Yayıncı "Elsevier" Mühendislik ve Doğa Bilimleri Fakültesi için listeleme
Toplam kayıt 18, listelenen: 1-18
-
Chemistry and engineering of brush type polymers: Perspective towards tissue engineering
(Elsevier, 2022)In tissue engineering, it is imperative to control the behaviour of cells/stem cells, such as adhesion, proliferation, propagation, motility, and differentiation for tissue regeneration. Surfaces that allow cells to behave ... -
COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images
(Elsevier, 2020)The Coronavirus Disease 2019 (COVID-19) outbreak has a tremendous impact on global health and the daily life of people still living in more than two hundred countries. The crucial action to gain the force in the fight of ... -
Deep rhythm and long short term memory-based drowsiness detection
(Elsevier, 2021)In this paper, a deep-rhythm-based approach is proposed for the efficient detection of drowsiness based on EEG recordings. In the proposed approach, EEG images are used instead of signals where the time and frequency ... -
The effect of fly ash and pine tree resin on thermo-mechanical properties of concretes with expanded clay aggregates
(Elsevier, 2021)We used expanded clay (EC) and cement, fly ash (FA), and pine tree resin as binders instead of conventional aggregate to produce low-density construction material. The EC ratios were 10 %, 20 %, 30 %, 40 %, and 50 %. The ... -
An efficient fault classification method in solar photovoltaic modules using transfer learning and multi-scale convolutional neural network
(Elsevier, 2022)Photovoltaic (PV) power generation is one of the remarkable energy types to provide clean and sustainable energy. Therefore, rapid fault detection and classification of PV modules can help to increase the reliability of ... -
Experimental characterization and theoretical investigation of Zn/Sm co-doped hydroxyapatites
(Elsevier, 2022)In this study, the wet chemical method was used to synthesize Zn-doped hydroxyapatite (HAp) samples, and the effects of varying the amount of Sm addition on structural, thermal, and biocompatibility in vitro properties ... -
Experimental investigation on the temperature distribution within a cylindrical adiabatic container as time-dependent and conjugate
(Elsevier, 2021)In this study, the time dependent heating of a solid cylindrical body replaced within an isolated cylindrical container and reciprocally the simultaneous heating of the fluid (air/water) inside the container is experimentally ... -
Generic and Shiga toxin-producing Escherichia coli (O157:H7) contamination of lettuce and radish microgreens grown in peat moss and perlite
(Elsevier, 2020)athogens can be transferred to microgreens from seeds, irrigation water and growth media. The purpose of this study was to evaluate the contamination of Shiga toxin-producing Escherichia coli (STEC O157:H7) and generic E. ... -
Investigation of waste EPS foams modified by heat treatment method as concrete aggregate
(Elsevier, 2021)The method for the recycling of expanded polystyrene foam (EPS) in waste state, which causes a significant environmental pollution, is presented in this study. With this method, modified EPS aggregate was produced by heat ... -
MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
(Elsevier, 2022)COVID-19PneumoniaArtificial intelligence (AI)Deep learningComputed tomography (CT) -
A new 3D segmentation approach using extreme learning machine algorithm and morphological operations
(Elsevier, 2020)Segmentation is one of the most crucial steps of image processing. Because 3D images contain depth information, they have gradually gained importance for numerical systems in image analysis. In the present study, a new 3D ... -
NTCDA compounds of optoelectronic interest: Theoretical insights and experimental investigation
(Elsevier, 2021)Structural, electronic, and spectroscopic properties of 1,4,5,8-naphthalene-tetracarboxylic dianhydride organic semiconductor molecule are reported based on experimental and computational methods. The spectroscopic ... -
SEM-Net: Deep features selections with Binary Particle Swarm Optimization Method for classification of scanning electron microscope images
(Elsevier, 2021)Materials Science is increasingly handling artificial intelligence methods to address the complexity in the field of everyday life necessities. Researchers in both academia and industry are interested in imaging techniques ... -
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
(Elsevier, 2021)Photovoltaic (PV) power generation has high uncertainties due to the randomness and imbalance nature of solar energy and meteorological parameters. Hence, accurate PV power forecasts are essential in the operation of PV ... -
Structural, spectroscopic, dielectric, and magnetic properties of Fe/Cu co-doped hydroxyapatites prepared by a wet-chemical method
(Elsevier, 2022)In this study, the effects of Cu and Fe additives on the structural, dielectric, magnetic, thermal and morphology of hydroxyapatite (HAp) samples were investigated and reported in detail for the first time. The prepared ... -
Theoretical and experimental characterization of Pr/Ce co-doped hydroxyapatites
(Elsevier, 2021)This study presents a more extensive report on the experimental and theoretical characterization of the Ce-doped hydroxyapatite (HAp) samples additionally doped with Pr at varying amounts. To achieve this goal, four ... -
When machine learning meets fractional-order chaotic signals: detecting dynamical variations
(Elsevier, 2022)The challenge of classifying multivariate time series generated by discrete and continuous dynamical systems according to their chaotic or non-chaotic behavior has been studied extensively in the literature. The examination ... -
WSFNet: An efficient wind speed forecasting model using channel attention-based densely connected convolutional neural network
(Elsevier, 2021)This paper introduces a novel deep neural network (WSFNet) to efficiently forecast multi-step ahead wind speed. WSFNet forms the basis of the stacked convolutional neural network (CNN) with dense connections of different ...