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Citation - WoS: 9
Citation - Scopus: 12
The Caputo-Fabrizio Time-Fractional Sharma-Tasso Equation and Its Valid Approximations
(Iop Publishing Ltd, 2022) Ilie, Mousa; Mirzazadeh, Mohammad; Baleanu, Dumitru; Park, Choonkil; Salahshour, Soheil; Hosseini, Kamyar
Studying the dynamics of solitons in nonlinear time-fractional partial differential equations has received substantial attention, in the last decades. The main aim of the current investigation is to consider the time-fractional Sharma-Tasso-Olver-Burgers (STOB) equation in the Caputo-Fabrizio (CF) context and obtain its valid approximations through adopting a mixed approach composed of the homotopy analysis method (HAM) and the Laplace transform. The existence and uniqueness of the solution of the time-fractional STOB equation in the CF context are investigated by demonstrating the Lipschitz condition for phi(x, t; u) as the kernel and giving some theorems. To illustrate the CF operator effect on the dynamics of the obtained solitons, several two- and three-dimensional plots are formally considered. It is shown that the mixed approach is capable of producing valid approximations to the time-fractional STOB equation in the CF context.
Citation - Scopus: 6
COVID-19 Classification Using Hybrid Deep Learning and Standard Feature Extraction Techniques
(Institute of Advanced Engineering and Science, 2023) El Shenbary, H. A.; Ebeid, Ebeid Ali; Baleanu, Dumitru I.
There is no doubt that COVID-19 disease rapidly spread all over the world, and effected the daily lives of all of the people. Nowadays, the reverse transcription polymerase chain reaction is the most way used to detect COVID-19 infection. Due to time consumed in this method and material limitation in the hospitals, there is a need for developing a robust decision support system depending on artificial intelligence (AI) techniques to recognize the infection at an early stage from a medical images. The main contribution in this research is to develop a robust hybrid feature extraction method for recognizing the COVID-19 infection. Firstly, we train the Alexnet on the images database and extract the first feature matrix. Then we used discrete wavelet transform (DWT) and principal component analysis (PCA) to extract the second feature matrix from the same images. After that, the desired feature matrices were merged. Finally, support vector machine (SVM) was used to classify the images. Training, validating, and testing of the proposed method were performed. Experimental results gave (97.6%, 98.5%) average accuracy rate on both chest X-ray and computed tomography (CT) images databases. The proposed hybrid method outperform a lot of standard methods and deep learning neural networks like Alexnet, Googlenet and other related methods. © 2022 Elsevier B.V., All rights reserved.
Citation - WoS: 10
Citation - Scopus: 11
Is There Convergence in Renewable Energy Deployment? Evidence From a New Panel Unit Root Test With Smooth and Sharp Structural Breaks
(Pergamon-elsevier Science Ltd, 2023) Omay, Tolga; Corakci, Aysegul
This study examines whether the contribution of renewable energy to the total primary energy supply converges in a panel of 24 OECD countries over the period 1960-2020. To this end, a new panel unit root test that allows for both sharp and smooth breaks is proposed to test for the stochastic convergence hypothesis. Although renewable energy convergence is not rejected when the newly proposed test is applied to the full panel of OECD countries, it found only moderate support within the members of the panel using a sequential panel selection methodology. In fact, in two high-income OECD countries, the contribution of renewable energy to the primary energy supply shows no sign of convergence: Poland and Iceland. Therefore, the renewable energy shares seem to be converging to a common steady state in only a group of OECD countries over the long run. This uneven pattern of convergence, in turn, suggests that the OECD countries are still far away from developing a common sustainable renewable energy target, calling for urgent international policy cooperation to encourage the divergent econo-mies to seek out the menu of policies that ensure the worldwide success of renewable energy transformation.
Açılı Cfrp Ankrajlı Şeritler ile Beton Yüzey Arasındaki Gerilme Deformasyon Davranışı için Yeni Bir Model Önerisi
(2020) Özgür, A. C. Anıl; Ghoroubi, Rahim; Mercimek, Ömer
Betonarme, çelik veya yığma yapılar birçok farklı nedenden dolayı güçlendirilmeleri veya onarılmaları gerekmektedir. Karbon takviyeli elyaf kumaşlar (CFRP) deprem performansı yetersiz yapıların onarım ve güçlendirme çalışmalarında son 20 yıldır yaygın olarak kullanılmaktadır. CFRP ile geliştirilen onarım ve güçlendirme detaylarında önemli olan tasarım kriterlerinden biri CFRP elemanların yüzeyden soyulmalarını geciktirmektir. Bu amaçla CFRP ile geliştirilen güçlendirme detaylarında ankrajların kullanılması artış göstermiştir. Güçlendirme detaylarında kullanılan fan tipi CFRP ankrajlı CFRP şeritler ile ilgili gerilme-kayma deplasmanı modellerinin ankrajsız CFRP şeritlere göre çok daha sınırlı sayıda olduğu görülmektedir. Bu konudaki sınırlı sayıdaki çalışmada ankrajlar CFRP şeritlere uygulanan eksenel çekme kuvvetine göre 90o açılı olacak şekilde yerleştirilmiştir. Yapılan literatür taramasında eksenel yüke göre değişik açılarda yerleştirilen ankrajlı CFRP şeritlerin eksenel kuvvet taşıma gücü ve gerilme kayma deplasmanı modelleri ile ilgili bir çalışmaya rastlanmamıştır. Bu nedenle deneysel bir çalışma düzenlenmiş ve 28 adet beton yüzeyine yapıştırılan açılı ankrajlı CFRP şerit deney elemanı eksenel çekme kuvveti etkisinde yazarlar tarafından tasarlanan bir deney düzeneği kullanılarak test edilmiştir. Deneysel çalışmada incelenen değişkenler CFRP şerit genişliği ve CFRP şeritler üzerindeki CFRP fan tipi ankrajların açılarıdır. Deneysel çalışma sonucunda açılı ankrajlı CFRP şeritlerin maksimum taşıma gücü değerlerinin hesaplanması için bir denklem ve yeni bir gerilme kayma deplasmanı modeli önerilmiştir.
Trajectory generation for open/close gap maneuvers in vehicle strings
(Çankaya Üniversitesi, 2017) Çankaya, Erkam
Cooperative adaptive cruise control (CACC) is an advanced technology allowing vehicle following at a small inter-vehicle spacing. In its classical usage, CACC assumes that vehicles are arranged in the form of a vehicle string and follow each other at a velocity-dependent distance. Nonetheless, practical driving situations include the case of lane changes, where vehicles can join or leave a vehicle string. In such case, it is required that gaps for joining vehicles are provided or gaps after leaving vehicles are closed in order to ensure safe and efficient driving. This thesis is concerned with gap opening and closing maneuvers in vehicle strings. Introducing a suitable control architecture, gap opening and closing maneuvers can be realized by the generation of feedforward input signals. To this end, the first contribution of the thesis is the development of five methods for the computation and representation of gap opening and closing trajectories that fulfill additional safety and comfort constraints. The first method is based on the solution of an optimal control problem, the second method uses a polynomial trajectory and plant inversion, the third method concatenates three polynomials and uses nonlinear programming to determine the polynomial coefficients, the fourth method uses a high-order polynomial and the fifth method uses concatenated polynomials in order to approximate the optimal control solution. A simulation study shows that the fifth method is particularly useful in practical applications since it computes trajectories that approximate the optimal control solution in real-time. The second contribution of the thesis is the implementation of a vehicle model that realizes CACC and additional feedforward signals in the form of a Matlab S-function.