Browsing by Author "Akter, Nasrin"

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An analysis on the effects of parenting style on offspring’s behavior using machine learning
(BRAC University, 12/4/2022) Akter, Nasrin; Mostakim, Moin; Reza, MD Tanzim
Parents are usually the most important person for a human being as they encourage and support an offspring’s physical, emotional, social, and intellectual development from infancy to maturity. An individual faces various challenges as they grow up. Proper parenting plays a prominent role in handling and abating those challenges. This paper aims to show various consequences on the attachment style and handling of depression, anxiety, stress, anger due to different types of parenting style. These consequences of parenting styles are to be figured out in an automated way so that one can acknowledge these factors on their own and bring various positive changes to their parenting. The term ”parenting style” refers to a collection of tactics that have various effects on children. These methods can have an impact on children’ minds that lasts long into adulthood, both positively and negatively. This research makes use of machine learning algorithms in order to differentiate between various parenting styles through various aspects of their life such as stress, anxiety, depression, attachment style, anger management etc. The lack of publicly accessible data prompted us to compile my own data set, which consisted of 2206 survey responses from students(school, college, university). Afterward, the survey data was stored and pre-processed. Then, machine learning algorithms such as Decision Tree, XG-BOOST, KNN, Support Vector Machine and Random Forest are utilized to detect parenting style by analyzing the effects of parenting on their offspring and the accuracy of these models are 84.70%, 76.71%, 87.30%, 87.30% and 85.185% sequentially.
Antibacterial Sensitivity Test of Crude Extract of (Curcuma zedoaria, Solanum virginianumand Stephania japonica) &Resistant Pattern of Clinically Isolated Bacteria against Conventionally Used Antibiotics
(East West University, 7/17/2017) Akter, Nasrin
According to WHO A medicinal plant is any plant which, in one or more of its organ, contains substance that can be used for therapeutic purpose or synthesis of useful drugs. The term of medicinal plants include a various types of plants used in herbalism and some of these plants have a medicinal activities. These medicinal plants consider as a rich resources of ingredients which can be used in drug development and synthesis. Moreover, these plants play a critical role in the development of human cultures around the whole world. Moreover, some plants consider as important source of nutrition and as a result of that these plants recommended for their therapeutic values. These plants include ginger, green tea, walnuts and some others plants. Other plants their derivatives consider as important source for active ingredients which are used in aspirin and toothpaste (Ghani, 2003).
Application of machine learning in identification of best teaching method for children with autism spectrum disorder
(BRAC University, 2022-05) Zoana, Zarin Tassnim; Akter, Nasrin; Shafeen, Mahmudul Wahed; Rahman, Tanvir
A good teaching method is incomprehensible for an autistic child. The autism spectrum disorder is a very diverse phenomenon. It is said that no two autistic children are the same. So, something that works for one child may not be fit for another. The same case is true for their education. Different children need to be approached with different teaching methods. But it is quite hard to identify the appropriate teaching method. As the term itself explains, the autistic spectrum disorder is like a spectrum. There are multiple factors to determine the type of autism of a child. A child might even be diagnosed with autism at the age of 9. Such a varied group of children of different ages, but specialized educational institutions still tend to them more or less the same way. This is where machine learning techniques can be applied to find a better way to identify a suitable teaching method for each of them. This paper first summarizes the research on previous researches on special educational needs of autistic children with a focus on the different behaviors that are involved in communicating with their teachers, peers and understanding capabilities that are most generally absent in children on the spectrum. The paper ends with a conclusion that uses Machine Learning algorithm in comparing different autistic traits with some suitable teaching methods, by analyzing their physical, verbal and behavioral performance. In this way, the proper teaching method can be suggested much more precisely compared to a diagnosis result. As a result, more children with autistic spectrum disorder can get better education that suits their needs the best.
Brain Sensing with Wearable Headband (ACP2)
(Scopus, 2021) Akter, Nasrin; Hossain, Nijar; Sattar, Abdus
This paper demonstrates an implementation of a mobile application capable of visualizing EEG data in a meaningful way. The project revolves around the Muse Wearable headband, a commercial device capable of reading EEG brainwaves of the user. With its compatible and downloadable application, Muse is designed to help the user with a meditation, providing aural feedback depending on the EEG measurements of the user during a meditation session. The paper also explores previously conducted research regarding EEG measurement studies. The observed studies include research work from the medical field, practical usability tests, and studies regarding meditation and human state of mind. All of the introduced research gives more insight in the usage of Muse Wearable Headband, EEG signal processing, or meditation research. The implementation is tested and evaluated. The evaluation phase includes separate test setups with different tasks. The aim of the evaluation is to test the performance of the implemented system, and also observe and analyze the EEG measurements while the user is performing different activities during the usage of the application.
Combined Cycle Power Plant and Substation of Ashuganj Power Station Company Limited (APSCL)
(East West University, 9/7/2012) Chisim, Jenifer Jue; Akter, Shafin; Akter, Nasrin
As a part of the requirement of B.Sc in Electrical Electronic and Engineering, we went through the procedure of electricity production, distribution and transmission system of Bangladesh in the following internship report. During our internship program, we have visited the second largest power station in Bangladesh that is Ashuganj Power Station Company Ltd and cultured several important features about APSCL. For instance, there are 9 units with installed capacity of 777 MW. Approximately 15%of the total demand for power (electricity) is met by APSCL. This internship program has opened a window of opportunity for us, as student of EEE department at East West University to validate, our theoretical knowledge with the field experience. We have observed different equipments and have learned different procedures of maintaining power station to run them efficiently and safely. This includes generator, boiler, water treatment plant, steam turbine, gas turbine, compressor, backup system. In addition we have also observed substation equipments such as power transformers, current transformer, potential transformer, protective relays, circuit breakers, insulator, lightning arrester and other key equipments. With the aid of this report, we primarily focus on the details of Combined Cycle Power Plant by incorporating the knowledge about power generation, transmission, maintenance and distribution system at Ashuganj Power Station Company Ltd.
Credibility of TV news in a developing country: the case of Bangladesh
(© 2012 AEJMC., 2012) Andaleeb, Syed Saad; Rahman, Anis; Rajeb, Mehdi; Akter, Nasrin; Gulshan, Sabiha
Television has recently experienced unprecedented expansion in Bangladesh. Given its popularity and influence, and with more people using it for their information, research on the credibility of TV news is warranted. Perceived independence of TV channels, their social role, source expertise, objectivity, and audiovisual quality were hypothesized to influence credibility perceptions of TV news. Based on factor analysis and multiple regression analysis, four of these five factors had a significant effect. Implications of TV news credibility in Bangladesh's development efforts are discussed.
Deployment of E-Services Based Contextual Smart Agro System Using Internet of Things
(Daffodil International University, 2022-02-01) Sattar, Abdus; Shampod, Yeasin Arafat; Ahmed, Md. Tanjid; Akter, Nasrin; Mahmud, Arif
Climate change's effects are becoming more apparent, and farmers are bearing the brunt of the consequences. As a result, by 2050, food production is expected to decline by 18%. Therefore, the study's goal is to develop effective and well-organized roadmap for context-based smart agricultural systems using a pre-determined ICT framework. Following that, this study offers a four-level conceptual framework for an e-services-based smart agro system utilizing internet of things (IoT). Here, each level optimizes the IoT infrastructure to accept e-services based on contextual information supplied by the e-services. Furthermore, the proposed ICTization process intends to broaden the role of ICT technology development. Besides, the system's views decrease misunderstandings about technology, growth, and connectivity while also enhancing raw data, administration, and service synchronization. Farmers, agricultural officers, and network operators, for example, are all included in the proposed roadmap, which includes omnipresent farm treatment services. Precision farming, on the other hand, need new knowledge and innovation in order to achieve an integrated and comprehensive approach to technology.
Design and Development Of Online Personal Finance Management System
(Daffodil International University, 2012-10) Akther, Maria; Akter, Nasrin
Personal finance management is everyday affair in our life and this always becomes difficult to manage due to lack of information management system in relation to finance. There are many accounts information system which are commercially used in different corporate house. But there is no standard information system available for personal finance management. In this context a personal finance management information system which is online is truly important. In this project a personal finance management based on the requirements is conceptualized and implemented. The system enables anyone to manage personal income and expenses with ease via online information system. It is designed to help users to manage their finances to understand where their money is going, pinpointing the areas of excessive expenditure and assist to take decision of cutting down unnecessary expenses. It is found that this information system helps to track finances and generate reports of all. The system is designed and developed using XHTML,PHP, and MySQL as the backend database on Apache Server. The system is developed and implemented and the result is satisfactory. In the future this system will be enhanced based on further requirements
Effect of cotton-polyester composite yarn on the physico-mechanical and comfort properties of woven fabric
(Scopus, 2024-06-10) Akter, Nasrin; Repon, Md. Reazuddin; Pranta, Arnob Dhar; Islam, Shaima; Khan, Azmat Ali; Malik, Abdul
Cotton is the most widely used natural cellulosic polymer and polyester is a synthetic polymer. The use of polyester fiber is increasing gradually day by day due to its strength and longevity, while the use of cotton fiber is decreasing due to its unavailability. At present, the use of cotton-polyester composites is ubiquitous. This research work aims to assess the physical, mechanical and comfort properties of the woven fabric using cotton-polyester composite yarns in a weft direction and coarser yarn count because of the use of these fabrics in the future for the denim manufacturing process. Four different samples were fabricated by using 100% cotton (10 Ne) yarn in the warp direction and 100% cotton, cotton-polyester composite, and 100% polyester yarn in the weft direction of the fabric. Similar fabric and machine parameters were maintained for manufacturing all the samples. The samples were then tested for areal density, tensile strength, thickness, abrasion resistance and pilling, drape, flexural rigidity, and air permeability to find the optimum capability of the fabric. Physico-mechanical properties with the proportion of increasing polyester components in fabrics improves areal density (184 to 199 g/m2), strength (almost 19 times in weft direction), drape (0.655% to 0.789%), and flexural rigidity (almost double). On the other hand, increasing comfortability properties with the proportion of cotton components in fabrics improve air permeability (139.85 to 159.58 cc/s/cm2), abrasion (only 3.036% mass loss), and pilling resistance (grading 4 after 2000 cycles)
Effect of natural thickener on printing performance over cotton woven fabric
(Scopus, 2024-05-30) Islam, Shaima; Akter, Nasrin; Repon, Md. Reazuddin; Mamun, Md. Abdullah Al
Execution of natural thickener (wild taro corm) over pretreated cotton woven fabric with reactive dye has been explored in this research work. Taro root was collected from Sherpur in Bangladesh and made into a fine powder using a grinder. Thickener pastes were prepared by using different concentrations of taro powder, then their viscosity was measured to find out the difference with sodium alginate thickener, which is traditionally used for reactive printing. A suitable thickener stock paste concentration was selected from a number of trials and depending on the result of visual sharpness of the printed samples. A suitable reactive printing method was selected between all in (1 step) and 2 step methods of reactive printing and finally the amount of thickener on the printing recipe was optimized. The color fastness to wash, color fastness to rubbing, bending length, K/S value, levelness, penetration%, print paste adds on and visual sharpness were measured to assess the printing quality. The findings indicate that when Taro corm powder is combined with boiled water, it produces a solution with higher viscosity. Additionally, a mixture of 15 % taro and boiled water yields the most distinct print outline. Comparatively, the 2-step reactive printing method offers a superior outline compared to the 1-step (all in one) method. Moreover, using 50 to 60 gm of taro corm thickening paste for every 100 g of print paste results in a higher K/S value. The results revealed that the wild taro corm could be used successfully as thickener for reactive printing. Finally, the cost was also calculated, and it was found economical as well compared to sodium alginate.
Evaluation and optimization of pretreatment process for lyocell knitted fabric dyeing with reactive dyestuff
(2024-02-20) Akter, Nahida; Akter, Nasrin; Repon, Md. Reazuddin; Islam, Tarekul; Al Mamun, Md. Abdullah; Shukhratov, Sharof
The optimization of pretreatment parameters is one of the most important factors for the successful dyeing of textile materials. The aim of this study was to investigate the most effective way of pre-treating cellulose based lyocell knitted fabric in order to achieve an optimal result when dyeing it with reactive dyestuffs. This research investigates the effects of pretreatment by exhaust method on lyocell knitted fabric, which is analyzed using five different recipes. Pretreatment techniques that are being used are mild pretreatment, hot wash without detergent, hot wash with detergent, causticization, and hot wash with causticization. Pretreated and untreated lyocell fabric is dyed with bi-functional reactive dyestuffs in a shade of 1%, to produce color. Three key factors are considered in this research work: optimum pretreatment technique, causticization time selection, and causticization concentration selection. In order to optimize the pretreatment technique, 16 trials are performed by varying the time and concentration. Compared to other pretreatment techniques, causticization is the best for dyeing lyocell fabric with reactive dyes. Additionally, causticization treatment is observed to have the best performance on lyocell fabric when applied for 30 min. The optimum concentration of NaOH for causticizing lyocell fabric is 3 mol/l, as determined by the results. This assessment of results is done based on four factors such as K/S value (color strength), strength loss %, weight loss % as well as pilling test results.
Nutritional And Micronutrient Status Of Female Workers In Garments Factory In Savar, Dhaka
(Daffodil International University, 2024-06-24) Akter, Nasrin
Background: There have been raised worries about the nutritional condition of Savar garments. workers for several years, yet there is still a lack of sufficient data available. The study aims to investigate the nutritional and micronutrient levels of female employees in a garment factory in Savar, Dhaka, and determine the potential connection between body mass index and micronutrient status. Approach: A survey was carried out on 400 female employees at a clothing factory in Savar using the cross-sectional method. Anthropometric measurements were conducted alongside micronutrient consumption analysis (energy, water, protein, carbohydrate, VitA, VitB1, VitB2, VitB6, potassium, magnesium, calcium, phosphorus, iron, zinc, etc.). Associations were evaluated using bivariate correlations. Findings: In total, 31.4% of employees were considered to be underweight, 26.9% were diagnosed with anemia, 22.1% were found to have iron deficiency, and 46.5% were discovered to have low iron reserves. There was no evidence found of inadequate levels of vitamin A or B12. There was a slight association between body mass index and serum ferritin levels (inversely) as well as serum retinol-binding protein levels (directly). Research on skinny and non-skinny employees found variations in iron deficiency and iron deficiency anemia, with a higher prevalence among the non-skinny individuals. Conclusions: There was a high rate of underweight, anemia, and low iron status. Young, nulliparous female textile workers in Savar could potentially face a greater risk of nutritional deficiencies. It is necessary to develop tactics to enhance their nutritional, micronutrient, and health conditions. Low levels of iron seem to play a role in the high occurrence of anemia. Both underweight and non-underweight Individuals were impacted by low levels of hemoglobin and iron deficiency. Although body mass index was inversely related with iron reserves, genuine variations in iron status between underweight and non-underweight participants could not be substantiated.
Parents Satisfaction Survey of Govt. Primary School A Study on Khagail Govt. Primary School
(Daffodil International University, 2018-12-19) Akter, Nasrin
There are more 1 lakh Govt. Primary school right now in Bangladesh. Khagail Govt. Primary School Established in the year 1973. Khagail GPS passed 45 successful years. This report contains 3(three) parts. First part contains the introduction part, second part contains the organizational profile of GPS, third part contains the practical work I learned from my 3 (three) months internship period. Finally, to support the whole report a general parent satisfaction survey was made by me on Khagail Govt. Primary School gurdian in Bangladesh. It was a randomly selected 20 respondent who gives their opinion on different services of GPS. The intention was to do this survey was to find the overall parent satisfaction, there view, the services GPS offer to interpret on the general discussion mas made by me.
Prediction of Academic Performance Applying NNs
(International Journal of Advanced Computer Science and Applications, 2019) Maitra, Shithi; Eshrak, Sakib; Bari, Md. Ahsanul; Al-Sakin, Abdullah; Munia, Rubana Hossain; Akter, Nasrin; Haque, Zabir
Automation has made it possible to garner and preserve students’ data and the modern advent in data science enthusiastically mines this data to predict performance, to the interest of both tutors and tutees. Academic excellence is a phenomenon resulting from a complex set of criteria originating in psychology, habits and according to this study, lifestyle and preferences–justifying machine learning to be ideal in classifying academic soundness. In this paper, computer science majors’ data have been gleaned consensually by surveying at Ahsanullah University, situated in Bangladesh. Visually aided exploratory analysis revealed interesting propensities as features, whose significance was further substantiated by statistically inferential Chi-squared (χ 2 ) independence tests and independent samples t-tests for categorical and continuous variables respectively, on median/mode-imputed data. The initially relaxed p-value retained all exploratorily analyzed features, but gradual rigidification exposed the most powerful features by fitting neural networks of decreasing complexity i.e., having 24, 20 and finally 12 hidden neurons. Statistical inference uniquely helped shed off weak features prior to training, thus optimizing time and generally large computational power to train expensive predictive models. The k-fold cross-validated, hyper-parametrically tuned, robust models performed with average accuracies wavering between 90% to 96% and an average 89.21% F1-score on the optimal model, with the incremental improvement in models proven by statistical ANOVA.
Road Condition Detection and Crowdsourced Data Collection for Accident Prevention: A Deep Learning Approach
(IEEE, 2023-11-21) Jahan, Md Saroar; Islam, Mominul; Hossain, Md Sanjid; Mim, Jhuma Kabir; Oussalah, Mourad; Akter, Nasrin
Bangladesh is one of the countries struggling to prevent road accidents, which is a global cause for concern. An early warning system that indicates road conditions can contribute to the prevention task. For this purpose, a deep-learning based approach using a Convolutional Neural Network (CNN) to learn from random road images the safety factor is developed. This results in a three-class categorization: (i) Severely risky roads, (ii) Mildly risky roads, and (iii) Normal roads. The application of deep learning techniques in this study yields an accuracy of 95.5% in detecting problematic road conditions. Furthermore, based on the study’s findings, a mobile application has been developed. The app enables real-time crowdsourced data collection of road conditions and provides a platform for users to share this information in real-time with other drivers, thereby, contributing to prevent accidents and raise awareness among drivers and users by pinpointing the location of the risky road. Finally, crowdsourced data has been reused to update the trained model, which further improves the classifier accuracy.
Sentiment Analysis on Food Review Using Machine Learning Approach
(International Conference on Artificial Intelligence and Smart Systems (ICAIS), IEEE, 2021-04-12) Islam, Nourin; Akter, Nasrin; Sattar, Abdus
Interpersonal interaction correspondence has obtained a customary standard way to deal with web. Casual correspondence insinuates the use of web-based life destinations and applications. Twitter is one of the mainstream web-based media utilized in the present-day life. Individuals share their inclination with a post in many exercises of our everyday lives. Supposition analysis has become commonly notable. Regardless, stable Twitter thought portrayal execution stays dangerous due to different issues: generous class lopsidedness in a multi-class issue, illustrative extravagance issues for feeling signs, and the usage of different ordinary semantic models. These issues are perilous since various sorts of online life assessment rely upon exact shrouded Twitter thoughts. As necessities seem to be, a book examination structure is proposed for Twitter notion investigation. Estimation investigation by utilizing twitter information is well known in this recorded. Words and articulations bespeak the perspectives of people about the things, organizations, governments and events through electronic systems administration media. Eliminating positive, negative or nonpartisan polarities from electronic life content names task of suspicion assessment in the field of NLP. The outstanding improvement of solicitations for business affiliations and governments, affect experts to accomplish their examination in assumption examination. This exploration utilizes three front line ML classifiers SVM, Logistic Regression, Random Forest, Naive Bayes classifier for development of product review analysis. The tests are performed using Twitter yelp datasets. This data is available online on the web. The discussion conversation, review objections, destinations are a bit of the appraisal of rich resources where the study or posted articles is their inclination or all-around end towards the subject.