PubMed İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8650

Browse

Now showing 1 - 20 of 113

Citation - WoS: 97
Citation - Scopus: 116
Anaerobic Digestion of Dairy Manure With Enhanced Ammonia Removal
(Academic Press Ltd- Elsevier Science Ltd, 2008) Uludag-Demirer, S.; Demirer, G. N.; Frear, C.; Chen, S.
Poor ammonia-nitrogen removal in methanogenic anaerobic reactors digesting animal manure has been reported as an important disadvantage of anaerobic digestion (AD) in several studies. Development of anaerobic processes that are capable of producing reduced ammonia-nitrogen levels in their effluent is one of the areas where further research must be pursued if AD technology is to be made more effective and economically advantageous. One approach to removing ammonia from anaerobically digested effluents is the forced precipitation of magnesium ammonium phosphate hexahydrate (MgNH4PO4-6H(2)O), commonly called struvite. Struvite is a valuable plant nutrient source for nitrogen and phosphorus since it releases them slowly and has non-burning features because of its low solubility in water. This study investigated coupling AD and controlled struvite precipitation in the same reactor to minimize the nitrogen removal costs and possibly increase the performance of the AD by reducing the ammonia concentration which has an adverse effect oil anaerobic bacteria. The results indicated that Lip to 19% extra COD and almost 11% extra NH3 removals were achieved relative to a control by adding 1750 mg/L of MgCl2-6H(2)O to the anaerobic reactor. (C) 2007 Elsevier Ltd. All rights reserved.
Citation - WoS: 68
Citation - Scopus: 89
Analysis of Fractional Model of Guava for Biological Pest Control With Memory Effect
(Elsevier, 2021) Ganbari, Behzad; Kumar, Devendra; Baleanu, Dumitru; Singh, Jagdev
Introduction: Fractional operators find their applications in several scientific and engineering processes. We consider a fractional guava fruit model involving a non-local additionally non-singular fractional derivative for the interaction into guava pests and natural enemies. The fractional guava fruit model is considered as a Lotka-Volterra nature. Objectives: The main objective of this work is to study a guava fruit model associated with a non-local additionally non-singular fractional derivative for the interaction into guava pests and natural enemies. Methods: Existence and uniqueness analysis of the solution is evaluated effectively by using Picard Lindelof approach. An approximate numerical solution of the fractional guava fruit problem is obtained via a numerical scheme. Results: The positivity analysis and equilibrium analysis for the fractional guava fruit model is discussed. The numerical results are demonstrated to prove our theoretical results. The graphical behavior of solution of the fractional guava problem at the distinct fractional order values and at various parameters is discussed. Conclusion: The graphical behavior of solution of the fractional guava problem at the distinct fractional order values and at various parameters shows new vista and interesting phenomena of the model. The results are indicating that the fractional approach with non-singular kernel plays an important role in the study of different scientific problems. The suggested numerical scheme is very efficient for solving nonlinear fractional models of physical importance. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University.
Citation - WoS: 19
Citation - Scopus: 21
Antecedents of Problematic Social Media Use and Cyberbullying Among Adolescents: Attachment, the Dark Triad and Rejection Sensitivity
(Springer, 2023) Demircioglu, Zeynep Isil; Goncu-Kose, Asli
With the acceleration of internet use, problematic social media use (PSMU) is included in our lives. When looking at the antecedents of PSMU, being young has been found to be a risk factor for PSMU. In addition to the benefits of technological advances in education and training, rapid technological developments may also result in problematic behaviors, especially among children and young. Recently, possibilities brought by technology and more widespread use of technology by young people have created a new concept, namely, cyberbullying. The present study aims to examine the effects of attachment anxiety and avoidance on PSMU and cyberbullying as with the partial mediating effects of the Dark Triad personality traits, angry rejection sensitivity, and anxious rejection sensitivity among adolescents. In general, the findings supported the proposed theoretical model. The results are discussed in terms of theoretical and practical implications along with suggestions for future research.
Citation - WoS: 71
Citation - Scopus: 80
An Application of Derivative and Continuous Wavelet Transforms To the Overlapping Ratio Spectra for the Quantitative Multiresolution of a Ternary Mixture of Paracetamol, Acetylsalicylic Acid and Caffeine in Tablets
(Elsevier Science Bv, 2005) Özdemir, A; Baleanu, D; Dinç, E
Quantitative multi resolution of tablets and ternary mixtures of paracetamol (PAR), acetylsalicylic acid (ASP) and caffeine (CAF) having strongly overlapping spectra was accomplished by two graphical transform methods as ratio spectra first derivative-zero crossing and ratio spectra-continuous wavelet transform-zero crossing (ratio spectra CWT-zero crossing) methods. In this study, ratio spectra derivative-zero crossing and ratio spectra CWT-zero crossing methods are based on the use of transformed signals of the ratio spectra and their calibration graphs were obtained by measuring the dA/dlambda and CWT amplitudes of the ratio spectra corresponding to zero crossing points. For the comparison purpose. PLS calibration method was applied to predict the content of the same mixtures containing the subject active Compounds. The obtained calibrations were tested by using the synthetic mixtures and standard addition technique and they applied to the simultaneous determination of PAR, ASP and CAF in commercial pharmaceutical preparation. The obtained results were statistically compared with each other as well as those obtained by HPLC method and they showed good agreement. (C) 2004 Published by Elsevier B.V.
Citation - WoS: 26
Citation - Scopus: 31
Asymptotic Solutions of Fractional Interval Differential Equations With Nonsingular Kernel Derivative
(Amer inst Physics, 2019) Ahmadian, A.; Salimi, M.; Ferrara, M.; Baleanu, D.; Salahshour, S.
Realizing the behavior of the solution in the asymptotic situations is essential for repetitive applications in the control theory and modeling of the real-world systems. This study discusses a robust and definitive attitude to find the interval approximate asymptotic solutions of fractional differential equations (FDEs) with the Atangana-Baleanu (A-B) derivative. In fact, such critical tasks require to observe precisely the behavior of the noninterval case at first. In this regard, we initially shed light on the noninterval cases and analyze the behavior of the approximate asymptotic solutions, and then, we introduce the A-B derivative for FDEs under interval arithmetic and develop a new and reliable approximation approach for fractional interval differential equations with the interval A-B derivative to get the interval approximate asymptotic solutions. We exploit Laplace transforms to get the asymptotic approximate solution based on the interval asymptotic A-B fractional derivatives under interval arithmetic. The techniques developed here provide essential tools for finding interval approximation asymptotic solutions under interval fractional derivatives with nonsingular Mittag-Leffler kernels. Two cases arising in the real-world systems are modeled under interval notion and given to interpret the behavior of the interval approximate asymptotic solutions under different conditions as well as to validate this new approach. This study highlights the importance of the asymptotic solutions for FDEs regardless of interval or noninterval parameters. Published under license by AIP Publishing.
Citation - WoS: 32
Citation - Scopus: 36
Attentional Control Is Partially Impaired in Obstructive Sleep Apnea Syndrome
(Wiley, 2013) Atalay, Nart Bedin; Kanat, Fikret; Suerdem, Mecit; Tulek, Baykal
Obstructive sleep apnea syndrome is associated with executive cognitive impairment. An important question is whether impairment in executive functioning in obstructive sleep apnea syndrome is independent of dysfunction in attention. Attentional control is a subcomponent of executive functioning that is mediated by frontal lobe processing. In the current study, we investigated whether attentional control is deficient in obstructive sleep apnea syndrome. Attentional control processes were investigated through conflict adaptation and conflict frequency paradigms. These neuropsychological paradigms were assessed by using the Simon, Flanker and Stroop tasks. We additionally analysed post-error slowing data within these tasks. Error processing is another index of cognitive control that is mediated by frontal lobe functioning. Our sample consisted of 14 healthy adults and 24 patients with untreated moderate-severe obstructive sleep apnea syndrome. Results indicated that attentional control is partially dysfunctional among patients with obstructive sleep apnea syndrome. Attentional control processes were deficient when focal attention (Flanker task) processes were involved, but were intact when observed using the Simon and Stroop tasks. A non-significant trend in post-error slowing data suggested that error processing, assessed with the Flanker task, was diminished among patients with obstructive sleep apnea syndrome. These results support the view that obstructive sleep apnea syndrome leads to some amount of frontal lobe dysfunction, and that attentional control and error processing might be particularly affected by obstructive sleep apnea syndrome.
Citation - WoS: 40
Citation - Scopus: 52
Automated Classification of Rheumatoid Arthritis, Osteoarthritis, and Normal Hand Radiographs With Deep Learning Methods
(Springer, 2022) Maras, Hadi Hakan; Ureten, Kemal
Rheumatoid arthritis and hand osteoarthritis are two different arthritis that causes pain, function limitation, and permanent joint damage in the hands. Plain hand radiographs are the most commonly used imaging methods for the diagnosis, differential diagnosis, and monitoring of rheumatoid arthritis and osteoarthritis. In this retrospective study, the You Only Look Once (YOLO) algorithm was used to obtain hand images from original radiographs without data loss, and classification was made by applying transfer learning with a pre-trained VGG-16 network. The data augmentation method was applied during training. The results of the study were evaluated with performance metrics such as accuracy, sensitivity, specificity, and precision calculated from the confusion matrix, and AUC (area under the ROC curve) calculated from ROC (receiver operating characteristic) curve. In the classification of rheumatoid arthritis and normal hand radiographs, 90.7%, 92.6%, 88.7%, 89.3%, and 0.97 accuracy, sensitivity, specificity, precision, and AUC results, respectively, and in the classification of osteoarthritis and normal hand radiographs, 90.8%, 91.4%, 90.2%, 91.4%, and 0.96 accuracy, sensitivity, specificity, precision, and AUC results were obtained, respectively. In the classification of rheumatoid arthritis, osteoarthritis, and normal hand radiographs, an 80.6% accuracy result was obtained. In this study, to develop an end-to-end computerized method, the YOLOv4 algorithm was used for object detection, and a pre-trained VGG-16 network was used for the classification of hand radiographs. This computer-aided diagnosis method can assist clinicians in interpreting hand radiographs, especially in rheumatoid arthritis and osteoarthritis.
Citation - WoS: 19
Citation - Scopus: 19
Bipolar Intuitionistic Fuzzy Graph Based Decision-Making Model To Identify Flood Vulnerable Region
(Springer Heidelberg, 2023) Augustin, Felix; Narayanamoorthy, Samayan; Ahmadian, Ali; Balaenu, Dumitru; Kang, Daekook; Nithyanandham, Deva
Bipolar intuitionistic fuzzy graphs (BIFG) are an extension of fuzzy graphs that can effectively capture uncertain or imprecise information in various applications. In graph theory, the covering, matching, and domination problems are benchmark concepts applied to various domains. These concepts may not be defined precisely using a crisp graph when the vertices and edges are more uncertain. Therefore, this study defines the covering, matching and domination concepts in bipolar intuitionistic fuzzy graphs (BIFG) using effective edges with certain important results. To define these concepts when the effective edges are absent, some novel approaches are discussed. To illustrate the domination concepts, the applications in disaster management and location selection problems are discussed. Further, a BIFG-based decision-making model is designed to identify the flood-vulnerable zones in Chennai, where the city's most and least vulnerable zones are identified. From the proposed model, Kodambakkam (Z(10)) is the most susceptible zone in Chennai. Finally, a comparative analysis is done with the existing techniques to show the efficiency of the model.
Citation - WoS: 26
Citation - Scopus: 31
Boger Nanofluid: Significance of Coriolis and Lorentz Forces on Dynamics of Rotating Fluid Subject To Suction/Injection Via Finite Element Simulation
(Nature Portfolio, 2022) Siddique, Imran; Hussain, Sajjad; Ali, Liaqat; Baleanu, Dumitru; Ali, Bagh
This study briefings the roles of Coriolis, and Lorentz forces on the dynamics of rotating nanofluids flow toward a continuously stretching sheet. The nanoparticles are incorporated because of their unusual qualities like upgrade the thermal transportation, which are very important in heat exchangers, modern nanotechnology, electronics, and material sciences. The primary goal of this study is to improve heat transportation. Appropriate similarity transformations are applied for the principal PDEs to transform into nonlinear dimensionless PDEs. A widely recognized Numerical scheme known as the Finite Element Method is employed to solve the resultant convective boundary layer balances. Higher input in the solvent fraction parameter has a rising effect on the primary velocity and secondary velocity magnitude, and decreasing impact on the distributions of temperature. It is seen that growing contributions of the Coriolis, and Lorentz forces cause to moderate the primary and secondary velocities, but the temperature and concentration functions show opposite trend. The concentration, temperature, and velocities distributions for suction case is prominently than that of injection case, but inverse trend is observed for local Nusselt and Sherwood numbers. These examinations are relevant to the field of plastic films, crystal growing, paper production, heat exchanger, and bio-medicine.
Citation - WoS: 30
Citation - Scopus: 42
Caputo Sir Model for Covid-19 Under Optimized Fractional Order
(Springer, 2021) Ullah, Malik Z.; Baleanu, Dumitru; Alshomrani, Ali S.
Everyone is talking about coronavirus from the last couple of months due to its exponential spread throughout the globe. Lives have become paralyzed, and as many as 180 countries have been so far affected with 928,287 (14 September 2020) deaths within a couple of months. Ironically, 29,185,779 are still active cases. Having seen such a drastic situation, a relatively simple epidemiological SIR model with Caputo derivative is suggested unlike more sophisticated models being proposed nowadays in the current literature. The major aim of the present research study is to look for possibilities and extents to which the SIR model fits the real data for the cases chosen from 1 April to 15 March 2020, Pakistan. To further analyze qualitative behavior of the Caputo SIR model, uniqueness conditions under the Banach contraction principle are discussed and stability analysis with basic reproduction number is investigated using Ulam-Hyers and its generalized version. The best parameters have been obtained via the nonlinear least-squares curve fitting technique. The infectious compartment of the Caputo SIR model fits the real data better than the classical version of the SIR model (Brauer et al. in Mathematical Models in Epidemiology 2019). Average absolute relative error under the Caputo operator is about 48% smaller than the one obtained in the classical case (nu=1). Time series and 3D contour plots offer social distancing to be the most effective measure to control the epidemic.
Citation - WoS: 111
Citation - Scopus: 128
A Comparative Review of Environmental Concern Prioritization: Leed Vs Other Major Certification Systems
(Academic Press Ltd- Elsevier Science Ltd, 2015) Suzer, Ozge
The matter of environmental concern prioritization integrated into globally used green building rating systems is a fundamental issue since it determines how the performance of a structure or development is reflected. Certain nationally-developed certification systems are used globally without being subjected to adjustments with respect to local geographical, cultural, economic and social parameters. This may lead to a situation where the results of an evaluation may not reflect the reality of the region and/or the site of construction. The main objective of this paper is to examine and underline the problems regarding the issue of weighting environmental concerns in the Leadership in Energy and Environmental Design (LEED) certification system, which is a US-originated but globally used assessment tool. The methodology of this study consists of; (i) an analysis of the approach of LEED in the New Construction and Major Renovations scheme in version 3 (LEED NC, v.3) and the Building Design and Construction scheme in version 4 (LEED BD + C, v.4), (ii) case studies in which regional priority credits (RPCs) set by LEED for four countries (Canada, Turkey, China and Egypt) are criticized with respect to countries' own local conditions, and, (iii) an analysis of the approaches of major environmental assessment tools, namely; BREEAM, SBTool, CASBEE and Green Star, in comparison to the approach in LEED, regarding the main issue of this paper. This work shows that, even in its latest version (v.4) LEED still displays some inadequacies and inconsistencies from the aspect of environmental concern prioritization and has not yet managed to incorporate a system which is more sensitive to this issue. This paper further outlines the differences and similarities between the approaches of the aforementioned major environmental assessment tools with respect to the issue of concern and the factors that should be integrated into future versions of LEED. (C) 2015 Elsevier Ltd. All rights reserved.
Citation - WoS: 24
Citation - Scopus: 26
Comparative Spectral Analysis of Veterinary Powder Product by Continuous Wavelet and Derivative Transforms
(Pergamon-elsevier Science Ltd, 2007) Kanbur, Murat; Baleanu, Dumitru; Dinc, Erdal
Comparative simultaneous determination of chlortetracycline and benzocaine in the commercial veterinary powder product was carried out by continuous wavelet transform (CWT) and classical derivative transform (or classical derivative spectrophotometry). In this quantitative spectral analysis, two proposed analytical methods do not require any chemical separation process. In the first step, several wavelet families were tested to find an optimal CWT for the overlapping signal processing of the analyzed compounds. Subsequently, we observed that the coiflets (COIF-CWT) method with dilation parameter, a = 400, gives suitable results for this analytical application. For a comparison, the classical derivative spectrophotometry (CDS) approach was also applied to the simultaneous quantitative resolution of the same analytical problem. Calibration functions were obtained by measuring the transform amplitudes corresponding to zero-crossing points for both CWT and CDS methods. The utility of these two analytical approaches were verified by analyzing various synthetic mixtures consisting of chlortetracycline and benzocaine and they were applied to the real samples consisting of veterinary powder formulation. The experimental results obtained from the COIF-CWT approach were statistically compared with those obtained by classical derivative spectrophotometry and successful results were reported. (C) 2006 Elsevier B.V. All rights reserved.
Citation - WoS: 62
Citation - Scopus: 59
Comparative Study of Artificial Neural Network Versus Parametric Method in Covid-19 Data Analysis
(Elsevier, 2022) Colak, Andac Batur; Sindhu, Tabassum Naz; Lone, Showkat Ahmad; Alsubie, Abdelaziz; Jarad, Fahd; Shafiq, Anum
Since the previous two years, a new coronavirus (COVID-19) has found a major global problem. The speedy pathogen over the globe was followed by a shockingly large number of afflicted people and a gradual increase in the number of deaths. If the survival analysis of active individuals can be predicted, it will help to contain the epidemic significantly in any area. In medical diagnosis, prognosis and survival analysis, neural networks have been found to be as successful as general nonlinear models. In this study, a real application has been developed for estimating the COVID-19 mortality rates in Italy by using two different methods, artificial neural network modeling and maximum likelihood estimation. The predictions obtained from the multilayer artificial neural network model developed with 9 neurons in the hidden layer were compared with the numerical results. The maximum deviation calculated for the artificial neural network model was -0.14% and the R value was 0.99836. The study findings confirmed that the two different statistical models that were developed had high reliability.
Citation - WoS: 15
Citation - Scopus: 15
Construct and Face Validity of the Educational Computer-Based Environment (Ece) Assessment Scenarios for Basic Endoneurosurgery Skills
(Springer, 2017) Ozcelik, Erol; Sengul, Gokhan; Berker, Mustafa; Cagiltay, Nergiz Ercil
Background In neurosurgery education, there is a paradigm shift from time-based training to criterion-based model for which competency and assessment becomes very critical. Even virtual reality simulators provide alternatives to improve education and assessment in neurosurgery programs and allow for several objective assessment measures, there are not many tools for assessing the overall performance of trainees. This study aims to develop and validate a tool for assessing the overall performance of participants in a simulation-based endoneurosurgery training environment. Methods A training program was developed in two levels: endoscopy practice and beginning surgical practice based on four scenarios. Then, three experiments were conducted with three corresponding groups of participants (Experiment 1, 45 (32 beginners, 13 experienced), Experiment 2, 53 (40 beginners, 13 experienced), and Experiment 3, 26 (14 novices, 12 intermediate) participants). The results analyzed to understand the common factors among the performance measurements of these experiments. Then, a factor capable of assessing the overall skill levels of surgical residents was extracted. Afterwards, the proposed measure was tested to estimate the experience levels of the participants. Finally, the level of realism of these educational scenarios was assessed. Results The factor formed by time, distance, and accuracy on simulated tasks provided an overall performance indicator. The prediction correctness was very high for the beginners than the one for experienced surgeons in Experiments 1 and 2. When non-dominant hand is used in a surgical procedure-based scenario, skill levels of surgeons can be better predicted. The results indicate that the scenarios in Experiments 1 and 2 can be used as an assessment tool for the beginners, and scenario-2 in Experiment 3 can be used as an assessment tool for intermediate and novice levels. It can be concluded that forming the balance between perceived action capacities and skills is critical for better designing and developing skill assessment surgical simulation tools.
Citation - WoS: 3
Citation - Scopus: 4
Convolutional Neural Network-Based Deep Learning for Landslide Susceptibility Mapping in the Bakhtegan Watershed
(Nature Portfolio, 2025) Feng, Li; Zhang, Maosheng; Mao, Yimin; Liu, Hao; Yang, Chuanbo; Dong, Ying; Nanehkaran, Yaser A.
Landslides pose a significant threat to infrastructure, ecosystems, and human safety, necessitating accurate and efficient susceptibility assessment methods. Traditional models often struggle to capture the complex spatial dependencies and interactions between geological and environmental factors. To address this gap, this study employs a deep learning approach, utilizing a convolutional neural network (CNN) for high-precision landslide susceptibility mapping in the Bakhtegan watershed, southwestern Iran. A comprehensive landslide inventory was compiled using 235 documented landslide locations, validated through remote sensing and field surveys. An equal number of non-landslide locations were systematically selected to ensure balanced model training. Fifteen key conditioning factors-including topographical, geological, hydrological, and climatological variables-were incorporated into the model. While traditional statistical methods often fail to extract spatial hierarchies, the CNN model effectively processes multi-dimensional geospatial data, learning intricate patterns influencing slope instability. The CNN model outperformed other classification approaches, achieving an accuracy of 95.76% and a precision of 95.11%. Additionally, error metrics confirmed its reliability, with a mean absolute error (MAE) of 0.11864, mean squared error (MSE) of 0.18796, and root mean squared error (RMSE) of 0.18632. The results indicate that the northern and northeastern regions of the Bakhtegan watershed are highly susceptible to landslides, highlighting areas where proactive mitigation strategies are crucial. This study demonstrates that deep learning, particularly CNNs, offers a powerful and scalable solution for landslide susceptibility assessment. The findings provide valuable insights for urban planners, engineers, and policymakers to implement effective risk reduction strategies and enhance resilience in landslide-prone regions.
Citation - WoS: 10
Citation - Scopus: 9
Cosine and Cotangent Similarity Measures for Intuitionistic Fuzzy Hypersoft Sets With Application in Madm Problem
(Cell Press, 2024) Saeed, Muhammad; Saeed, Ayesha; Ijaz, Aleen; Ashraf, Mobeen; Jarad, Fahd; Jafar, Muhammad Naveed
Intuitionistic fuzzy hypersoft sets (IFHSSs) are a novel model that is projected to address the limitations of Intuitionistic fuzzy soft sets (IFSSs) regarding the entitlement of a multi-argument domain for the approximation of parameters under consideration. It is more flexible and reliable as it considers the further classification of parameters into their relevant parametric valued sets. In this paper, we proposed some trigonometric (cosine and cotangent) similarity measures and their weighted trigonometric similarity measures (SMs). Trigonometric Similarity measures (SMs) for intuitionistic fuzzy hypersoft sets (IFHSSs) are significantly implied to check the similarity measures and help to determine the similarity between different factors. Also, in order to evaluate the validity of the significant study and apply the results to a daily life problem. We use them to solve problems involving the selection of renewable energy sources. According to several technical contributing factors, the analysis identifies the ideal location for the implementation of the energy production units. Future case studies with many features and additional bifurcation along with multiple decision-makers can use the suggested methodologies. Also, several existing structures, such as fuzzy, Pythagorean fuzzy, Neutrosophic theories, etc., can be utilized with the suggested method.
Citation - WoS: 8
Citation - Scopus: 9
Damping Constant (Linewidth) and the Relaxation Time of the Brillouin La Mode for the Ferroelectric-Paraelectric Transition in Pbzr1-Xtixo3
(Ieee-inst Electrical Electronics Engineers inc, 2016) Kiraci, Ali; Yurtseven, Hamit
The damping constant (linewidth) of the longitudinal acoustic (LA) mode is calculated as a function of temperature using the observed Brillouin frequencies of this mode from the literature for the ferroelectric-paraelectric transition (T-C = 657 K) in PbZr1-xTixO3 (x = 0.45). For this calculation of the damping constant, the pseudospin-phonon coupled model and the energy fluctuation model are used by fitting to the observed data for the Brillouin frequencies of the LA mode in the ferroelectric (T < T-C) and paraelectric (T > T-C) phases of this compound (x = 0.45). Values of the activation energy are deduced for both ferroelectric and paraelectric phases. The relaxation time is also obtained by means of fitting to the observed data from the literature for the inverse relaxation time at various temperatures in the paraelectric phase of PbZr1-xTixO3. The temperature dependences of the damping constant and of the relaxation time with the values of the activation energy that we have calculated indicate that the pseudospin-phonon coupled model and the energy fluctuation model are capable of describing the ferroelectric-paraelectric transition (T-C = 657 K) in PbZr1-xTixO3 (x = 0.45) adequately.
Citation - WoS: 46
Citation - Scopus: 51
A Delayed Plant Disease Model With Caputo Fractional Derivatives
(Springer, 2022) Baleanu, Dumitru; Erturk, Vedat Suat; Inc, Mustafa; Govindaraj, V; Kumar, Pushpendra
We analyze a time-delay Caputo-type fractional mathematical model containing the infection rate of Beddington-DeAngelis functional response to study the structure of a vector-borne plant epidemic. We prove the unique global solution existence for the given delay mathematical model by using fixed point results. We use the Adams-Bashforth-Moulton P-C algorithm for solving the given dynamical model. We give a number of graphical interpretations of the proposed solution. A number of novel results are demonstrated from the given practical and theoretical observations. By using 3-D plots we observe the variations in the flatness of our plots when the fractional order varies. The role of time delay on the proposed plant disease dynamics and the effects of infection rate in the population of susceptible and infectious classes are investigated. The main motivation of this research study is examining the dynamics of the vector-borne epidemic in the sense of fractional derivatives under memory effects. This study is an example of how the fractional derivatives are useful in plant epidemiology. The application of Caputo derivative with equal dimensionality includes the memory in the model, which is the main novelty of this study.
Citation - WoS: 33
Citation - Scopus: 38
Design of a Fractional-Order Atmospheric Model Via a Class of Act-Like Chaotic System and Its Sliding Mode Chaos Control
(Aip Publishing, 2023) Baishya, Chandrali; Veeresha, Pundikala; Baleanu, Dumitru; Naik, Manisha Krishna
Investigation of the dynamical behavior related to environmental phenomena has received much attention across a variety of scientific domains. One such phenomenon is global warming. The main causes of global warming, which has detrimental effects on our ecosystem, are mainly excess greenhouse gases and temperature. Looking at the significance of this climatic event, in this study, we have connected the ACT-like model to three climatic components, namely, permafrost thaw, temperature, and greenhouse gases in the form of a Caputo fractional differential equation, and analyzed their dynamics. The theoretical aspects, such as the existence and uniqueness of the obtained solution, are examined. We have derived two different sliding mode controllers to control chaos in this fractional-order system. The influences of these controllers are analyzed in the presence of uncertainties and external disturbances. In this process, we have obtained a new controlled system of equations without and with uncertainties and external disturbances. Global stability of these new systems is also established. All the aspects are examined for commensurate and non-commensurate fractional-order derivatives. To establish that the system is chaotic, we have taken the assistance of the Lyapunov exponent and the bifurcation diagram with respect to the fractional derivative. To perform numerical simulation, we have identified certain values of the parameters where the system exhibits chaotic behavior. Then, the theoretical claims about the influence of the controller on the system are established with the help of numerical simulations.
Citation - WoS: 15
Citation - Scopus: 16
Design of Gudermannian Neuroswarming To Solve the Singular Emden-Fowler Nonlinear Model Numerically
(Springer, 2021) Baleanu, Dumitru; Shoaib, Muhammad; Sabir, Zulqurnain; Raja, Muhammad Asif Zahoor; Cengiz, Korhan
The current investigation is related to the design of novel integrated neuroswarming heuristic paradigm using Gudermannian artificial neural networks (GANNs) optimized with particle swarm optimization (PSO) aid with active-set (AS) algorithm, i.e., GANN-PSOAS, for solving the nonlinear third-order Emden-Fowler model (NTO-EFM) involving single as well as multiple singularities. The Gudermannian activation function is exploited to construct the GANNs-based differential mapping for NTO-EFMs, and these networks are arbitrary integrated to formulate the fitness function of the system. An objective function is optimized using hybrid heuristics of PSO with AS, i.e., PSOAS, for finding the weights of GANN. The correctness, effectiveness and robustness of the designed GANN-PSOAS are verified through comparison with the exact solutions on three problems of NTO-EFMs. The assessments on statistical observations demonstrate the performance on different measures for the accuracy, consistency and stability of the proposed GANN-PSOAS solver.

Browse

Browsing PubMed İndeksli Yayınlar Koleksiyonu by WoS Q "Q1"