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Now showing items 15314-15333 of 50304
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Machine Learning Application for Optimizing Asymmetrical Reduction of Acetophenone Employing Complete Cell of Lactobacillus Senmaizuke as an Environmentally Friendly Approach
( Hysen MANKOLLI, Earth System Science Interdisciplinary Center (ESSIC) , 2020 , Article)Recently, optimization of the bioreduction reactions by optimization methodologies has gained special interest as these reactions are affected by several extrinsic factors that should be optimized for higher yields. An ... -
MACHINE LEARNING APPLICATION FOR OPTIMIZING ASYMMETRICAL REDUCTION OF ACETOPHENONE EMPLOYING COMPLETE CELL OF LACTOBACILLUS SENMAIZUKE AS AN ENVIRONMENTALLY FRIENDLY APPROACH
( Prof. Hysen Mankolli, IJEES Electronic Journal Publication , 2020 , Article)Recently, optimization of the bioreduction reactions by optimization methodologies has gained special interest as these reactions are affected by several extrinsic factors that should be optimized for higher yields. An ... -
Machine Learning Approach to Predict Metro Ridership based on Land Use Densities
( Qatar University Press , 2021 , Poster)Predicting metro ridership is an essential requirement for efficient metro operation and management. The dependence of metro ridership on the land use densities entails a need for an accurate predictive model. To this end, ... -
Machine Learning Based Cloud Computing Anomalies Detection
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ... -
Machine learning based photovoltaics (PV) power prediction using different environmental parameters of Qatar
( MDPI AG , 2019 , Article)Photovoltaics (PV) output power is highly sensitive to many environmental parameters and the power produced by the PV systems is significantly affected by the harsh environments. The annual PV power density of around 2000 ... -
Machine learning driven intelligent and self adaptive system for traffic management in smart cities
( Springer , 2022 , Article)Traffic congestion is becoming a serious problem with the large number of vehicle on the roads. In the traditional traffic control system, the timing of the green light is adjusted regardless of the average traffic rate ... -
Machine learning driven intelligent and self adaptive system for traffic management in smart cities
( Springer Nature , 2022 , Article)Traffic congestion is becoming a serious problem with the large number of vehicle on the roads. In the traditional traffic control system, the timing of the green light is adjusted regardless of the average traffic rate ... -
Machine Learning for Anomaly Detection and Categorization in Multi-Cloud Environments
( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Cloud computing has been widely adopted by application service providers (ASPs) and enterprises to reduce both capital expenditures (CAPEX) and operational expenditures (OPEX). Applications and services previously running ... -
Machine Learning for Capillary Pressure Estimation
( Society of Petroleum Engineers (SPE) , 2022 , Article)Capillary pressure plays an essential role in controlling multiphase flow in porous media and is often difficult to be estimated at subsurface conditions. The Leverett capillary pressure function J provides a convenient ... -
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
( Elsevier B.V. , 2022 , Article Review)In modern Smart Grids (SGs) ruled by advanced computing and networking technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this connection, a portion of transported data, containing ... -
Machine learning for prediction of the uniaxial compressive strength within carbonate rocks
( Springer Science and Business Media Deutschland GmbH , 2023 , Article)The Uniaxial Compressive Strength (UCS) is an essential parameter in various fields (e.g., civil engineering, geotechnical engineering, mechanical engineering, and material sciences). Indeed, the determination of UCS in ... -
Machine learning for the security of healthcare systems based on Internet of Things and edge computing
( Elsevier , 2022 , Book chapter)Using the Internet of Medical Things (IoMT) for treatment and diagnosis has exponentially grown due to its diverse use cases and efficient planning with defined resources. IoMT in the e-healthcare system enables continuous ... -
Machine learning in hydrogen production
( Institution of Chemical Engineers , 2022 , Other)Global demand for clean fuels is growing due to pollution and global warming. Undoubtedly, hydrogen is one of the main options for producing clean energy, which has been receiving special attention for years and global ... -
Machine learning in the Internet of Things: Designed techniques for smart cities
( Elsevier B.V. , 2019 , Article)Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide ... -
Machine Learning Methods for Dysgraphia Screening with Online Handwriting Features
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)Dysgraphia, a major learning disorder that primarily interferes with writing skills can hinder the academic track of children unless recognized in the early stage. The diversity in the symptoms, as well as the emergence ... -
A machine learning model for early detection of diabetic foot using thermogram images
( Elsevier , 2021 , Article)Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the institution of preventative measures through ... -
Machine Learning Prediction of Cancer from The Publicly Available Dataset
(2024 , Master Thesis)Prostate cancer in the second most common cause of cancer in men around the world and in Qatar with a high incidence rate worldwide. This has resulted in an increased mortality rate, making prostate cancer a healthcare ... -
MACHINE LEARNING PREDICTION OF DIABETES FROM A PUBLICLY AVAILABLE DATASET
(2024 , Professional Masters Project)A wide array of medical conditions necessitate invasive diagnostic techniques, with diabetes being one of the most well-known among them. To address this challenge, a predictive model was developed using a publicly available ... -
Machine Learning Screening of COVID-19 Patients Based on X-ray Images for Imbalanced Classes
( IEEE , 2021 , Conference Paper)COVID-19 is a virus that has infected more than one hundred and fifty million people and caused more than three million deaths by 13th of Mai 2021 and is having a catastrophic effect on the world population's safety. ... -
Machine learning screening of COVID-19 patients based on X-ray images for unbalanced classes
( Hamad bin Khalifa University Press (HBKU Press) , 2021 , Article)Background: COVID-19 is a pandemic that had already infected more than forty-six million people and caused more than a million deaths by 1st of November 2020. The virus pandemic appears to have had a catastrophic effect ...
