Mhd Saeed Sharif
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View article: Enhancing COPD Diagnosis Accuracy: A Study on Regression Analysis and the Generalized Linear Model Technique
Enhancing COPD Diagnosis Accuracy: A Study on Regression Analysis and the Generalized Linear Model Technique Open
The emergence of telemedicine as a transformative information technology paradigm has significantly impacted various industries worldwide, particularly healthcare. With the advancement of machine learning (ML), new avenues have opened for …
View article: Assessing Driver Cognitive Load from Handsfree Mobile Phone Use: Innovative Analysis Approach Based on Heart Rate, Blood Pressure and Machine Learning
Assessing Driver Cognitive Load from Handsfree Mobile Phone Use: Innovative Analysis Approach Based on Heart Rate, Blood Pressure and Machine Learning Open
Although using a handheld mobile phone while driving is illegal, hands-free (HF) use remains permitted, despite causing cognitive distraction. This study investigated the cognitive impact of HF phone use on drivers using real-time physiolo…
View article: AI Investment Advisory: Examining Robo-Advisor Adoption Using Financial Literacy and Investment Experience Variables
AI Investment Advisory: Examining Robo-Advisor Adoption Using Financial Literacy and Investment Experience Variables Open
Artificial intelligenceAI advancement in the financial sector to support investment management, digital investment advisers can support making better decisions by providing investment recommendations for diversified investment portfolios u…
View article: Innovative computation to detect stress in working people based on mode of commute
Innovative computation to detect stress in working people based on mode of commute Open
Introduction: Commuting is an integral part of modern life for many people, shaping daily routines and impacting overall well-being. With various transportation options, including driving, public transport, walking, and cycling, commuters …
View article: Revolutionizing heart attack prognosis: Introducing an innovative regression model for prediction
Revolutionizing heart attack prognosis: Introducing an innovative regression model for prediction Open
Objective:: Heart attack prediction using machine learning is crucial for preemptive action and personalized healthcare. This research aims to predict heart attacks by employing machine learning in healthcare using a diverse range of patie…
View article: Machine Learning-Based Techniques for Assessing Critical Factors for European Tick Abundance
Machine Learning-Based Techniques for Assessing Critical Factors for European Tick Abundance Open
Tick-borne diseases are a significant health risk to humans and animals worldwide. It is important to understand the environmental and climatic factors that contribute to tick occurrence rates in order to reduce the proliferation of tick-b…
View article: A Call for Revising the Perfect Tenses Content in the EFL Course Books
A Call for Revising the Perfect Tenses Content in the EFL Course Books Open
View article: Classifying the Cognitive Performance of Drivers While Talking on Hands-Free Mobile Phone Based on Innovative Sensors and Intelligent Approach
Classifying the Cognitive Performance of Drivers While Talking on Hands-Free Mobile Phone Based on Innovative Sensors and Intelligent Approach Open
The use of mobile phones while driving is restricted to hands-free mode. But even in the hands-free mode, the use of mobile phones while driving causes cognitive distraction due to the diverted attention of the driver. By employing innovat…
View article: Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events
Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events Open
gov/study/NCT05436613.
View article: Adopting security practices in software development process: Security testing framework for sustainable smart cities
Adopting security practices in software development process: Security testing framework for sustainable smart cities Open
The dependence on smart city applications has expanded in recent years. Consequently, the number of cyberattack attempts to exploit smart application vulnerabilities significantly increases. Therefore, improving smart application security …
View article: Analysing an imbalanced stroke prediction dataset using machine learning techniques
Analysing an imbalanced stroke prediction dataset using machine learning techniques Open
A stroke is a medical condition characterized by the rupture of blood vessels within the brain which can lead to brain damage. Various symptoms may be exhibited when the brain's supply of blood and essential nutrients is disrupted. To fore…
View article: Elevating metaverse virtual reality experiences through network‐integrated neuro‐fuzzy emotion recognition and adaptive content generation algorithms
Elevating metaverse virtual reality experiences through network‐integrated neuro‐fuzzy emotion recognition and adaptive content generation algorithms Open
Interactions between individuals and digital material have completely changed with the advent of the Metaverse. Due to this, there is an immediate need to construct cutting‐edge technology that can recognize the emotions of users and conti…
View article: Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events
Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events Open
Current treatments for bipolar depression have limited effectiveness, tolerability and acceptability. Transcranial direct current stimulation (tDCS) is a novel non-invasive brain stimulation method that has demonstrated treatment efficacy …
View article: Federated learning with hybrid differential privacy for secure and reliable <scp>cross‐IoT</scp> platform knowledge sharing
Federated learning with hybrid differential privacy for secure and reliable <span>cross‐IoT</span> platform knowledge sharing Open
The federated learning has gained prominent attention as a collaborative machine learning method, allowing multiple users to jointly train a shared model without directly exchanging raw data. This research addresses the fundamental challen…
View article: Outstanding EFL Students' Role in Peer Learning: A Pedagogical Overview
Outstanding EFL Students' Role in Peer Learning: A Pedagogical Overview Open
View article: Insights into the Contribution of Multiple Factors on Tick Abundance Across Europe Spanning 20 Years Using Different Machine Learning Algorithms
Insights into the Contribution of Multiple Factors on Tick Abundance Across Europe Spanning 20 Years Using Different Machine Learning Algorithms Open
View article: Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis
Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis Open
Antibiotic-resistant bacteria have proliferated at an alarming rate as a result of the extensive use of antibiotics and the paucity of new medication research. The possibility that an antibiotic-resistant bacterial infection would progress…
View article: Securing IoT Devices Against Emerging Security Threats: Challenges and Mitigation Techniques
Securing IoT Devices Against Emerging Security Threats: Challenges and Mitigation Techniques Open
The increasing prevalence of IoT devices has brought about numerous security challenges due to their relatively simple internal architecture and low-powered hardware warranted by their small footprint requirement. As there are billions of …
View article: An Innovative Random-Forest-Based Model to Assess the Health Impacts of Regular Commuting Using Non-Invasive Wearable Sensors
An Innovative Random-Forest-Based Model to Assess the Health Impacts of Regular Commuting Using Non-Invasive Wearable Sensors Open
Regular commutes to work can cause chronic stress, which in turn can cause a physical and emotional reaction. The recognition of mental stress in its earliest stages is very necessary for effective clinical treatment. This study investigat…
View article: An innovative approach based on machine learning to evaluate the risk factors importance in diagnosing keratoconus
An innovative approach based on machine learning to evaluate the risk factors importance in diagnosing keratoconus Open
Background and objective: Keratoconus is a non-inflammatory corneal condition affecting both eyes and is present in one out of every 2,000 people worldwide. The cornea deforms into a conical shape and thins, resulting in high-order aberrat…
View article: An Intelligent Model to Predict the Impact on Health Due to Commuting to Work on a Regularbasis
An Intelligent Model to Predict the Impact on Health Due to Commuting to Work on a Regularbasis Open
View article: An Effective Cost-Sensitive Convolutional Neural Network for Network Traffic Classification
An Effective Cost-Sensitive Convolutional Neural Network for Network Traffic Classification Open
The volume, and density of computer network traffic are increasing dramatically with the technology advancements, which has led to the emergence of various new protocols. Analyzing the huge data in large business networks has become import…
View article: An Effective Hybrid Approach Based on Machine Learning Techniques for Auto-Translation: Japanese to English
An Effective Hybrid Approach Based on Machine Learning Techniques for Auto-Translation: Japanese to English Open
In recent years machine learning techniques have been able to perform tasks previously thought impossible or impractical such as image classification and natural language translation, as such this allows for the automation of tasks previou…
View article: Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach
Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach Open
Commuting to work is an everyday activity for many which can have a significant effect on our health. Commuting on regular basis can be a cause of chronic stress which is linked to poor mental health, high blood pressure, heart rate, and e…
View article: Retracted: Defeating the Credit Card Scams Through Machine Learning Algorithms
Retracted: Defeating the Credit Card Scams Through Machine Learning Algorithms Open
Credit card fraud is a significant problem that is not going to go away. It is a growing problem and surged during the Covid-19 pandemic since more transactions are done without cash in hand now. Credit card frauds are complicated to disti…
View article: An Effective Knowledge-Based Modeling Approach towards a “Smart-School Care Coordination System” for Children and Young People with Special Educational Needs and Disabilities
An Effective Knowledge-Based Modeling Approach towards a “Smart-School Care Coordination System” for Children and Young People with Special Educational Needs and Disabilities Open
There is a significant need for a computer-aided modeling, effective information analysis and ontology knowledge base models to support both special needs children and care providers. As this research work correlated to the symmetry scope,…
View article: A Machine-Learning-Based Approach to Predict the Health Impacts of Commuting in Large Cities: Case Study of London
A Machine-Learning-Based Approach to Predict the Health Impacts of Commuting in Large Cities: Case Study of London Open
The daily commute represents a source of chronic stress that is positively correlated with physiological consequences, including increased blood pressure, heart rate, fatigue, and other negative mental and physical health effects. The purp…
View article: Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software
Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software Open
Objectives: Harmonisation is the process whereby standardised uptake values from different scanners can be made comparable. This PET/CT pilot study aimed to evaluate the effectiveness of harmonisation of a modern scanner with image reconst…
View article: An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study
An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study Open
The predominant application of positron emission tomography (PET) in the field of oncology and radiotherapy and the significance of medical imaging research have led to an urgent need for effective approaches to PET volume analysis and the…
View article: Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All
Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All Open
Imbalanced classes in multi-classed datasets is one of the most salient hindrances to the accuracy and dependable results of predictive modeling. In predictions, there are always majority and minority classes, and in most cases it is diffi…