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Item Factors Causing Stunting Among Under-Five Children in Bangladesh(Springer, 2020-10-22) Abid, Dm. Mehedi Hasan; Haque, Aminul; Hossain, Md. KamrulMalnutrition is one of the major problems in developing countries including Bangladesh. Stunting is a chronic malnutrition, which indicates low height for age and interrupt the growth. The purpose of this research is to find out the factors associated with the malnutrition status and test the accuracy of the algorithms used to identify the factors. Data from Bangladesh Demographic Health Survey (BDHS), 2014, is used. Factors like demographic, socioeconomic, and environmental have differential influence on stunting. Based on analysis, about 36% of under-five children were suffering from stunting. Decision tree algorithm was applied to find the associated factors with stunting. It is found that mothers’ education, birth order number, and economic status were associated with stunting. Support vector machine (SVM) and artificial neural network (ANN) are also applied with the stunting dataset to test the accuracy. The accuracy of decision tree is 74%, SVM is 76%, and ANN is 73%.Item International Summit on Employability and Soft Skills (ISESS2017)(Daffodil International University, 2017-03-25) University, Daffodil InternationalIt is my pleasure that Daffodil International University (DIU) is going to host an international academic event titled “International Summit on Employability and Soft Skills (ISESS2017)” to facilitate more opportunity to our graduates. I love to think that our graduates are our sprit to build our motherland into an incomparable sky height. DIU has redesigned its motto as the employability first. During interviewing a graduate, an employer looks not only for subject knowledge up to the mark, but also communication skills, presentation skills, confidence, spirit to harness their soft skills. For that reason, DIU has introduced presentation in each and every course as an integral part of the course, including some practical involvement.Item Modelling the Knowledge-Sharing Behaviour of Students on Facebook(ProQuest LLC, 2018) Hossain, Mohamed Emran; Bhuiyan, Touhid; Mahmud, Imran; Arman, Md. ShohelThis paper aims to illustrate the relationship between the constructs of social cognitive theory and social exchange theory with regard to the knowledge-sharing behaviour of students on Facebook. This research was conducted on 123 students using self-administrative survey questionnaires. The technique of structural equation modelling was employed to examine the hypothesized relationships between the variables. The findings of this study indicate that affiliation and innovativeness significantly the knowledge-sharing behaviour of students. Overall, perceived reciprocal benefit, perceived enjoyment, knowledge power, and affiliation and outcome expectations are found to be strong predictors of such behaviour. Previous research mostly examined the knowledge sharing attitude or intention in the industry setting. This study has been conducted in the educational setting and particularly focuses on the influence of the educational climate and expectation outcome on the knowledge sharing attitude of students.Item Watershed-Matching Algorithm: A New Pathway for Brain Tumor Segmentation(Springer Nature, 2017-10-29) Hasan, S. M. Kamrul; Sarkar, Yugoshree; Ahmad, MohiuddingBrain tumor detection through Magnetic Resonance Imaging (MRI) is a very challenging task even in today’s modern medical image processing research. To form images of the soft tissue of the human body, surgeons use MRI analysis. They segment the images manually by partitioning into two distinct regions which is erroneous and at the same time, may be time-consuming. So, it is a must be better the MRI images segmentation. This paper outlines a new finding to detect brain tumor for better accuracy than earlier techniques. We segment the tumor area from the MR image and then to find the area of the segmented region, we use another algorithm to match the segmented part with the input image. In addition, the paper concludes with the status checking of the tumor and provides a necessary diagnosis of brain tumor. Lastly, we compare our proposed model with other techniques and get a far better result.Item An Adaptive Feature Dimensionality Reduction Technique Based on Random Forest on Employee Turnover Prediction Model(Springer Nature, 2018-10-26) Islam, Md. Kabirul; Alam, Mirza Mohtashim; Islam, Md. Baharul; Mohiuddin, Karishma; Das, Amit Kishor; Kaonain, Md. ShamsulThis paper is based on the theme of employee attrition where the reasoning behind employee turnover has predicted with the help of machine learning approach. As employee turnover has become a vital issue these days due to heavy work pressure, less salary, less work satisfaction, poor working environment; it’s high time to uphold a better solution on this term. Therefore, we have come up with a prediction model based on machine learning approach where we have used each feature’s respective Random Forest importance weights while threshold based correlated feature merging into each of the single combined variable. Again, we scale specific features to get the correlated matrix of features matrix by defining threshold. Certainly, this newly developed technique has achieved good result for some algorithms compared to Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for the same dataset.Item Highly sensitive SPR based PCF for biological substance sensing: design and analysis(SPIE., 2018-05-17) Asaduzzama, Sayed; Paul, Bikash Kumar; Ahmed, Kawsar; Bhuiyan, Touhid; Rahman, SAM MatiurProposed and numerically investigated by Finite Element Method (FEM). The proposed SPR-based In this paper, a surface Plasmon resonance (SPR) based photonic crystal fiber has been PCF shows higher average wavelength interrogation sensitivity than the previous structures. Different plasmonic materials have been used to show the difference in results. Liquid filled cores with metallic surface can be exited with leaky-Gaussian core guided mode. Numerical investigation of optical properties for the proposed PCF has been established by changing the designing parameters like pitch, diameters etc. The proposed PCF is simple in nature and can be easily fabricated by existing methods. Biological substances, biochemical, organic chemical analysis, bimolecules can be detected by our proposed SPR based PCF.Item PRMT: Predicting Risk Factor of Obesity among Middle-Aged People Using Data Mining Techniques(Elsevier B.V., 2018-06-08) Hossain, Rifat; Mahmud, S.M. Hasan; Hossin, Md Altab; Noori, Sheak Rashed Haider; Jahan, HosneyObesity is an anatomical condition characterized by an extreme growth of body fat. The obesity rate is increasing gradually; from prior research, obesity is the serious health disease in the globe. This study collected 259 data from specified urban and rural areas regarding different risk factor of our daily activities. The purpose of the study is to simulate the risk factor by using statistical tools (SPSS), which helpsto predict the major risk factor of obesity by testing the class level attribute according to cross-sectional study with other attributes. By analyzing the P-value (p<0.05), the outcome of this process Age (0.002), Height (0.002), Weight 0.000), Healthy lifestyle (0.000), Marital status (0.001), BMI (0.000), Economic (0.028), Sleep per day (0.011) has a significant relationship with our obesity class. This study proposed a risk mining technique (PRMT)that foretells a model to analyze the risk factor of obesity class using different data mining classifiers, using WEKA to estimate the accuracy and error measurement. The outcome of this process Naïve Bayes is the best classifier for the 10-fold cross-validation study. The proposed model collaborates to predict human factor who want to control and mitigate this major cardiovascular disease.Item Role of Absorptive Capacity in Predicting Continuance Intention to Use Digital Libraries: An Empirical Study(Springer International Publishing, 2018-07-20) Hossain, Mohamed Emran; Bhuiyan, Touhid; Mahmud, Imran; Ramayah, T.; Scholtz, BrendaThe purpose of this paper is to investigate the impact of absorptive capacity and the quality dimensions of technology on students’ continuance intention to use the e-library system. To measure the continuance intention, an integrated research model was developed using expectation-confirmation theory (ECT) and absorptive capacity theory. This empirical study was undertaken at a university in Bangladesh with a sample size of 297. Data was collected via a survey questionnaire. The results reveal that the dimensions of absorptive capacity have a strong effect on confirmation of the system and a partial impact on perceived usefulness (PU). Confirmation of the system has a significant effect on the PU of and satisfaction with the system. Satisfaction was found to be a strong predictor for the continuance intention to use the e-library. Finally, ECT fully fits in this context and students’ satisfaction has the largest effect on the continuance intention.Item Modeling the Role of C2C Information Quality on Purchase Decision in Facebook(The International Federation for Information Processing, 2018-10-12) Haque, Rafita; Mahmud, Imran; Sharif, Md. Hasan; Kabir, S. Rayhan; Chowdhury, Arpita; Akter, Farzana; Akhi, Amatul BushraA market which provides an innovative way to allow customers to interact with each other called Customer-to-customer (C2C) market. In C2C communications, online communities play an important role in decision making to buy a product. This investigation develops a research model for online communities of Facebook commerce (F-Commerce) in Bangladesh region, which is based on Information Adoption Model (IAM). This study exhibits a model to influences of C2C communication on Bangladeshi consumers’ purchase decision in the online communities of F-Commerce. The proposed model used the Partial Least Squares (PLS) technique to test 120 effective survey data. This survey data has been taken from the Bangladesh Facebook users and strongly involved in product buy-sell at F-Commerce. The analyzed results show that Argument Quality (AQ), Source Credibility (SC) and Tie Strength (TS) positively influence Purchase Decision (PD) through Product Usefulness Evaluation (PUE). In addition, Tie Strength exhibits difference effect on Product Usefulness Evaluation between the contexts of consumers communicating with virtual consumers relationships. Theoretical and executive implications are discussed for constructing our proposed model.Item A Potent Model to Recognize Bangla Sign Language Digits Using Convolutional Neural Network(Elsevier B.V., 2018-11-19) (Md.), Sanzidul Islam; Mousumi, Sadia Sultana Sharmin; Rabby, AKM Shahariar Azad; Hossain, Sayed Akhter; Abujar, SheikhHearing impaired people have own language called Sign Language but it is difficult for understanding to general people. Sign language is the basic method of communication for deaf people during their everyday of life. Sign digits are also a major part of sign language. So machine translator is necessary to allow them to communicate with general people. For making their language understandable to general people, computer vision based solutions are well known nowadays. In this research work we aim at constructing a model in deep learning approach to recognize Bangla Sign Language (BdSL) digits. In this approach there used Convolutional Neural Network (CNN) to train particular signs with a respective training dataset (Eshara-Lipi) for acquiring our aim. The model trained and tested with respectively 860 training images and 215 (20%) test images of tent classes of digits. Finally, the training model gained about 95% accuracy at recognition of Bangla sign language digits. This model will contribute for moving one step forward to make BdSL machine translator.