Gahangir Hossain

University of North Texas | UNT

Non-invasive brain stimulation offers a painless and safe approach to neurological rehabilitation, providing minimal side effects, and has been used by thousands of people worldwide. Non-invasive brain stimulation modulates the brain's excitability to aid in treating neurological disorders. The latest work has moved well beyond implementations of t...

Dementia, marked by progressive brain degeneration, involves disruptions across brain regions. Traumatic experiences, stress, and post-stroke scarring contribute to dementia onset. Although a cure remains elusive, reversible interventions can mitigate its impact. Integrating assistive technologies like ChatGPT empowers successful aging. We propose...

This research introduces an innovative strategy to bolster cybersecurity within Transportation 5.0 and Supply Chain realms via a Multi-Objective Identification and Optimization Framework. Specifically crafted to tackle the intricate challenges posed by a mixed-integer non-linear problem (MINLP), this framework employs post-linearization techniques....

In the digital age, IoT devices have revolutionized connectivity and data exchange by embedding sensors, software, and technology into physical objects. From household appliances to industrial tools, IoT facilitates seamless integration across various domains. However, the rising cost of IoT devices necessitates resource sharing in small-scale envi...

—Digital twin (DT) technologies have undergone decades of evolution and now find diverse applications, including in the food and agriculture field. This paper investigates the potential advantages of integrating digital twin technologies into agriculture to enhance productivity, resilience, cybersecurity, and sustainability. The paper devolves into...

IoT systems, comprising interconnected devices like cameras, sensors, and manufacturing equipment, bring benefits such as enhanced efficiency and safety, but they're also vulnerable to security threats like data theft and operational disruptions. Existing security assessment frameworks often struggle with IoT complexities. This paper proposes an an...

Abstract— In the transition to Agriculture 5.0, emphasizing human-machine interactions, the agricultural industry faces a heightened risk of cybersecurity threats stemming from human vulnerabilities. This study emphasizes the necessity of addressing human factors to ensure a balanced approach to technological advancement and cybersecurity in A...

Sentence analysis is a crucial task in natural language processing that finds applications in various fields, including sentiment analysis. The growing volume of Bangla data on the Internet has drawn significant attention to sentiment analysis. Bangla is the official language of Bangladesh and is also spoken in the eastern part of India. With the m...

Highlights Data integrity threat is one of the challenges faced by smart agriculture, where humans make complex decisions based on the results and recommendations of automated farm/livestock monitoring systems. Smart or digital farming heavily relies on data, which can face various integrity threats including data modification, data destruction, et...

Text prediction and classification are crucial tasks in modern Natural Language Processing (NLP) techniques. Long short-term memory (LSTM), a type of Recurrent Neural Network (RNN), is well-known for its outstanding performance in text classification. Phrasal verbs, also known as Bagdhara in Bangla, play a vital role in making language more express...

The purpose of this study was to conduct a content analysis of research on technology use for teaching mathematics to students with disabilities. We applied word networks and structural topic modeling of 488 studies published from 1980 to 2021. Results showed that the words "computer" and "computer-assisted instruction" had the highest degree of ce...

In digital image processing and steganography, images are often described using edges and local binary pattern (LBP) codes. By combining these two properties, a novel hybrid image steganography method of secret embedding is proposed in this paper. This method only employs edge pixels that influence how well the novel approach embeds data. To increa...

According to a report by UN and WHO, by 2030 the number of senior people (age over 65) is projected to grow up to 1.4 billion, and which is nearly 16.5% of the global population. Seniors who live alone must have their health state closely monitored to avoid unexpected events (such as a fall). This study explains the underlying principles, methodolo...

Electroencephalograph (EEG) analysis from human subjects have demonstrated that beta oscillations carried perceptual information across the cortex featuring amplitude and phase modulation occurrences when subjects are engaged in task-oriented activities. A hypothesis was tested that synchronized patterns could be found in the scalp EEG of two human...

Due to the COVID-19 pandemic and working from home with portable devices, we are spending a longtime on the device screen. Prolonged focus on devices like computer screens, tablets, e-readers, and cellphones – Video Display Terminals (VDTs) has been linked with vision problems which affect over 60 million people globally. The computer related ocula...

These Post-COVID days, seventy percent of businesses have or are working on a digital transformation, which make us to spend more time with media interaction [1]. Media has always existed in much of our history; the shape and function of such media instruments may have evolved over time, but human nature has always been drawn to them. Social networ...

These Post-COVID days, seventy percent of businesses have or are working on a digital transformation, which make us to spend more time with media interaction [1]. Media has always existed in much of our history; the shape and function of such media instruments may have evolved over time, but human nature has always been drawn to them. Social networ...

Advances in data mining and machine learning methods for classification and regression open the door of identifying complex patterns from domain sensitive data. In biomedical applications, massive amounts of clinical data are generated and collected to predict diseases. Diagnosis of diseases, such as diabetes and liver diseases, needs more tests th...

Technology advancements made it easy to measure non-invasive and high-quality electroencephalograph (EEG) signals from human's brain. Hence, development of robust and high-performance AI algorithms becomes crucial to properly process the EEG signals and recognize the patterns, which lead to an appropriate control signal. Despite the advancements in...

This research proposes machine learning algorithms in conjunction with cognitive-based networking as a remote patient monitoring framework for accurately predicting disease state and disease parameters from remotely monitored and measured patient biometric and biomedical signals. This system would facilitate doctors and clinicians by providing hosp...

Home health monitoring can facilitate patient monitoring remotely for diabetes and blood pressure patients. Early detection of hypertension and diabetes is extremely important, as these chronic diseases often result in life-threatening complications when found at a later stage. This work proposes a smart home health monitoring system that helps to...

This research presents an independent stand-alone graphical computational tool which functions as a neurological disease prediction framework for diagnosis of neurological disorders to assist neurologists or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images. The tool was built in collabo...

Research in last few years on neurophysiology focused on several areas across the cortex during cognitive processing to determine the dominant direction of electrical activity. However, information about the frequency and direction of episodic synchronization related to higher cognitive functions remain unclear. Our aim was to determine whether neu...

The amount of working memory recourses available (or required) to process a cognitive task (easy or hard) represents human cognitive effort. Working memory resources (visual or auditory) and cognitive efforts are interconnected with visual or auditory pathways. In this review, various facets of pupillary dynamics literature are compared in order to...

The design of a robust communication among two different sensory disabilities (Deaf vs. Blind) remains an emerging field of research in disability healthcare communication system design. As an important part of modern technology, android and iPhone applications are frequently used in designing such communication systems. However, there is no ‘one-s...

Self-reporting is used as a subjective measure of usability study of technology solutions. In assistive technology research, more than often the ‘a coordinator’ directly assist the ‘subject’ in the scoring process. This makes the rating process slower and also introduces bias, such as, ‘Forer effect’ and/or ‘Hawthorne’ effect. To address these issu...

The design of a robust communication among two different sensory disabilities (Deaf vs. Blind) remains an emerging field of research in disability healthcare communication system design. As an important part of modern technology, android and iPhone applications are frequently used in designing such communication systems. However, there is no 'one-s...

Generally falls may occur from moving or resting postures. This may include slipping from bed and fall from a sitting, or from running or walking. The pre-fall is a non-equilibrium state of human position that may lead to serious injuries, and may negatively impact the quality life condition, particularly for elders. Physical disabilities resulting...

To support mobile, eyes-free web browsing, users can listen to ‘playlists’ of web content—aural flows. Interacting with aural flows, however, requires users to select interface buttons, tethering visual attention to the mobile device even when it is unsafe (e.g. while walking). This research extends the interaction with aural flows through simulate...

A robust seizure prediction methodology would enable a “closed-loop” system that would only activate as impending seizure activity is detected. Such a system would eliminate ongoing stimulation to the brain, thereby eliminating such side effects as coughing, hoarseness, voice alteration, and paresthesias (Murphy et al., 1998; Ben-Menachem, 2001), w...

Smartphones have become a basic necessity in lives of all human beings. Apart from the core functionality of communication, these become a medium for storage of sensitive personal information, financial data and official documents. Hence, there is an inevitable need to emphasize on securing access to such devices considering the nature of data bein...

We investigated the application of Causal Bayesian Networks (CBNs) to large data sets in order to predict user intent via internet search prediction. Here, sample data are taken from search engine logs (Excite, Altavista, and Alltheweb). These logs are parsed and sorted in order to create a data structure that was used to build a CBN. This network...

Cognitive consistency analysis aims to continuously monitor one's perception equilibrium towards successful accomplishment of cognitive task. Opposite to cognitive flexibility analysis – cognitive consistency analysis identifies monotone of perception towards successful interaction process (e.g., biometric authentication) and useful in generation o...

Cognitive networks rapidly proliferating into all aspects of computing and communication. Some of them are specially designed for the people with specific ability. However, very few are designed with assistance of the people with disability and elderly who need help during networking. The goal of this project is to study network accessibility issue...

This paper describes the secondary research on feature extraction and selection for decoding the brain electroencephalograph (EEG) signals in designing a prosthetic arm, a Brain Computer Interface (BCI) system. It considers EEG pattern recognition using Principal Component Analysis (PCA) for Feature Extraction. The data used for this research is th...

Maintaining alternative decisions in working memory (WM) can lead accumulating high cognitive load. Some aspects of cognitive load improve attentiveness, but adding a cognitively inconsistent (conflict) situation results in a failure in cognitive task performance. This research introduces the notion of the human ability-demand gap (discrepancy betw...

Task-evoked pupillary responses reveal the relationship between working memory capacity and its effect on cognitive states. Understanding the effects of cognitive load requires robust analysis of pupillary responses. In this paper, we introduced a Hilbert transform analytic phase based method to compute temporal patterns from pupillary responses. A...

A better understanding of human cognitive ability-demand gap (ADG) is critical in designing assistive technology solution that is accurate and adaptive over a wide range of human-agent interaction. The main goal is to design systems that can adapt with the user’s abilities and needs over a range of cognitive tasks. It will also enable the system to...

Collaborative sense making is the process by which people assign meaning to experience in collaborative information sharing and decision making. Recent technological advances made it possible for people with disabilities to collaborate among themselves using smart phones. The main research goal of this pilot study is to investigate the suitability...

This study investigates phase relationships between electrocorticogram (ECoG) signals through Hilbert-Huang Transform (HHT), combined with Empirical Mode Decomposition (EMD). We perform spatial and temporal filtering of the raw signals, followed by tuning the EMD parameters. It can be seen that carefully tuning of EMD filter, it is possible to capt...

Co-adapted learning involves complex, dynamically unfolding interactions between human and artificial pedagogical agents (PAs) during learning with intelligent systems. In general, these interactions lead to effective learning when (1) learners correctly monitor and regulate their cognitive and metacognitive processes in response to internal (e.g.,...

Co-adapted learning involves complex, dynamically unfolding interactions between human and artificial pedagogical agents (PAs) during learning with intelligent systems. In general, these interactions lead to effective learning when (1) learners correctly monitor and regulate their cognitive and metacognitive processes in response to internal (e.g.,...

Intelligent educational interfaces are becoming important part of online future educational system. Interface with understanding of user's essential cognitive capabilities make it adaptive and may reduce gap between human computer interactions. In online learning environment, a student interacting with such intelligent interface experiences differe...

People with disability are unique in their own ways. Hence, adaptive systems are imperative to effectively assist individual with disabilities. Assistive thinking is a new concept in design and implementation of such a system that requires a holistic approach. The key idea is to identify user's preference and resources early and incorporate them im...