Domain-Specific Sentiment Lexicon for Classification

Nowadays 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

Low Incidence of Renal Dysfunction among HIV-Infected Patients on a Tenofovir-Based First Line Antiretroviral Treatment Regimen in Myanmar.

BACKGROUND: Since 2004, Médecins Sans Frontières-Switzerland has provided treatment and care for people living with HIV in Dawei, Myanmar. Renal function is routinely monitored in patients on tenofovir (TDF)-based antiretroviral treatment (ART), and this provides an opportunity to measure incidence and risk factors for renal dysfunction. METHODS: We used routinely collected program data on all patients aged ≥15 years starting first-line TDF-based ART between January 2012 and December 2013. Creatinine clearance (CrCl) was assessed at base line and six-monthly, with renal dysfunction defined as CrCl < 50 ml/min/1.73 m2. We calculated incidence of renal dysfunction and used Cox regression analysis to identify associated risk factors. RESULTS: There were 1391 patients, of whom 1372 had normal renal function at baseline. Of these, 86 (6.3%) developed renal dysfunction during a median time of follow-up 1.14 years with an incidence rate of 5.4 per 100 person-years: 78 had CrCl between 30-50 ml/min/1.73 m2 and were maintained on TDF-based ART, but 5 were changed to another regimen: 4 because of CrCl <30 ml/min/1.73 m2. Risk factors for renal dysfunction included age ≥45 years, diagnosed diabetes, underlying renal disease, underweight and CD4 count <200 cells/mm3. There were 19 patients with baseline renal dysfunction and all continued on TDF-based ART: CrCl stayed between 30-49 ml/min/1.73 m2 in five patients while the remainder regained normal renal function. CONCLUSIONS: In a resource-poor country like Myanmar, the low incidence of renal toxicity in our patient cohort suggests that routine assessment of CrCl may not be needed and could be targeted to high risk groups if resources permit

Integration of Services for Academic and Research on Private Cloud System

Service composition and integration are well investigated problems in Service Oriented Architecture (SOA). However, they still remain among the hard SOA challenges for which automated approaches have yet to be developed. These issues are hindering the agile and costeffective development of service-based business solutions, and the need for addressing them becomes more pressing with the increase in the number of online (cloud) services. The modern design of business and academic IT landscapes is based upon service-oriented architectures. The integration of (external) services raises various challenges to combine the services. In this system workflows are the preferred means for the integration of services on private cloud systems. The proposed workflow model allows academic users to deploy and run the services on (external) private cloud providers. As a Test-bed environment this system uses a Eucalyptus open source system to build up academic institutionbased private cloud system

Integration of Services for Academic and Research on private cloud system

Service composition and integration are wellinvestigated problems in Service OrientedArchitecture (SOA). However, they still remainamong the hard SOA challenges for whichautomated approaches have yet to be developed.These issues are hindering the agile and costeffectivedevelopment of service-based businesssolutions, and the need for addressing thembecomes more pressing with the increase in thenumber of online (cloud) services. The moderndesign of business and academic IT landscapesis based upon service-oriented architectures. Theintegration of (external) services raises variouschallenges to combine the services. In thissystem workflows are the preferred means for theintegration of services on private cloud systems.The proposed workflow model allows academicusers to deploy and run the services on (external)private cloud providers. As a Test-bedenvironment this system uses a Eucalyptus opensource system to build up academic institutionbasedprivate cloud system

Integration of Application Services on Private Cloud System

Service composition and integration are well investigated problems in Service Oriented Architecture (SOA). However, this still remaining among the hard SOA challenges. These issues are hindering the agile and cost-effective development of service-based business solutions, and the need for addressing them becomes more pressing with the increase in the number of online cloud services. This system presents a composition of services that solves a business problem as a solution. As well as it describes the solution reuse at a large scale can be exploited to address challenges of service composition and integration. This paper proposes a reference architecture and technical design of a platform for representation, sharing, and search of solutions

Speech Enhancement Techniques for Noisy Speech in Real World Environments

Communication between computer andhuman has become increasingly popular in todayworld. Investigation of human emotion importance isalso growing in several domains. But under realworld condition, speech signal is often, corruptedwith several noise types and the accuracy ofrecognition is degraded from these noisy signal.Therefore this paper focuses on the speechenhancement techniques to develop emotionrecognition system for the noisy signal in the realworld environment. The various popularenhancement techniques are analyzed by adding thebackground noise to the clean signal using variousSNR. To test the accuracy of the system, the widelyused MFCC signal features are against with the SVMclassifier. Results after enhancing were compared tothat noisy signal and that clean signal to measure thesystem performance. The experimental results showthe best performance algorithm and all enhancementalgorithms improve the emotion recognition systemperformance under various SNRs level of real worldbackground noise

Sentiment Analysis on Myanmar News Articles

Sentiment 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

Application of new serological (Major Membrane Protein II) enzyme linked immunosorbent assay for leprosy patients in Myanmar

As serodiagnosis is the easiest way of diagnosing a disease, the utility of (Major Membrane Protein II) MMP-II antigen in the serodiagnosis of leprosy was examined and compared with NTP-BSA ELISA test. It was carried out on the blood samples of new leprosy cases and their contacts from Nyaungdon Township, and on new adult pulmonary TB cases of Yangon TB Center and childhood TB cases of Yangon Children's Hospital and North Okkalapa General Hospital between November 2006 and December 2007. The sensitivity of the tests on detecting leprosy patients who had not been treated was 58/77 (75.32%) and 54/77 (70.1%) for MB patients using MMP-II and NTP-BSA ELISA tests, respectively. It was 48/64 (75.0%) and 40/64 (62.50%) for PB patients using MMP-II and NTP-BSA ELISA tests, respectively. The sensitivity of MMP-II ELISA test was higher than that of NTP-BSA ELISA test on both leprosy patients. The sensitivity of MMP-II ELISA test was also higher than that of NTP-BSA ELISA test on TB patients in our study. Therefore, our data indicate that MMP-II ELISA could be useful as a supporting serodiagnostic tool in diagnosis of leprosy and childhood tuberculosi