Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651

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Citation - Scopus: 8
Advanced Analysis of Local Fractional Calculus Applied To the Rice Theory in Fractal Fracture Mechanics
(Springer Science and Business Media Deutschland GmbH, 2022) Baleanu, D.; Srivastava, H.M.; Yang, X.-J.; 56389
In this chapter, the recent results for the analysis of local fractional calculus are considered for the first time. The local fractional derivative (LFD) and the local fractional integral (LFI) in the fractional (real and complex) sets, the series and transforms involving the Mittag-Leffler function defined on Cantor sets are introduced and reviewed. The uniqueness of the solutions of the local fractional differential and integral equations and the local fractional inequalities are considered in detail. The local fractional vector calculus is applied to describe the Rice theory in fractal fracture mechanics. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Citation - Scopus: 6
Advanced Topics in Fractional Differential Equations a Fixed Point Approach
(Springer Nature, 2023) Benchohra, M.; Karapınar, Erdal; Karapınar, E.; Lazreg, J.E.; Salim, A.; 19184; Matematik
Analog and Digital Filter Design
(Springer Science and Business Media B.V., 2018) Gazi, O.
In this chapter, we will study analog and digital filter design techniques. A filter is nothing but a linear time invariant (LTI) system. Any LTI system can be described using its impulse response. If the impulse response of a LTI system is known, then for any arbitrary input the system output can be calculated by taking the convolution of the impulse response and arbitrary input. This also means that filtering operation is nothing but a convolution operation. And filter design is nothing but finding the impulse response of a linear time invariant system. For this purpose, we can work either in time domain or frequency domain. © Springer Nature Singapore Pte Ltd. 2018.
Andropov, Yuri Vladimirovich (1914-1984)
(Bloomsbury Publishing Plc., 2014) Karadelli, S.C.
Application of Various Modelling Techniques Into Consumer Confidence Index
(CRC Press, 2025) Kalayci, B.; Purutçuoğlu, V.; Weber, G.W.; Uğur, Ö.; Defterli, Ö.
The principles of sentiment are presented by economic conditions such that most of the variance in consumer sentiment is caused by economic situations, either directly or indirectly. There are political and economic repercussions to investors’ economic optimism or pessimism. Customer expenditures and hence, the direction of the economy’s future are predicted by the degree of consumer confidence. Investors, who are in a similar way, are positioned economically, but, have different biased thoughts bringing forward quite different sentiments about the future of economics. © 2025 CRC Press.
Artificial Intelligence in Dentistry
(CRC Press, 2025) Cagiltay, Nergiz Ercil; Kılıçarslan, Mehmet Ali; Basmaci, Fulya
Today, with advanced technologies, collecting detailed and big data from the environment and analyzing it using intelligent techniques has become possible, providing important insights into phenomena as well as future predictions. Big data is characterized by its high volume, velocity, and variety. Here, the volume is the amount and size of the data, which is measured in terabytes, petabytes, exabytes, or zettabytes. Velocity is the offered form of big data, which can be batch, near-real-time, real-time, or streaming. Finally, variety is the structure of the big data, which can be structured, such as in relational or dimensional models, as in warehouses, or unstructured, which is stored without any organization. It can also be in semi-structured form, where the data is unstructured but there is some meta-data or some tags for describing the data. Today, these forms of data are being collected for different dental purposes in several formats, such as images, raw data, or coordinates. © 2025 Elsevier B.V., All rights reserved.
Citation - Scopus: 6
Artificial Neural Network Modeling of Systems Biology Datasets Fit Based on Mittag-Leffler Functions With Heavy-Tailed Distributions for Diagnostic and Predictive Precision Medicine
(Elsevier, 2022) Baleanu, D.; Karaca, Y.; 56389
Being the most complex physical system in the universe, life, at all scales requires the understanding of the massive complexity including its origin, structure, dynamic, adaptation and organization. Both the number of substructures and interacting pathways of each substructure along with other ones and neurons determine the degree of complexity. Neural networks, as descriptive models, in systems biology setting, provide the means to gather, store and use experiential knowledge; and are designed in a way to emulate different operations of the human brain. One of the major ongoing challenges of integrating fractional calculus in cases of complexity requires an effective use of empirical, numerical, experimental and analytical methods to tackle complexity. In that regard, Artificial Neural Networks (ANNs), including a family of nonlinear computational methods, are employed to handle experimental data in differing domains owing to their capability of tackling complex computations so that their progressive application can solve practical problems. One of the other most noteworthy tools which arises in the fractional calculus context is the Mittag-Leffler (ML) functions. Mittag-Leffler distributions have extensive application domains when dealing with irregular and nonhomogeneous environments for dynamic problems' solutions. They can be used in reliability modeling as an alternative for exponential distribution, particularly this provides upper hand for diagnostic and predictive purposes in precision medicine through novel algorithmic models. To address this, the proposed method in the current study has obtained the generation of optimum model strategies for different biology datasets along with Mittag-Leffler functions with heavy-tailed distributions (see Part I). Within this framework, the proposed integrated approach in this study investigates the dynamics of diseases related to biological elements; and arising in the different solutions of varying complex biological systems, ML function generalizes the exponential function. To this end, firstly, the two-parametric Mittag-Leffler function was applied to biological datasets (cancer cell dataset and diabetes dataset, namely raw datasets), namely cancer cell and diabetes in order to obtain the new datasets (ml_cancer cell dataset and ml_diabetes dataset). Heavy-tailed distributions (The Mittag-Leffler distribution, Pareto distribution, Cauchy distribution and Weibull distribution) were applied to the new datasets obtained with their comparison performed in relation to the performances (by employing the log likelihood value and the Akaike Information Criterion (AIC)). ML functions that represent the cancer cell and diabetes data were identified so that the two parameters Eα,β(z) yielding the optimum value based on the distributions fit could be found. Secondly, one of the ANN algorithms, namely Multi-layer Perceptron (MLP) (along with the accuracy, sensitivity, precision, specificity, F1-score, multi-class classification (MCC), ROC curve), was applied for the diagnosis and prediction of the disease course regarding the optimum ML functions that represent the cancer cell and diabetes datasets obtained and the performances of the ML functions with heavy-tailed distributions were compared with ANN training functions (Levenberg-Marquart, Bayes Regularization and BFGS-Quasi-Newton) accordingly. The integrative modeling scheme proposed herein, which has not been addressed through this sort of approach before, is concerned with the applicability and reliability of the solutions obtained by Mittag-Leffler functions with heavy-tailed distributions. The results obtained by the current study for diseases related to biological datasets based on mathematical models demonstrate that the integrative approach with Mittag-Leffler function and ANN applications is applicable and fits very well to the related data with the robust parameters' values observed and estimated. When the fact that complex biological phenomena involve various intrinsic and extrinsic aspects is considered, it becomes a major difficulty to make identifications and recognition on the basis of a single type of data merely. Thus, the proposed approach of our study corroborates its applicability for diagnostic and predictive purposes in precision medicine through the novel algorithmic model, which plays a significant role in the effective and timely management of unpredictable phenomena in dynamic and nonlinear complex situations. © 2022 Elsevier Inc. All rights reserved.
At the Convergence of Energy Corridors: Energy Situation in Turkey and a Critical Evaluation With Porter's Model
(Igi Global, 2017) Gokmen, Aytac; Nakip, Mahir; 17660; 118963
Turkey is at the threshold of Eurasia connecting various energy corridors. It has an improving economic volume and is one of the 20 largest economies in the world. Energy and economic development are highly correlated. Turkey is dependent on imported energy. In order to keep up with the economic expansion, the energy requirements of Turkey must be met in a diversified, timely and reliable way. Thus, the aim of this paper is to define the geographic disposition of Turkey at the convergence of energy lines, review its energy situation comprehensively and make critical evaluations on energy and economy related issues, also with using the diamond model developed by Michael E. Porter resting on credible national and international publications and data.
Beyond the Bully: Exploring the Surprising Performance-Related Outcomes of Abusive Supervision
(Nova Science Publishers, Inc., 2024) Tokat, T.; Çivit, S.; Göncü-Köse, A.
The common definitions of leadership include positive qualities such as vision, ethics, responsibility, respect, and trustworthiness. However, recent studies revealed an increase in unethical behaviors performed by organizational leaders, prompting academics to investigate the harmful types and impacts of leadership. One area of focus has been abusive supervision, which was found to have both positive and negative effects on organizational outcomes including subordinate and supervisor performance. While the harmful effects on subordinates have been a major focus in studies on abusive supervision, some scholars suggested that supervisors’ abusive behaviors may yield temporary functional results and be used as a strategy for leaders to improve work performance. To illustrate, researchers demonstrated the positive association between abusive supervision and work performance when subordinates attribute abusive behaviors to an effort to increase motivation rather than an intention to harm the employee (Li et al., 2022; Liao et al., 2021; Tepper et al., 2015). However, there is limited knowledge about these destructive behaviors’ impact on supervisors. One of these few studies showed that engaging in abusive supervisory behavior was positively correlated with supervisors’ recovery levels. Moreover, abusive supervisory behavior indirectly contributed to increased work engagement through its positive effect on the recovery level (Qin et al., 2018). The present chapter provides a comprehensive overview of the effects of abusive supervision on work performance, outlining both the negative and positive work-, employee-, and supervisor-related outcomes. Additionally, this chapter unfolds potential directions for future research regarding the relationships of abusive supervision with in-role and extra-role performance. Finally, we present practical recommendations for leaders and organizations to minimize the detrimental effects of abusive supervision. The literature findings will be presented in conjunction with various theoretical explanations, concepts, and propositions. © 2024 by Nova Science Publishers, Inc.
Citation - Scopus: 8
Bitcoin Market Price Analysis and an Empirical Comparison With Main Currencies, Commodities, Securities and Altcoins
(Springer Science and Business Media Deutschland GmbH, 2019) Dinçergök, B.; Haşlak, Ş.; Pirgaip, B.
The purpose of this study is to analyze Bitcoin (BTC) market prices and to answer the question of whether there is a relationship between BTC and other asset prices, where other assets include currencies, commodities, securities and altcoins. In the empirical part, we evaluate the lead-lag relationships among each type of asset. Consequently, we compare BTC with major currencies and stock exchanges of the U.S., the EU, the U.K. and Japan (USD-SPX, EUR-DAX, GBP-FTSE and JPY-NIK), with currencies and stock exchanges of the U.S., the U.K., Russia, Venezuela and China where BTC is actively traded (USD-SPX, GBP-FTSE, RUB-MOEX, VEF-IBVC and YUAN-SSCE), with major commodities (GOLD and OIL) and with major altcoins (ETH, XRP and LTC) on a daily basis for the period spanning from 2010.07 to 2018.12. We employ Johansen co-integration, Granger causality, impulse response functions and forecast error variance decomposition analyses in our study. Our results show that BTC does not have a long-run relationship with any asset type, but that it has a short-run relationship with gold and especially altcoins, which are both significant and bidirectional. While BTC and altcoins are closely interrelated with each other, BTC price variation is mostly borne by its own prices in all cases. © Springer Nature Switzerland AG 2019.
Board Structure and Sustainability Performance: a Study on Turkish Manufacturing Companies
(IGI Global, 2025) Aksu, A.; Şener, İ.; Kadir Varoğlu, A.
The adoption of the innovative perspective of Industry 5.0 at the highest level in organizations is important for ensuring sustainability in every field and the board of directors’ role becomes increasingly important in improving companies' sustainability performance. This chapter first presents the theoretical and conceptual background of Industry 5.0 and sustainability, the role of boards of directors in sustainability, and corporate sustainability reporting. Then, the findings of an empirical study that examine the impact of board structure on companies' sustainability performance are presented. The study aims to contribute by revealing which characteristics of companies’ boards of directors positively impact sustainability performances of the companies. The data from 166 manufacturing firms listed on Borsa Istanbul have been used in the research. Findings suggest that both the size of the board and the presence of women on the board have a positive impact on sustainability performance. © 2025 by IGI Global Scientific Publishing. All rights reserved.
Business Information Systems, Importance of Information, Business Intelligence, Corporate Excellence, and ICTs Within the Development of Organizations
(IGI Global, 2024) Gökmen, A.; Temiz, D.
An important shift takes places in organizations which is the shift in priorities to strategic management and increasing human demand for reliable information to run the business competitively in the global context. Nevertheless, executives and managers are exposed to a considerable amount of information which is both invaluable, as well as difficult to acquire, process, store, disseminate and utilize. Therefore, the objective of this study is to focus on the subjects as business information systems, information systems, business intelligence, corporate excellence, business intelligence, ICTs and other topics related to these issues in order to emphasize the importance of information and knowledge in the 21st century. © 2025 by IGI Global Scientific Publishing. All rights reserved.
Citation - WoS: 1
Citation - Scopus: 1
Cantor-Type Spherical-Coordinate Method for Differential Equations Within Local Fractional Derivatives
(de Gruyter Open Ltd, 2015) Rahmat, Mohamad Rah Segi; Baleanu, Dumitru; Yang, Xiao-Jun
In this article, we utilize the Cantor-type spherical coordinate method to investigate a family of local fractional differential operators on Cantor sets. Some examples are discussed to show the capability of this method for the damped wave, Helmholtz and heat conduction equations defined on Cantor sets. We show that it is a powerful tool to convert differential equations on Cantor sets from Cantorian-coordinate systems to Cantor-type spherical-coordinate systems.
Citation - Scopus: 1
Carrier Selection for Less-Than (Ltl) Shipments
(Elsevier, 2021) Konur, D.; Yıldırım, G.; Cesaret, B.
This chapter reviews the basics of carrier selection for less-than-truckload (LTL) shipments. First, the impacts of LTL carrier selection on various strategic, tactical, and operational supply chain planning decisions are discussed. Then, the key principles of LTL carriers and the key carrier attributes LTL shippers account for in their selection of LTL carriers are summarized. A numerical study using a continuous review inventory control model under stochastic demand is presented in order to demonstrate the effects of four key LTL carrier attributes (transit time, transit time variability, and freight minimums and maximums) on a shipper's cost and service level. © 2021 Elsevier Ltd. All rights reserved
Citation - Scopus: 1
The Causal Relationship Between Esg and Economic Growth: Evidence From the Panel of Commonwealth Independent States
(Springer International Publishing, 2024) Baskaraagac, N.Y.
This paper analyzes the causal relationship between ESG and economic growth for CIS member states over the sample period 1996–2020. Since the results of the varied panel stationarity tests suggest mixed findings on the order of integration, the ARDL model is employed to determine the co-integration relation among the series. The result of the VEC model, which is estimated to explore the long-run and short-run dynamics of this casual relation between the series in a basic way, suggests that there is a causal relationship running from income level to ESG criteria. This implies that the adaptation of macroeconomic policies which will stimulate the economic growth process in CIS countries may also encourage the ESG indicator levels of the economy. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Channel Coding Theorem
(Springer Science and Business Media Deutschland GmbH, 2018) Gazi, O.; 102896
In this chapter, we will discuss the channel coding theorem in details. Channel coding theorem can be accepted as a milestone in electronic communication field. For this reason, it is very critical for a communication engineer to comprehend the channel coding theorem very well. In many information theory books, or in many lecture notes delivered in classes about information theory, channel coding theorem is very briefly summarized, for this reason, many readers fail to comprehend the details behind the theorem. © 2018, Springer Nature Singapore Pte Ltd.
Clean Energy Generation in Residential Green Buildings
(inst Engineering Tech-iet, 2019) Aylı, Ülkü Ece; Yapici, Ekin Ozgirgin; Ayli, Ece; Makine Mühendisliği
Due to the recent investigations, buildings consume a considerable amount of the electricity, drinking water, global final energy use and as a result are responsible for one third of the global carbon emissions. Therefore, building sector has a key role to reach global energy targets. In this sight, this study draws attention to the sustainable energy performances of green buildings (GBs) and aims towards the GBs concept which includes renewable sources in the construction and lifetime utilization. The remainder of the chapter is subjected as follows: Section 2.1 gives a brief information about residential GBs, and in Section 2.2, certification systems for sustainability ratings of residential GBs are given. This is followed by case studies related to the certification systems in Section 2.3 part. In Section 2.4, GBs incentives are summarized. Section 2.5 provides information about energy demand modelling for residential GBs, and in Section 2.6, clean energy generation systems in residential GBs are described in detail. Finally, outlook for the works that is performed up to now and the outlook for the future is given.
Comparison of Different Turbulent Models in Turbulent-Forced Convective Flow and Heat Transfer Inside Rectangular Cross-Sectioned Duct Heating at the Bottom Wall
(Springer International Publishing, 2014) Onur, N.; Arslan, K.; 53858
In this study, steady-state turbulent-forced flow and heat transfer in a horizontal smooth rectangular cross-sectioned duct was numerically investigated. The study was carried out in the turbulent flow region where Reynolds number ranges from 1 × 104 to 5 × 104. The flow was developing both hydrodynamically and thermally. The bottom surface of the duct was assumed to be under constant surface temperature. A commercial CFD program Ansys Fluent 12.1 with different turbulent models was used to carry out the numerical study. Different turbulence models (k–ε Standard, k–ε Realizable, k–ε RNG, k–ω Standard and k–ω SST) were used. Based on the present numerical solutions, new engineering correlations were presented for the heat transfer and friction coefficients. The numerical results for different turbulence models were compared with each other and the experimental data available in the literature. It was observed that k–ε turbulence models represented the turbulent flow condition very well for the present study. © Springer International Publishing Switzerland 2014.
Citation - Scopus: 8
Computational Fractional-Order Calculus and Classical Calculus Ai for Comparative Differentiability Prediction Analyses of Complex-Systems Paradigm
(Elsevier, 2022) Baleanu, D.; Karaca, Y.; 56389
Modern science having embarked on the thorough and accurate interpretation of natural and physical phenomena has proven to provide successful models for the analysis of complex systems and harnessing of control over the various processes therein. Computational complexity, in this regard, comes to the foreground by providing applicable sets of ideas or integrative paradigms to recognize and understand the complex systems' intricate properties. Thus, while making the appropriate, adaptable and evolutive decisions in complex dynamic systems, it is essential to acknowledge different degrees of acceptance of the problems and construct the model it to account for its inherent constraints or limits. In this respect, while hypothesis-driven research has its inherent limitations regarding the investigation of multifactorial and heterogeneous diseases, a data-driven approach enables the examination of the way variables impact one another, which paves the way for the interpretation of dynamic and heterogeneous mechanisms of diseases. Fractional Calculus (FC), in this scope characterized by complexity, provides the applicable means and methods to solve integral, differential and integro-differential equations so FC enables the generalization of integration and differentiation possible in a flexible and consistent manner owing to its capability of reflecting the systems' actual state properties, which exhibit unpredictable variations. The fractional integration and differentiation of fractional-order is capable of providing better characterization of nonstationary and locally self-similar attributes in contrast to constant-order fractional calculus. It becomes possible to model many complex systems by fractional-order derivatives based on fractional calculus so that related syntheses can be realized in a robust and effective way. To this end, our study aims at providing an intermediary facilitating function both for the physicians and individuals by establishing accurate and robust model based on the integration of fractional-order calculus and Artificial Neural Network (ANN) for the diagnostic and differentiability predictive purposes with the diseases which display highly complex properties. The integrative approach we have proposed in this study has a multistage quality the steps of which are stated as follows: first of all, the Caputo fractional-order derivative, one of the fractional-order derivatives, has been used with two-parametric Mittag-Leffler function on the stroke dataset and cancer cell dataset, manifesting biological and neurological attributes. In this way, new fractional models with varying degrees have been established. Mittag-Leffler function, with its distributions of extensive application domains, can address irregular and heterogeneous environments for the solution of dynamic problems; thus, Mittag-Leffler function has been opted for accordingly. Following this application, the new datasets (mlf_stroke dataset and mlf_cancer cell dataset) have been obtained by employing Caputo fractional-order derivative with the two-parametric Mittag-Leffler function (α,β). In addition, classical derivative (calculus) was applied to the raw datasets; and cd_stroke dataset and cd_cancer cell dataset were obtained. Secondly, the performance of the new datasets as obtained from the Caputo fractional derivative with the two-parametric Mittag-Leffler function, the datasets obtained from the classical derivative application and the raw datasets have been compared by using feed forward back propagation (FFBP) algorithm, one of the algorithms of ANN (along with accuracy rate, sensitivity, precision, specificity, F1-score, multiclass classification (MCC), ROC curve). Based on the accuracy rate results obtained from the application with FFBP, the Caputo fractional-order derivative model that is most suitable for the diseases has been generated. The experimental results obtained demonstrate the applicability of the complex-systems-grounded paradigm scheme as proposed through this study, which has no existing counterpart. The integrative multi-stage method based on mathematical-informed framework with comparative differentiability prediction analyses can point toward a new direction in the various areas of applied sciences to address formidable challenges of critical decision making and management of chaotic processes in different complex dynamic systems. © 2022 Elsevier Inc. All rights reserved.
Concept of Information, Discrete Entropy and Mutual Information
(Springer Science and Business Media Deutschland GmbH, 2018) Gazi, O.; 102896
In this chapter, we will try to explain the concept of information, discrete entropy and mutual information in details. To master on the information theory subjects, the reader should have a knowledge of probability and random variables. For this reason, we suggest to the reader to review the probability and random variables topics before studying the information theory subjects. Continuous entropy and continuous mutual information are very closely related to discrete entropy and discrete mutual information. For this reason, the reader should try to understand very well the fundamental concepts explained in this chapter, then proceed with the other chapters of the book. © 2018, Springer Nature Singapore Pte Ltd.

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