Analyzing Customer Buying Habits Using Transaction Data

Data mining is the process of digging trough large files and databases to discover useful, non-obvious and often unexpected trends and relationships. Association rules are popular representations in data mining. It finds interesting association or correlation relationships among large set of data items. Most of the recent years, a very influential association rule mining algorithm, Apriori, has been used. It is to find frequent patterns, which produces candidate generation and multiple scans of database. Therefore, it is time consuming. Frequent pattern mining (FP-growth), is another milestone in development of association rules mining, which breaks the main bottlenecks of the Apriori. The frequent itemsets are generated with only two passes over the database and without any candidate generation process. This paper presents user buying habits using the sales transaction of stationery and FP-growth algorithm in association rule mining which is efficient and without candidate generation

Burden of Chikungunya Virus Infection during an Outbreak in Myanmar

Chikungunya virus (CHIKV) infection is a re-emerging arboviral disease with no approved vaccine, although numerous options are in development. Before vaccine implementation, disease burden, affected age group, and hospitalization rate information should be documented. In 2019, a sizeable outbreak of the East Central South African genotype of CHIKV occurred in Myanmar, and during this period, a cross-sectional study was conducted in two regions, Mandalay and Yangon, to examine the molecular and seropositivity rate of the CHIKV infection. The participants (1124) included dengue-suspected pediatric patients, blood donors, and healthy volunteers, who were assessed using molecular assays (quantitative real-time RT-PCR), serological tests (anti-CHIKV IgM capture and IgG indirect enzyme-linked immunosorbent assays), and neutralization tests. The tests confirmed the following positivity rates: 11.3% (127/1124) for the molecular assay, 12.4% (139/1124) for the anti-CHIKV IgM Ab, 44.5% (500/1124) for the anti-CHIKV IgG Ab, and 46.3% (520/1124) for the CHIKV neutralizing Ab. The highest rate for the molecular test occurred with the dengue-suspected pediatric patients. The seroprevalence rate through natural infection was higher in the healthy volunteers and blood donors than that in the pediatric patients. The results of this study will help stakeholders determine the criteria for choosing appropriate recipients when a CHIKV vaccine is introduced in Myanmar

Acute-phase Serum Cytokine Levels and Correlation with Clinical Outcomes in Children and Adults with Primary and Secondary Dengue Virus Infection in Myanmar between 2017 and 2019

The dengue virus (DENV) has been endemic in Myanmar since 1970, causing outbreaks every 2–3 years. DENV infection symptoms range from mild fever to lethal hemorrhage. Clinical biomarkers must be identified to facilitate patient risk stratification in the early stages of infection. We analyzed 45 cytokines and other factors in serum samples from the acute phase of DENV infection (within 3–5 days of symptom onset) from 167 patients in Yangon, Myanmar, between 2017 and 2019. All of the patients tested positive for serum DENV nonstructural protein 1 antigen (NS1 Ag); 78.4% and 62.9% were positive for immunoglobulin M (IgM) and G (IgG), respectively; and 18.0%, 19.8%, and 11.9% tested positive for serotypes 1, 3, and 4, respectively. Although the DENV-4 viral load was significantly higher than those of DENV-1 or DENV-3, disease severity was not associated with viral load or serotype. Significant correlations were identified between disease severity and CCL5, SCF, PDGF-BB, IL-10, and TNF-α levels; between NS1 Ag and SCF, CCL5, IFN-α, IL-1α, and IL-22 levels; between thrombocytopenia and IL-2, TNF-α, VEGF-D, and IL-6 levels; and between primary or secondary infection and IL-2, IL-6, IL-31, IL-12p70, and MIP-1β levels. These circulating factors may represent leading signatures in acute DENV infections, reflecting the clinical outcomes in the dengue endemic region, Myanmar