http://dlib.iit.ac.lk/xmlui/handle/123456789/57 2026-04-21T02:37:33Z http://dlib.iit.ac.lk/xmlui/handle/123456789/432 A language independent algorithm to send secret messages using steganography Ganeshkumar, Vijayaratnam; Koggalage, Ravindra The radical growth of internet & cybercrime during the last few years has forced us to think about how to improve information security efficiently during communication. Protecting the information during communication via the internet is the major challenge against eavesdropper. Encryption is a widely used technique to ensure secure communication; however, sending encrypted messages often draws an eavesdropper's attention. Steganography is a method of writing secret messages in a way that nobody, except for the sender and the recipient, suspects the existence of a hidden message. In this paper a new steganographic technique is proposed to transmit concealed messages in multi-language or combination of languages, which can be represented in Unicode. Use of inter-character spacing technique is proposed as the steganographic technique and a prototype implementation has been done with Rich Text Format (RTF) documents. An additional optimized compression technique is also proposed with enhanced user defined codes, to support Unicode language. Another advantage is that the secret message (hidden) can be in a different language than which is transmitted through the communication channel. 2010-01-01T00:00:00Z http://dlib.iit.ac.lk/xmlui/handle/123456789/64 Discourse marker based topic identification and search results refining Suwandaratna, Nipun; Perera, M. S. U. Most research oriented search queries consist of multiple topics belonging to one or more domains of knowledge. The objective of such search queries is to find the relationship or impact that each topic has on the other(s). Though web search engines provide easy means to retrieve information off the web, search engines are mainly key word oriented and do not consider the different topics and relationships between such topics present in the results. This project presents a software solution, `SearchDroid' that acts as an intermediate user between a search engine and the end user, refining search results based on different topics identified in the search query and their presence and relationships depicted in search results. A discourse parsing approach has been used to build discourse structures that represent the rhetorical relations of text in search results; this is used to re-rank results based on topics identified in the search query. The project combines linguistics research under discourse parsing with web information retrieval techniques. The lack of literature combining discourse parsing techniques with web information retrieval has been compensated for by introducing a fresh algorithmic approach. An abstract information retrieval mechanism has been created with the use of discourse parsing techniques, and can be integrated into any web information retrieval approach. The system was evaluated by Linguistic Experts, Technical Experts and End users. All experts agreed that a discourse parsing approach was suitable for addressing the problem at hand and that the project had high research value in the aspect of linking linguistics research with web information retrieval research. Hands-on testing of the system by End Users produced high user acceptance of the proposed system. 2010-01-01T00:00:00Z http://dlib.iit.ac.lk/xmlui/handle/123456789/63 Enhancing learning for Visually Impaired with technology: MATHVIS Soysa, Lahiri; Lokuge, Kulari; Wimalasundera, Isuru; De Silva, Menaka N Mathematics for Visually Impaired Students (MATHVIS) is a researched and developed software application that is capable of uplifting the educational background of visually impaired students. This research focuses on providing access to education for all, including the visually impaired, using MATHVIS, which embraces game based learning methodology. The critical factor in the project is the use of sound to communicate with the visually impaired students. All voice instructions were provided along with soundtracks and a menu to enable selecting local languages such as Sinhala and English. The main emphasis of this paper is to discuss the current generation of MATHVIS, which has been extended in several ways, through intensive evaluation and testing. The evaluators selected from categories such as technical personnel, instructors and visually impaired students carried out in depth reviews of the application. This paper discusses the features of the application, evaluation carried out, the technology and learning pedagogy used to develop the application for visually impaired students. The paper also highlights how MATHVIS can be used to provide education for all, including the visually impaired. 2010-01-01T00:00:00Z http://dlib.iit.ac.lk/xmlui/handle/123456789/62 Interactive machine learning for incorporating user emotions in automatic music harmonization Soysa, Amani Indunil; Lokuge, Kulari Harmonization enriches piano melodies by adding variations such as mood, sound enhancements and beats that are the key building blocks of piano music. However, not all piano players and song writers are gifted with the musical talent of harmonizing piano melodies effectively since it requires keeping track of an extensive set of western music rules and concepts, years of training and practice and also musicality within them to harmonize a melody accurately. This paper discusses a solution for the tedious task of harmonization by introducing `ChordATune', an interactive tool for harmonizing melodies and generating chord progressions according to user emotions. Further, ChordATune provides a mechanism to arrange chords according to different genres, drum beats and tempi based on user preference. A machine learning approach with Hidden Markov Model (HMM), along with dynamic programming is used to generate the chord progression for a given melody and embed the emotional factor of the user. The melody is taken in as an audio file to the system, where a pitch class profile is created at run time representing the pitch content of the file over time. In order to embed the emotional factor, the Hidden Markov Model is dynamically created, and HMM properties are generated at run time according to the selected emotional factor and the input pitch classes (melody). Around 250 lead sheets were used to train the system using data driven and heuristic approaches, and the evaluation results represented 80% user satisfaction of the prototype. This research further opens a path for research concerning chord progression generation for vocals, taking into account the extraction of words, emotional factor and the tune extracted from the actual voice of the use 2010-01-01T00:00:00Z