Ashad Kabir

• PhD
• Professor of Computer Science at Charles Sturt University

This book presents a review of traditional context-aware computing research, identifies its limitations in developing social context-aware pervasive systems, and introduces a new technology framework to address these limitations. Thus, this book provides a good reference for developments in context-aware computing and pervasive social computing. It...

As the use of web browsers continues to grow, the potential for cybercrime and web-related criminal activities also increases. Digital forensic investigators must understand how different browsers function and the critical areas to consider during web forensic analysis. Web forensics, a subfield of digital forensics, involves collecting and analyzi...

Automatic text summarization, particularly headline generation, remains a critical yet under-explored area for Bengali religious news. Existing approaches to headline generation typically rely solely on the article content, overlooking crucial contextual features such as sentiment, category, and aspect. This limitation significantly hinders their e...

Deep learning (DL) techniques have emerged as promising solutions for medical wound tissue segmentation. However, a notable limitation in this field is the lack of publicly available labelled datasets and a standardised performance evaluation of state-of-the-art DL models on such datasets. This study addresses this gap by comprehensively evaluating...

Virtual reality (VR) technology can be used to treat anxiety symptoms and disorders. However, most VR interventions for anxiety have been therapist guided rather than self-guided. This systematic review aimed to examine the effectiveness and user experience (i.e., usability, acceptability, safety, and attrition rates) of self-guided VR therapy inte...

In the livestock sector, the fragmented data landscape across isolated systems presents a significant challenge, necessitating interoperability and integration. In this article, we introduce the Livestock Event Information Sharing Architecture (LEISA), a novel architecture designed to facilitate the sharing of livestock event information among vari...

The skin, as the largest organ of the human body, is vulnerable to a diverse array of conditions collectively known as skin lesions, which encompass various dermatoses. Diagnosing these lesions presents significant challenges for medical practitioners due to the subtle visual differences that are often imperceptible to the naked eye. While not all...

Convolutional Neural Networks (CNNs) have drawn researchers' attention to identifying cattle using muzzle images. However, CNNs often fail to capture long-range dependencies within the complex patterns of the muzzle. The transformers handle these challenges. This inspired us to fuse the strengths of CNNs and transformers in muzzle-based cattle iden...

Background and Objective: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource settings. Accurate differentiation between viral and bacterial pneumonia is essential for guiding appropriate treatment, yet it remains challenging due to overlapping clinical and radiographic features. A...

Soil colour is a key indicator of soil health and the associated properties. In agriculture, soil colour provides farmers and advises with a visual guide to interpret soil functions and performance. Munsell colour charts have been used to determine soil colour for many years, but the process is fallible, as it depends on the user’s perception. As s...

Automatic text summarization, particularly headline generation, remains a critical yet underexplored area for Bengali religious news. Existing approaches to headline generation typically rely solely on the article content, overlooking crucial contextual features such as sentiment, category, and aspect. This limitation significantly hinders their ef...

In the livestock sector, the fragmented data landscape across isolated systems presents a significant challenge, necessitating interoperability and integration. In this article, we introduce the Livestock Event Information Sharing Architecture (LEISA), a novel architecture designed to facilitate the sharing of livestock event information among vari...

Diabetes-related foot ulcers (DFUs) are a severe complication of diabetes, affecting about 15% of diabetic patients in their lifetime. Poorly managed DFUs can lead to severe infections, amputations, reduced quality of life, or death. Offloading footwear is a critical intervention that promotes healing by reducing pressure on the ulcerated area. How...

This research presents a robust approach to classifying COVID-19 cough sounds using cutting-edge machine learning techniques. Leveraging deep neural decision trees and deep neural decision forests, our methodology demonstrates consistent performance across diverse cough sound datasets. We begin with a comprehensive extraction of features to capture...

Adherence to prescribed medication is essential for effective treatment, as medications work only when taken as directed. Non-adherence poses a significant challenge to healthcare professionals, reducing clinical outcomes and increasing healthcare costs across various medical disciplines. Automatically detecting self-reported medication changes on...

Near-infrared spectroscopy (NIRS) is a non-invasive and fast technology that has been increasingly used to analyse livestock diet quality. The objective of this study was to conduct a systematic review of the literature to examine the utilisation of NIRS technology for analysing livestock diet quality, with a focus on identifying trends, methodolog...

Artificial intelligence (AI) has emerged as a promising tool for predicting COVID-19 from medical images. In this paper, we propose a novel continual learning-based approach and present the design and implementation of a mobile application for screening COVID-19. Our approach demonstrates the ability to adapt to evolving datasets, including data co...

In this study, we propose a novel and robust framework, Self-DenseMobileNet, designed to enhance the classification of nodules and non-nodules in chest radiographs (CXRs). Our approach integrates advanced image standardization and enhancement techniques to optimize the input quality, thereby improving classification accuracy. To enhance predictive...

As the use of web browsers continues to grow, the potential for cybercrime and web-related criminal activities also increases. Digital forensic investigators must understand how different browsers function and the critical areas to consider during web forensic analysis. Web forensics, a subfield of digital forensics, involves collecting and analyzi...

Major Depressive Disorder (MDD), commonly called depression, is a prevalent psychiatric condition diagnosed via questionnaire-based mental status assessments. However, this method often yields inconsistent and inaccurate results. Furthermore, there is currently a lack of a comprehensive diagnostic framework for MDD that assesses various brainwaves...

Assistive technologies have been developed to enhance blind users’ typing performance, focusing on speed, accuracy, and effort reduction. One such technology is word prediction software, designed to minimize keystrokes required for text input. This study investigates the impact of word prediction on typing performance among blind users using an on-...

With the proliferation of wound assessment apps across various app stores and the increasing integration of artificial intelligence (AI) in healthcare apps, there is a growing need for a comprehensive evaluation system. Current apps lack sufficient evidence-based reliability, prompting the necessity for a systematic assessment. The objectives of th...

The rapid dissemination of misinformation on the internet complicates the decision-making process for individuals seeking reliable information, particularly parents researching child development topics. This misinformation can lead to adverse consequences, such as inappropriate treatment of children based on myths. While previous research has utili...

Assistive technologies have been developed to enhance blind users' typing performance, focusing on speed, accuracy, and effort reduction. One such technology is word prediction software, designed to minimize keystrokes required for text input. This study investigates the impact of word prediction on typing performance among blind users using an on-...

The rapid dissemination of misinformation on the internet complicates the decision-making process for individuals seeking reliable information, particularly parents researching child development topics. This misinformation can lead to adverse consequences, such as inappropriate treatment of children based on myths. While previous research has utili...

Machine learning models have the potential to identify cardiovascular diseases (CVDs) early and accurately in primary healthcare settings, which is crucial for delivering timely treatment and management. Although population-based CVD risk models have been used traditionally, these models often do not consider variations in lifestyles, socioeconomic...

Diabetes-related foot complications, including neuropathic plantar forefoot ulcers, are a significant contributor to morbidity and increased healthcare costs. This retrospective clinical audit examines the characteristics of people accessing pedorthics services who are at risk of neuropathic plantar forefoot ulcer (re)occurrence and the pathways an...

Sentiment analysis, a transformative force in natural language processing, revolutionizes diverse fields such as business, social media, healthcare, and disaster response. This review delves into the intricate landscape of sentiment analysis, exploring its significance, challenges, and evolving methodologies. We examine crucial aspects like dataset...

The COVID-19 pandemic has sparked widespread health-related discussions on social media platforms like Twitter (now named ‘X’). However, the lack of labeled Twitter data poses significant challenges for theme-based classification and tweet aggregation. To address this gap, we developed a machine learning-based web application that automatically cla...

In this paper, a seamless connection between sensor technology and machine learning (ML) has been presented which has wide applicability in rehabilitation and physical medicine. The intent is to identify an ML algorithm which has a better performance, easy to deploy, and has less training time and consumes less computational resources. In short, we...

This study investigates the impact of personalised footwear and insole design and modification features on offloading efficacy and patient adherence in people at risk of diabetes-related neuropathic plantar forefoot ulceration. This study involved a series of non-randomised, unblinded N-of-1 trials with 12 participants who had a history of neu...

Soil analysis involves evaluating the physical, chemical, and biological properties of soil samples, encompassing factors such as composition, nutrient content, structure, pH levels, microbial activity, and organic matter. Hyperspectral imaging (HSI) in conjunction with machine learning (ML) techniques represents an emerging research trend for iden...

Diabetes-related foot ulcers and complications are a significant concern for individuals with diabetes, leading to severe health implications such as lower-limb amputation and reduced quality of life. This chapter discusses applying AI-driven personalised offloading device prescriptions as an advanced solution for preventing such conditions. By har...

The COVID-19 outbreak, declared a pandemic in March 2020, lacked specific treatments until vaccine development. Medication misinformation via media caused panic, self-prescription, and drug resistance. False propaganda led to shortages. This study analyzes Google Trends for hydroxychloroquine (HCQ), azithromycin, and BCG vaccine searches across six...

The integration of big data into infectious disease surveillance signifies a radical shift in public health, driven by technological advancements and expanded data-gathering capabilities. This convergence highlights the incorporation of large data- reservoirs, strengthens and further complements traditional disease-monitoring strategies. This study...

The estimation of soil properties is an important factor in agriculture. With the advancement of smartphones and artificial intelligence, estimating soil properties such as the Munsell soil color, pH, soil organic matter and moisture is tangible, alleviating the need for laboratories, which are time-consuming and costly. While there are several sma...

Near-infrared spectroscopy (NIRS) is a non-invasive and fast technology that has been increasingly used to analyse livestock diet quality. This study provides a comprehensive analysis of the use of NIRS technology in evaluating livestock diet quality. The objective of this study was to critically evaluate the accuracy and reliability of NIRS measur...

Handwriting is a crucial way to enhance character recognition and learn new words. However, the Bangla characters consist of very complex shapes and similar patterns. Deep learning (DL) techniques have become a prominent solution for handwritten Bangla character recognition (HBCR) due to their ability to extract high-level features from complex dat...

Livestock producers often need help in standardising (i.e., converting and validating) their livestock event data. This article introduces a novel solution , LEI2JSON (Livestock Event Information To JSON). The tool is an add-on for Google Sheets, adhering to the livestock event information (LEI) schema. The core objective of LEI2JSON is to provide...

Data-driven advances have resulted in significant improvements in dairy production. However, the meat industry has lagged behind in adopting data-driven approaches, underscoring the crucial need for data standardisation to facilitate seamless data transmission to maximise productivity, save costs, and increase market access. To address this gap, we...

Background Diabetes-related foot complications, including neuropathic plantar forefoot ulcers, are a significant contributor to morbidity and increased healthcare cost. This retrospective clinical audit examines the characteristics of people accessing pedorthics services who are at risk of neuropathic plantar forefoot ulcer (re)occurrence and the p...

Desire is a set of human aspirations and wishes that comprise verbal and cognitive aspects that drive human feelings and behaviors, distinguishing humans from other animals. Understanding human desire has the potential to be one of the most fascinating and challenging research domains. It is tightly coupled with sentiment analysis and emotion recog...

Childhood vaccination is a cornerstone of public health, safeguarding children against life-threatening diseases. However, in many developing countries, a significant number of children either miss their routine vaccinations or receive incomplete doses, leaving them vulnerable to preventable illnesses. This chapter presents a framework aimed at add...

Under review

The Internet of Medical Things (IoMT) has become an attractive playground to cybercriminals because of its market worth and rapid growth. These devices have limited computational capabilities, which ensure minimum power absorption. Moreover, the manufacturers use simplified architecture to offer a competitive price in the market. As a result, IoMTs...

Diabetes is a chronic disease caused by a persistently high blood sugar level, causing other chronic diseases, including cardiovascular, kidney, eye, and nerve damage. Prompt detection plays a vital role in reducing the risk and severity associated with diabetes, and identifying key risk factors can help individuals become more mindful of their lif...

The outbreak of coronavirus disease (COVID-19), reported in December 2019, was declared a pandemic in March 2020. There was no specific recommended treatment for COVID-19 until the development of COVID-19 vaccine. Healthcare providers and the Government were struggling to find appropriate treatment regimens to manage the pandemic. Medication misinf...

Autism Spectrum Disorder (ASD) is a neurological impairment condition that severely impairs cognitive, linguistic, object recognition, interpersonal, and communication skills. Its main cause is genetic, and early treatment and identification can reduce the patient’s expensive medical costs and lengthy examinations. We developed a machine learning (...

Simple Summary Palliative care is a vital aspect of healthcare that aims to improve the quality of life for individuals battling life-threatening diseases, such as cancer. Our research delved into the potential of deep learning (DL) model approaches to predict survival outcomes for end-stage cancer patients. Furthermore, we compared the results of...

Precise Soil Moisture (SM) assessment is essential in agriculture. By understanding the level of SM, we can improve yield irrigation scheduling which significantly impacts food production and other needs of the global population. The advancements in smartphone technologies and computer vision have demonstrated a non-destructive nature of soil prope...

Background Several research studies have demonstrated the potential of mobile health apps in supporting health management. However, the design and development process of these apps are rarely presented. Objective We present the design and development of a smartphone-based lifestyle app integrating a wearable device for hypertension management. Me...

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...

Precise Soil Moisture (SM) assessment is essential in agriculture. By understanding the level of SM, we can improve yield irrigation scheduling which significantly impacts food production and other needs of the global population. The advancements in smartphone technologies and computer vision have demonstrated a non-destructive nature of soil prope...

Nowadays, with the proliferation of different news sources, fake news detection is becoming a crucial topic to research. Millions of articles are published daily in the press, on social media, and in electronic media, and many of them may be fake. It is common for scammers to spread fake news to mislead people for malicious purposes. For researcher...

Business Process Management (BPM) has emerged as a fundamental aspect of modern business, revolutionizing task execution and operational efficiency. This study explored the integration of BPM, virtualization, and work design to enhance organizational performance and productivity. The objective is to contribute to the ongoing dialogue on the combine...

Background—Smartphones and wearable devices have become a part and parcel of the healthcare industry. The use of wearable technology has already proved its potentials in improving healthcare research, clinical work, and patient care. The real time data allow the care providers to monitor the patients’ symptoms remotely, prioritize the patients’ vis...

The foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. Hence, precise foot dimensions are essential not only for custom footwear design, but also for the clinical treatment of foot health. Most existing research on measuring foot dimensions depends on a heavy setup environment, which is costl...

You Only Look Once (YOLO) is a single-stage object detection model popular for real-time object detection, accuracy, and speed. This paper investigates the YOLOv5 model to identify cattle in the yards. The current solution to cattle identification includes radio-frequency identification (RFID) tags. The problem occurs when the RFID tag is lost or d...

Increased biosecurity and food safety requirements may increase demand for efficient traceability and identification systems of livestock in the supply chain. The advanced technologies of machine learning and computer vision have been applied in precision livestock management, including critical disease detection, vaccination, production management...

The Munsell soil color chart (MSCC) is a in laboratories under controlled conditions. To support an appbased solution, this paper explores three research areas including: (i) identifying the most effective color space, (ii) establishing then important reference for many professionals in the area of soil color analysis. Currently, the functionality...

BACKGROUND Several research studies have demonstrated the potential of mobile health applications (apps) in supporting health management. However, the design and development process of these apps are rarely presented. OBJECTIVE We present the design and development of a smartphone-based lifestyle app integrating a wearable device for hypertension...

Increased biosecurity and food safety requirements may increase demand for efficient traceability and identification systems of livestock in the supply chain. The advanced technologies of machine learning and computer vision have been applied in precision livestock management, including critical disease detection, vaccination, production management...

Having precise specifications of service APIs is essential for many Software Engineering activities. Unfortunately, available documentation of services is often inadequate and/or imprecise and, hence, cannot be fully relied upon. Generating service documentation manually is a tedious and error-prone task, especially in light of changes to services....

In this technologically advanced era, with the proliferation of artificial intelligence, many mobile apps are available for plant disease detection, diagnosis, and treatment, each with a variety of features. These apps need to be categorized and reviewed following a proper framework that ensures their quality. This study aims to present an approach...

The advancement of artificial intelligence (AI) and the significant growth in the use of food consumption tracking and recommendation-related apps in the app stores have created a need for an evaluation system, as minimal information is available about the evidence-based quality and technological advancement of these apps. Electronic searches were...

In this technologically advanced era, with the proliferation of artificial intelligence, many mobile apps are available for plant disease detection, diagnosis, and treatment, each with a variety of features. These apps need to be categorized and reviewed following a proper framework that ensures their quality. This study aims to present an approach...

The inflammable growth of misinformation on social media and other platforms during pandemic situations like COVID-19 can cause significant damage to the physical and mental stability of the people. To detect such misinformation, researchers have been applying various machine learning (ML) and deep learning (DL) techniques. The objective of this st...

The advancement of artificial intelligence (AI) and the significant growth in the use of food consumption tracking and recommendation-related apps in the app stores have created a need for an evaluation system, as minimal information is available about the evidence-based quality and technological advancement of these apps. Electronic searches were...

Background Due to the limited availability and high cost of the reverse transcription‐polymerase chain reaction (RT‐ PCR) test, many studies have proposed machine learning techniques for detecting COVID‐19 from medical imaging. The purpose of this study is to systematically review, assess and synthesize research articles that have used different ma...

This study aims to identify artificial intelligence (AI) technologies that are applied in climate-smart agricultural practices and address ethical concerns of deploying those technologies from legal perspectives. As climate-smart agricultural AI, the study considers those AI-based technologies that are used for precision agriculture, monitoring pea...

The aim of this study is to analyse the coronavirus disease 2019 (COVID-19) outbreak in Bangladesh. This study investigates the impact of demographic variables on the spread of COVID-19 as well as tries to forecast the COVID-19 infected numbers. First of all, this study uses Fisher’s Exact test to investigate the association between the infected gr...

This research aims to analyze the performance of state-of-the-art machine learning techniques for classifying COVID-19 from cough sounds and to identify the model(s) that consistently perform well across different cough datasets. Different performance evaluation metrics (precision, sensitivity, specificity, AUC, accuracy, etc.) make selecting the b...

The livestock sector contributes to agricultural development, poverty reduction, and food security globally. The digitization of the supply chain entails cost savings and improved flexibility, both of which are essential ingredients for boosting resilience in the world food chains. Recently, microservice architectures are becoming popular alternati...