A5066228107- EEG and Brain-Computer Interfaces
- Software Reliability and Analysis Research
- Emotion and Mood Recognition
- Brain Tumor Detection and Classification
- Software Testing and Debugging Techniques
- Asian Geopolitics and Ethnography
- Maternal and fetal healthcare
- Bangladesh Politics, Society, and Development
- Gaze Tracking and Assistive Technology
- Software Engineering Research
- Blind Source Separation Techniques
- Advanced Computing and Algorithms
- Agricultural Practices and Plant Genetics
- Medical Imaging Techniques and Applications
- Gestational Diabetes Research and Management
- Advanced Radiotherapy Techniques
- COVID-19 diagnosis using AI
- Smart Systems and Machine Learning
- ECG Monitoring and Analysis
- Neuroscience and Neural Engineering
- Employment and Welfare Studies
- South Asian Studies and Conflicts
- Cell Image Analysis Techniques
- Digital Imaging for Blood Diseases
- Radiomics and Machine Learning in Medical Imaging
Gopalganj Science and Technology University
2023-2024
Bangamata Sheikh Fojilatunnesa Mujib Science and Technology University
2024
North Carolina State University
2024
Begum Rokeya University
2023
Hebei University of Technology
2020-2022
Bangladesh Agricultural University
2022
Gono University
2019
Emotion recognition based on brain-computer interface (BCI) has attracted important research attention despite its difficulty. It plays a vital role in human cognition and helps making the decision. Many researchers use electroencephalograms (EEG) signals to study emotion because of easy convenient. Deep learning been employed for system. recognizes into single or multi-models, with visual music stimuli shown screen. In this article, convolutional neural network (CNN) model is introduced...
Motor Imagery (MI) classification using electroencephalography (EEG) has been extensively applied in healthcare scenarios for rehabilitation aims. EEG signal decoding is a difficult process due to its complexity and poor signal-to-noise ratio. Convolutional neural networks (CNN) have demonstrated their ability extract time–space characteristics from signals better results. However, discover dynamic correlations these signals, CNN models must be improved. Hyperparameter choice strongly...
Recent work in automated program repair (APR) proposes the use of reasoning and patch validation feedback to reduce semantic gap between LLMs code under analysis. The idea has been shown perform well for general APR, but its effectiveness other particular contexts remains underexplored. In this work, we assess impact context vulnerability repair, an important challenging task security. To support evaluation, present VRpilot, LLM-based technique based on feedback. VRpilot (1) uses a...
Brain tumor detection from MRI images is a time consuming and precarious task due to irregular characteristics of tissue image segmentation. In MR permit convincing evidence play decisive part in diagnosing the different kinds tumors. The segmentation recognition extraction area (MRI) magnetic resonance are an initial interest. clinical or radiologist specialists performed time-consuming tedious but their precision relies on experience. Therefore, usage computer-aided expertise becomes...
In the medical domain, brain image classification is an extremely challenging field. Medical images play a vital role in making doctor's precise diagnosis and surgery process. Adopting intelligent algorithms makes it feasible to detect lesions of quickly, especially necessary extract features from images. Several studies have integrated multiple toward domain. Concerning feature extraction image, vast amount data analyzed achieve processing results, helping physicians deliver more case...
People around the world have been affected in some way by coronavirus pandemic. Garo people disproportionately impacted COVID-19, which has had a high impact on their daily lives. The present study was an attempt to explore of covid-19 pandemic Community at Madhupur Upazila Tangail District. Attaining broad objective also focused relevant objectives such as, gathering information about socio-demographic condition people, knowing psycho-social problem faced person, observing psychological...
Background: Gestational diabetes mellitus (GDM) is glucose intolerance during pregnancy, with or without remission after pregnancy. It poses risks to the mother and baby, including future maternal up 42.9% perinatal mortality. Proper diagnosis management can improve outcomes. This study analyzes complications in women GDM. Methods: cross-sectional was conducted at department of obstetrics gynecology Uttara Adhunik medical college hospital, Dhaka, Bangladesh for 1 year; January 2020- December...
Abstract Aim: To estimate the Gross Tumor Volume (GTV) using different modes (axial, helical, slow, KV-CBCT & 4D-CT) of computed tomography (CT) in pulmonary tumors. Materials Methods: We have retrospectively included ten previously treated case carcinoma primary lung or metastatic Stereotactic Body Radiation Therapy (SBRT) this study. All patients underwent 4 CT scan Axial, Helical, Slow 4D-CT GE discovery 16 Slice PET-CT scanner and daily for treatment verification. For...
A Brain-computer interface (BCI) using an electroencephalogram (EEG) signal has a great attraction in emotion recognition studies due to its resistance humans’ deceptive actions. This is the most significant advantage of brain signals over speech or visual context. major challenge EEG-based that lot effort required for manually feature extractor, EEG recordings show varying distributions different people and same person at time instances. The Poor generalization ability network model as well...
Motor imagery based on brain-computer interface (BCI) has attracted important research attention despite its difficulty. It plays a vital role in human cognition and helps making the decision. Many researchers use electroencephalogram (EEG) signals to study brain activity with left right-hand movement. Deep learning (DL) been employed for motor (MI). In this article, deep neural network (DNN) is proposed classification of right movement EEG signal using Common Spatial Pattern (CSP) as...
The brinjal shoot and fruit borer, Leucinodes orbonalis is one of the most serious pests crop in Bangladesh causes damage up to 90% yield loss. It very difficult control. An experiment was conducted at Entomology Field Laboratory, Department Entomology, Agricultural University (BAU), Mymensingh from December 2020 April 2021 on management Brinjal Shoot Fruit Borer (BSFB) using three colored exclusion nets, viz., white, blue, yellow, along with an untreated Brinjal, specifically Singnath...