Ashad Kabir

Ashad Kabir
Charles Sturt University · School of Computing and Mathematics

BSc, MS, PhD

About

115
Publications
71,960
Reads
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1,116
Citations
Additional affiliations
March 2015 - present
Swinburne University of Technology
Position
  • Adjunct Research Fellow
September 2013 - February 2015
Swinburne University of Technology
Position
  • PostDoc Position
Description
  • Large-Scale Emulation of Enterprise Software Environments (an ARC linkage project with Computer Associate) focusing research on Automatically Mining Software Behavior from Interaction Logs, for details (http://quoll.ict.swin.edu.au/)
Education
July 2009 - October 2013
Swinburne University of Technology
Field of study
  • Computer and Software Engineering
September 2006 - August 2008
Pusan National University
Field of study
  • Computer Engineering, RFID System
August 1999 - July 2004
Chittagong University of Engineering & Technology
Field of study
  • Computer Science and Engineering

Publications

Publications (115)
Conference Paper
Full-text available
Knowledge graph is useful for many different domains like search result ranking, recommendation, exploratory search, etc. It integrates structural information of concepts across multiple information sources, and links these concepts together. The extraction of domain specific relation triples (subject, verb phrase, object) is one of the important t...
Article
Full-text available
With the advances of Internet technologies and an explosive growth in the popularity of social media, an increasingly large part of human life is getting digitized and becoming available on the web. This phenomenon brings opportunities and motivates us to infer users’ situations by exploiting their interaction events in various social media such as...
Article
Full-text available
Social context information has been used with encouraging results in developing socially aware applications in different domains. However, users’ social context information is distributed over the Web and managed by many different proprietary applications, which is a challenge for application developers as they must collect information from differe...
Article
Full-text available
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...
Article
Full-text available
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...
Article
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....
Article
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Chapter
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...
Article
Context: Service virtualization has become a popular tool to provide testing environments for highly connected enterprise software systems. It enables the enterprise system under test to interact with and obtain responses from model-based service emulations instead of the actual services they use in production environments, providing accessibility...
Article
Full-text available
COVID-19’s unanticipated consequences have resulted in the extended closure of various educational institutions, causing significant hardship to students. Even though many institutions rapidly transitioned to online education programs, various issues have emerged that are impacting many aspects of students’ lives. An online survey was conducted wit...
Article
Full-text available
The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide incons...
Article
Full-text available
The dark web is a section of the Internet that is not accessible to search engines and requires an anonymizing browser called Tor. Its hidden network and anonymity pave the way for illegal activities and help cybercriminals to execute well-planned, coordinated, and malicious cyberattacks. Cyber security experts agree that online criminal activities...
Article
Full-text available
Augmented reality (AR) has been widely used in education, particularly for child education. This paper presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing. The app has two main features: (i) guided learning to teach users how to write the alphab...
Chapter
Visual speech recognition (VSR) is a very challenging task. It has many applications such as facilitating speech recognition when the acoustic data is noisy or missing, assisting hearing impaired people, etc. Modern VSR systems require a large amount of data to achieve a good performance. Popular VSR datasets are mostly available for the English la...
Preprint
Full-text available
The objectives of this research are analysing the performance of the state-of-the-art machine learning techniques for classifying COVID-19 from cough sound and identifying the model(s) that consistently perform well across different cough datasets. Different performance evaluation metrics (such as precision, sensitivity, specificity, AUC, accuracy,...
Preprint
Full-text available
Objective: This study aims to identify the social determinants of mental health among undergraduate students in Bangladesh, a developing nation in South Asia. Our goal is to identify the broader social determinants of mental health among this population, study the manifestation of these determinants in their day-to-day life, and explore the feasibi...
Article
Full-text available
This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various lev...
Preprint
Full-text available
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 machine learn...
Article
Full-text available
Selective harmonic elimination (SHE) technique is used in power inverters to eliminate specific lower-order harmonics by determining optimum switching angles that are used to generate Pulse Width Modulation (PWM) signals for multilevel inverter (MLI) switches. Various optimization algorithms have been developed to determine the optimum switching an...
Conference Paper
The impact of road traffic incidents (e.g., road accidents, vehicle breakdowns) have become progressively worse over the years, being a major cause of many adverse issues such as serious injury, economic loss, and lifelong disabilities. Thus, it is essential to acknowledge these issues and proactively construct appropriate solutions to mitigate the...
Preprint
Full-text available
The objectives of this study are understanding the requirements of a CSA education app, identifying the limitations of existing apps, and providing a guideline for better app design. An electronic search across three major app stores(Google Play, Apple, and Microsoft) is conducted and the selected apps are rated by three independent raters. Total 1...
Article
Full-text available
The goal of this research is to develop and implement a highly effective deep learning model for detecting COVID-19. To achieve this goal, in this paper, we propose an ensemble of Convolutional Neural Network (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 from chest X-rays. To make the proposed model more robust, we have used one of...
Article
Full-text available
Autism Spectrum Disorder (ASD), which is a neuro development disorder, is often accompanied by sensory issues such an over sensitivity or under sensitivity to sounds and smells or touch. Although its main cause is genetics in nature, early detection and treatment can help to improve the conditions. In recent years, machine learning based intelligen...
Article
Full-text available
Software behavioral models have proven useful for emulating and testing software systems. Many techniques have been proposed to infer behavioral models of software systems from their interaction traces. The quality of the inferred/mined model is critical to their successful use. While generalization is necessary to deduce concise behavioral models,...
Article
Mobile games can contribute to learning at greater success. In this paper, the authors have developed and evaluated a novel educational game, named FoodCalorie, to learn food calorie intake standard. The game is aimed to learn calorie values of various traditional foods of Bangladesh and the calorie intake standard that varies with age and gender....
Article
Full-text available
Background The undergraduate student population has been actively studied in digital mental health research. However, the existing literature primarily focuses on students from high-income nations, and undergraduates from limited-income nations remain understudied. Objective This study aims to identify the broader social determinants of mental hea...
Article
Full-text available
Exploring and analyzing data using visualizations is at the heart of many decision-making tasks. Typically, people perform visual data analysis using mouse and touch interactions. While such interactions are often easy to use, they can be inadequate for users to express complex information and may require many steps to complete a task. Recently nat...
Preprint
Software behavioral models have proven useful for emulating and testing software systems. Many techniques have been proposed to infer behavioral models of software systems from their interaction traces. The quality of the inferred model is critical to its successful use. While generalization is necessary to deduce concise behavioral models, existin...
Article
Today information in the world wide web is overwhelmed by unprecedented quantity of data on versatile topics with varied quality. However, the quality of information disseminated in the field of medicine has been questioned as the negative health consequences of health misinformation can be life-threatening.There is currently no generic automated t...
Conference Paper
Stakeholders in the insurance industry are committed to yet lack the timely and actionable information for alleviating policyholder's mental health concerns and the industry's mental health climate. Existing research has revealed that personal data, such as depression, anxiety, and stress, can provide deeper insights into policyholder's mental heal...
Chapter
Full-text available
Mental health is a global epidemic, affecting close to half a billion people worldwide. Chronic shortage of resources hamper detection and recovery of affected people. Effective sensing technologies can help fight the epidemic through early detection, prediction, and resulting proper treatment. Existing and novel technologies for sensing mental hea...
Preprint
Full-text available
Autism Spectrum Disorder (ASD), which is a neuro development disorder, is often accompanied by sensory issues such an over sensitivity or under sensitivity to sounds and smells or touch. Although its main cause is genetics in nature, early detection and treatment can help to improve the conditions. In recent years, machine learning based intelligen...
Preprint
Full-text available
Mental health is a global epidemic, affecting close to half a billion people worldwide. Chronic shortage of resources hamper detection and recovery of affected people. Effective sensing technologies can help fight the epidemic through early detection, prediction, and resulting proper treatment. Existing and novel technologies for sensing mental hea...
Preprint
Full-text available
This paper proposed an ensemble of deep convolutional neural networks (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 using a large chest X-ray data set. At first, the open-access large chest X-ray collection is augmented, and then ImageNet pre-trained weights for EfficientNet is transferred with some customized fine-tuning top layer...
Article
Full-text available
The COVID-19 pandemic continues to severely undermine the prosperity of the global health system. To combat this pandemic, effective screening techniques for infected patients are indispensable. There is no doubt that the use of chest X-ray images for radiological assessment is one of the essential screening techniques. Some of the early studies re...
Article
Full-text available
This paper presents an analysis on a hexagonal cladding with a rotated-hexa core in photonic crystal fiber (H-PCF) based optical sensor formation with simultaneously minimal confinement loss and higher sensitivity for chemical sensing functions. The numerical assessment of the designed structure is achieved with the procedure of finite element meth...
Preprint
Mobile games can contribute to learning at greater success. In this paper, we have developed and evaluated a novel educational game, named FoodCalorie, to learn food calorie intake standard. Our game is aimed to learn calorie values of various traditional Bangladeshi foods and the calorie intake standard that varies with age and gender. We are the...
Preprint
Full-text available
BACKGROUND With the public coverage of smartphones now at a global level, a major growth in the use of apps related to the health category, specifically those concerned with foot health can be observed. Although new, these apps are being used practically for scanning feet with an aim to providing accurate information about various properties of the...
Article
Full-text available
Background As the use of smartphones increases globally across various fields of research and technology, significant contributions to the sectors related to health, specifically foot health, can be observed. Numerous smartphone apps are now being used for providing accurate information about various foot-related properties. Corresponding to this a...
Conference Paper
Typically, people perform visual data analysis using mouse and touch interactions. While such interactions are often easy to use, they can be inadequate for users to express complex information and may require many steps to complete a task. Recently natural language interaction has emerged as a promising technique for supporting exploration with vi...
Preprint
The rapid dissemination of health misinformation poses an increasing risk to public health. To best understand the way of combating health misinformation, it is important to acknowledge how the fundamental characteristics of misinformation differ from domain to domain. This paper presents a pathway towards domain-specific characterization of misinf...
Preprint
Full-text available
The COVID-19 pandemic continues to severely undermine the prosperity of the global health system. To combat this pandemic, effective screening techniques for infected patients are indispensable. There is no doubt that the use of chest X-ray images for radiological assessment is one of the essential screening techniques. Some of the early studies re...
Article
Full-text available
Smart Home automation is increasingly gaining popularity among current applications of Internet of Things (IoT) due to the convenience and facilities it provides to the home owners. Sensors are employed within the home appliances via wireless connectivity to be accessible remotely by home owners to operate these devices.With the exponential increas...
Preprint
The information ecosystem today is overwhelmed by an unprecedented quantity of data on versatile topics are with varied quality. However, the quality of information disseminated in the field of medicine has been questioned as the negative health consequences of health misinformation can be life-threatening. There is currently no generic automated t...
Article
Full-text available
Epilepsy is a common neurological disorder, and epileptic seizure detection is a scientific challenge since sometimes patient do not experience any alert. The objective of this research is to reduce the seizure detection time while maintaining high accuracy, and locate the brain hemisphere that is mostly affected by seizure. We argue that by using...
Article
Autism spectrum disorder (ASD) is a brain development disorder that restricts a person's communication abilities and social interaction capabilities from natural growth. In this paper, we have applied various supervised classification techniques to detect the presence of child autism. Our findings show that the Sequential Minimal Optimization (SMO)...