Md. Kamrul Hasan, Md. Ashraful Alam, Dola Das, Eklas Hossain et al.
Diabetes, also known as chronic illness, is a group of metabolic diseases due to a high level of sugar in the blood over a long period. The risk factor and severity of diabetes can be reduced significantly if the precise early prediction is possible. The robust and accurate prediction of diabetes is...
Pronab Ghosh, Sami Azam, Mirjam Jonkman, Asif Karim et al.
Cardiovascular diseases (CVD) are among the most common serious illnesses affecting human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce mortality rates. Identifying risk factors using machine learning models is a promising approach. We would like to propose a mod...
Mahmud Akhter Shareef, Bhasker Mukerji, Yogesh K. Dwivedi, Nripendra P. Rana et al.
This study was conducted to conceptualise advertising value and consumer attitudes towards advertisements. The research was developed to reveal the effect of the source of advertisements on credibility perception through the theoretical framework of Ducoffe's (1995) advertising value model. The rese...
Abu Reza Md. Towfiqul Islam, Swapan Talukdar, Susanta Mahato, Sonali Kundu et al.
Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods. Therefore, earlier identification of fl...
Robert Goodman, Dawn Renfrew, Mohammad S. I. Mullick
A computerised algorithm was developed to predict child psychiatric diagnoses on the basis of the symptom and impact scores derived from Strengths and Difficulties Questionnaires (SDQs) completed by parents, teachers and young people. The predictive algorithm generates "unlikely", "possible" or "pro...
Md Manjurul Ahsan, Shahana Akter Luna, Zahed Siddique
Globally, there is a substantial unmet need to diagnose various diseases effectively. The complexity of the different disease mechanisms and underlying symptoms of the patient population presents massive challenges in developing the early diagnosis tool and effective treatment. Machine learning (ML)...
Sivaramakrishnan Rajaraman, Sameer Antani, Mahdieh Poostchi, Kamolrat Silamut et al.
parasites transmitted through the bite of female Anopheles mosquito. Microscopists commonly examine thick and thin blood smears to diagnose disease and compute parasitemia. However, their accuracy depends on smear quality and expertise in classifying and counting parasitized and uninfected cells. Su...
Chowdhury Rafeed Rahman, Preetom S. Arko, Mohammed Eunus Ali, Mohammad Ashik Iqbal Khan et al.
Accurate and timely detection of diseases and pests in rice plants can help farmers in applying timely treatment on the plants and thereby can reduce the economic losses substantially. Recent developments in deep learning-based convolutional neural networks (CNN) have greatly improved image classifi...
Habib Zaman Khan
Purpose The purpose of this paper is to investigate the corporate social responsibility (CSR) reporting information of Bangladeshi listed commercial banks and explores the potential effects of corporate governance (CG) elements on CSR disclosures. Design/methodology/approach The annual reports of al...
Kazi Md. Rokibul Alam, Nazmul Siddique, Hojjat Adeli
This paper presents a novel dynamic ensemble learning (DEL) algorithm for designing ensemble of neural networks (NNs). DEL algorithm determines the size of ensemble, the number of individual NNs employing a constructive strategy, the number of hidden nodes of individual NNs employing a constructive–...
Asmaul Hosna, Ethel Merry, Jigmey Gyalmo, Zulfikar Alom et al.
Infinite numbers of real-world applications use Machine Learning (ML) techniques to develop potentially the best data available for the users. Transfer learning (TL), one of the categories under ML, has received much attention from the research communities in the past few years. Traditional ML algor...
Mohammad Shafenoor Amin, Yin Kia Chiam, Kasturi Dewi Varathan
Jianying Huang, Shuhui Li, Mingzheng Ge, Lingmeng Wang et al.
Multifunctional robust TiO<sub>2</sub>@fabrics with special wettability demonstrated potential applications for excellent UV shielding, effective self-cleaning, efficient oil–water separation and microfluidic management.
Shafiul Hasan Rafi, Nahid‐Al Masood, Shohana Rahman Deeba, Eklas Hossain
In this study, a new technique is proposed to forecast short-term electrical load. Load forecasting is an integral part of power system planning and operation. Precise forecasting of load is essential for unit commitment, capacity planning, network augmentation and demand side management. Load forec...
Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo
Learning subtle yet discriminative features (e.g., beak and eyes for a bird) plays a significant role in fine-grained image recognition. Existing attention-based approaches localize and amplify significant parts to learn fine-grained details, which often suffer from a limited number of parts and hea...