Browsing by Author "Billah, Md Masum"

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Heavy Metals in Popularly Sold Branded Cigarettes in Bangladesh and Associated Health Hazards from Inhalation Exposure
(Springer Nature, 2023-08-29) Hasan, Mehedi; Hossain, Md Moazzem; Abrarin, Shaifa; Kormoker, Tapos; Billah, Md Masum; Bhuiyan, Md Khurshid Alam; Akbor, Md Ahedul; Salam, Sayed M A; Khan, Rahat; Naher, Kamrun; Salam, Mohammed Abdus; Ali, Mir Mohammad; Rahman, Md Mostafizur; Emran, Talha Bin; Mahmoud, Z.; Khandaker, Mayeen Uddin; Siddique, Md Abu Bakar
Tobacco products are widely recognized as a major contributor to death. Cigarette smoke contains several toxic chemicals including heavy metals particulate causing high health risks. However, limited information has been available on the health risks associated with the heavy metals in cigarettes commonly sold in the Bangladeshi market. This study evaluated the concentrations and potential health risks posed by ten concerned heavy metals in ten widely consumed cigarette brands in Bangladesh using an atomic absorption spectrometer. The concentration (mg/kg) ranges of heavy metals Pb, Cd, Cr, As, Co, Ni, Mn, Fe, Cu, and Zn vary between 0.46–1.05, 0.55–1.03, 0.80–1.2, 0.22–0.40, 0.46–0.78, 2.59–3.03, 436.8–762.7, 115.8–184.4, 146.6–217.7, and 34.0–42.7, respectively. We assume that the heavy metals content among cigarette brands is varied due to the differences in the source of tobacco they use for cigarette preparation. The carcinogenic risks posed by heavy metals follow the order of Cr > Co > Cd > As > Ni > Pb, while the non-carcinogenic risks for Cu, Zn, Fe, and Mn were greater than unity (HQ > 1), except for Fe. The existence of toxic heavy metals in cigarette tobacco may thus introduce noticeable non-carcinogenic and carcinogenic health impacts accompanying inhalation exposure. This study provides the first comprehensive report so far on heavy metal concentration and associated health risks in branded cigarettes commonly sold in Bangladesh. Hence, this data and the information provided can serve as a baseline as well as a reference for future research and have potential implications for policy and legislation in Bangladesh.
Identifying Factors for Studying in an English Medium Schools or International Curriculum in Secondary and Higher Secondary Levels in Bangladesh
(Daffodil International University, 2022-01-19) Billah, Md Masum
Educational Data mining is a conspicuous research area that helps to develop an educational context. The primary purpose of this work is to find out the factors or attributes for studying in English Medium school or any International Curriculum in grade V to XII in Bangladesh. To prepare the set of attributes, help was taken from some of the renowned persons of the English Medium School and International Curriculum in Bangladesh, such as country director, principal, vice-principal, coordinator, teacher, human resources manager, parents, and students. A set of questionnaires with 29 different questions were prepared. Google form is used to collect data from students to identify the relevant attributes. After pre-processing the data, different clustering algorithms are used to find the best cluster. K-means cluster with 3 clusters gives the best result and found some main attributes or reasons for studying in Bangladesh's international Curriculum. The finding of this thesis is revealed the main factors for studying in an English Medium school or International curriculum and the differences among other schools in Bangladesh. This study finds the importance and the key features of the English Medium School in Bangladesh. It reflects the idea of English Medium School's students on their Curriculum and school. This thesis will help the students select the Curriculum and help the parents decide while admitting their children. This work also reflects the student's and parent's demands on a school and its Curriculum. In the future, this study will help find the main differences between different curriculums in the Bangladeshi education system.
Unsupervised Method of Clustering and Labeling of the Online Product Based on Reviews
(International Journal of Modeling, Simulation, and Scientific Computing, 2021) Billah, Md Masum; Bhuiyan, Mohammad Nuruzzaman; Akterujjaman, Md.
This paper presents an unsupervised approach to cluster reviews of products collected from Amazon and then generates its labels of each cluster. Instead of using a complete review, this paper splits a review into sentences and considers all sentences from the reviews as inputs for Clustering. Hierarchical Agglomerative Clustering (HAC) is used to cluster sentences. The approaches of cluster labeling are also unsupervised. For labeling, three different methods have been used to find a limited number of essential words for each cluster. Extracted essential words are used to construct phrases. Constructed phrases are used as labels for each cluster. This paper compares the result of the labeling method with baseline labeling. In the result evaluation, all the labeling methods outperform the baseline method. The aim of this research is cluster labeling that makes a set of labels to describe a cluster content and distinguishes the labels from other cluster labels.