https://onlineresource.ucsy.edu.mm/handle/123456789/24 Mon, 08 Jun 2026 10:28:25 GMT 2026-06-08T10:28:25Z https://onlineresource.ucsy.edu.mm/handle/123456789/493 Syllabus Segmentation from Palm Leaf Manuscripts Soe, Nwe Nwe; Htay, Win Historical handwritten palm leaf manuscripts are very informative documents from which we can learn precious and various experiences from them. This paper presents the character segmentations of historical handwriting from palm leaf manuscripts for handwriting character extraction. In this paper an experiment is carried out to choose color array of an image for binarization of palm leaf manuscripts. To extract images of each character from the leaf selected color intensity array is used for binarization by using famous Otsu thresholding algorithm. After that, image is segmented line by line searching optimal points among the lines using object frequency histogram along the line and Otsu algorithm again. These segmented images are the input elements and the character segmentation process as the final stage of this work. The end result is the images array which contains character images of palm leaf manuscripts. These images, the output of this work, can be applied to optical character recognition for text extraction. Thu, 22 Feb 2018 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/493 2018-02-22T00:00:00Z https://onlineresource.ucsy.edu.mm/handle/123456789/490 Scalable Community Detection using Island based Artificial Bee Colony Algorithm Aung, Thet Thet; Nyunt, Thi Thi Soe Many system of interest in sciences can be represented as network (social network, biological network, computer science and etc), sets of nodes joined in pairs by edges. Detecting community structure is become one of the challenging issues in the study of networked system. Community can be detected by clustering social network where nodes have more intra-community connections rather than inter-community connections. Artificial Bee Colony (ABC) algorithm is a relative new swarm intelligence base algorithm that mimics the foraging behavior of honey bee. It is fast, high efficient and doesn’t need to know the original communities number. So, it is suitable to solve complex clustering problems. ABC can also perform global search over the complex solution space. This paper proposes the large scale community detection algorithm using Island based ABC algorithm on the Spark framework and want to obtain more accurate results than in previous work has been improved. Thu, 22 Feb 2018 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/490 2018-02-22T00:00:00Z https://onlineresource.ucsy.edu.mm/handle/123456789/488 Movements Recognition Towards An Automatic Lip Reading System for One Syllable Myanmar Consonants Thein, Thein; San, Kalyar Myo Lip reading is a process of extracting visual information, observing the movement of the lips of the speaker with or without sound. To extract visual information, reliable movements of the lips are necessary. The major challenge is to recognize lip movements because of many possible lip motions and lip shapes. The accuracy and robustness of a speech recognition system can be improved by using visual information from lip movements and the need for lip reading system is ever increasing for every language. Therefore, this paper presents Myanmar consonant recognition based on lip movements toward lip reading by using CIELa*b* color transformation, Moore Neighborhood Tracing algorithm and Otsu global thresholding technique. This research aims to develop a visual teaching method system for the hearing impaired persons precisely identifying the features of lip movement. Thu, 22 Feb 2018 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/488 2018-02-22T00:00:00Z https://onlineresource.ucsy.edu.mm/handle/123456789/487 Stochastic Context Free Grammar for Statistical Parsing of Myanmar Natural Language Processing Aung, Myintzu Phyo; Aung, Ohnmar; Hlaing, Nan Yu; San, Thida; Moe, Zun Hlaing Parsing is breaking a sentence into its constituent nonterminal. Parsing of simple noun-phrase is useful in the study of artificial intelligence for various reasons, such as, for an index-term generation in an information retrieval; for the extraction of collocation knowledge from large corpora; development of computational tools for language analysis. In this paper, Context Free Grammar and Stochastic Context Free Grammar of Myanmar Noun phrase are presented. These Grammars can be applied in statistical parsing of Myanmar Natural Language Processing, which is convenience for many NLP tasks of Myanmar language such as machine translation, phrase alignment, reordering and text summarization. Thu, 22 Feb 2018 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/487 2018-02-22T00:00:00Z