30 research outputs found
Awareness on health hazard of smoking among students in Yangon University of Economics (Ma Kay Zin Win, 2019)
No full textIn this study, awareness on health hazard of smoking among students in Yangon University of Economics was analyzed. The sample 256 students were selected from total 4337 undergraduate students at Yangon University of Economics by using stratified random sampling. In this study, canonical correlation analysis was used to express the relationship between socio-economic characteristics and awareness on health hazard of smoking. The factor analysis was used to analyze the awareness on health hazard of smoking that contributes significantly to the percentage of variance. In canonical correlation analysis, all of the multivariate tests of significance are statistically significant and six canonical roots are obtained. The results show that the socio-demographic information and the awareness of smoking are positively correlated. The factor analysis shows that the seven principal components are obtained to contribute the awareness on health hazard of smoking among students. It has been found that all principal components support the effects on the awareness on health hazard of smoking among students
"Study of Phase Shift of N-N Scattering Using Green Function Method"
No full text"In order to know the information concerning two-body interaction, the scattering
parameters related to it such as phase shift, scattering differential cross section, total
cross section and scattering amplitude were stuied. By using the Green function method
to find the phase shift and the respective partial cross-section for N-N scattering process.
Then the time independent Schrodinger equation is transformed into the Lippmann
Schwinger equation. And it is solved numerically with Exponential potential within the
energy range of 0 to 330MeV.
Application of A Radial Basis Function Neural Network for Diagnosis of Diabetes Mellitus
No full textIn this paper, an attempt is made to study the applicability of a general purpose, supervised feed forward neural network with one hidden layer, namely; Radial Basic Function (RBF) neural network. It uses relatively smaller number of locally tuned units and its adaptive in nature. RBFs are suitable for pattern recognition and classification. An artificial neural network with radial basic function is applied for the diagnosis of diabetes mellitus system This system consists of three phases: preprocessing, training and testing
Triple Patterns Extraction from Unstructured Sentence Using Domain Specific Ontology
No full textTriplet extraction algorithms can assist the webquery service in order to translate the unstructuredinput query to ontology understanding query SPARQL.SPARQL query language has a graph based structureand can be built by using the triplets (i.e. subjects,predicates and object). However, end users enter theunstructured sentence (words, statements, etc.) as aninput when they wanted to search the requiredinformation on the web. So, it is needed to extract thetriplets (i.e. subjects, predicates and objects) from theinput query to build the ontology browsing querySPARQL. Although there are many triplet extractionalgorithms, either they can’t fully define all triplepatterns from the incoming query or they are timeconsuming process. The proposed algorithm presentedin this paper can handle this triplet’s incompletenessproblem and the aim of this system is to extract thespecific triplets from incoming query and to add thenecessary information for supporting SPARQL querygenerating process in a time-saving manner. Thisalgorithm mainly detects the noun form of words fromthe input query with the help of domain specificontology instead of using parser and takes the worstcase time complexity O(n2) to extract the triplets fromthe unstructured sentences
An analysis of YouTube videos for teaching information literacy skills
No full textTraditionally librarians and educators have been using a variety of methods such as lectures, discussions, demonstrations, and hand-on sessions for imparting information literacy skills. An exciting addition to such initiatives is the availability of Web 2.0 applications. Among the Web 2.0 tools, YouTube is quickly becoming a new way of teaching information literacy skills in a more interesting and engaging manner. The purpose of this study was to analyze information literacy videos on YouTube using the Big6 information literacy model. This paper also makes certain suggestions for using YouTube for imparting information literacy skills effectively
Identification of Dengue Serotypes in Children with Dengue Infection at Yangon Children's Hospital in 2015
No full textDengue is the most important arthropod-borne viral infection of humans. Allfour dengue virus serotypes (DENV1-DENV4) were circulating in Myanmar and DENV-1 was the most frequently isolated one starting in 2001. To identify dengue serotype, a total of 234 paired serum samples were collected from patients with clinically suspected dengue infection attending Medical Wards of Yangon Children’s Hospital from January to July 2015. The convalescent serum samples (S2) were tested by Immunochromatographic tests. The proportion of serologically confirmed cases was 76% (178 out of 234). Out of these, 178 seropositive cases, 46(26%) were diagnosed as primary and 132(74%) as secondary dengueinfection.</p
Domain-Specific Sentiment Lexicon for Classification
No full textNowadays people express their opinions about products, government policies, schemes and programs over social media sites using web or mobile. At the present time, in our country, government changes policies in every sector and people follow with the eyes or the mind on these policies and express their opinion by writing comments on social media especially using Facebook news media pages. Therefore, our research group intends to do sentiment analysis on new articles. Domain-specific sentiment lexicon has played an important role in opinion mining system. Due to the ubiquitous domain diversity and absence of domain-specific prior knowledge, construction of domain-specific lexicon has become a challenging research topic in recent year. In this paper, lexicon construction for sentiment analysis is described. In this work, there are two main steps: (1) pre-processing on raw data comments that are extracted from Facebook news media pages and (2) constructing lexicon for coming classification work. The word correlation and chi-square statistic are applied to construct lexicon as desired. Experimental results on comments datasets demonstrate that proposed approach is suitable for construction the domain-specific lexicon
Sentiment Analysis on Myanmar News Articles
No full textSentiment Analysis (SA) is one of the
most active research areas in Natural Language
Processing (NLP), web/social network mining and
text/multimedia data mining. Traditional news agencies
on online social media allow news consumers to express
their opinions about the news articles. The analysis of
news articles helps to measure and understand the
social importance of many news of events like about 21st
century Panglong Conference, Yangon Bus Service
(YBS) Transportation, and so on. The sentiment
analysis for Myanmar news upon social media is rarely
conducted among researchers to the best of our
knowledge. This research aims to mine opinion of
Myanmar people upon news articles from Facebook
news media pages written in Myanmar language. It
consists of two main steps: (1) extract subjective
sentences and (2) sentiment analyze and classify from
extracted subjective sentences. The main outcome of the
research will be positive and negative human opinion of
Myanmar news comments. Therefore, this research will
be not only opened a window to tap into the
psychological thinking but also studied the general
mind-state of communities especially for Ministries of
the government. Knowing news consumer reactions are
very useful for decision making of politicians and policy
makers
An Investigation on the Effectiveness of Prepared Activated Carbon from Lignocellulosic Waste (Groundnut Shell) on the Decolourization of Fish Sauce
No full textThe present research work focused on the extraction of natural dye from Mangosteen peel (Garciniamangostana Linn). The physico-chemical properties such as moisture content, ash content, total solids content and pH of Mangosteen peel were determined by association of official Analytical Chemists (AOAC) method. The chemical compounds present in Mangosteen peel were investigated by phytochemical tests. Natural dye was extracted from Mangosteeen peel with pure water at 70ºC for 60 minutes. The physico-chemical properties of extracted natural dye were also determined by AOAC method. An attempt was made on the dyeing of cotton fabrics using extracted natural dye with three different mordants such as zinc sulphate, potassium dichromate, potash alum and three different dyeing methods such as pre-mordanting, post-mordanting and simultaneous mordanting and different dyeing methods on the properties of dyed cotton fabrics were also investigated. Moreover, washing and rubbing fastness properties, staining and colour change of dyed cotton fabrics were assessed by using standard Grey scale
Feature Extraction Method for Aspect-Based Sentiment Analysis
No full textIn our daily life, we take opinions of our friends and we
are influenced in decision making process. Opinion is
the view or the judgment about something. Opinion
Mining (OM) or Sentiment Analysis (SA) is the
computational analysis of public’s opinion, emotion,
sentiments, and attitude toward entities and their
attributes expressed in written text. These entities may
be products, services, organizations, individuals, events,
issues, or topics. In sentiment analysis, formal and
informal opinion text like product reviews, news
articles, tweets, forum discussions, blogs, and Facebook
posts are also applicable to all domains. The main
purpose of sentiment analysis is to extract the main
opinions, on which the decision can be made very right.
Paper intends to classify sentiment polarity on product
review datasets by using Mutual Information as a
feature selection method. Because product reviews are
highly focused and they are opinion rich. After the
feature selection, we aim to classify the extracted
features with Naïve Bayes, SVM and Maximum Entropy
to get the accurate sentiment polarity
