Browsing by Author "Hasan, Md. Robiul"

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Analysis Technical Relationships within Count, Stitch Length and GSM of (1x1) Interlock and (1x1) grey Rib Fabric
(Daffodil International University, 2018-12-10) Sayed, Md. Abu; Hasan, Md. Robiul; Ali, Md. Hasem
This project mainly concentrated on Rib and Interlock fabric where we find out relationships within count, stich length and GSM. Most of the industries are faced some ordinary problem concerning the proper selection of count, GSM and stitch length to manufacture a good quality knit fabric. In this project, both the empirical and analytical data were compared with each other to find through an equation where if the stich length and count increase then the GSM will be decreased. This occurred due to the relation within GSM, count and stitch length; where count and stitch length is inversely proportional to the GSM. This project mainly concentrated on grey knit fabric GSM where yarn count respectively 26Ne, 28Ne, 34Ne for (1x1) rib, and 26Ne, 30Ne, 32Ne used for (1x1) interlock. In this project, we have been compared both the theoretical as well as the practical implications from the factory and we have to try our best mark on the adjustable points of fabric GSM, count and stitch length directly and indirectly. This report set up an acceptable result, which would be preferable for workable use and would simplify for carrying out further activities related to this type of research.
Early Prediction of Chronic Kidney Disease
(Daffodil International University, 22-08-29) Mondol, Chaity; Shamrat, F. M. Javed Mehedi; Hasan, Md. Robiul; Alam, Saidul; Ghosh, Pronab; Tasnim, Zarrin; Ahmed, Kawsar; Bui, Francis M.; Ibrahim, Sobhy M.
Chronic kidney disease (CKD) is one of the most life-threatening disorders. To improve survivability, early discovery and good management are encouraged. In this paper, CKD was diagnosed using multiple optimized neural networks against traditional neural networks on the UCI machine learning dataset, to identify the most efficient model for the task. The study works on the binary classification of CKD from 24 attributes. For classification, optimized CNN (OCNN), ANN (OANN), and LSTM (OLSTM) models were used as well as traditional CNN, ANN, and LSTM models. With various performance matrixes, error measures, loss values, AUC values, and compilation time, the implemented models are compared to identify the most competent model for the classification of CKD. It is observed that, overall, the optimized models have better performance compared to the traditional models. The highest validation accuracy among the tradition models were achieved from CNN with 92.71%, whereas OCNN, OANN, and OLSTM have higher accuracies of 98.75%, 96.25%, and 98.5%, respectively. Additionally, OCNN has the highest AUC score of 0.99 and the lowest compilation time for classification with 0.00447 s, making it the most efficient model for the diagnosis of CKD.
Helping hand donation system
(Daffodil International University, 2018-05-07) Jamil, M. Yousuf; Hasan, Md. Robiul; Hossain, Md. Sajal
Now the time of internet technology. This time internet is the most exoteric communication media in the world. We conduct this technology to digitalize a crucial part of real life that is fundraising campaign. There are people who are holding philanthropically mindset to support humanity by means of creating donation fund for the powerless and impecunious people. In this context, we conceptualized project on “Helping Hand Donation System: (Give so others can live)” to facilitate these funds from different category donor to the final beneficiary, the people. In this system donor seeker or user can sign up as a member. When he/she become a member after then he/she create a campaign for donation. The campaign was pending and only admin can approve the campaign with fulfill terms & condition. When a member post any campaign, the member must submit his/her bio details and campaign details by contact mail or contact directly “Helping Hand Donation System's” office/admin panel/management team. In this project, we identify requirement based on practical interactions with different stakeholders. The requirement is transformed into a webbased application for appropriate systematic interaction. The system is implemented on PHP and MySQL platform. The system is tested and reviewed for satisfactory performance. In the future, the system will be further extended based on changes in requirements.
Industrial Attachment at Robintex Group Vulta, Rupgong, Narayangong
(Daffodil International University, 2018-11-29) Sayed, Md. Abu; Hasan, Md. Robiul; Ali, Md. Hasem
The Industrial Attachment is the most effective way for Textile Engineering student to be achieved the knowledge about the practical field of the Textile Manufacturing. It brings an opportunity to all the learners to enrich their academic knowledge by practicing with the experts of the practical field of textile.
RentUs Bd
(Daffodil International University, 23-02-18) Hasan, Md. Robiul; Alam, Saidul
"RentUsBd" connects renters and property owners online. Where renters can easily find their property. Today's urban renters need help finding suitable housing. Given the circumstances, a collaborative online space might be of great assistance. These apps allow property owners and renters to sign up, and renters can use them to find available properties by communicating with owners. This project created an online rental management app for property owners and renters. This web application is useful and easy to use, and it has many features that renters won't find on any other Bangladeshi house-rental website. The app made it easier and faster to find properties and ensured more rental options. once This web app will improve nationwide service. Its smart features inspired an online bright property rental service.