Fahim Sufi

Federal Government

This paper develops a new clustering technique based on Hellinger distance (HD) that can improve the Particle Swarm Optimization (PSO) search. Selection of features plays an important role in disease detection. Evidently, most machine learning algorithms are unable to accurately identify the optimal features in medical datasets due to the complexit...

The exponential growth of digital news sources presents a critical challenge in efficiently processing and analyzing vast datasets to derive actionable insights. This paper introduces a GPT-based news analytics system that addresses this issue using advanced mathematical modeling and AI techniques. Over a 405-day period, the system processed 1,033,...

This research, introduces a new dynamic clustering method offering a new approach utilizing Minkowski Distance methods for calculating similarity of xml messages to effectively compress and aggregate them. The increase in Web services utilization has led to bottlenecks and congestion on network links with limited bandwidth. Furthermore, Simple Obje...

In this systematic literature review, the intersection of deep learning applications within the aphasia domain is meticulously explored, acknowledging the condition’s complex nature and the nuanced challenges it presents for language comprehension and expression. By harnessing data from primary databases and employing advanced query methodologies,...

This research confronts the persistent challenge of data scarcity in medical machine learning by introducing a pioneering methodology that harnesses the capabilities of Generative Pre-trained Transformers (GPT). In response to the limitations posed by a dearth of labeled medical data, our approach involves the synthetic generation of comprehensive...

In contemporary discourse, the pervasive influences of Generative Pre-Trained (GPT) and Large Language Models (LLM) are evident, showcasing diverse applications. GPT-based technologies, transcending mere summarization, exhibit adeptness in discerning critical information from extensive textual corpuses. Through prudent extraction of semantically me...

In the face of escalating cyber threats that have contributed significantly to global economic losses, this study presents a comprehensive dataset capturing the multifaceted nature of cyber-attacks across 225 countries over a 14-month period from October 2022 to December 2023. The dataset, comprising 77,623 rows and 18 fields, provides a detailed c...

Natural and manmade disasters like landslides, floods, earthquake, cyclone, shooting, riots have detrimental effect in precious life, infrastructure, and economy. This study addresses the need for a comprehensive analysis of Generative Pre-Trained Transformers (GPT) in the context of open-source disaster intelligence, a topic where existing literat...

Transformer technologies, like generative pre-trained transformers (GPTs) and bidirec-tional encoder representations from transformers (BERT) are increasingly utilized for understanding diverse social media content. Despite their popularity, there is a notable absence of a systematic literature review on their application in disaster analytics. Thi...

GPT (Generative Pre-trained Transformer) represents advanced language models that have significantly reshaped the academic writing landscape. These sophisticated language models offer invaluable support throughout all phases of research work, facilitating idea generation, enhancing drafting processes, and overcoming challenges like writer's block....

Since the onset of the COVID-19 crisis, scholarly investigations and policy formulation have harnessed the potent capabilities of artificial intelligence (AI)-driven social media analytics. Evidence-driven policymaking has been facilitated through the proficient application of AI and natural language processing (NLP) methodologies to analyse the va...

Utilizing social media data is imperative in comprehending critical insights on the Russia–Ukraine cyber conflict due to their unparalleled capacity to provide real-time information dissemination, thereby enabling the timely tracking and analysis of cyber incidents. The vast array of user-generated content on these platforms, ranging from eyewitnes...

The prevalence of cybercrime has emerged as a critical issue in contemporary society because of its far-reaching financial, social, and psychological implications. The negative effects of cyber-attacks extend beyond financial losses and disrupt people's lives on social and psychological levels. Conventional practice involves cyber experts sourcing...

The COVID-19 pandemic has had far-reaching consequences globally, including a significant loss of lives, escalating unemployment rates, economic instability, deteriorating mental well-being, social conflicts, and even political discord. Vaccination, recognized as a pivotal measure in mitigating the adverse effects of COVID-19, has evoked a diverse...

The surge in cybercrime has emerged as a pressing concern in contemporary society due to its far-reaching financial, social, and psychological repercussions on individuals. Beyond inflicting monetary losses, cyber-attacks exert adverse effects on the social fabric and psychological well-being of the affected individuals. In order to mitigate the de...

Cyber threats are projected to cause USD 10.5 trillion in damage to the global economy in 2025. Comprehending the level of threat is core to adjusting cyber posture at the personal, organizational, and national levels. However, representing the threat level with a single score is a daunting task if the scores are generated from big and complex data...

Understanding the complex dynamics of landslides is crucial for disaster planners to make timely and effective decisions that save lives and reduce the economic impact on society. Using the landslide inventory of the Chittagong Metropolitan Area (CMA), we have created a new artificial intelligence (AI)-based insight system for the town planners and...

Algorithms have evolved from machine code to low-code-no-code (LCNC) in the past 20 years. Observing the growth of LCNC-based algorithm development, the CEO of GitHub mentioned that the future of coding is no coding at all. This paper systematically reviewed several of the recent studies using mainstream LCNC platforms to understand the area of res...

Anti-Vax social movement possesses a dire threat to governments’ aim of mass vaccination. Moreover, by propagating serious misconceptions and misinformation about COVID-19, Anti-Vaxxers directly and indirectly cause harm to the overall health and wellbeing of society. In addition, the ongoing clashes between Anti-Vaxxers and Pro-Vaxxers have create...

This paper reports a method for automatically identifying, analyzing and explaining anomalies in different indexes of COVID-19 crisis using Artificial Intelligence (AI) based techniques. With systematic application of News sensor, language detection & translation, Keyword-based extraction of COVID-19 indexes, Convolutional Neural Network (CNN) base...

Negative events are prevalent all over the globe round the clock. People demonstrate psychological affinity to negative events, and they incline to stay away from troubled locations. This paper proposes an automated geospatial imagery application that would allow a user to remotely extract knowledge of troubled locations. The autonomous application...

Existing studies on Twitter-based natural disaster analysis suffer from shortcomings like limitations on supported languages, lack of sentiment analysis, regional restrictions, lack of end-to-end automation, and lack of Mobile App support. In this study, we design and develop a fully-automated artificial intelligence (AI) based Decision Support Sys...

Tropical cyclones take precious lives, damage critical infrastructure, and cause economic losses worth billions of dollars in Australia. To reduce the detrimental effect of cyclones, a comprehensive understanding of cyclones using artificial intelligence (AI) is crucial. Although event records on Australian tropical cyclones have been documented ov...

AI-Tornado is a decision support system for analyzing Tornadoes from any Tornado-event dataset using artificial intelligence (AI) based algorithms. With automated linear and logistic regression, it identifies which tornado features (e.g., duration, speed, area) matter the most, in Tornado-related causalities with detailed AI-based explanations. Sin...

Tropical cyclones devastate large areas, take numerous lives and damage extensive property in Bangladesh. Research on landfalling tropical cyclones affecting Bangladesh has primarily focused on events occurring since AD1960 with limited work examining earlier historical records. We rectify this gap by developing a new Tornado catalogue that include...

Tropical cyclones devastate large areas, take numerous lives and damage extensive property in Bangladesh. Research on landfalling tropical cyclones affecting Bangladesh has primarily focused on events occurring since AD1960 with limited work examining earlier historical records. We rectify this gap by developing a new tornado catalogue that include...

AI-SocialDisaster is a decision support system for identifying and analyzing natural disasters like earthquakes, floods, bushfires using social media feeds. It captures real-time social media messages and then uses Natural Language Processing (NLP) based algorithms like entity detection, category classification, and sentiment analysis to identify a...

Understanding the complex dynamics of landslides is crucial for disaster planners to make timely and effective decision that saves lives and reduces the economic impact on society. Using the landslide inventory of Chittagong Metropolitan Area (CMA), we created a new Artificial Intelligence (AI) based insight system for the town planners and senior...

Modern-day news agencies cater for a wide range of negative news, since multiple studies show general people are more attracted towards negative news. Once a highly negative incident is reported by a local news agency, it is often propagated by many other foreign news agencies at a global scale characterizing the news as breaking news. This propaga...

The coronavirus disease (COVID-19) pandemic has affected the lives of social media users in an unprecedented manner. They are constantly posting their satisfaction or dissatisfaction over the COVID-19 situation at their location of interest. Therefore, understanding location-oriented sentiments about this situation is of prime importance for politi...

p>Worldwide disasters like bushfires, earthquakes, floods, cyclones, heatwaves etc. have affected the lives of social media users in an unprecedented manner. They are constantly posting their level of negativity over the disaster situations at their location of interest. Understanding location-oriented sentiments about disaster situation is of prim...

p>Worldwide disasters like bushfires, earthquakes, floods, cyclones, heatwaves etc. have affected the lives of social media users in an unprecedented manner. They are constantly posting their level of negativity over the disaster situations at their location of interest. Understanding location-oriented sentiments about disaster situation is of prim...

Social media platforms such as Twitter have been used by political leaders, heads of states, political parties, and their supporters to strategically influence public opinions. Leaders can post about a location, a state, a country, or even a region in their social media accounts, and the posts can immediately be viewed and reacted to by millions of...

AI-GlobalEvents is a decision support dashboard for policy planners to conduct strategic threat assessments based on global news and events. It uses AI services and algorithms to automatically aggregate global news from online news portals, websites and social media for analyzing the events and identifying critical events requiring imminent attenti...

Worldwide disasters like bushfires, earthquakes, floods, cyclones, and heatwaves have affected the lives of social media users in an unprecedented manner. They are constantly posting their level of negativity over the disaster situations at their location of interest. Understanding location-oriented sentiments about disaster situation is of prime i...

The modern era, with information overload, has compelled strategic decision makers to obtain assistance from artificial intelligence- (AI) based decision support systems (DSS). Data-driven DSSs powered by powerful AI algorithms can instantly categorize unstructured data, assign context, and produce meaningful insights from such data. This paper pre...

AI-Landslide is a decision support software for a city planner, disaster recovery strategist or landslide researcher. The software can be deployed in a number of platforms including mobile phones (Android or iOS), tablets or desktop environments. AI-Landslide uses AI based algorithms like automated regression analysis, decomposition analysis and an...

Understanding the complex dynamics of global landslides is essential for disaster planners to make timely and effective decisions that save lives and reduce the economic impacts on society. Using NASA’s inventory of global landslide data, we developed a new machine learning (ML)–based system for town planners, disaster recovery strategists, and lan...

Background The current investigation examined the determinants of oral health experiences associated with dentine hypersensitivity using prospective diary methodology. Methods Staff and students from a large UK university who had self-diagnosed dentine hypersensitivity completed an online daily diary and text survey for 2 weeks recording their mood...

The original Dentine Hypersensitivity Experience Questionnaire (DHEQ) has 48 items, 34 of which comprise the scale that measures the subjective impacts of dentine hypersensitivity (DH). If a questionnaire is extensive, it is helpful to develop a short form to minimize participant burden by reducing the time to complete it. Doing so will also limit...

Construction and validation of the quality of life measure for dentine hypersensitivity (DHEQ). Abstract Aim: To develop and validate a condition specific measure of oral health-related quality of life for dentine hypersensitivity (Dentine Hypersensitivity Experience Questionnaire, DHEQ). Materials and Methods: Questionnaire construction used a mul...

Objective: Response shift (RS) involves changes in the subjective understanding of quality of life such as changes in the internal standards of comparison. It can therefore undermine evaluation of treatments using person centred outcomes. The aim of this study was to explore RS and its influence on the assessment of treatments in a clinical trial o...

To update the Australian System for Cardiac Operative Risk Evaluation (AusSCORE) model for operative estimation of 30-day mortality risk after isolated coronary artery bypass grafting in the Australian population. Data were collected by the Australian and New Zealand Society of Cardiac and Thoracic Surgeons registry from 2001 to 2011 in 25 hospital...

Dentine hypersensitivity is a common oral health problem, however, there has been little research on how people cope with this condition. This study aimed to quantify the effects of illness beliefs and coping strategies on the health outcomes of individuals with dentine hypersensitivity. Participants were purposively sampled from students and staff...

To validate the Dentine Hypersensitivity Experience Questionnaire in terms of responsiveness to change and to determine the minimally important difference (MID). The study was a secondary analysisof data from three randomised controlled trials with 311 participants. Three aspects of responsiveness were examined: change within individuals, differenc...

To derive and evaluate a short form of the Dentine Hypersensitivity Experience Questionnaire (DHEQ). Data from three previous studies of dentine hypersensitivity (n=353) were pooled and randomly divided in half. Ten- and fifteen-item short forms were derived in the first half of the data using the item impact and regression methods. The four short...

Objective: Response shift refers to the changes in subjective understanding of quality of life over time. It can therefore undermine evaluations of treatments using person centred outcomes. The aim of this study was to explore response shift and its underlying psychosocial mechanisms in people with dentine hypersensitivity (DH). Method: Two semi-...

Objectives: A product comparison study to compare the short term clinical efficacy of a strontium acetate/silica toothpaste with an arginine/calcium carbonate paste for pain reduction in dentine hypersensitivity. Methods: The study was examiner blind of two arm parallel design. Eighty healthy adult subjects from general dental practice with ≥2 s...

Objective: To evaluate and compare the efficacy in reducing dentine hypersensitivity of a 5% potassium nitrate/ 1450 ppm sodium fluoride dentifrice to a marketed control containing 1450ppm F as sodium monofluorophosphate in a Chinese population. Method: This was a single center, randomised, stratified, examiner-blind, two-arm, parallel group stud...

National and international standards detail in vitro methodologies for assessing toothpaste abrasivity using human enamel and dentine coupled with profilometric or radioisotope analysis. This profilometry-based study investigates the influence of brushing simulator design and choice of standard abrasive on enamel/dentine wear. Four simulators were...

Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of Electrocardiography (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional ste...

In recent times, dealing with deaths associated with cardiovascular diseases (CVD) has been one of the most challenging issues. The usage of mobile phones and portable Electrocardiogram (ECG) acquisition devices can mitigate the risks associated with CVD by providing faster patient diagnosis and patient care. The existing technologies entail delay...

Compressed Electrocardiography (ECG) is being used in modern telecardiology applications for faster and efficient transmission. However, existing ECG diagnosis algorithms require the compressed ECG packets to be decompressed before diagnosis can be applied. This additional process of decompression before performing diagnosis for every ECG packet in...

Electrocardiography (ECG) signal is popularly used for diagnosing cardiovascular diseases (CVDs). However, in recent times ECG is being used for identifying person. As ECG signals contain sensitive private health information along with details for person identification, it needs to be encrypted before transmission through public media. Moreover, th...

In this paper, a data mining technique is used on Cardioid based person identification mechanism using electrocardiogram (ECG). Recent studies in Cardioid based ECG biometric excites a new dimension of efficient patient authentication, which places new hope in faster patient care. However, existing research suffers from lower accuracy due to random...

Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of electrocardiogram (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional step...

Usage of compressed ECG for fast and efficient telecardiology application is crucial, as ECG signals are enormously large in size. However, conventional ECG diagnosis algorithms require the compressed ECG packets to be decompressed before diagnosis can be performed. This added step of decompression before performing diagnosis for every ECG packet i...

To prevent the threat of Cardiovascular Disease (CVD) related deaths, cardiac rehabilitation centers can play a major role. However, having the CVD risked patient motivated towards the strenuous exercise routine is a challenge. Therefore, in this paper, we have implemented a software system that dynamically changes the music tempo for keeping the C...

In this paper, a person identification method using electrocardiogram (ECG) is presented based on cubic spline interpolation method. Three different databases with two different sampling rates containing 36 ECG recordings were used for development and evaluation. Each ECG recording is divided into two segments: a segment for enrolment, and a segmen...

Boiko OV, Baker SR, Gibson BJ, Locker D, Sufi F, Barlow, APS, Robinson PG. Construction and validation of the quality of life measure for dentine hypersensitivity (DHEQ). J Clin Periodontol 2010; 37: 973–980. doi: 10.1111/j.1600-051X.2010.01618.x. Aim: To develop and validate a condition specific measure of oral health-related quality of life for d...

To evaluate salivary fluoride retention from a new high fluoride daily use mouthrinse over a 120 min period. Sixteen subjects completed a randomised single-blind, four-treatment cross-over trial. Sensodyne® Pronamel® mouthrinse (A) contained 450 ppm fluoride; reference products were Colgate® Fluorigard® (B), Listerine® Total Care (C) and Listerine...

To prevent the threat of Cardiovascular Disease (CVD) related deaths, the usage of mobile phone based computational platforms, body sensors and wireless communications is proliferating. Since mobile phones have limited computational resources, existing PC based complex CVD detection algorithms are often unsuitable for wireless telecardiology applic...

Objective: To develop and validate a condition specific measure of oral health-related quality of life for dentine sensitivity (DSEQ). Materials and Methods: Questionnaire construction used a multi-staged impact approach and an explicit theoretical model linking clinical variables to quality of life [Juniper et al 1996, Wilson & Cleary 1995]. Quali...

Objectives: To compare salivary fluoride retention profiles from a new mouthrinse versus a number of commercial products.. Methods: Sixteen subjects with normal salivary secretion completed a randomized single-blind, cross-over trial. The test mouthrinses were Sensodyne Pronamel (A), containing 450 ppm F (as NaF); and Colgate Fluorigard (B), Lister...

Existing electrocardiography (ECG) based biometric systems are constantly being challenged by higher misclassification error, longer acquisition time, larger template size, slower processing time and pertinence of abnormal beats within the biometric template. These challenges are the prime hindrance for ECG based biometric being commercialized as a...

This in situ study compared the abrasive effect of repeated brushings (over 10 days) of a low relative abrasive dentine (RDA) toothpaste with moderate and high relative abrasive dentine (RDA) toothpastes, on human dentine in situ. The study design was single centre, single blind, randomized, split mouth, two period, four-treatment cross-over, in si...

In Wireless telecardiology applications ECG signal is compressed before transmission to support faster data delivery and reduce consumption of bandwidth. However, most of the ECG analysis and diagnosis algorithms are based on processing of the original ECG signal. Therefore, compressed ECG data needs to be decompressed first before the existing alg...

A biometric system performs template matching of acquired biometric data against template biometric data [17.1]. These biometric data can be acquired from several sources like deoxyribonucleic acid (DNA), ear, face, facial thermogram, fingerprints, gait, hand geometry, hand veins, iris, keystroke, odor, palm print, retina, signature, voice, etc. Ac...

For wireless telecardiology, limited bandwidth is one of the major bottlenecks of faster diagnosis [1]. Since the cardiac cell damage is an irrecoverable process that may be initiated after a cardiac arrest, faster diagnosis and treatment can be a life saver [2,3]. Therefore, for cardiologists, the term “time is muscle” is of utmost importance. To...

The objective of this clinical study was to evaluate and compare the efficacy of a dentifrice containing 8% strontium acetate and 1040 ppm fluoride (from sodium fluoride) in a silica base (test dentifrice) to a control dentifrice containing 1450 ppm fluoride (from sodium fluoride) in a silica base, to reduce dentin hypersensitivity immediately afte...

To make street orienteering sports attractive and interesting to global online viewers it is important to build a system that is capable of tracking mobile competitor positions in real-time using global positioning systems (GPS) and wireless networking to collect information at a central server to be displayed to the viewers. Another important aspe...

As the number of cardiovascular related deaths is increasing not only in the western world but also in the developing countries, and there are only limited cardiac diagnosis related resources, it is expected that many healthcare centres will turn to automated diagnosis of ECGs for large number of patients. While systems and tools have been proposed...

With the advent of high-speed internet band-width consuming video conferencing applications will rapidly become attractive to e-patients seeking real-time video consultations from e-doctors. In a conventional system patients connect to a known server in a medical center of his choice. If the server (i.e. a server via which a medical consultant comm...

The aim of this study was to determine if the abrasive effect on dentine of two commercially available toothpastes, known to vary in their in vitro abrasive levels, can be differentiated in an in situ model after 10 days, assessed by contact profilometry. This was a single centre, single blind, randomized, split mouth, two treatment, in situ study,...