Browsing by Author "Billah, Masum"

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A Novel Simulator of Multijunction Solar Cells-MSCS-1D
(International Journal of Renewable Energy Research, 2020) Kowsar, Abu; Sakib, Syed Nazmus; Billah, Masum; Dey, Sujoy; Babi, Khaledun Nahar; Bahar, Ali Newaz; Farhad, Syed Farid Uddin
In this work, a novel simulation tool named one-dimensional multijunction solar cell simulator (MSCS-1D) has been reported. This tool provides an easy platform to verify whether the intended work on a multijunction solar cell can be simulated as per expectations. A modified version of spectral p-n junction model has been used to develop this simulator. The congenial dialog box and graphical user interface (GUI) facilitate rapid data entry and visualization of the simulated results. To ascertain the performance of MSCS-1D, the simulated results from this tool were compared with MATLAB simulated results and found in good agreement. The newly developed simulator could provide the user with an easy and fast-run operating procedure compared to the complex MATLAB programming as well as other solar cell simulators available in the literature.
Abnormal situation in educational institutions during Covid-19 pandemic
(The Independent, 2021-08-31) Billah, Masum
Comparative Study on Solar Cell Simulators
(2019 2nd International Conference on Innovation in Engineering and Technology (ICIET), IEEE, 2019-12-24) Kowsar, Abu; Billah, Masum; Dey, Sujoy; Debnath, Sumon Chandra; Yeakin, Sazzatul; Farhad, Syed Farid Uddin
This paper represents a comparative study on the major thirteen solar cell simulators such as PC1D, AMPS-1D, wxAMPS-1D, SCAPS-1D, ASA, Gpvdm, ASPIN, PECSIM, SETFOS, AFORS-HET, ADEPT, SILVACO ALTAS and TCAD. The inventive year, software development platform, semiconductor model and applications of these simulators have been studied for developing a new solar cell simulator. A comparison among the mentioned simulators has been tabulated for identifying the appropriate tool for evaluating the solar cell performance. A novel multi-junction solar cell simulator MSCS-1D has been presented. This simulator has been created using JavaScript (JS), PHP, PHP: Security and Bootstrap. The simulated results obtained by our MSCS-1D simulator have been compared with the reported MATLAB simulated results and found a good agreement.
Counsel-pro
(Daffodil International University, 2021-07-01) Billah, Masum; Nirab, Abrar Alvi
The title of our project is “AN ANDROID BASED MOBILE APPLICATION FOR BOOKING & INTERACTING WITH TEACHER FOR COUNSELLING TIME”. In this project we focused to take appointment from faculty member of an educational institution like University or College. This appointment is taken by students. Both student and faculty member use only one application. In this project both student and faculty members of an institution have to register in this system to communicate with each other. Student can search their specific faculty member by searching their name. And can sent appointment with the proper reason. A student also can get the details information of this faculty member like (email, phone, office location, designation, appointment schedule, department etc.). After sent request a notification received by faculty member and can see the details (student name, department, ID, email, reason of request etc.) of this appointment request. Then faculty member can accept or deny of this request with a short message. After accept/deny student notify this response. Both student and faculty member can see their appointment in their dashboard of the application. The faculty member can take note about his/her giving appointment in “Note Section”. Which will save in this system.
Investment Activities of Social Islami Bank Limited
(Daffodil International University, 2019-01-07) Billah, Masum
This report is a pre-requirement for the competition of 1.5 years MBA course, to get knowledge of practical banking activities. This report focuses three months working experiences in Social Islami Bank Bangladesh Limited (SIBL). This report has been developed by the secondary data of banking activities of Social Islami Bank Bangladesh Limited and primary data from day to day activities during my internship period. Social Islami Bank Bangladesh Ltd is the first and major private sector commercial bank in Bangladesh fully owned by the Bangladeshi Entrepreneurs. The Bank started its operation from 13March 1983. Now, with its 251 branches in all over the country SIBL serving its valued customers through diversified banking activities. The whole banking process of SIBL is divided into 3 sections. These are General Banking, Investment, and Foreign Exchange Division. Here first chapter discuss background of the report, objective and methodology used in preparation of the report and limitation faced in preparation. Next, I have tried to concentrate on company profile and internship duties.In the First Chapter: Origin of the report, Objectives of the report, Methodology of the report, Limitations of the report has been discussed in this chapter. In the Second Chapter: Historical Background, Mission &Vision, Operating Performance, SIBL Department, Organogram of SIBL, Products and Services, Corporate Social Responsibility (CSR), Investment, Investment Management, Theoretical Aspect, Concepts of Social Islami Bank Ltd has been discussed in this chapter. In the Third Chapter: Different Investment Modes, Investment Policies of SIBL, Investment Approval has been discussed in this chapter. In the Fourth Chapter: Investment Monitoring / Recovery Cell, Total Deposits, Deposit Mix of SIBL, Investment as a % of Client Deposits, Investments (General), Investment (Shares & Securities), Net Investment Income, Industry Wise Classification of Investment, Portion of Bad/ Loss as of Total Classified Investment, Risk Weighted Capital Adequacy Ratio, Recovery Ratio has been discussed in this chapter. In the Fifth Chapter: Finding, Recommendation, and Conclusion has been discussed in this chapter.
Operational Procedures and Guest Satisfaction of Food and Beverage Service Department at The Renaissance Dhaka Gulshan Hotel
(Daffodil International University, 22-06-12) Billah, Masum
The internship report gives a brief observation of the Renaissance Dhaka Gulshan Hotel during the six-month internship. But both of are equally important. The report is divided into several sections based on the supervisor's report Instructions. The goal of study is to build abilities via knowing about different areas of organization. In Bangladesh, there are only a few five-star hotels. They could lead the organization easily. The Renaissance Dhaka Gulshan Hotel is one of Bangladesh's five-star hotels. It is mostly a business hotel rather than a pleasure hotel. The majority of Renaissance Dhaka Gulshan Hotel's customers are business professionals that stay here to attend crucial business meetings. So, in order to please the guests, the hotel's key assets are its rooms and restaurants. The research would include information on the company's history, as well as a focus on consumers, listening to client needs, and other service-related activities. Every time renaissance Dhaka Gulshan Hotel tries to improve their quality and bring new ideas to them. This study allows us to get mastery of bookish information through a realistic and grasp the differences between the two techniques
Performance Analysis of Heart Disorder Prediction Using Machine Learning Approaches
(Daffodil International University, 2022-01-18) Ahmed, Md. Emtiyaz; Sany, Nazmul Hasan; Billah, Masum
Machine learning, Data mining are fundamental in health care also in health care information and identification are essential. Machine learning approaches has recently been utilized to detect and forecast a variety of major health hazards, including diabetes prediction, brain tumor detection, renal problem prediction, and Covid-19 identification, among others. The part of heart is precious organ of our body and if it has any problem then the impact is more dangerous to our body. According to the Centers for Disorder Control and Prevention (CDC) Trusted Source, heart disorder is the leading cause of death worldwide. We use a few attributes to check our heart disorder analysis, and this attribute is one of the most common causes of heart disorder. As a consequence, 6 machine learning classifiers are employed to evaluate the data using Google Collaboratory: Naive Bayes (NB), Logistic Regression (LG), K Nearest Neighbor, Bagging, Decision Tree (DT), and Random Forest (RF). Using the Seaborn distplot, we extract all attributes' features. Here, Applying Random Forest Algorithm (RF) we get the best accuracy, which is 99.18 %. We have the biggest value of the ROC (receiver operating characteristic) curve of any other algorithm.
Performance Analysis of Heart Disorder Prediction Using Machine Learning Approaches
(Daffodil International University, 2022-01-18) Ahmed, Md. Emtiyaz; Sany, Nazmul Hasan; Billah, Masum
Machine learning, Data mining are fundamental in health care also in health care information and identification are essential. Machine learning approaches has recently been utilized to detect and forecast a variety of major health hazards, including diabetes prediction, brain tumor detection, renal problem prediction, and Covid-19 identification, among others. The part of heart is precious organ of our body and if it has any problem then the impact is more dangerous to our body. According to the Centers for Disorder Control and Prevention (CDC) Trusted Source, heart disorder is the leading cause of death worldwide. We use a few attributes to check our heart disorder analysis, and this attribute is one of the most common causes of heart disorder. As a consequence, 6 machine learning classifiers are employed to evaluate the data using Google Collaboratory: Naive Bayes (NB), Logistic Regression (LG), K Nearest Neighbor, Bagging, Decision Tree (DT), and Random Forest (RF). Using the Seaborn distplot, we extract all attributes' features. Here, Applying Random Forest Algorithm (RF) we get the best accuracy, which is 99.18 %. We have the biggest value of the ROC (receiver operating characteristic) curve of any other algorithm.
Performance Analysis of Heart Disorder Prediction Using Machine Learning Approaches
(Daffodil International University, 2022-01-18) Ahmed, Md. Emtiyaz; Sany, Nazmul Hasan; Billah, Masum
Machine learning, Data mining are fundamental in health care also in health care information and identification are essential. Machine learning approaches has recently been utilized to detect and forecast a variety of major health hazards, including diabetes prediction, brain tumor detection, renal problem prediction, and Covid-19 identification, among others. The part of heart is precious organ of our body and if it has any problem then the impact is more dangerous to our body. According to the Centers for Disorder Control and Prevention (CDC) Trusted Source, heart disorder is the leading cause of death worldwide. We use a few attributes to check our heart disorder analysis, and this attribute is one of the most common causes of heart disorder. As a consequence, 6 machine learning classifiers are employed to evaluate the data using Google Collaboratory: Naive Bayes (NB), Logistic Regression (LG), K Nearest Neighbor, Bagging, Decision Tree (DT), and Random Forest (RF). Using the Seaborn distplot, we extract all attributes' features. Here, Applying Random Forest Algorithm (RF) we get the best accuracy, which is 99.18 %. We have the biggest value of the ROC (receiver operating characteristic) curve of any other algorithm.
Study on production process of double jersey Knitted fabric
(Daffodil International University, 2018-04-15) Billah, Masum; Rahman, Md.Tarif
On this study was complete by the production process of double jersey knitting machine . and this article are focused on interlock and rib structure and how this type of machine are work. We also focus about different type of problem those are face to done by the machine running . we get some problem. The major problem of this types of machine are wastage. We discus how can we reduce the wastage of fabric. Compare the different type of rib and interlock machine production process get different type of production data.
Sustainable Grain Protection: Combatting Rice Weevils (Sitophilus oryzae) with Natural Plant Powders
(Asian Journal of Research in Crop Science, 2024) Hasan, Rakibul; Rana, Sohel; Nasim, Roconuzzaman; Billah, Masum; Rahaman, Sadia; Shahrin, Kazi Rifat; Rahman, Anisur; Das, Krishna Rany; Ahmed, Kazi Shahanara
Grain storage plays a pivotal role in ensuring food security and sustaining agriculture for future generations. However, a wide array of insect pests, including the rice weevil (Sitophilus oryzae), pose a significant threat to stored grains. This study was conducted at the Laboratory of the Department of Seed Science and Technology, Bangladesh Agricultural University, Mymensingh, from October 2019 to March 2020, to evaluate the efficacy of plant-based powders for managing rice weevils. The experiment was designed using a Completely Randomized Design (CRD) with three replications and seven treatments. These treatments included five botanical powders—Ocimum tenuiflorum (Tulsi), Azadirachta indica (Neem), Polygonum hydropiper (Biskatali), Nicotiana tabacum (Tobacco), and Lantana camara (Lantana)—applied at three dosage levels: 1 g, 3 g, and 5 g per 100 g of grain. Additionally, a chemical insecticide (Sevin 85 SP @ 0.25%) and an untreated control were included for comparison. Results revealed that neem leaf powder was the most effective, achieving the highest adult insect mortality and the lowest adult emergence. In contrast, Lantana powder exhibited the least efficacy, allowing 94.38% more adult insects to emerge compared to neem powder. Untreated grains experienced a 20% weight loss due to rice weevil infestation after one month of storage, whereas treatment with 5% neem leaf powder reduced weight loss to a mere 0.14%. This reduction was statistically significant compared to all other treatments. These findings suggest that neem leaf powder at 5% is a highly effective, eco-friendly, and safe alternative to chemical insecticides for controlling rice weevils in stored grains.
Two Decades of Endemic Dengue in Bangladesh (2000–2022): Trends, Seasonality, and Impact of Temperature and Rainfall Patterns on Transmission Dynamics
(BMJ Yale Publications, 2024-07-18) Hasan, Mohammad Nayeem; Khalil, Ibrahim; Chowdhury, Muhammad Abdul Baker; Rahman, Mahbubur; Asaduzzaman, Md.; Billah, Masum; Banu, Laila Arjuman; Alam, Mahbub-Ul; Ahsan, Atik; Traore, Tieble; Uddin, Md. Jamal; Galizi, Roberto; Russo, Ilaria; Zumla, Alimuddin; Haider, Najmul
Background The objectives of this study were to compare the dengue virus (DENV) infection, deaths, case-fatality ratio, as well as meteorological parameters between the first and and the recent decade (2000-2010 vs. 2011-2022) and to understand the trends, seasonality, and impact of change of temperature and rainfall pattern on transmission dynamics of Dengue in Bangladesh Methods For the period 2000-2022, dengue cases and death data from Bangladesh’s Ministry of Health and Family Welfare’s website, and meteorological data from the Bangladesh Meteorological Department were analyzed. Mann-Kendall and Sen’s slop tests were used for trends and variations and fitted a time series Poisson regression model to identify the impact of meteorological parameters on the incidence of dengue cases. A forecast of dengue cases was performed using an autoregressive integrated moving average model. Results Over the past 22 years, a total of 244,246 dengue cases were reported including 849 deaths (Case fatality ratio [CFR] =0.34%). The mean annual number of dengue cases increased eight-fold during the second decade, with 2216 cases during 2000-2011 vs. 18,321 during 2012-2022. The mean annual deaths have doubled (21 vs. 46) although the overall CFR had decreased to one-third (0.69 vs 0.24). Between the periods, the annual temperature increased by 0.49 °C, and rainfall decreased by 314 mm despite increasing unusual rainfall in the pre-and-post monsoon period. An increasing trend of dengue cases is observed with a much stiffer rise after 2018. Monthly mean temperature (Incidence risk ratio [IRR]: 1.26), first-lagged rainfall (IRR: 1.08), and second-lagged rainfall (IRR: 1.17) were significantly associated with monthly dengue incidence. Conclusions The increased local temperature and unusual rainfall might have contributed to the increased incidence of DENV infection in Bangladesh. Community engagement, vector control, and destruction of mosquito habitats are key to controlling dengue.
Understanding Challenges and Coping Strategies of University Students in Dhaka City During COVID-19
(East West University, 2023-11-22) Tanjeela, Mumita; Billah, Masum; Rutherford, Shannon
The COVID-19 health emergency has challenged the socio-economic circumstances and health status of mankind worldwide. The effect of these disruptions trickled down and impacted the lives of vulnerable people, including students. The prolonged closure of educational institutions has contributed to aggravating these negative impacts. Around 40 million students have experienced adverse financial and health repercussions amidst the pandemic in Bangladesh. Students experienced inevitable changes in the trajectory of their lives, including lifestyles, relationships with family and community, and reliance on support. As the pandemic-ordained lockdown required virtual learning, students found themselves unprepared, anxious, and ambivalent. The coping strategies of the students amidst the COVID-19 have not been adequately explored in Bangladesh. The objectives of our study are firstly, to delve deeper into the challenges and coping strategies embraced by the students from public and private universities in Dhaka. Secondly, it aimed to identify how social connectedness supported students for resilience building.