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2. DeepTriNet: A Tri-Level Attention Based DeepLabv3+ Architecture for Semantic Segmentation of Satellite Images

Author

Ovi, Tareque Bashar, Mosharrof, Shakil, Bashree, Nomaiya, Islam, Md Shofiqul, and Islam, Muhammad Nazrul

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The segmentation of satellite images is crucial in remote sensing applications. Existing methods face challenges in recognizing small-scale objects in satellite images for semantic segmentation primarily due to ignoring the low-level characteristics of the underlying network and due to containing distinct amounts of information by different feature maps. Thus, in this research, a tri-level attention-based DeepLabv3+ architecture (DeepTriNet) is proposed for the semantic segmentation of satellite images. The proposed hybrid method combines squeeze-and-excitation networks (SENets) and tri-level attention units (TAUs) with the vanilla DeepLabv3+ architecture, where the TAUs are used to bridge the semantic feature gap among encoders output and the SENets used to put more weight on relevant features. The proposed DeepTriNet finds which features are the more relevant and more generalized way by its self-supervision rather we annotate them. The study showed that the proposed DeepTriNet performs better than many conventional techniques with an accuracy of 98% and 77%, IoU 80% and 58%, precision 88% and 68%, and recall of 79% and 55% on the 4-class Land-Cover.ai dataset and the 15-class GID-2 dataset respectively. The proposed method will greatly contribute to natural resource management and change detection in rural and urban regions through efficient and semantic satellite image segmentation, Comment: Keywords: Attention mechanism, Deep learning, Satellite image, DeepLabv3+, Segmentation

Published
2023

4. HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

Author

Islam, Md Shofiqul, Hasan, Khondokar Fida, Sultana, Sunjida, Uddin, Shahadat, Lio, Pietro, Quinn, Julian M. W., and Moni, Mohammad Ali

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

In this paper have developed a novel hybrid hierarchical attention-based bidirectional recurrent neural network with dilated CNN (HARDC) method for arrhythmia classification. This solves problems that arise when traditional dilated convolutional neural network (CNN) models disregard the correlation between contexts and gradient dispersion. The proposed HARDC fully exploits the dilated CNN and bidirectional recurrent neural network unit (BiGRU-BiLSTM) architecture to generate fusion features. As a result of incorporating both local and global feature information and an attention mechanism, the model's performance for prediction is improved.By combining the fusion features with a dilated CNN and a hierarchical attention mechanism, the trained HARDC model showed significantly improved classification results and interpretability of feature extraction on the PhysioNet 2017 challenge dataset. Sequential Z-Score normalization, filtering, denoising, and segmentation are used to prepare the raw data for analysis. CGAN (Conditional Generative Adversarial Network) is then used to generate synthetic signals from the processed data. The experimental results demonstrate that the proposed HARDC model significantly outperforms other existing models, achieving an accuracy of 99.60\%, F1 score of 98.21\%, a precision of 97.66\%, and recall of 99.60\% using MIT-BIH generated ECG. In addition, this approach substantially reduces run time when using dilated CNN compared to normal convolution. Overall, this hybrid model demonstrates an innovative and cost-effective strategy for ECG signal compression and high-performance ECG recognition. Our results indicate that an automated and highly computed method to classify multiple types of arrhythmia signals holds considerable promise., Comment: 23 pages

Published
2023
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7. Quantification of Wave-Induced Liquefaction in Small-Scale Surf Zone Sandbar

Author

Islam, Md Shofiqul, Suzuki, Takayuki, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Tajima, Yoshimitsu, editor, Aoki, Shin-ichi, editor, and Sato, Shinji, editor

Published
2024
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23. A Novel BiGRUBiLSTM Model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM

Author

Islam, Md. Shofiqul, Ghani, Ngahzaifa Ab, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Ab. Nasir, Ahmad Fakhri, editor, Ibrahim, Ahmad Najmuddin, editor, Ishak, Ismayuzri, editor, Mat Yahya, Nafrizuan, editor, Zakaria, Muhammad Aizzat, editor, and P. P. Abdul Majeed, Anwar, editor

Published
2022
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24. IoT-Based AI-Integrated Device for Farmers: A Recommendation System for Crop Cultivation

Author

Khan, MD. Rafatuzzaman, primary, Ahmed, Abrar, additional, Mahi, Minhazul Islam, additional, Ahmed, Jubair, additional, Hoque, Navidul, additional, Akhtaruzzaman, M., additional, Islam, Md Shofiqul, additional, Sattar, MD. Abdus, additional, Mokhlesur Rahman, Maj Md, additional, Krishna, T Gopi, additional, Jahan, Hosney, additional, and Baki, Ramisha Fariha, additional

Published
2024
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32. Fresh water bearing zone identification using VES at Shahjalal University of Science and Technology Campus, Sylhet, Bangladesh

Author

Islam, Md. Shofiqul, primary, Ibrahim, Md., additional, Emranul Hoque Chowdhury, A.K.M., additional, Rafin, Hasan, additional, Hasan, Md. Khalid, additional, Islam, Md. Zahidul, additional, Karim, Ehsanul, additional, Kamal, Athay Reashed, additional, Chowdhury, Mohammed Asir Awosaf, additional, Hussain, Md. Ashraf, additional, and Akter, Sharmin, additional

Published
2022
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35. Physiotherapy interventions in treating patients following total hip arthroplasty: a narrative review.

Author

Ahmed, Faruq, Islam, Md Shofiqul, Hassan, Md Nazmul, Ahmed, Md Shahoriar, Sultan Nahid, Zahid Bin, and Hoque Rasel, Md Aminul

Subjects
TOTAL hip replacement, RANDOMIZED controlled trials, CLINICAL trials, RANGE of motion of joints, MUSCLE strength
Abstract

Introduction. Total hip arthroplasty (THA) is the most common, successful modern surgical intervention in orthopedic practice. Physiotherapy interventions are a major part of patient rehabilitation following THA. This study aimed to evaluate the effectiveness of physiotherapy interventions for improving functional outcomes following THA. Methods. This narrative review was conducted on electronic platforms and databases, including PubMed, PEDro, CINAHL, and EMBASE, using a combination of search terms related to "physical therapy", "physiotherapy", "physical exercise", "physiotherapy intervention", "hip arthroplasty", "total hip arthroplasty", and "hip joint replacement". Inclusion criteria included randomized controlled trials or clinical trials published in English from 2014 to 2021. Where THA was recognized as the primary concern, and physiotherapy management was one of the treatment options. Results. The initial search of the databases revealed a total of 77 studies. Of those studies, 19 were selected as potentially meeting the inclusion criteria. Eventually, 10 studies were analyzed for the narrative review's final conclusions. The evaluations supported the hypothesis that physiotherapy interventions have favorable outcomes for patients with THA. Conclusions. After reviewing, it has been revealed that physiotherapy can improve physical function, balance, range of motion, muscle strength, and gait pattern following THA. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Effects of unbalanced fertilizer use on system productivity and profitability under rice‐based cropping systems: Evidence from Eastern Gangetic Plain.

Author

Islam, Md. Shofiqul, Bell, Richard W., Miah, M. A. Monayem, and Alam, Mohammad Jahangir

Subjects
RICE farming, AGRICULTURE, PROPENSITY score matching, AGRICULTURAL policy, FARMERS
Abstract

Unbalanced nutrient supply is one of the key causes of yield gaps and low farming profitability which impact food insecurity globally. However, the effects of an unbalanced nutrient supply on rice yields and farming profitability have not been quantified for diverse rice‐based cropping systems. To explore the effects, 412 respondents (mostly smallholder farmers) were surveyed in 2019 for the rice crops in three fully rice‐based cropping systems in four agro‐ecological zones of Bangladesh. Two robust estimation approaches namely propensity score matching and endogenous switching regression approaches were used to quantify the effects of unbalanced fertilizer use. The results show that about 68% of farmers in the study areas used unbalanced (over‐doses or under‐doses) nutrient rates relative to government‐endorsed recommendations. Adoption of recommended fertilizer rates was influenced by education, amount of organic manure used, off‐farm income, crop farming‐related training, organizational membership and lack of soil testing tendency. The findings also indicate that adopters of recommended nutrient rates received almost 16% and 46% higher system rice yield and system net return, respectively, relative to non‐adopters. However, based on our research findings, formulation and implementation of effective agricultural policies like effective extension services, strengthening soil testing facilities, increasing organizational membership and targeted awareness programmes could motivate smallholder rice farmers towards adoption of recommended nutrient rates. Adoption of recommended fertilizer rates can significantly enhance crop yields and farming profitability which can boost food security and rural livelihoods in the Eastern Gangetic Plain. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Understanding how a community-based intervention for people with spinal cord injury in Bangladesh was delivered as part of a randomised controlled trial: a process evaluation

Author

Liu, Hueiming, Hossain, Mohammad Sohrab, Islam, Md. Shofiqul, Rahman, Md. Akhlasur, Costa, Punam D., Herbert, Robert D., Jan, Stephen, Cameron, Ian D., Muldoon, Stephen, Chhabra, Harvinder S., Lindley, Richard I., Biering-Sorensen, Fin, Ducharme, Stanley, Taylor, Valerie, and Harvey, Lisa A.

Published
2020
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44. The effects of 10,000 voluntary contractions over 8 weeks on the strength of very weak muscles in people with spinal cord injury: a randomised controlled trial

Author

Chen, Lydia W., Glinsky, Joanne V., Islam, Md. Shofiqul, Hossain, Muzaffor, Boswell-Ruys, Claire L., Kataria, Chitra, Redhead, Jason, Xiong, Yuan, Gollan, Emilie, Costa, Punam D., Denis, Sophie, Ben, Marsha, Chaudhary, Lovely, Wang, Jun, Hasnat, Md. Abu Khayer, Yeomans, Jayne, Gandevia, Simon C., and Harvey, Lisa A.

Published
2020
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