Browsing by Subject "Machine Learning"
Now showing items 1-20 of 43
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A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis
( Public Library of Science , 2022 , Article)The bubble point pressure (Pb) could be obtained from pressure-volume-temperature (PVT) measurements; nonetheless, these measurements have drawbacks such as time, cost, and difficulties associated with conducting experiments ... -
A survey on recent approaches in intrusion detection system in IoTs
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)Internet of Things (IoTs) are Internet-connected devices that integrate physical objects and internet in diverse areas of life like industries, home automation, hospitals and environment monitoring. Although IoTs ease daily ... -
AI-EMPOWERED UAVS FOR RAPID DISASTER RESPONSE AND MANAGEMENT
(2024 , Master Thesis)Efficient disaster response and survivor detection are essential in minimizing casualties and mitigating the impact of disastrous events. This thesis presents an innovative approach to addressing these challenges through ... -
ANN-Based traffic volume prediction models in response to COVID-19 imposed measures
( Elsevier , 2022 , Article)Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with ... -
Applications of Machine Learning for Predicting Heart Failure
( Wiley , 2022 , Book chapter)Heart Failure is a major health burden for healthcare systems worldwide. Early diagnosis, prediction and management of patients with these conditions are critical to improve patient health outcome. The availability of large ... -
APPLYING VARIOUS MACHINE LEARNING METHODOLOGIES INTO THE FINANCIAL MARKET
(2022 , Master Thesis)The modernization of the financial market, with the introduction of the internet, made it easier for the average, everyday people, around the world to invest in the plentiful trading assets in the market. This created a ... -
Assessment and Prediction of Body Fat Composition Using A Variety of Machine Learning Algorithms
(2023 , Master Thesis)Body composition is critical for health outcomes and has been researched in various populations and conditions like obesity, diabetes, and many more. Qatar Biobank collected anthropometric and biomedical data from individuals ... -
Audio based drone detection and identification using deep learning
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)In recent years, unmanned aerial vehicles (UAVs) have become increasingly accessible to the public due to their high availability with affordable prices while being equipped with better technology. However, this raises a ... -
Augmented Reality Interface for Complex Anatomy Learning in the Central Nervous System: A Systematic Review
( Hindawi , 2020 , Article)The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the ... -
Bioinformatics investigation on blood-based gene expressions of Alzheimer's disease revealed ORAI2 gene biomarker susceptibility: An explainable artificial intelligence-based approach
( Springer , 2023 , Article)The progressive, chronic nature of Alzheimer's disease (AD), a form of dementia, defaces the adulthood of elderly individuals. The pathogenesis of the condition is primarily unascertained, turning the treatment efficacy ... -
DDPG Performance in THz Communications over Cascaded RISs: A Machine Learning Solution to the Over-Determined System
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)THz technology is considered a key element in 6G wireless communication because it provides ultra-high bandwidths, considerable capacities, and significant gains. However, wireless systems operating at high frequencies are ... -
Deep learning in classifying sleep stages
( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)This paper presents a deep feed-forward neural network classifier to automatically classify the stages of sleep using raw data taken from a single electropalatogram channel (Fpz-Cz). No features are extracted at all from ... -
Feasibility of Supervised Machine Learning for Cloud Security
( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. ... -
Features Ranking Techniques for Single Nucleotide Polymorphism Data
(2017 , Master Thesis)Identifying biomarkers like single nucleotide polymorphisms (SNPs) is an important topic in biomedical applications. Such SNPs can be associated with an individual’s metabolism of drugs, which make these SNPs targets for ... -
Finding Behavioural and Imaging Biomarkers of Major Depressive Disorder (MDD) using Artificial Intelligence: A Review
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Major Depressive Disorder (MDD) is a serious ailment in mental health and is a medical illness that has a debilitating impact on a person's ability to think effectively. According to the World Health Organization (WHO), ... -
HARNESSING MACHINE LEARNING IN CLINICAL DECISION SUPPORT: THEORY AND PRACTICE
(2021 , Dissertation)Decision making is a central activity in all clinical professions. Clinical decisions bear wellbeing and economic risks and consequences for patients, families, employers, and national economies. Thus, clinicians should ... -
HYPER-VINES: A HYbrid Learning Fault and Performance Issues ERadicator for Virtual NEtwork Services over Multi-Cloud Systems
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)Fault and performance management systems, in the traditional carrier networks, are based on rule-based diagnostics that correlate alarms and other markers to detect and localize faults and performance issues. As carriers ... -
Integrated Machine Learning Approaches for Comprehensive Bearing Health Monitoring and Fault Classification Using Multi-Sensory Data
(2024 , Master Thesis)Modern industries heavily rely on machines equipped with rolling-element (RE) bearings. However, these machines face substantial risks due to potential bearing faults, where even minor defects can lead to catastrophic ... -
Interest-determining web browser
(2010 , Conference Paper)This paper investigates the application of data-mining techniques on a user's browsing history for the purpose of determining the user's interests. More specifically, a system is outlined that attempts to determine certain ... -
Joint Use of Vital Signs and Cough Sounds for Pandemic Detection
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2024 , Article)In response to the challenges once posed by the COVID-19 pandemic, this paper presents a comprehensive solution that integrates advanced techniques to enhance the detection of infections remotely, using sensors on a wearable ...