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Now showing items 1632-1651 of 2257
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
(2017-05)The High Efficiency Video Coding (HEVC) standard presents a substantial video compression efficiency improvement at the expense of increasing the computational complexity. This enhancement is primarily due to the introduction ... -
Predicting COVID-19 in the UAE Using Machine Learning
(2022-08)As of 17th August 2022, the United Arab Emirates (UAE) have recorded over 1 million Covid-19 cases since the start of the pandemic with over 2000 deaths and the numbers are still increasing. To combat Covid-19, UAE has ... -
Predicting gasoline prices using Michigan survey data
(2015-07)This study investigates the predictive power of Michigan Surveys of Consumers (MSC) data for gasoline prices. Specifically, we utilize the MSC data on both expected inflation and consumer sentiment to construct a vector ... -
Predicting Hypoglycemia in Diabetic Patients using Machine Learning Techniques
(2014-06)Diabetes is a chronic disease that needs continuous blood glucose monitoring and self-management. The improper control of blood glucose levels in diabetic patients can lead to serious complications such as kidney and heart ... -
Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding
(Springer, 2020)This paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding ... -
Predicting split decisions of coding units in HEVC video compression using machine learning techniques
(Springer, 2018)In this work, we propose to reduce the complexity of HEVC video encoding by predicting the split decisions of coding units. We use a sequencedependent approach in which a number of frames belonging to the video being encoded ... -
Predicting Stock Prices in Dubai Financial Market Using Neural Networks and the Polynomial Classifiers
(2007-05)Predicting stock prices has always been the aim of investors in stock markets around the globe and has been considered as one of the most challenging applications of modern Time Series Forecasting. Accordingly, there were ... -
Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
(2009-09)Artificial Neural Networks (ANN) have recently been used in modeling the mechanical behavior of fiberreinforced composite materials. ANN have also been successfully used in predicting the fatigue behavior of a certain ... -
Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
(2022-04)Energy security, environmental pollution, and global warming have become major concerns due to significant population and economic growth. The transition from fossil fuels, which can be used to generate power constantly, ... -
Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound
(IEEE Explore, 2015)In this paper, the estimation of acoustic drug release from micelles is addressed. The release is measured as a decrease in fluorescence once ultrasound is applied. Initially, a Kalman filter is used to fuse the drug ... -
Prediction of Backwater Level of Bridge Constriction using ANN
(2012-12)Bridge constriction in channels usually causes afflux which results in increase in backwater level well above the normal level and may possibly result in overflow on the flood plain surrounding the channel during flooding ... -
Prediction of EV Charging Behavior Using Machine Learning
(IEEE Access, 2021)As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are becoming increasingly popular for their contribution in reducing greenhouse gas emissions. One of the key challenges, however, ... -
Prediction of minimum factor of safety against slope failure in clayey soils using artificial neural network
(2015)This paper presents prediction of minimum factor of safety (FS) against slope failure in clayey soils using artificial neural network (ANN). Two multilayer perceptron ANN models were used to predict the minimum factor of ... -
Prediction of Stability Limits for Binary and Ternary Systems Using the NTRL Liquid Phase Model
(2013-01)Stability limits (spinodal loci) were determined for 53 binary systems and 26 ternary systems. Rigorous thermodynamic criteria for spinodal limits and criticality conditions in terms of mixture Gibbs free energy were derived ... -
Prediction of the Backwater Level Due to Bridge Constriction in Waterways
(2019-05)Worldwide, bridges and culverts built across rivers are obstacles to the flow which cause an increase in water depth at the upstream of the structure that significantly intensifies flooding of land and property upstream. ... -
Prediction of Turbulence Statistics in a Model Dump Combustor Using Artificial Neural Networks
(2011-05)The flowfield characteristics downstream of an axisymmetric suddenexpansion dump combustor model are important to designers of gas turbines and liquid-fuel ramjets ducted rockets. Many experimental techniques such as Laser ... -
Preliminary Modeling of Transfer RNA Kinetics in the Cytoplasm of Escherichia coli Bacteria
(American Scientific Publishers, 2010)Transfer RNAs (tRNAs) can recognize a specific amino acid from a possible pool of 20. Theyare able to transport these protein building-blocks to the ribosome, the site where amino acids assemble into protein chains. Accurate ... -
Preliminary Results of Combining Low Frequency Low Intensity Ultrasound and Liposomal Drug Delivery to Treat Tumors in Rats
(American Scientific Publishers, 2011)Ultrasound is a convenient trigger for site-specific drug delivery in cancer therapy. Nanosized liposomes formulated from soy phosphatidyl choline, cholesterol, 1,2-distearoyl-sn-glycero- 3-phosphoethanolamine-N-[carboxy ... -
Preparation and characterization of gatifloxacin-loaded sodium alginate hydrogel membranes supplemented with hydroxypropyl methylcellulose and hydroxypropyl cellulose polymers for wound dressing
(PKP, 2016)Introduction: The aim of this study is to evaluate gatifloxacin-loaded sodium alginate hydrogel membranes, supplemented with glycerol (a plasticizer), glutaraldehyde (a cross-linking agent), and hydroxypropyl methylcellulose ...