Scopus İndeksli Yayınlar Koleksiyonu
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Article Citation Count: 0Economic Uncertainty and Climate Change Exposure(Academic Press, 2025) Danisman, G.O.; Bilyay-Erdogan, S.; Demir, E.This paper explores how economic uncertainty affects firms’ climate change exposure. We use an extensive sample from 24 countries from 2002 to 2021. Employing a novel measure of firm-level climate change exposure developed by Sautner et al. (2023b), we empirically demonstrate that prior to the Paris Agreement in 2015, economic uncertainty leads to a decrease in climate change disclosures. However, after the Paris Agreement, our findings reveal a positive association between economic uncertainty and climate change exposure. The positive disclosure effect is primarily driven by higher climate-related opportunities and regulatory exposures. Our findings are robust when we employ alternative definitions for economic uncertainty, alternative samples, additional firm-level and country-level control variables, and alternative methodologies. We find that institutional and foreign ownership positively moderates the association between economic uncertainty and climate change exposure after the Paris Agreement. Further analysis investigates the moderating impact of country-level environmental performance indicators. We present novel empirical evidence suggesting that firms operating in countries with less climate vulnerability, higher readiness, more stringent environmental policies, superior climate protection performance, and higher environmental litigation risk tend to have higher climate change exposure in uncertain times. © 2024 Elsevier LtdArticle Citation Count: 0Segregation of Hourly Electricity Consumption: Quantification of Demand Types Using Fourier Transform(Econjournals, 2025) Yucekaya, A.; Bilge, A.H.; Yukseltan, E.; Aktunc, E.A.Although aggregate electricity consumption provides valuable information for market analysis, it does not provide demand composition, including industrial, residential, illumination, and other uses. The information for subconsumptions is required for the reliable and cost-effective operation of the power system. As a first step towards the segregation of hourly total electricity consumption into its components, we use spectral analysis (Fast Fourier Transform) to determine relative strengths of the harmonics of annual, weekly and daily variations, to quantify the share of electricity consumption for heating, cooling, illumination and industrial activities. The method is applied to the data of France, Sweden, Finland, Norway, Turkiye, Italy, Spain, Greece, Germany, Great Britain, Poland and the Netherlands. Quantitative results obtained via spectral analysis are supplemented by qualitative features observed via time-domain analysis. The consumption ratios for each demand type are calculated using daily, weekly and annual harmonics and the results are presented. © 2025, Econjournals. All rights reserved.Article Citation Count: 0Towards a Scalable and Efficient Full- Adder Structure in Atomic Silicon Dangling Band Technology(Elsevier B.V., 2025) Rasmi, H.; Mosleh, M.; Navimipour, N.J.; Kheyrandish, M.Atomic Silicon Dangling Bond (ASDB) is a promising new nanoscale technology for fabricating logic gates and digital circuits. This technology offers tremendous advantages, such as small size, high speed, and low power consumption. As science and technology progress, ASDB technology may eventually replace the current VLSI technology. This nanoscale technology is still in its early stages of development. Recently, many computing circuits, such as full-adder, have been designed. However, these circuits have a common fundamental problem; they consume a lot of energy and occupy a lot of area, which reduces the performance of complex circuits. This paper proposes a novel ASDB layout for designing an efficient full-adder circuit in ASDB technology. Moreover, a four-bit ASDB ripple carry adder(RCA) is designed using the proposed ASDB full-adder. The proposed ASDB full-adder not only improves the stability of the output but also surpasses the previous works, in terms of energy and accuracy,by 90% and 38%, respectively. Also, it has very favorable conditions in terms of occupied area and is resistant to DB misalignment defects. © 2024Conference Object Citation Count: 0Building Damage Assessment To Facilitate Post-Earthquake Search and Rescue Missions by Leveraging a Machine Learning Algorithm(Institute of Electrical and Electronics Engineers Inc., 2024) Zaker, M.; Alsan, H.F.; Arsan, T.Earthquakes have a severe impact on people's lives and infrastructure. Many emergency institutes and search and rescue missions need accurate post-earthquake response strategies, particularly in building damage assessment. Traditional methods, relying on manual inspections, are inefficient compared to Machine Learning (ML) algorithms. Thus, Random Forest (RF) algorithms stand out because they handle diverse datasets effectively and minimize overfitting. The study outlines the methodology encompassing data preparation, exploratory analysis, feature engineering, and model building, employing a preprocessing pipeline integrating numerical and categorical features. Additionally, Principal Component Analysis (PCA) is applied to reduce dimensionality. The results of the RF model showed an accuracy of 94% and the highest F1-score of 97% among all the grades, demonstrating its efficacy in predicting damage grades post-earthquake. The results can help support better disaster management plans by helping to prioritize rescue operations and allocate resources wisely. © 2024 IEEE.Conference Object Citation Count: 0Capacity Planning for Electricity Utility Call Centers: a Time Series Analysis Approach(Institute of Electrical and Electronics Engineers Inc., 2024) Kavas, E.; Alsan, H.F.; Arsan, T.Electric power systems are crucial for modern society, yet their reliability can be challenged by unforeseen disruptions, causing electricity supply disruptions. Call centers are essential for managing customer inquiries during such outages, acting as communication hubs for electricity utility companies. Effective capacity planning is vital for these call centers to maintain efficient operations and meet customer demands promptly. Proper workforce management ensures that enough skilled agents can handle calls effectively and maintain high service quality. Capacity planning begins with analyzing historical data to understand call volumes, patterns, and peak times. This data analysis identifies trends and factors influencing call patterns, enabling accurate forecasting of future demand and optimizing staffing levels. This paper provides a comprehensive overview of quantitative forecasting methods, focusing on Time Series Analysis applied to a dataset from a Turkish electric utility company that exhibits typical seasonal fluctuations. Specifically, the study examines the performance of AutoRegressive Integrated Moving Average and Seasonal AutoRegressive Integrated Moving Average models. Results indicate that both models perform well, with the Seasonal AutoRegressive Integrated Moving Average model demonstrating slightly superior performance compared to the AutoRegressive Integrated Moving Average model. This suggests that the Seasonal AutoRegressive Integrated Moving Average model may be more suitable for forecasting inbound calls at electricity utility call centers. This paper's detailed analysis and methodology offer valuable insights for optimizing operational efficiency, reducing costs, and enhancing customer satisfaction in dynamic and challenging operational scenarios. © 2024 IEEE.Conference Object Citation Count: 0Graph Theoretical Approach For Path Selection İn Logistic Problems;(Institute of Electrical and Electronics Engineers Inc., 2024) Gökdağ, Z.H.; Bilge, A.H.In this study, we propose a solution for determining operationally acceptable paths by partitioning a graph structure into cliques. In the proposed approach, the graph representing the road network is partitioned into cliques, with boundary vertices connected by k-partite graphs. A path is considered acceptable if its length lies within a certain neighborhood of the minimal distance between the source node and the end node. The clique and k-partite decomposition increase the efficiency of determining acceptable paths. Formulas and numerical examples show that the number of possible paths between any two vertices in a complete graph is higher than the number of possible paths computed by partitioning the graph into cliques with boundary vertices connected by k-partite graphs. The method was applied to the graph structure that includes certain cities in Turkey, where cliques are based on operational preferences. As a result, it was seen as an effective approach that could be suitable for the real-world road network structure. © 2024 IEEE.Conference Object Citation Count: 0A Data Science Perspective on Global Trends in Energy Production(Institute of Electrical and Electronics Engineers Inc., 2024) Hatira, N.; Alsan, H.F.; Arsan, T.As global demand for energy continues to rise, understanding the trends and dynamics of energy generation is crucial to ensure a sustainable and efficient energy future. This study employs data science techniques to analyze global energy production data from 48 countries spanning 2010 to 2023. Initially, we use clustering methods to categorize countries based on their energy production profiles into three distinct groups: high, medium, and low production. This clustering provides insights into the diverse energy strategies and capacities across different regions. Subsequently, we apply and compare two classification models, specifically Random Forest and Gradient Boosting, to predict the dominant energy source for each cluster. Furthermore, we perform a comparative analysis of two forecasting models, SARIMA and Prophet, to predict future renewable energy production for countries with high production profiles, such as the USA and China. The forecasting results show the efficacy of these models in capturing seasonal trends and providing accurate predictions. © 2024 IEEE.Conference Object Citation Count: 0Clustering And Mathematical Optimization Approaches For Efficient Estimation Of Electric Vehicles Charging Stations' Locations;(Institute of Electrical and Electronics Engineers Inc., 2024) Ekmekçi, Y.C.; Demirörs, D.; Rassad, N.A.; Polat, Z.A.; Akkaya, E.B.; Baytürk, E.; Pehlivan, M.The increasing effects of global warming have led to a shift to more environmentally friendly fuels. As electric vehicles become more popular in Türkiye, the demand for charging stations has also increased. However, charging stations are not able to meet demand, hence there is no strategically located charging network. In this study, a prototype for the optimal placement of electric vehicle charging stations is developed using analytical and mathematical approaches such as clustering and mathematical modeling, and Kocaeli province of Türkiye is selected as the prototype city. A preliminary survey was designed to better understand the needs and preferences of electric vehicle users. Supported by an extensive literature review, this research collected critical data on the most important criteria for the construction of EV charging stations and created a dataset by applying a systematic and iterative selection process. Various clustering methods were applied to this dataset and the K-Means algorithm achieved the highest score. With the K-Means algorithm, the data were divided into three clusters and classified as good, medium and poor according to the survey results and distribution. Using the developed clustering model, predictions were made for 50 coordinates where charging stations are planned to be installed. The 22 coordinates that were rated as good and medium by the estimation were selected for further mathematical analysis. The mathematical model with the most critical constraints aimed to maximize the number of users. The solution consists of three phases, with each phase allowing only one installation per region. At each stage, locations from previous stages were removed from the model and rerun with updated utilization scores. With the mathematical model, the most suitable charging station locations were determined within 22 coordinates. © 2024 IEEE.Article Citation Count: 0University Librarians’ Perceptions Of Artificial Intelligence, Its Application Areas İn Libraries, And The Future;(University and Research Librarians Association (UNAK), 2024) Çuhadar, S.; Mert, S.; Gezer, Ç.; Helvacioğlu, E.; Arus, O.; Aslan, Ö.; Atli, S.Today, libraries are among the institutions affected by changing technology and innovations. The popularization of artificial intelligence (AI) technologies has also begun to transform library services. In this research, a survey was conducted to determine the adjustments that university libraries in Turkey have made and plan to make during the development process of AI technologies and applications, and to identify the services they have developed specific to the relevant period. The survey was carried out with the participation of 111 university library managers from 208 university libraries in Turkey. Through the analysis of the data, the status, knowledge, and awareness levels of university libraries regarding AI technologies and applications were determined, and measures and recommendations were presented to improve deficiencies and weaknesses. This research is the first and most comprehensive study conducted in Turkey by obtaining opinions and suggestions from university library managers on artificial intelligence. The research findings revealed that university libraries use AI applications such as ChatGPT, Gemini, and Grammarly to a certain extent; however, they have needs in developing institutional policies, enhancing personnel competencies, and planning related to AI. © 2024 University and Research Librarians Association (UNAK). All rights reserved.Article Citation Count: 0On the Generalisation Performance of Geometric Semantic Genetic Programming for Boolean Functions: Learning Block Mutations(Association for Computing Machinery, 2024) Corus, D.; Oliveto, P.S.In this article, we present the first rigorous theoretical analysis of the generalisation performance of a Geometric Semantic Genetic Programming (GSGP) system. More specifically, we consider a hill-climber using the GSGP Fixed Block Mutation (FBM) operator for the domain of Boolean functions. We prove that the algorithm cannot evolve Boolean conjunctions of arbitrary size that are correct on unseen inputs chosen uniformly at random from the complete truth table i.e., it generalises poorly. Two algorithms based on the Varying Block Mutation (VBM) operator are proposed and analysed to address the issue. We rigorously prove that under the uniform distribution the first one can efficiently evolve any Boolean function of constant size with respect to the number of available variables, while the second one can efficiently evolve general conjunctions or disjunctions of any size without requiring prior knowledge of the target function class. An experimental analysis confirms the theoretical insights for realistic problem sizes and indicates the superiority of the proposed operators also for small parity functions not explicitly covered by the theory. © 2024 Copyright held by the owner/author(s).Conference Object Citation Count: 0Age Classification by Wgan Brain Mr Image Augmentation(Institute of Electrical and Electronics Engineers Inc., 2024) Yaman, B.; Yilmaz, O.Z.; Darici, M.B.; Ozmen, A.Medical image augmentation plays a crucial role in enhancing the performance of Artificial Intelligence (AI) applications in medical sciences. Augmenting medical images is important for solving data scarcity, increasing data diversity, enhancing robustness and reliability of model and improving training and test results that can be done in medical sciences. In this work we show that Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) can be used for increasing the performance of data classification. To achieve that, we have augmented healthy brain MR images by using WGAN and updated the dataset. The results give that when dataset augmented by WGAN-GP is used as input for CNN-based model to solve age classification problem, accuracy of this model increases to 98,37% from 95,14%. It can be concluded that the purposed WGAN-based brain MR image augmentation method enhances the performance of image classification. © 2024 IEEE.Conference Object Citation Count: 0Enhancing Eye-Hand Coordination in Volleyball Players: a Comparative Analysis of Vr, Ar, and 2d Display Technologies and Task Instructions(Institute of Electrical and Electronics Engineers Inc., 2024) Hatira, N.; Aliza, A.; Batmaz, A.U.; Sarac, M.Previous studies analyzed user motor performance with Virtual Reality (VR) and Augmented Reality (AR) Eye-Hand Coordination Training Systems (EHCTSs) while asking participants to follow specific task instructions. Although these studies suggested VR & AR EHCTSs as potential training systems for sports players, they recruited participants for their user studies among general population. In this paper, we examined the training performance of 16 professional volleyball players over 8 days using EHCTSs with three display technologies (VR, AR, and 2D touchscreen) and with four distinct task instructions (prioritizing speed, error rate, accuracy, or none). Our results indicate that volleyball players performed best with 2D touchscreen in terms of time, error rate, accuracy, precision, and throughput. Moreover, their performance was superior when using VR over AR. They also successfully followed the task instructions given to them and consistently improved their throughput performance. These findings underscore the potential of EHCTS in volleyball training and highlight the need for further research to optimize VR & AR user experience and performance. © 2024 IEEE.Conference Object Citation Count: 0Data-Driven Methods for Optimal Setting of Legacy Control Devices in Distribution Grids(IEEE Computer Society, 2024) Savasci, A.; Ceylan, O.; Paudyal, S.This study presents machine learning-based dispatch strategies for legacy voltage regulation devices, i.e., onload tap changers (OLTCs), step-voltage regulators (SVRs), and switched-capacitors (SCs) in modern distribution networks. The proposed approach utilizes k-nearest neighbor (KNN), random forest (RF), and neural networks (NN) to map nodal net active and reactive injections to the optimal legacy controls and resulting voltage magnitudes. To implement these strategies, first, an efficient optimal power flow (OPF) is formulated as a mixed-integer linear program that obtains optimal decisions of tap positions for OLTCs, SVRs, and on/off status of SCs. Then, training and testing datasets are generated by solving the OPF model for daily horizons with 1-hr resolution for varying loading and photovoltaic (PV) generation profile. Case studies on the 33-node feeder demonstrate high-accuracy mapping between the input feature and the output vector, which is promising for integrated Volt/VAr control schemes. © 2024 IEEE.Article Citation Count: 0Would You Like To Travel After the Covid-19 Pandemic? a Novel Examination of the Causal Correlations Within the Attitudinal Theory of Planned Behaviour(International Hellenic University, 2024) Lam, J.M.S.; Kozak, M.; Ariffin, A.A.Purpose: This present study examines the correlation between tourist attitudes toward international travel post-Covid-19 pandemic as well as the image of the travel destination and the perceived risk. Methods: A cross-sectional method was used to collect data via self-administered questionnaires from 432 international respondents visiting Malaysia in 2023. The causal correlations were then examined using partial least squares structural equation modelling (PLS-SEM). Results: Both the subjective norms and perceived behavioural control of TPB, and destination image significantly influence tourist attitudes, and, subsequently tourist satisfaction. This present study also lists its managerial and theoretical implications as well as its limitations and suggestions for imminent studies. Implications: This study contributes to the limited empirical research on travel post-pandemic by applying the established theory of planned behaviour (TPB). Most of the variables of the theory of planned behaviour, an attitudinal theory, correlate with travel intentions but this study takes another perspective. This study also bridges the gap by correlating the TPB to on-travel experiences by measuring tourist satisfaction. © 2024 Authors.Article Citation Count: 2Low-Energy 3:2 Compressor Using Xor-Xnor Gate Combined With 2:1 Multiplexer in Qca Technology(Allerton Press Inc., 2024) Kassa, S.; Misra, N.K.; Ahmadpour, S.-S.; Bhoi, B.K.Abstract: In the field of circuit design, there is a growing trend toward the design of high-speed circuits with a minimum amount of faults on a nanoscale level. In this way, quantum-dot cellular automata (QCA) is a nanoscale-based paradigm that uses a quantum cell with four dots and two electrons to compute logic bits, comparable to transistor-based CMOS architecture. This article focuses on the low-energy compressor design employing an XOR-XNOR gate and a 2:1 multiplexer. Furthermore, a compressor design provides 152 cells employing a coplanar arrangement in QCA with eight majority gates (MG). The compressor energy dissipation is examined using the QCAPro tool, which has various tunneling energy values. Furthermore, the compressor thermal and polarisation layouts are presented. The novel circuit performance is compared with the best existing circuits on QCA regarding cell count, entire area, MG, and latency to assess the newly designed compressor performance. The proposed compressor is tested using the missing cells in the QCADesigner tool. This design has only 5 test vectors, 100% fault coverage, and is best suited for design for testability (DFT). The proposed compressor can be used with various multipliers, including the Wallace tree multiplier, DADDA multiplier, and higher order 7:3 compressor. © Allerton Press, Inc. 2024.Book Part Citation Count: 0The Political Economic Sources of Policy Non-Design and the Decay in Policy Capacity in Turkey(Palgrave Macmillan, 2024) Coban, M.K.This chapter studies the political economic sources of policy design with a specific focus on the policy non-design and on the haphazard instrument choices in Turkey during the two overlapping crises: Covid-19 crisis and the currency crisis-induced economic crisis in 2018. The chapter argues that the haphazard crisis response and policy non-design was a deliberate choice of the authoritarian Turkish government, which originated from its prioritisation of higher economic growth to serve electoral and political economic constituencies. In addition, haphazard instrument choice and policy non-design caused decay in systemic and organisational policy capacity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Article Citation Count: 1Algorithm for Key Transparency With Transparent Logs(F1000 Research Ltd, 2024) Mollakuqe, E.; Rexhepi, S.; Bunjaku, R.; Dag, H.; Chukwu, I.J.Background: Cryptography plays a crucial role in securing digital communications and data storage. This study evaluates the Transparent Key Management Algorithm utilizing Merkle trees, focusing on its performance and security effectiveness in cryptographic key handling. Methods: The research employs simulated experiments to systematically measure and analyze key operational metrics such as insertion and verification times. Synthetic datasets are used to mimic diverse operational conditions, ensuring rigorous evaluation under varying workloads and security threats. Implementation is carried out using R programming, integrating cryptographic functions and Merkle tree structures for integrity verification. Results: Performance analysis reveals efficient insertion and verification times under normal conditions, essential for operational workflows. Security evaluations demonstrate the algorithm's robustness against tampering, with approximately 95% of keys verified successfully and effective detection of unauthorized modifications. Simulated attack scenarios underscore its resilience in mitigating security threats. Conclusions: The Transparent Key Management Algorithm, enhanced by Merkle trees and cryptographic hashing techniques, proves effective in ensuring data integrity, security, and operational efficiency. Recommendations include continuous monitoring and adaptive algorithms to bolster resilience against evolving cybersecurity challenges, promoting trust and reliability in cryptographic operations. Copyright: © 2024 Mollakuqe E et al.Book Citation Count: 0Reflection and Intuition in a Crisis- Ridden World: Thinking Hard or Hardly Thinking?(Taylor and Francis, 2024) Saribay, S.A.; Yilmaz, O.This book provides a definitive guide to the value of reflective thinking in the modern world, showing how today’s most fundamental problems are, to an important degree, based on citizens’ thinking styles. The authors highlight the importance of reflection by systematically revealing the causes underlying differences in people’s thinking styles and the consequences of thinking in different ways. These different ways of thinking contribute to socio-political views, and can result in misunderstandings of complex issues such as beliefs in conspiracy theories and fake news, anti-vaccine attitudes, and even fundamentalism and extremism. By training and strengthening reflective thinking in society, via education and other means, we can encourage individuals to challenge misinformation, and their own belief systems around controversial topics. The book also explores the idea that reflection is not enough on its own and examines the shortcomings of reflection and the other skills that complement it positively, especially holistic and systems thinking. In doing so, the authors highlight how implementing a solid, science-based understanding of key issues in education and society at large, can contribute to the solution of problems, from climate change to economic inequality. By showing how we can put our reflective capacity to good use, alongside critically examining reflection in relation to modern problems experienced by humanity, this book is a fascinating reading for students, researchers, and academics in psychology, politics, and the broader social sciences. © 2025 S. Adil Saribay and Onurcan Yilmaz.Article Citation Count: 0Uğur Tanyeli, Korku Metropolü İstanbul: 18. Yüzyıldan Bugüne. İstanbul: Metis, 2022. 432 Sayfa, 26 Şekil. Isbn: 9786053162643(Istanbul Research Institute, 2023) Yıldırım, Y.[No abstract available]Book Part Citation Count: 0Economics of Energy and Green Growth: Decoupling Debate(CRC Press, 2022) Ucal, M.It is well known that energy is crucial for both human welfare and the continuous development of society. Energy sources can be categorized as either depletable or renewable and storable or non-storable, respectively. Today, global energy consumption mostly depends on fossil fuels. On the other hand, the increasing use of renewable energy sources is very promising due to the disruptive effects of climate change. Increased use and production of renewable energy will also contribute to the transition towards green growth. In this context, it is not possible to talk about the concept of decoupling; we can choose a way to grow without damaging the nature and the environment. To locate these conceptual expressions, developed countries should look at national and international production strategies in this direction. Especially societies and countries that grow with energy production need to be careful about this issue. Energy consumed in different amounts and methods is among the factors that accelerate environmental destruction. Without decoupling, ongoing and growing economic growth in developed and the increasing environmental pressures, inevitably exceeding the carrying capacity of ecosystems, and the corresponding environmental impacts and adversities on society will inevitably refer to developing countries. If the pressure on the environment caused by climate change greenhouse gas emissions cannot be successfully separated (decoupled) from economic growth, it will not be possible to reach the desired targets. Decoupling is defined as 'relative' ('weak') or 'absolute' ('strong'). Relative decoupling signifies higher rates of economic growth than rates of growth in material and energy consumption and environmental impact. Consequently, relative decoupling implies a gain in efficiency rather than the removal of the link between impact and GDP. In this chapter, the economics of energy (in terms of production), green growth, and their impact on the environment will be discussed in terms of decoupling. © 2023 selection and editorial matter, Muhammad Asif. All rights reserved.
