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

Poverty among households living in slum area of Hlaing Tharyar Township, Yangon City, Myanmar

Background: Slums can be regarded as physical manifestations of urban poverty. Although the world has made dramatic improvement in reducing poverty since 1990, poverty still persists at an unacceptable level. Although current situations highlights the importance of slum areas to be given priority in poverty alleviation, there are limited data on poverty level among people living in urban slums of Myanmar.Methods: A cross-sectional study was conducted among households living in slum areas of Hlaing Tharyar Township, Yangon City, Myanmar during 2016. Multi-staged systematic random sampling and face-to-face interview were applied in selecting the samples and collecting the data, respectively. The new global poverty line (1.9 USD per person per day) was used as a threshold in determining the poverty. Chi-squared test and multivariate logistic regression analysis were utilized in data analysis.Results: Altogether 254 participants were recruited after getting informed consent. The occurrence of poverty among households was 54.3% (95% CI: 48.2%, 60.5%). Head counts of poverty among study population was 58.8%. The education status of household’s head, size of household and the presence of less than 15 years old children in the household were detected as significant determinants of being poor household.Conclusions: Poverty among households living in slum area of Hlaing Tharyar Township, Yangon City was high. Measures to alleviate poverty in urban slums should be intensified. Education level of household’s heads should be improved. Family planning or birth spacing programme should also be strengthened, especially in urban slums.

Automatic Car Number Plate Extraction Using Connected Components and Geometrical Features Approach

As today information era of advanced and secure digital technology field, monitoring system and security mechanisms are played as the most important role. By using specialized security camera in public sectors and pedestrian crossings, it can monitor and record a real time events and information of the sectors as video clips to track criminals. According to get the important data clearly and correctly from the video clips, the detection and extraction methods are essential. The proposed system focuses on the detection and extraction of car number plate that are taken from over speed driving cars. So, these number plates are deblurred to overcome some of the security threat and enhance the motion deblurring technique. Our proposed method is the combination of connected component based approach with the regional geometrical features. In this method, key frames are generated from an input video clips using Discrete Wavelet Transform (DWT) based approach. From the key frame images, rectangle shape areas which has high luminance value is detected and extracted as foreground regions and others are discarded as background by using regional geometric features. Finally, the rectangle shapes are checked whether any text is included or not. If a rectangle shape area contains text, this system accepts that it is a number plate and other region is omitted. Then the accuracy of the research method is evaluated with various experiments to compare with previous researches. This system can be widely used in

Comparison of Count Normalization Methods for Statistical Parametric Mapping Analysis Using a Digital Brain Phantom Obtained from Fluorodeoxyglucose-positron Emission Tomography

Objective(s): Alternative normalization methods were proposed to solve the biased information of SPM in the study of neurodegenerative disease. The objective of this study was to determine the most suitable count normalization method for SPM analysis of a neurodegenerative disease based on the results of different count normalization methods applied on a prepared digital phantom similar to one obtained using fluorodeoxyglucose-positron emission tomography (FDG-PET) data of a brain with a known neurodegenerative condition.Methods: Digital brain phantoms, mimicking mild and intermediate neurodegenerative disease conditions, were prepared from the FDG-PET data of 11 healthy subjects. SPM analysis was performed on these simulations using different count normalization methods. Results: In the slight-decrease phantom simulation, the Yakushev method correctly visualized wider areas of slightly decreased metabolism with the smallest artifacts of increased metabolism. Other count normalization methods were unable to identify this slightly decreases and produced more artifacts. The intermediate-decreased areas were well visualized by all methods. The areas surrounding the grey matter with the slight decreases were not visualized withthe GM and VOI count normalization methods but with the Andersson. The Yakushev method well visualized these areas. Artifacts were present in all methods. When the number of reference area extraction was increased, the Andersson method better-captured the areas with decreased metabolism and reduced the artifacts of increased metabolism. In the Yakushev method, increasing the threshold for the reference area extraction reduced such artifacts.Conclusion: The Yakushev method is the most suitable count normalization method for the SPM analysis of neurodegenerative disease

Molecular Epidemiology of Dengue Viruses Co-circulating in Upper Myanmar in 2006

To understand the molecular epidemiology of circulating dengue viruses (DENV) in Upper Myanmar, DENV isolation was attempted by inoculating the sera of a panel of 110 serum samples onto a C6/36 mosquito cell line. The samples were collected from dengue (DEN) patients admitted at Mandalay Children’s Hospital in 2006. Infected culture fluids were subjected to a RT-PCR to detect the DENV genome. Three DENV strains were isolated. This was the first DENV isolation performed either in Mandalay or in Upper Myanmar. One strain belonged to DENV serotype-3 (DENV-3), and two other strains belonged to DENV serotype-4 (DEN-4). The sequence data for the envelope gene of these strains were used in a phylogenetic comparison of DENV-3 and DENV-4 from various countries. Phylogenetic analyses revealed that this DENV-3 strain was clustered within genotype II, and the two DENV-4 strains were clustered within genotype I in each serotype. The Myanmar strains were closely related to strains from the neighboring countries of Thailand and Bangladesh. These results are important for elucidating the trends of recent and future DEN outbreaks in Myanmar

Hybrid Intrusion Detection System Design for Advanced Threats

Due to the increase in the use of internetand rise in number of network attacks, intrusiondetection has become significant research issue.The objective of this work is to propose a hybridintrusion detection system design to solve thesecurity issue of the today advanced threats. Inthis research work, both anomaly and misusedetection systems are used so that not only theattacks that is already known but also new formof threats can be detected. Agent technology isused to implement in this system. Each detectionengine is autonomous and feedback mechanismis provided so that the system will be modified ifnew form of threats is detected. This proposedsystem will give high accuracy in detection rateand reduce the false positive rate

A Study on some members of Chlorophyta found in Taung-Tha-Man Lake

Algae are photosynthetic organisms that occur in most habitats, ranging from marine and freshwater to desert sands and from hot boiling springs to snow and ice. The term algae refer to a large and diverse assemblage of eukaryotic organisms that contain chlorophyll. They are classified into eight divisions, namely Cyanophyta, Chlorophyta, Euglenophyta, Xanthophyta, Bacillariophyta, Pyrrophyta, Phaeophyta and Rhodophyta. This study emphasized only on the Chlorophyta. Algae specimens were collected from Taung-tha-man Lake which is located at the East of Amarapura Township, Mandalay Division. 18 genera of Chlorophyceae have been identified and described in this paper. All specimens were described with colourful photographic records

Effect of Spirulina on The Germination and Growth of Cicer arietinum L.

Spirulina was used as a biofertilizer in cultivation of chick pea seeds. These chick pea seeds were treated with 2%, 4%, 6%, 8%, and 10% of Spirulina powder (w / w) and experimentally studied in laboratory, pot and plot culture. Germination percentage of chick pea was observed that Spirulina 2% in laboratory, pot and plot culture was the best. On the shoot growth in pot and plot culture, Spirulina 6% treatment was better than other percentages and control during third week. Protein content of chick pea desi type cultivated in control and Spirulina treatment were 13.03% and 18.80%, showing a 45% significant increase with treatment over control. It is obvious that Myanmar Spirulina actually promotes the germination, the growth and protein content of chick pea. It can be pointed out that this increase in protein content of chick pea, due to prebiotic effect of Spirulina on the root nodule system, that increase the nutrients value is a major mile stone in the use of microalgae biotechnology in agriculture. Further study with other legumes should also be investigated extensively to solve the potential problem of food in recent year

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome