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Evaluate and Predict Concentration of Particulate Matter (PM10) Using Machine Learning Approach
M. F. Mridha,Md. Abdul Hamid,Shaon Hossain Sani,Akramkhan Rony,Seungmin Oh,Jinsul Kim 한국디지털콘텐츠학회 2019 The Journal of Contents Computing Vol.1 No.1
Particulate matter (PM10) is a general term used for a mixture of solid particles and liquid droplets. PM10 is the most significant air pollutant associated with diseases and death compared to other measured criteria pollutants. In this paper, we have focused on PM10 concentration at Dhaka city in Bangladesh. With the help of our proposed predictive model to predict hourly criteria air pollutant concentrations. The ambient air quality data were collected from October 2016 to March 2019. We have used Artificial Neural Network (ANN) to fill the missing value of our Dataset. And we have used Ensemble model (StackNet) to predict PM10. The average correlation coefficient (R) and root-mean square error (RMSE) values when comparing predictions and measurements were 0.94 and 26.14, respectively.
Evaluating Employee Fringe Benefits Provided by the Entrepreneurs in BSCIC Industrial Estates
Md. Mokarremul Hoque Helal MRIDHA,Md. KAMRUZZAMAN,Md. Alamgir HOSSAIN,Renhong WU Korea Distribution Science Association 2023 Asian journal of business environment Vol.13 No.4
Purpose: The objective of this study is to evaluate the fringe benefits provided by the entrepreneurs in BSCIC (Bangladesh Small and Cottage Industries Corporation) industrial estates in light of the relevant labor laws of Bangladesh. Research question: Fringe benefits are one of the major factors in compensation that play a vital role in employee satisfaction. However, the issue has yet to be taken into consideration in the industrial units. So, the question arises: what is the present condition of employee fringe benefits in industrial estates? Research design, data, and methods: To conduct this mixed-methods research, a total of 222 respondents were selected randomly from employees and entrepreneurs. Two sets of self-administered questionnaires and KIIs were used to collect primary data, while SPSS was used to analyze the data. Major findings and conclusions: The study shows that the conditions of leave and holidays do not comply with labor laws. Further, aspects of maternity leaves, disability/death benefits, retirement benefits, and other financial and non-financial benefits are found not to be at a satisfactory level and do not comply with the existing labor laws. However, the benefits relating to environmental issues are found to be satisfactory. It is expected that the study findings will contribute to the existing literature related to fringe benefits and will help stakeholders and policymakers in formulating and monitoring compensation packages.
Evaluating Employee Fringe Benefits Provided by the Entrepreneurs in BSCIC Industrial Estates
Md. Mokarremul Hoque Helal MRIDHA,Md. KAMRUZZAMAN,Md. Alamgir HOSSAIN,Renhong WU 한국유통과학회 2023 Asian Journal of Business Environment (AJBE) Vol.13 No.4
Purpose: The objective of this study is to evaluate the fringe benefits provided by the entrepreneurs in BSCIC (Bangladesh Small and Cottage Industries Corporation) industrial estates in light of the relevant labor laws of Bangladesh. Research question: Fringe benefits are one of the major factors in compensation that play a vital role in employee satisfaction. However, the issue has yet to be taken into consideration in the industrial units. So, the question arises: what is the present condition of employee fringe benefits in industrial estates? Research design, data, and methods: To conduct this mixed-methods research, a total of 222 respondents were selected randomly from employees and entrepreneurs. Two sets of self-administered questionnaires and KIIs were used to collect primary data, while SPSS was used to analyze the data. Major findings and conclusions: The study shows that the conditions of leave and holidays do not comply with labor laws. Further, aspects of maternity leaves, disability/death benefits, retirement benefits, and other financial and non-financial benefits are found not to be at a satisfactory level and do not comply with the existing labor laws. However, the benefits relating to environmental issues are found to be satisfactory. It is expected that the study findings will contribute to the existing literature related to fringe benefits and will help stakeholders and policymakers in formulating and monitoring compensation packages.
Full Dynamic Transmission Model and Threat Analysis of COVID-19
Abu Quwsar Ohi,M. F. Mridha,Md. Abdul Hamid,Muhammad Mostafa Monowar,Md. Ferdous Mridha,AKM Ashiquzzaman 한국디지털콘텐츠학회 2020 The Journal of Contents Computing Vol.2 No.1
No doubt, the COVID-19 outbreak exemplifies ongoing biothreats to humanity as a whole. This necessitates an emergency response towards its remedy because it is heightened in importance and compressed in the time frame. Consequently, significant research efforts have been noticed to tackle this pressing crisis. In this paper, we endeavor to formulate a mathematical model of the transmission of COVID-19. The dynamics of the disease are illustrated by a compartmental model that involves differential equations. The paper also exhibits a mathematical estimation of the future threats induced by COVID-19 universally, which is computed based on the immediate statistical data. We compute the current transmission rate of COVID-19 to be 0.0462, considering the current fertility and mortality of the world population. From the threat estimation, it is expected that the COVID-19 may eliminate around 30% of the current population by the next three years, and it may obliterate nearly 43% of the current population by the next five years.
Nandi, Rajasree,Mridha, M.A.U.,Bhuiyan, Md. Kalimuddin Institute of Forest Science 2014 Journal of Forest Science Vol.30 No.3
Status of Arbuscular Mycorrhizal (AM) colonization in seven tree species (Albizia saman, Acacia auriculiformis A. Cunn. ex Benth., Albizia lebbeck, Chickrassia tabularis A. Juss., Eucalyptus camaldulensis Dehnn., Gmelina arborea (Roxb) DC, Swietenia macrophylla King.) collected from the hilly areas of Chittagong University (CU) was investigated. Roots and rhizosphere soil samples were collected in different seasons (pre-monsoon, monsoon and post monsoon). Percentage of AM colonization in root and number of spores/100 gm dry soil were assessed. The result of the investigation reveals that the intensity and percentage of AM colonization varied in different forest tree species in different seasons. In this study, maximum AM colonization and spore population were found in pre-monsoon and minimum were in monsoon season. The intensity of colonization was maximum in C. tabularis (74.43%) in pre-monsoon, A. lebbeck (69.45%) in monsoon and S. macrophylla (67.8%) in post monsoon seasons and minimum in A. auriculiformis (53.75%) during pre-monsoon, A. saman (24.4%) in monsoon and A. saman (19.36%) in post monsoon. The number of spores found per 100 g dry soil ranged between 164-376 during pre-monsoon, 27-310 during monsoon and 194-299 in post monsoon season. Out of six recognized genera of AM fungi, Glomus, Sclerocystis, Entrophospora, Scutellospora, Acaulospora and other unidentified spores were observed.
Optimizing Energy Consumption Prediction Models using Genetic Algorithms
Seungmin Oh,Yeonggwang Kim,Muhammad Firoz Mridha 한국디지털콘텐츠학회 2021 The Journal of Contents Computing Vol.3 No.1
Prediction and managing energy consumption is essential for smart grid, smart energy management. Recently, Various AI models are being researched to predict energy consumption. Machine learning or deep learning models are essential to improve performance through hyper-parameter optimization. However, Optimization has the disadvantage of having sufficient relevant knowledge or requiring mathematical calculations. In this paper, the performance improvement of XGBoost Regression, RNN, and LSTM models using genetic algorithms could be achieved by improving performance up to 72% on the MSE.
Al-Zaman, Md. Sayeed,Noman, Mridha Md. Shiblee Korea Institute of Science and Technology Informat 2021 Journal of Information Science Theory and Practice Vol.9 No.2
Social media has become a popular source of information around the world. Previous studies explored different trends of social media news consumption. However, no studies have focused on Bangladesh to date, where social media penetration is very high in recent years. To fill this gap, this research aimed to understand its popularity trends during the period. For that reason, this work analyzes 97.67 million page likes and 3.48 billion interaction data collected from nine Bangladeshi news media's Facebook pages between December 2016 to November 2020. The analysis shows that the growth rates of page likes and interaction rates declined during this period. It suggests that the media's Facebook pages are gradually losing their popularity among Facebook users, which may have two more interpretations: Facebook's aggregate appeal as a news source is decreasing to users, or Bangladeshi media's appeal is eroding to Facebook users. These findings challenge the previous results, i.e., Facebook's demand as a news source is increasing with time. We offer four explanations of the decreased popularity of Facebook's news: information overload, exposure to incidental news, users' selective exposure and different aims of using Facebook, and conflict between media agendas and users' interests. Some theoretical and practical significance of the results has been discussed as well.