17 results for "Murad Al-Rajab"
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A framework model using multifilter feature selection to enhance colon cancer classification.
Gene expression profiles can be utilized in the diagnosis of critical diseases such as cancer. The selection of biomarker genes from these profiles is significant and crucial for cancer detection. This paper presents a framework proposing a two-stage multifilter hybrid model of feature selection…
Also available at: PLOS
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Sustainable EnergySense: a predictive machine learning framework for optimizing residential electricity consumption
Abstract In a world where electricity is often taken for granted, the surge in consumption poses significant challenges, including elevated CO2 emissions and rising prices. These issues not only impact consumers but also have broader implications for the global environment. This paper endeavors to…
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Machine Learning Algorithms for Early Fall Detection of Elderly People
Falls are a serious concern among the elderly people, causing severe physical pain to them and placing a strain on medical infrastructure. The global elderly population is expected to grow significantly in the coming years, as advances in healthcare allow lifespans to increase globally. This will…
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A Multimodal Approach of Machine and Deep Learnings to Enhance the Fall of Elderly People
Falls are a serious concern among the elderly due to being a major cause of harm to their physical and mental health. Despite their potential for harm, they can be prevented with proper care and monitoring. As such, the motivation for this research is to implement an algorithmic solution to the…
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Predicting new crescent moon visibility applying machine learning algorithms
Abstract The world's population is projected to grow 32% in the coming years, and the number of Muslims is expected to grow by 70%—from 1.8 billion in 2015 to about 3 billion in 2060. Hijri is the Islamic calendar, also known as the lunar Hijri calendar, which consists of 12 lunar months, and it is…
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A deep learning model to enhance lung cancer detection using ‘Dual-Branch’ model classification approach
Cancer remains a life-threatening global challenge, with lung cancer ranking among the most devastating forms, impacting millions annually. Early detection and accurate classification are essential for improving patient survival rates, and computed tomography (CT) has become a critical tool in lung…
Also available at: DOAJ
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Smart Application for Every Car (SAEC). (AR Mobile Application)
Technology is continuously evolving at an exponential rate. Fast technological advances are being made, especially in the field of smart phones, that facilitate the conduct of our daily activities in many areas such as driving. The ever-increasing number of vehicles on roads increases the…
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Toward a globally lunar calendar: a machine learning-driven approach for crescent moon visibility prediction
Abstract This paper presents a comprehensive approach to harmonizing lunar calendars across different global regions, addressing the long-standing challenge of variations in new crescent Moon sightings that mark the beginning of lunar months. We propose a machine learning (ML)-based framework to…
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A hybrid machine learning feature selection model—HMLFSM to enhance gene classification applied to multiple colon cancers dataset
Colon cancer is a significant global health problem, and early detection is critical for improving survival rates. Traditional detection methods, such as colonoscopies, can be invasive and uncomfortable for patients. Machine Learning (ML) algorithms have emerged as a promising approach for…
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Optimizing Urban Travel Time Using Genetic Algorithms for Intelligent Transportation Systems
Urban congestion causes further increases in travel times, fuel consumption and greenhouse-gas emissions. In this regard, we conduct a systematic study of a Genetic Algorithm (GA) for real-time routing in an urban scenario in Bethlehem City, based on a SUMO microsimulation that has been calibrated…
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An AI approach to lunar phase detection: enhancing the identification of the new crescent with astronomical data integration
IntroductionThe observation of the lunar crescent is significant in astronomy, cultural traditions, and religious lunar calendar determinations. However, earth-based imaging that captures all lunar phases, particularly the new crescent across multiple months, remains limited. This study explores…
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A smart secure virtual reality immersive application for alzheimer’s and dementia patients
Abstract Alzheimer’s disease (AD) poses significant challenges for the elderly, leading to cognitive decline, social isolation, and lower quality of life. Current interventions often require cumbersome wearable devices e.g. the camera-based monitoring that may raise privacy concerns. However, these…
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Artificial intelligence-enhanced CSI-based Wi-Fi sensing for non-contact vital sign monitoring: a systematic review
Background In the recent era, non-invasive health monitoring has gained attention as a crucial component of healthcare. Especially with the advancements in artificial intelligence (AI) and Wi-Fi-based sensing technologies offering promising solutions. These technologies can detect vital signs and…