Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Perspectives on Audit Opinions and Key Audit Matters in the Global Airline Industry and the COVID-19 Pandemic(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Dansık, Umutcan; Öztürk, C.The present study investigates whether the COVID-19 pandemic had a negative effect on audit opinion and led to differences in the composition of key audit matters (KAMs) observed in the airline industry. This study uses a sample of 55 airlines whose financial statements are based on International Financial Reporting Standards (IFRSs) and whose financial statement audit follows National or International Standards on Auditing (ISAs) for audit opinion, as well as a sample of 42 airlines whose financial statements are based on IFRSs and whose financial statement audit follows ISAs for the composition of KAMs. A textual analysis, a content analysis, a frequency distribution, and a chi-square test were conducted for the periods before, during, and after the COVID-19 pandemic. The findings reveal that the COVID-19 pandemic had no significant effect on audit opinion, except for one airline whose audit report declared a disclaimer of opinion. In contrast, the impairment of goodwill and intangible assets (as an industry-specific KAM) and going concern (as a KAM specific to the COVID-19 pandemic) were the two KAMs that were typically observed during the COVID-19 pandemic due to increased uncertainty. This was found to be the case, even though the main KAMs in the airline industry are usually revenue recognition; lease accounting; property, plant, and equipment (PPE); and hedge accounting. This study contributes to the debate on the effect of the COVID-19 pandemic on audit opinions and KAMs by offering evidence from the underexplored airline industry. © 2025 by the authors.Article The Effect of Technological Development on Renewable Energy(IGI Global, 2025) Avşar, D.; Temiz, D.; Gökmen, A.Renewable energies have an essential role in the reduction of external dependency of countries by meeting their energy needs from domestic resources, sustainable energy use as a result of diversification of resources and minimizing the damage to the environment from energy consumption. The study aims to measure technological developments' impact on Turkey’s renewable energy production. Therefore, this study uses annual time series data on Turkey from 1980-2022 to investigate the causal link between technology and renewable energy production. This study applies Augmented Dickey-Fuller (ADF) (1981), Phillips-Perron (PP) (1988), Kwiatkowski-Phillips-Schmidt-Shin (KPSS) (1992) and Ng-Perron (2001) tests for data analysis. In the long run, it has been found that there is a significant positive relationship between technological development and renewable energy; in addition, it has been found that there is a bidirectional causality relationship between renewable energy production and economic growth in the short term. © 2025 IGI Global. All rights reserved.Article The Expanded and Intensive Trade in Turkey's Automotive Sector(IGI Global, 2024) Temiz, D.; Kutlu, R.; Gökmen, A.Extensive trade is the export of existing foreign trade countries in a country at a higher amount or price. Intensive trade is the average of new products exported or new exports made by existing foreign trade in a country. The study found that the quantity component was 77.97% and the price component was 17.82%. Turkey's common trade share in automotive sub-industry production is 4.21%. According to these findings, it is seen that the strength of Turkey's automotive main and sub-industry exports stems from intense trade. It also appears that intense trading means a large number of pieces of the price device are being explained. © 2024 IGI Global. All rights reserved.Conference Object Citation - Scopus: 3On Parallelized Serially Concatenated Codes(Ieee, 2007) Gazi, Orhan; Yilmaz, A. OezguerSerial concatenated codes show very good performance at low signal to noise ratios. However, large decoding delays due to long input frame lengths constitute a major disadvantage for these type of codes. In this study we introduce a new class of concatenated convolutional codes which are very suitable for parallel decoding, thus have much less decoding delays and also show comparable performance to that of classical serial concatenated convolutional codes. The analytical upper bound expressions for performance of the proposed structures are derived using the uniform interleaver concept.Article Citation - Scopus: 7Robust Classification for Sub Brain Tumors by Using an Ant Colony Algorithm With a Neural Network(Innovative Information Science and Technology Research Group, 2024) Faris, R.A.; Mosa, Q.; Albdairi, M.A brain tumor is responsible for the highest number of fatalities across the globe. Identifying and diagnosing the tumor correctly at an early stage can significantly improve the chances of survival. Classifying a brain tumor can be aided by factors like type, texture, and location. In this research, we propose a robust technique for detecting sub-brain tumors using an ant colony algorithm coupled with a neural network. To achieve this, we employ an ant colony optimization algorithm (ACO) to eliminate extraneous features extracted from the image, enabling us to find the most effective representation of the image. This, in turn, assists the Neural Network (NN) in the process of classification. Our system involves a series of five steps. Initially, we perform cropping processing as the initial step to eliminate unnecessary background from the original MRI images. This enhances the overall quality of the images, thereby improving the performance of the classification method. In the next step, we conduct image preprocessing to enhance image quality, making it easier for the feature extractor to accurately extract features. The third step involves employing a feature extractor for each image. In the fourth step, we utilize the ant colony optimization algorithm (ACO) to identify the most suitable representation of the image, which further aids the NN in classification. In the fifth and final step, we utilize an NN method to classify the vector obtained from the fourth step (optimization method) to determine the subtype of the brain tumor (normal, glioma, meningioma, and pituitary). Our model's performance is evaluated using the publicly available BT-large-4c dataset, and it surpasses current state-of-the-art methods with exceptional accuracy, attaining a rate of 87.7%. The effectiveness of our approach is particularly evident in maintaining accurate classifications within MRI input images. © 2024, Innovative Information Science and Technology Research Group. All rights reserved.Article Citation - Scopus: 4Ion-Acoustic Solitons in Magnetized Plasma Under Weak Relativistic Effects on the Electrons(Springer, 2023) Madhukalya, B.; Das, R.; Hosseini, K.; Baleanu, D.; Salahshour, S.Investigating ion-acoustic disturbances in a magnetized plasma, consisting of relativistic electrons and non-thermal ions, entails a comprehensive study into the nonlinear wave structure. By condensing the fundamental set of fluid equations for the flow variables, a singular equation known as the Sagdeev potential equation is derived using the pseudopotential approach. In this investigation of the magnetized relativistic plasma, we have observed only dip (rarefactive) (N< 1) soliton under both subsonic (M< 1) and supersonic (M> 1) conditions. The occurrence of the soliton depends on the wave velocities in different propagation directions. The magnitude of amplitudes of the relativistic solitons is higher for higher Mach number (M> 1) irrespective of the wave’s propagation direction. Furthermore, the magnitude of amplitudes of the solitary wave is seen to increase near the direction of the magnetic field. © 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.Article Citation - Scopus: 1Qualitative Analysis of Nonlinear Hilfer Fractional Implicit Differential Equations in a Banach Space(DergiPark, 2023) Dhawan, K.; Vats, R.K.; Karapinar, E.This article focuses on the class of nonlinear implicit Hilfer-type fractional differential equations. By using the non-linear growth condition, we have derived the existence of at least one solution by applying Schauder’s fixed point theorem and using Lipschitz conditions, we have derived the uniqueness of the solution with the help of the Banach contraction principle. In addition, we have discussed the stability analysis by using Ulam-Hyers and Ulam-Hyers-Rassias stabilities. All results of this paper are established in a Banach space instead of R. We illustrate our results with the help of two examples. © 2023, DergiPark. All rights reserved.Article Citation - Scopus: 5Modeling of Tumor-Immune System Interaction With Stochastic Hybrid Systems With Memory: a Piecewise Linear Approach(Erdal Karapinar, 2021) Gökgöza, N.; Öktem, H.In this work, we benefit from hybrid systems that are advantageous because of their analytical and computational usefulness in the case of inferential modeling. In fact, many biological and physiological systems exhibit historical responses such that the system and its responses depend on the whole history rather than a combination of historical events. In this work, we use and improve hybrid systems with memory (HSM) in the subclass of piecewise linear differential equations. We also include stochastic calculus to our model to exhibit uncertainties and random perturbations clearly, and we call this model stochastic hybrid systems with memory (SHSM). Finally, we choose tumor-immune system data from the literature and show that the model is capable to model history dependent behavior. © 2021, Erdal Karapinar. All rights reserved.Other Citation - Scopus: 14Multicriteria Decision-Making Approach for Pythagorean Fuzzy Hypersoft Sets' Interaction Aggregation Operators(Hindawi Limited, 2021) Zulqarnain, R.M.; Siddique, I.; Ali, R.; Jarad, F.; Iampan, A.In this paper, we examine the multicriteria decision-making (MCDM) difficulties for Pythagorean fuzzy hypersoft sets (PFHSSs). The PFHSSs are a suitable extension of the Pythagorean fuzzy soft sets (PFSSs) which deliberates the parametrization of multi-subattributes of considered parameters. It is a most substantial notion for describing fuzzy information in the decision-making (DM) procedure to accommodate more vagueness comparative to existing PFSSs and intuitionistic fuzzy hypersoft sets (IFHSSs). The core objective of this study is to plan some innovative operational laws considering the interaction for Pythagorean fuzzy hypersoft numbers (PFHSNs). Also, based on settled interaction operational laws, two aggregation operators (AOs) i.e., Pythagorean fuzzy hypersoft interaction weighted average (PFHSIWA) and Pythagorean fuzzy hypersoft interaction weighted geometric (PFHSIWG) operators for PFHSSs operators have been presented with their fundamental properties. Furthermore, an MCDM technique has been established using planned interaction AOs. To ensure the strength and practicality of the developed MCDM method, a mathematical illustration has been presented. The usefulness, influence, and versatility of the developed method have been demonstrated via comparative analysis with the help of some conventional studies. © 2021 Rana Muhammad Zulqarnain et al.Correction A New Approach To Increase the Flexibility of Curves and Regular Surfaces Produced by 4-Point Ternary Subdivision Scheme (Vol 2020, 6096545, 2020)(Hindawi Ltd, 2021) Hameed, Rabia; Mustafa, Ghulam; Liaqat, Amina; Baleanu, Dumitru; Khan, Faheem; Al-Qurashi, Maysaa M.; Chu, Yu-Ming