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2023 Kahramanmaraş Deprem Fayları Üzerinde Gözlemler ve Değerlendirmeler
No full textOne of the largest earthquakes hits the Kahramanmara & scedil;region and caused a major disaster. Numerous papers based on satellite data and computer modeling have since been published, but the models commonly contradict each other. A long time has passed since then, and the primary purpose of this publication is now to view the main topics, namely, the major fault zones that caused the earthquakes and the tectonic regimes that generated them, based primarily on the field data that has long been ignored. The faults that affected the February 6Kahramanmara & scedil;earthquakes are extensions of the regional-scale strike-slip faults known from Anatolia and its surroundings. These include the East Anatolian Transform Fault, the Dead Sea Transform Fault, the Antakya Transform Fault, the Sar & imath;z-Saimbeyli Mega Shear Zone, the faults of the Foreland Fold-Thrust Belt, and the Karasu Graben boundary faults. The interactions among these faults appear to have increased the magnitude of the earthquakes.Emerging Sources Citation Inde
Epistemic Norm Differences Matter
No full textTempleton Religion Trust [TRT0424]This work was supported by Templeton Religion Trust: [grant number TRT0424]
Modern Dünyanın Çoklu Krizlerine Holistik Düşünce Üzerinden Bakış
No full textGünümüz dünyasının beraberinde getirdiği iklim krizi, pandemi, ekonomik eşitsizlik gibi çoklu krizler birbirine bağlı ve karmaşık yapıdadır. Bu karmaşık yapı, indirgemeci ve tek yönlü bir bakış açısı yerine bu sistemler arası ilişkileri anlamaya imkân sağlayacak karmaşık düşünce biçimini gerektirmektedir. Olguları kategorilere ayırarak ilerleyen analitik düşüncenin ötesinde olgular arasındaki ilişkileri vurgulayan holistik düşüncenin, modern dünyanın krizlerine çözüm üretme noktasında etkili bir yaklaşım sağlayabileceğini öneriyoruz. Bu amaçla, farklılıklarının ve temel ilkelerinin kapsamlı bir şekilde anlaşılabilmesi adına öncelikle analitik ve holistik düşünce biçimlerinin felsefi ve evrimsel kökenlerini ele aldık. Daha sonrasında holistik düşüncenin günümüzün ve geleceğin önemli problemlerinden olan iklim krizi, COVID-19 pandemisi ve ekonomik eşitsizlik özelinde sağlayabileceği avantajları çeşitli bulgularla özetledik. Ele alınan bulgular ışığında, kavramları çözümleme ve tanımlama açısından analitik düşüncenin önemini vurgularken holistik düşüncenin bu parçalar arasındaki ilişkileri anlamadaki tamamlayıcı rolünü savunuyoruz. Bu bütüncül yaklaşımın, modern dünyanın karşı karşıya olduğu çoklu krizleri kapsamlı bir şekilde ele almak için önemli bir çerçeve sunacağını öne sürüyoruz
A Modified Plate Design for Capacitive Wireless Power Transfer Systems
No full textThe share of capacitive wireless power transfer in recent wireless power transfer research has been increasing. The advantage of these systems mainly comes from their simple structures. The power is transferred between the plates, and there is no need for magnetic shielding as there is no magnetic field involved. The transferred energy depends on the capacitance of the plates, and increasing the effective area of the plate without changing its size can be effective. This paper proposes a simple technique to increase the effective area of plates. Basically, the effective area is increased by grooving the surface, like the fins of heat sinks. The proposed technique has been tested on a four-plate horizontal structure. The results show that the proposed method can be effective
Spatial Optimism in Individuals Future Thinking About the Covid-19 Pandemic
No full textSpatial optimism is the tendency to underestimate the severity of environmental threats in local relative to global contexts. We investigated whether spatial optimism was evident in people's beliefs about the estimated duration and severity of the COVID-19 pandemic. Participants from 15 countries provided estimates of (i) when the pandemic would be brought under control and (ii) infection rates for their country and globally. Overall, individuals estimated that the pandemic would end sooner and with a lower infection rate in their own country relative to the rest of the world. This spatial optimism bias was moderated by the severity of COVID-19 at the country level, such that the bias was greatest in countries with lower levels of pandemic severity. Findings parallel those observed for environmental threats and provide evidence for a spatial optimism bias in a distinct domain of collective thought. Implications for public-health messaging are discussed.Social Science Citation Inde
A Holistic Empirical Approach To Marketing Activities and Performance Interaction in Banking Industry: the Mediating Role of Customer-Based Brand Equity
No full textPurpose: This paper aims to examine the direct impacts of marketing resources and marketing activities on several business performance indicators in the banking industry and the indirect effects through customer-based brand equity. Design/methodology/approach: We use a holistic empirical approach based on resource-based view and marketing productivity chain. The main study consists of a secondary analysis using quarterly data of fourteen banks over four years. We analyze the data using fixed-effect panel data regression, namely seemingly unrelated regressions. Findings: We find that customer-based brand equity is one of the most influential factors on business performance. Moreover, the indirect effect through customer-based brand equity should be considered in improving business performance. Marketing-related financial resources positively impact customer-based brand equity and business performance. Regarding marketing activities, pricing strategies affect the bank preferences of customers, which in turn affect the growth of deposit volumes and churn rates. Additionally, the number of bank branches positively impacts business performance. Advertising spending on different media has differentiated impacts on the performance indicators; thus, the allocation of advertising budget and advertising planning are critical. Originality/value: This study examines the inter-relationships among marketing resources, marketing activities, consumer response through brand equity and marketing performance. This study contributes to the literature by integrating the resource-based view and the marketing productivity chain to analyze the inter-relationships using panel data and several sector-related metrics. This study provides valuable insights to decision-makers in the banking industry. © 2024, Emerald Publishing Limited.Banks Association of TurkeySocial Science Citation Inde
Secure Quantum-Based Adder Design for Protecting Machine Learning Systems Against Side-Channel Attacks
No full textMachine learning (ML) has recently been adopted in various application domains. Usually, a well-performing ML model relies on a large volume of training data and powerful computational resources. Recently, hardware accelerators utilizing field programmable gate arrays (FPGAs) have been developed to provide high-performance hardware while maintaining the required accuracy for ML tools. However, one of the main challenges hindering the FPGA-based ML models is their susceptibility to adversarial attacks, such as physical side-channel attacks. In this study, various kinds of countermeasures, including masking and hiding techniques, are examined to mitigate the aforementioned shortcomings and enhance the security of FPGA-based ML systems. In addition to FPGA-based defenses, the advantages of quantum computing for designing circuits to enhance data protection are also elaborated. However, concerning FPGA-based ML models, which are used to defend against physical side-channel attacks, quantum dot cellular automata (QCA) offers a more promising option. Its inherent security, lower power consumption, higher speed, and reduced vulnerability to side-channel leakage make it the best alternative. Therefore, this study emphasizes the implementation of the quantum nature of QCA to protect valuable information against physical side-channel attacks. It also offers quantum masking circuits for protecting sensitive information in machine learning systems, including XOR, adder, and RCA. Furthermore, the presented work advocates for leveraging QCA technology to augment the security of machine learning systems by mitigating the disclosure of sensitive data. The proposed QCA-based masked designs, which include an adder and a ripple carry adder (RCA), pose some qualities, which include a single-layer structure, minimal cell count, and low latency. When compared with the best counterparts among the recommended designs, these designs exhibit significant improvements regarding cell consumption and occupied area, with improvements of 33.3% and 36.6% respectively.Science Citation Index Expande
Universities Between Revenue and Status: a Typology of Organizational Responses
No full textPrior research on behavioral responses to performance has provided limited attention to how different types of performance outcomes interact to affect organizational reactions. Focusing on the pursuit of revenue and status goals by private universities, we offer a typology of organizational responses (i.e., reducing ambitions, compensatory strategies, and complementary use of slack to pursue new opportunities) which are shaped by the set of challenges and capabilities that poor and superior performance in these goal dimensions present. When poor performance in both revenue and status leads to different types of liabilities that together result in a low likelihood of recovery, universities respond by reducing ambitions and diversifying into a lower status market segment, which offers a more promising path to survival. In response to a mixed performance outcome in revenue and status, universities employ compensatory strategies where they make use of the achievement in one goal dimension to repair the damage in the other. Finally, universities expand the scope of activities when they achieve superior performance in both goals, and the resulting slack in revenue and status provides complementary capabilities to pursue new opportunities. These findings extend the early Carnegie proposal and indicate that the portfolio of organizational responses to performance gaps may be broader than previously considered. © 2023 European Academy of Management.Social Science Citation Inde
A Nano-Scale Design of Vedic Multiplier for Electrocardiogram Signal Processing Based on a Quantum Technology
No full textHeidari, Arash/0000-0003-4279-8551; Ahmadpour, Seyed-Sajad/0000-0003-2462-8030An electrocardiogram (ECG) measures the electric signals from the heartbeat to diagnose various heart issues; nevertheless, it is susceptible to noise. ECG signal noise must be removed because it significantly affects ECG signal characteristics. In addition, speed and occupied area play a fundamental role in ECG structures. The Vedic multiplier is an essential part of signal processing and is necessary for various applications, such as ECG, clusters, and finite impulse response filter architectures. All ECGs have a Vedic multiplier circuit unit that is necessary for signal processing. The Vedic multiplier circuit always performs multiplication and accumulation steps to execute continuous and complex operations in signal processing programs. Conversely, in the Vedic multiplier framework, the circuit speed and occupied area are the main limitations. Fixing these significant defects can drastically improve the performance of this crucial circuit. The use of quantum technologies is one of the most popular solutions to overcome all previous shortcomings, such as the high occupied area and speed. In other words, a unique quantum technology like quantum dot cellular automata (QCA) can easily overcome all previous shortcomings. Thus, based on quantum technology, this paper proposes a multiplier for ECG using carry skip adder, half-adder, and XOR circuits. All suggested frameworks utilized a single-layer design without rotated cells to increase their operability in complex architectures. All designs have been proposed with a coplanar configuration in view, having an impact on the circuits' durability and stability. All proposed architectures have been designed and validated with the tool QCADesigner 2.0.3. All designed circuits showed a simple structure with minimum quantum cells, minimum area, and minimum delay with respect to state-of-the-art structures.Science Citation Index Expande
Stock Price Forecasting Through Symbolic Dynamics and State Transition Graphs With a Convolutional Recurrent Neural Network Architecture
No full textAccurate stock price forecasting remains a critical challenge in financial analytics due to volatile market conditions, non-stationary dynamics, and abrupt regime shifts that often defy traditional modeling techniques. This study proposes a comprehensive framework for stock price forecasting that integrates symbolic dynamics, graph-based state representations, and deep learning. By converting continuous-valued stock prices into discrete symbolic states representing amplitude and trend information, the method constructs transition matrices capturing probabilistic relationships within financial time series. These transition matrices are then processed by a convolutional recurrent neural network (CRNN), in which convolutional layers isolate local spatial dependencies in the symbolic-state domain, while recurrent LSTM layers capture multi-scale temporal dynamics extending across multiple time horizons. Experimental evaluations are conducted over prediction horizons of 1 day, 10 days, and 100 days, spanning pre-COVID, COVID, and post-COVID market regimes. The results indicate that while longer prediction horizons naturally incur greater forecasting uncertainty due to compounding variability, the integration of symbolic-state preprocessing with deep temporal modeling demonstrates significant robustness in handling non-stationary financial environments. During the stable pre-COVID period, the proposed methodology achieves reductions in mean squared error (MSE) of up to 98% relative to the volatile COVID phase, highlighting its capability to effectively leverage well-defined market patterns in stable economic conditions. Furthermore, the model consistently delivers competitive forecasting performance across all prediction horizons and market regimes. Collectively, these findings emphasize the potential of symbolic-state-based deep learning architectures as a viable pathway to address the complexity and volatility characteristic of modern financial markets. © The Author(s) 2025.Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TUBITA