Fourteenth International Conference On Computer Applications (ICCA 2016)
https://onlineresource.ucsy.edu.mm/handle/123456789/22
2024-03-28T11:02:28ZProposed Framework of Rule-based Grammar Checker for Myanmar Language
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
2016-02-25T00:00:00ZMyanmar Summarized Text with Verb Frame Resource
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.
2016-02-25T00:00:00ZMessage Scheduling Delivery on Disaster Notification System
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.
2016-02-25T00:00:00ZIris Recognition using Secant Lines Segments Histogram
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.
2016-02-25T00:00:00Z