https://onlineresource.ucsy.edu.mm/handle/123456789/22 Mon, 08 Jun 2026 10:28:51 GMT 2026-06-08T10:28:51Z https://onlineresource.ucsy.edu.mm/handle/123456789/2370 Proposed Framework of Rule-based Grammar Checker for Myanmar Language Latt, Tin Myo; Thida, Aye Natural language processing is normally used to describe the function of computer system which analyze or synthesize spoken or written language. One area of Natural language processing is concerned with creating proofing systems, such as grammar checkers. Many researchers have been worked for Grammar checker of Asian Languages. However, Myanmar Grammar Checker has not still well developed yet. This paper develops the grammar checker which uses to detect grammatical errors in the formal texts written in Myanmar language. The aim of this paper is to develop the Grammar Checker for detecting grammatical errors in Myanmar texts and resulting from the lack of agreement, order of words in various phrases. Rule-based approach will be used for Grammar Checking System. The proposed framework of this paper is to describe the overview of Myanmar grammar checker Thu, 25 Feb 2016 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/2370 2016-02-25T00:00:00Z https://onlineresource.ucsy.edu.mm/handle/123456789/2369 Myanmar Summarized Text with Verb Frame Resource Naing, May Thu; Thida, Aye In today’s era, when the size of information and data is increasing exponentially, there is an upcoming need to create a concise version of the information available. This paper presents a summary generation system that will accept a single document as input in Myanmar. In addition, this work presents analysis on the influence of the semantic roles in summary generation. The proposed summarization system uses semantic role of each verb from Myanmar Verb Frame Resource (MVF) to compress original texts. And then, summarization system extracts and combines the sentences according to cut-and-paste method. After that, the system abstracts the important information in fewer words from extraction summary from single documents. The compression ratio of summarization system for 75 documents is 61 percent. Thu, 25 Feb 2016 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/2369 2016-02-25T00:00:00Z https://onlineresource.ucsy.edu.mm/handle/123456789/2368 Message Scheduling Delivery on Disaster Notification System Zan, Thu Thu; Phyu, Sabai Natural disaster cannot be prevented, but its impacts can be eliminated or reduced. Mobile devices are the most effective and convenient communication tools which are not restricted by time and place. In this paper, the main service task is the timely delivery of possibly disaster information to mobile devices which are in the imminent disaster area. The system finds whether a mobile is within a defined disaster area using its GPS coordinates. The system architecture is built for sending notifications to mobile devices in disaster area. This system also proposes an algorithm for server side message scheduling based on queuing theory. This algorithm can handle queuing of messages and delivery to the target devices. Thu, 25 Feb 2016 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/2368 2016-02-25T00:00:00Z https://onlineresource.ucsy.edu.mm/handle/123456789/2367 Iris Recognition using Secant Lines Segments Histogram Win, Ei Phyu; Aye, Nyein Biometrics is a method for recognizing based on physiological and behavioral characteristics. Iris recognition is one of the robust biometric technologies used for authentication applications. An iris recognition system is composed of segmentation, normalization, feature extraction and matching. The performance of iris recognition system depends on the selection of iris features. Most commercial iris recognition systems used patented algorithms developed by Daugman’s Gabor filter for feature extraction. These methods have large computation. To overcome this problem, a new effective method, Secant Lines Segments Histogram, is proposed for extracting features of iris. In this paper, Hough Transform is applied for localizing the iris region. The segmented iris is normalized using Daugman’s Rubber Sheet Model. For extracting iris features, Secant Lines Segments Histogram is used. The two iris feature vectors are matched using Euclidean Distance. The proposed iris recognition system reduces the computation and time load for extracting features of the iris. Thu, 25 Feb 2016 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/2367 2016-02-25T00:00:00Z