Md Anisur Rahman

• Doctor of Philosophy
• Lecturer in Business Analytics at La Trobe University

Many existing clustering techniques including K-Means require a user input on the number of clusters. It is often extremely difficult for a user to accurately estimate the number of clusters in a data set. The genetic algorithms (GAs) generally determine the number of clusters automatically. However, they typically choose the genes and the number o...

Machine learning algorithms such as clustering, classification, and regression typically require a set of parameters to be provided by the user before the algorithms can perform well. In this paper, we present parameter independent density-based clustering algorithms by utilizing two novel concepts for neighborhood functions which we term as Unique...

It is a crucial need for a clustering technique to produce high-quality clusters from biomedical and gene expression datasets without requiring any user inputs. Therefore, in this paper we present a clustering technique called KUVClust that produces high-quality clusters when applied on biomedical and gene expression datasets without requiring any...

In machine learning, the nature of the dataset itself such as convexity of the data point sets affects the right choice of clustering algorithm to give good performance. This brief paper first focuses on how data convexity influences the clustering performance on biomedical datasets. Then it addresses the main challenges of two well-known clusterin...

A recently published state-of-the-art density-based clustering technique called ICFSFDP for partial discharge detection requires various sensitive user-defined input parameters. This paper presents a parameter-free clustering technique called PDAutoClust for partial discharge detection. The PDAutoClust algorithm can produce high-quality clusters fo...

Cardiovascular Disease (CVD) has become a serious reason of death all over the world. According to the Australian Institute of Health and Welfare report, CVD was the underlying cause of 42,700 deaths (25% of all) in 2021. Therefore, accurate detection of CVD is crucial for early treatment. An Electrocardiogram (ECG) signal is used to measure the rh...

Respiratory diseases including severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), HIV, influenza A (H1N1), and COVID-19 can cause lung infections. Among these, COVID-19 has been considered as an epidemic in the past few years. According to the World Health Organization (WHO), about 2.7 million deaths occurred due to...

In recent years, there has been a growing interest in deep learning-based clustering. A recently introduced technique called DipDECK has shown effective performance on large and high-dimensional datasets. DipDECK utilises Hartigan’s dip test, a statistical test, to merge small non-viable clusters. Notably, DipDECK was the first deep learning-based...

Background The study aims to map the patient journey in a regional Emergency Department (ED), identify factors causing extended Length of Stay (LOS) in ED during pre-COVID (2016–2019), COVID (2020–2022) and post-COVID (2023), and analyse the patient journey using clinical informatics. Through systematic analysis and root cause identification, the s...

Users utilize Location-Based Social Networks (LBSNs) to check into diverse venues and share their experiences through ratings and comments. However, these platforms typically feature a considerably larger number of locations than users, resulting in a challenge known as insufficient historical data or user-location matrix sparsity. This sparsity ar...

Social media and smartphone use are strongly linked to users' emotional states. While numerous studies have established that fear of missing out (FOMO), boredom, and loneliness predict social media and smartphone use, numerous other studies have concluded that social media and smartphone use negatively impact these emotional states (i.e., FOMO, bor...

Research has indicated a negative impact of physical activity on academic burnout among students, however, there is a paucity of evidence about the underlying mechanism of this association in Pakistani students. The present research seeks to investigate the relationship between physical activity and academic burnout by investigating the potential m...

Objectives: Assess brief intervention that included opportunistic advice and encouragement, behaviour change support, pharmacotherapy prescription or recommendation, and referral to quit service included in brief intervention without any post discharge supportive contact which was based on two primary outcomes: attempt to quit smoking and quit smok...

Hyperspectral imaging is now used in diverse applications like agriculture, forestry, and geology. Despite its versatility, accurately classifying hyperspectral data is challenging due to its high dimensionality and complexity. To address this problem Principal Component Analysis (PCA) might be used to extract the intrinsic features. However, PCA d...

Hyperspectral imagery, with its rich spectral information, is indispensable in various remote sensing applications. However, working with hyperspectral data introduces two formidable challenges: the curse of dimensionality and the predicament of class imbalance. The inherent high dimensionality necessitates substantial computational resources, whil...

Purpose. Acute surgical unit (ASU) enables timely operative procedures and rapid assessment of emergency patients. This pilot audit analysed activity of ASU at Wagga Wagga Hospital. Methodology. A retrospective review of ASU admissions via electronic medical records from February 2021 to January 2022 was conducted. Data of maximum 40 patients each...

Ontology-based clustering has gained attention in recent years due to the potential benefits of ontology. Current ontology-based clustering approaches have mainly been applied to reduce the dimensionality of attributes in text document clustering. Reduction in dimensionality of attributes using ontology helps to produce high quality clusters for a...

The use of data in modern healthcare systems is increasing rapidly with the advancement of state-of-the-art information technology. Research in healthcare systems data has received a great deal of attention in recent years from the research community to improve health outcomes. Development and deployment of novel and existing data mining and machin...

Ontology-based clustering has gained attention in recent years due to the potential benefits of ontology. Current ontology-based clustering approaches have mainly been applied to reduce the dimensionality of attributes in text document clustering. Reduction in dimensionality of attributes using ontology helps to produce high quality clusters for a...

The increased use of urban technologies in smart cities brings new challenges and issues. Cyber security has become increasingly important as many critical components of information and communication systems depend on it, including various applications and civic infrastructures that use data-driven technologies and computer networks. Intrusion dete...

Research on Phubbing has received a lot of attention in recent years from the research community. However, the studies conducted are mainly based on linear statistics, which is a very conservative method for data analysis. To overcome this limitation, we adopted a data mining and machine learning-based approach to identify the patterns related to P...

Gene classification and pattern extraction from gene sequence data is essential in understanding different gene sequence features. The field of gene expression data analysis has grown in the past few years from being purely data-centric to integrative, aiming at complementing micro-array analysis with data and knowledge from diverse available sourc...

Internet is free and straightforward access to an immense measure of crude content information that can be mined for sentiment analysis. For a long time, this is being used for market research, user opinion mining, recommendation systems, analyze people's views on a topic, etc. Many different techniques have been developed, yet much complication re...

Mental stress is the main well-being problem world-wide today. It is responsible for most of all mental-brain diseases.Mental stress does not need any specific reason to happen. It canbe experienced from a very little incident to a huge issue. Theconsequence of it depends on how people handle it. Depressionand anxiety are one of the results of it,...

Stress refers to body’s physical, emotional and psychological reaction to any environmental change needing adjustment with major impact on human psychology. Stress is specially difficult to manage for visually impaired people (VIP) as they can become easily stressed in unknown situations. Electroencephalogram (EEG) signals can be used to detect str...

As brain is the most vital organ of the human body, the affects of brain related diseases can be severe. One of the most harmful diseases is brain tumor, which results in a very short life expectancy of the affected patient. Detection of brain tumor is a challenging task in the early stages. Still, with the help of modern technology and machine lea...

Over the centuries, human aimed to achieve the ability to understand the inner functions of the mind and brain. One of the techniques to understand such functions is the application of neurofeedback. Neurofeedback is the procedure which has an influence on physiological brain conditions that takes place by allowing self-regulation of brain activiti...

The human brain is the most important and central organ of the body. The brain receives information from the environment through the sensory organs, processes, analyses and integrates the information and sends instructions to the rest of the organs. There is also communication between billions of neurons within the brain for emotion, thoughts and b...

Epilepsy is one of the chronic diseases of brain that occurs as a result of sudden and abnormal change in electric waves of brain. A lot of research has been carried out to predict the epileptic seizures. However, the literature shows that there are opportunities for further improvement in early seizure prediction. Therefore, in this paper, we aim...

Neuromarketing is applying neuropsychology in marketing research studying consumer sensory-motor actions such as cognitive and affective responses to marketing stimuli with the help of modern technologies. It is one of the most recent marketing research strategies and may become the future of marketing research. Many research works have been carrie...

Background and Objective The Coronavirus 2019, or shortly COVID-19, is a viral disease that causes serious pneumonia and impacts our different body parts from mild to severe depending on patient’s immune system. This infection was first reported in Wuhan city of China in December 2019, and afterward, it became a global pandemic spreading rapidly ar...

Covid R - Largest Covid 19 Dataset https://www.kaggle.com/ehrupok/covid-r-largest-covid-19-dataset

Alzheimer’s disease is an irremediable, continuous brain disorder that gradually destroys memory and thinking skills and eventually, the ability to carry out the simplest tasks. It has become one of the critical diseases throughout the world. Moreover, there is no remedy for Alzheimer’s disease. Machine learning techniques especially deep learning...

Cyber-attacks are exponentially increasing daily with the advancements of technology. Therefore, the detection and prediction of cyber-attacks are very important for every organization that is dealing with sensitive data for business purposes. In this paper, we present a framework on cyber security using a data mining technique to predict cyber-att...

Mind Wandering (MW) is the recurrent occurrence in which our mind gets disengaged from the immediate task and focused on internal trains of thought. MW can have both good as well as detrimental effects. Hence, it is crucial to measure MW. This interesting phenomenon and part of our daily life can be effectively measured using EEG signals. Several t...

As populations around the world increase, the problem of safely and efficiently managing waste also grows. In recent years many cities have designed and implemented data collection network architectures as a part of'Smart Cities' initiatives. Some waste managers have taken advantage of these networks to gather environmental data from waste bins thr...

Objectives: Health services have an imperative to reduce prolonged patient length of stay (LOS) in Emergency Department (ED). Our objective is to develop and validate an accurate prediction model for patient LOS in ED greater than 4 hours using a data mining technique. Methods: Data were collected from a regional Australian public hospital for all...

Data are being collected from various aspects of life. These data can often arrive in chunks/batches. Traditional static clustering algorithms are not suitable for dynamic datasets, i.e., when data arrive in streams of chunks/batches. If we apply a conventional clustering technique over the combined dataset, then every time a new batch of data come...

Objectives: Health services have an imperative to reduce prolonged patient length of stay (LOS) in Emergency Department (ED). Our objective is to develop and validate an accurate prediction model for patient LOS in ED greater than 4 hours using a data mining technique. Methods: Data were collected from a regional Australian public hospital for all...

The detection of the number of clusters in a biomedical dataset is very important for generating high quality clusters from the biomedical dataset. In this paper, we aim to evaluate the performance of a density based K-Means clustering technique called DenClust on biomedical datasets. DenClust produces the number of clusters and the high quality in...

Knowledge discovery from data demands that it shall be the data themselves that reveal the groups (i.e. the data elements in each group) and the number of groups. For the ubiquitous task of clustering, K-MEANS is the most used algorithm applied in a broad range of areas to identify groups where intra-group distances are much smaller than inter-grou...

In this paper we propose a novel attribute weight selection technique called AWST that automatically determines attribute weights for a clustering purpose. The main idea of AWST is to assign weight on an attribute based on the ability of the attribute to cluster the records of a dataset. The attributes with higher abilities get higher weights for c...

In this paper we present two clustering techniques called ModEx and Seed-Detective. ModEx is a modified version of an existing clustering technique called Ex-Detective. It addresses some limitations of Ex-Detective. Seed-Detective is a combination of ModEx and Simple K-Means. Seed-Detective uses ModEx to produce a set of high quality initial seeds...

Clustering is an important data mining task which is a process of grouping similar records into one cluster and dissimilar records into different clusters. It is used in various fields for knowledge discovery and decision making. There are many existing clustering techniques. However, many of them have a number of limitations such as the requiremen...

In this paper we present a clustering technique called DenClust that produces high quality initial seeds through a deterministic process without requiring an user input on the number of clusters k and the radius of the clusters r. The high quality seeds are given input to K-Means as the set of initial seeds to produce the final clusters. DenClust u...

In this paper we present a novel clustering technique called DenClust. By using a deterministic process, DenClust selects high quality initial seeds for K-Means. The deterministic process uses a density based approach for initial seed selection. DenClust calculates the density for each record based on the distances. The density of a record is the n...

We present a novel fuzzy clustering technique called CRUDAW that allows a data miner to assign weights on the attributes of a data set based on their importance (to the data miner) for clustering. The technique uses a novel approach to select initial seeds deterministically (not randomly) using the density of the records of a data set. CRUDAW also...

In this paper we present a novel clustering technique called Seed-Detective. It is a combination of modified versions of two existing techniques namely Ex-Detective and Simple K-Means. Seed-Detective first discovers a set of preliminary clusters using our modified Ex-Detective. The modified Ex-Detective allows a data miner to assign different weigh...

Algorithm (TORA) have been implemented. In this paper, a comprehensive attempt has been made to compare the performance of two prominent on-demand reactive routing protocols for mobile ad hoc networks: DSR and AODV, along with the traditional proactive DSDV protocol. A simulation model with MAC and physical layer models have been used to study inte...

Transmission Control Protocol (TCP) includes eleven variants-Tahoe, FullTcp, TCP/Asym, Reno, Reno/Asym, Newreno, Newreno/Asym, Sack1, Fack, Vegas and VegasRBP as source and five-TCPSink, TCPSink/Asym, Sack1, DelAck and Sack1/DelAck as destination, implemented in Network Simulator (NS-2). Performance of TCP versions indicates how they respond to var...

Traditional TCP implementations are tuned to work well over wired networks. A packet loss is occurred in a wired network mainly due to network congestion. On the other hand in a wireless link packet losses are caused mainly due to bit errors resulted from noise, interference, and various kinds of fadings. TCP performance in these environments is im...

The ever-increasing volume in the collection of image data in various fields of science, medicine, security and other fields has brought the necessity to extract knowledge. Face classification/recognition is one of the challenging problems of computer vision. This paper presents details development of a real time face recognition system (FRS) aimed...

In this paper some commonly used concurrency control protocols have been implemented through simulation. It is well known that the transactions have mainly four properties: atomicity, consistency, isolation and durability, which are known as the ACID properties. The objective of concurrency control is to ensure consistency when a shared database is...