M. Irfan Uddin
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In-depth exploration of software defects and self-admitted technical debt through cutting-edge deep learning techniques Open
Most previous research focuses on finding Self-Admitted Technical Debt (SATD) or detecting bugs alone, rather to addressing the concurrent identification of both issues. These study investigations solely identify and classify the SATD or f…
Enhancing feature learning of hyperspectral imaging using shallow autoencoder by adding parallel paths encoding Open
Conventional image formats have limited information conveyance, while Hyperspectral Imaging (HSI) offers a broader representation through continuous spectral bands, capturing hundreds of spectral features. However, this abundance leads to …
Deep learning techniques for detecting freezing of gait episodes in Parkinson’s disease using wearable sensors Open
Freezing of Gait (FoG) is a disabling motor symptom that characterizes Parkinson’s Disease (PD) patients and significantly affects their mobility and quality of life. The paper presents a novel hybrid deep learning framework for the detect…
View article: Enhancing Seizure Detection Accuracy in Wearable EEG Devices Using Deep Learning Algorithms
Enhancing Seizure Detection Accuracy in Wearable EEG Devices Using Deep Learning Algorithms Open
Wearable electroencephalography (EEG) devices for seizure detection accuracy and reliability are deep learning (DL) applications in the field of epilepsy diagnosis. In this study, we sought to increase the accuracy of seizure detection usi…
AI-Driven Innovation Using Multimodal and Personalized Adaptive Education for Students With Special Needs Open
This study provides an in-depth exploration of the use of multimodal techniques in developing adaptive learning systems designed for students with special needs using various neural network models: a Baseline Neural Network, Convolutional …
View article: Utilizing Conditional GANs for Synthesis of Equilibrated Hyperspectral Data to Enhance Classification and Mitigate Majority Class Bias
Utilizing Conditional GANs for Synthesis of Equilibrated Hyperspectral Data to Enhance Classification and Mitigate Majority Class Bias Open
A land cover scene is described by vegetation, urban infrastructure, water bodies, bare soil, and many other physical materials. Satellite imagery and remote sensing techniques analyze the scene for the management of natural resources and …
Enhancing Adaptive Learning with Generative AI for Tailored Educational Support for Students with Disabilities Open
This paper explores the integration of generative artificial intelligence (AI) into adaptive learning systems to create customized learning support aids for students with disabilities, as traditional educational aids commonly fail to meet …
A WaveNet Deep Learning Framework for Real-Time FoG Prediction in Patients with Parkinson’s Disease Open
Freezing of gait (FoG) is among the most disabling motor symptoms experienced by individuals with movement disorders, particularly Parkinson’s disease (PD). FoG episodes can severely limit mobility, heighten the risk of falls, disrupt dail…
View article: Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer
Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer Open
This research delves into the obstacles and difficulties associated with predicting cryptocurrency movements in the volatile global financial market. This study develops and evaluates an advanced Deep Learning-Enhanced Temporal Fusion Tran…
An Efficient Artificial Intelligence (AI) and Internet of Things (IoT's) Based MEAN Stack Technology Applications Open
This paper examines the components of the MEAN development stack integration with artificial intelligence (AI) and Internet of things (IoTs), we see that we are a part of a society where technology has its roots in every aspect of life. No…
An Efficient Systematic Approach for Adaptability Synthesis of IOT's Performance Open
The Internet of Things (IoT) has profoundly impacted various facets of contemporary society, transforming the ways in which individuals live, work, travel, and conduct business. Given its significance, it becomes imperative to ensure that …
Optimal Emerging trends of Deep Learning Technique for Detection based on Convolutional Neural Network Open
There has never been a more important need for early, non-invasive lung cancer detection because lung cancer is still one of the world's biggest health concerns. Conventional diagnostic methods such as CT scans and X-rays are very helpful …
An Efficient E-Commerce Web Platform Based on Deep Integration of MEAN Stack Technologies Open
In the dynamic landscape of modern business, staying attuned to customer demands is imperative for success. The ability to seamlessly bring buying and selling activities online empowers customers to access a diverse range of products effor…
OUTCOMES OF PATIENTS UNDERGOING PERCUTANEOUS CORONARY INTERVENTION WITH CHRONIC TOTAL OCCLUSIONS Open
This study aimed to assess the efficacy of percutaneous coronary intervention (PCI) with chronic total occlusions (CTO) in a cardiology department in Peshawar, Pakistan, between January 2021 and December 2022. The study included 190 to 200…
Prediction of Gender-Biased Perceptions of Learners and Teachers Using Machine Learning Open
Computers have enabled diverse and precise data processing and analysis for decades. Researchers of humanities and social sciences are increasingly adopting computational tools such as artificial intelligence (AI) and machine learning (ML)…
A Cross-Layer Solution for Contention Control to Enhance TCP Performance in Wireless Ad-Hoc Networks Open
With the development of wireless technology, users not only have wireless access to the Internet, but this has also sparked the emergence of Wireless Ad-hoc Networks (WANETs); this promising networking paradigm has the potential to adopt t…
Smart E-Learning Framework for Personalized Adaptive Learning and Sequential Path Recommendations Using Reinforcement Learning Open
Learning activities are considerably supported and improved by the rapid advancement of e-learning systems. This gives students a tremendous chance to participate in learning activities worldwide. The Massive Open Online Courses (MOOCs) pl…
Developing a Personalized E-Learning and MOOC Recommender System in IoT-Enabled Smart Education Open
Smart strategies and intelligent technologies are enabling the designing of a smart learning environment that successfully supports the development of personalized learning and adaptive learning. This trend towards integration is in line w…
View article: Near Feasibility Driven Adaptive Penalty Functions Embedded MOEA/D
Near Feasibility Driven Adaptive Penalty Functions Embedded MOEA/D Open
This work extends a near feasibility threshold (NFT) based adaptive penalty function for constrained multiobjective optimization. The NFT zone adjoining the feasible region is considered as good one, where infeasible solutions are relative…
RACE-SM: Reliability and adaptive cooperation for efficient UWSNs using sink mobility Open
Underwater Wireless Sensor Networks (UWSNs) are the most crucial method for exploring the hidden resources under the water. It enables many underwater applications, such as military, commercial, disaster prevention, ocean sampling, and oth…
Memory Load and Performance-based Adaptive Smartphone E-learning Framework for E-commerce Applications in Online Learning Open
The term e-commerce is not confined to the purchase and sale of goods only. There are several occasions where students are not able to comprehend any idea on their own. With the availability of online learning platforms such as Massive Ope…
Probabilistic Approach to COVID-19 Data Analysis and Forecasting Future Outbreaks Using a Multi-Layer Perceptron Neural Network Open
The present outbreak of COVID-19 is a worldwide calamity for healthcare infrastructures. On a daily basis, a fresh batch of perplexing datasets on the numbers of positive and negative cases, individuals admitted to hospitals, mortality, ho…
Impact analysis of keyword extraction using contextual word embedding Open
A document’s keywords provide high-level descriptions of the content that summarize the document’s central themes, concepts, ideas, or arguments. These descriptive phrases make it easier for algorithms to find relevant information quickly …
Optimizing Convolutional Neural Networks with Transfer Learning for Making Classification Report in COVID-19 Chest X-Rays Scans Open
The coronavirus disease (COVID-19) outbreak, which began in December 2019, has claimed numerous lives and impacted all aspects of human life. COVID-19 was deemed an outbreak by the World Health Organization (WHO) as time passed, putting a …