on the number of user and number of resources used. On demand resource planning avoids under and over provisioning of the resource enhancing the resource utilization.
Factors Influencing the Students’ Intention to Adopt E-learning Special Reference to Eastern University, Sri Lanka.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Nirushan, K.
E-Learning is becoming an important part of learning process. With the evolvement of Information Technology, the “Teacher Centered” traditional learning methodology has started to change to “Learner Centered” methodology. As per this change in learning process, the use of technology plays an important role to enable students to engage fully in their program of study. Moreover, elearning process makes the students very easy to engage with their academic activities. In most of the developed countries, “Distance learning” became huge popular with the use of e-learning process. In Sri Lanka, also most of the higher institutions are trying to provide e-learning facilities to their students in order to utilize the advancement of modern technologies. However, it is necessary to identify the influencing factors regards to e-learning process to fuel the utilization of this emerging technologies such as Virtual Classroom, Learning Management System (LMS). This study examines the influencing factors on students’ intention to adopt e-learning as a tool of learning. Therefor 210 students were randomly selected from Eastern University, Sri Lanka and data were collected through a structured questionnaire. Correlation and Multiple regression analysis were done based on the Technology Acceptance Model (TAM). More than this model a variable called “Prior Knowledge on ITC” was added and analysis was run. Correlation denotes that Perceived ease of use has significant medium positive relationship with intention to adoption of e-learning where r=0.483, p=0.000<0.01. Perceived usefulness and prior knowledge has significant positive strong relationship with intention to adoption of e-learning where r=0.773, p=0.000<0.01 and r=0.863, p=0.000<0.01 respectively. However, multiple regression analysis reveals that “Prior knowledge in ICT” is the most influencing factor on intention of adoption to the e-learning activities. Chi-square test confirms that there is a difference between two gender group in intention of adoption to e-learning activities and crosstabulation analysis shows that boys are more intent to adopt e-learning activities than girls.
Foreign Exchange Rate Prediction using Artificial Neural Network and Sentiment Analysis
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Shrestha, S.; Baral, S.; Subedi, S.; Ranjit, S.; Shakya, S.
Foreign currency exchange plays an important role for currency trading in the financial market. Modern approach to the foreign currency exchange market requires support from the computer algorithms to manage huge volume of transactions. There occurs problems like trading without a plan, failing to adapt to the market, having unrealistic expectation and many more. Due to these problems, predictions are to be done. This paper investigates on prediction of foreign exchange market using neural network and sentiment analysis. There are many algorithms for performing prediction but different algorithms have different accuracy. One of the best method with high accuracy is given by Artificial Neural Networks (ANN). Neural network parameters include number of hidden layers, number of neurons, use of bias neurons, activation functions and training methods. Input nodes are price of gold, crude oil, Nasdaq index, yesterday’s price. Our model contains 4 input node, 1 hidden layer and 7 hidden nodes. At first, pre-processing is done and inputs are fed to the neural network. By using backpropagation algorithm, training is done and then testing is performed. Mean absolute percentage error is found to be 0.39%. The price movement is also directly related to market sentiment. We aim to employ a statistical technique to the opinion of different traders and finding the overall sentiment. Sentiments are taken from tweets and then filtering the tweets are performed. After that, features are extracted and by using Naïve Bayes algorithm, the results are classified as positive or negative.
Machine Learning Dashboard for Aviation Fuel Optimization.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Samarasinghe, R.M.N.S.; Dias, N.G.J.
The aviation industry is the one of the fastest-growing travel industry in the world. This industry is growing 7% per year and is giving its facilities for more than 1.5 billion passengers. The International Air Transport Association (IATA) indicates that this number will pass in the next 20 years by 7.3 billion of passengers. Due to this large growing passenger count, airplane manufacturing companies such as Boeing & Airbus are making more efficient planes to handle this amount. Aviation fuel is the biggest cost in air transport. IATA (The International Air Transport Association) figures show that everyone dollar increase in the cost of oil per barrel increases the airline industry's costs by about $1 billion. So that airline companies do their best to optimize the fuel usage managing many types of maintenance, weight flowing management to reduce the plane taxi fuel. Airplane manufacturing companies are also gearing up to make more fuel-efficient planes. This research project built finding suitable variables and providing a solution to overcome the high fuel usage by using a neural network model to predict the fuel usage, CO2 emission dashboard to get necessary steps to reduce CO2. Finding the suitable variables are the most challenging part in this research. To find them, correlation coefficient method was used. Before using this method need to normalize the dataset using the statistical normalization method after that used this method to find the linear combinations of the fuel usage & other dependent variables. If the value is next to -1 then it gives a perfect negative relation or if +1 then it is a perfect positive relation. For this analysis, the best fit regression model was created based on the variables Actual passenger count, Flight wing size, Flight length, Flight height, Distance between airports, zero fueling weight identified are those variables. For a prediction model, it is more practical to use simple model than a complex model. Before developing this model, data need to be clean (without empty data sets) and eliminate the outlier data from the data set after the normalization process which was done by using the statistical quartile method. For this model 2 types of training, functions were used to create the models ‘Bayesian regularization back-propagation’ and ‘scaled conjugate gradient back-propagation’. ‘Bayesian regularization’ method is the best training to train noisy data sets. After training these 5 layers (4-hidden layer) 5-10-5-10 hidden neuron model, then it was selected as the minimal error rate. There were 26, 834 data points & 70% were used to train this model and the rest 30% was used for testing. For this research, there are lots of future works could be done adding weather data, giving a recommendation in flight scheduling process.
Conflict Categorization of ERP Implementations in Asia Pacific Region.
(Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2017) Herath, H.M.P.S.; Rajakaruna, J.P.
An Enterprise Resource Planning (ERP) system is an integrated software system, typically offered by a vendor as a package that supports the seamless integration of all the information flowing through Business Processes, Business Intelligence, Business Integrations, Collaborations, etc. This research is intended to discuss on complications in ERP implementation in Asia Pacific (APAC) region with the client, vendor, implementer, consultant and project management perspectives. The objective of this research-in-progress paper is to develop a clear visibility of categories of conflicts in ERP projects in multicultural environments. Categorization of ERP project implementation related conflicts would provide better preparation for a successful project implementation and delivery. This is the first attempt for the journey to consolidate the literature on the conflicts associated with ERP projects. Also seeking for uplift the understanding of conflict and managing the same effectively in APAC region. In this case our research question is “Can we categorize ERP project related conflicts?” and if so, “What are the categories of conflicts in relation to ERP implementation in APAC region?” Alsulami (2013) on his “Consolidating Understanding of ERP Conflicts : A dialectic Perspective, Computer Science and Information Systems Faculty, Umm Al-Qura University” categorised ERP projects conflict related to Australian experience into two; such as “Technical related and Process related”. However, thirteen business cases in Sri Lanka, India and Malaysia show us conflicts can be categorised as “People related, Technology related & Methodology related”. These findings can be effectively used by ERP Implementers, Vendors, Consultants, Project Managers and Researchers in their respective projects.