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How Did Turkish Higher Education Respond To Emergency Distance Education in the Covid-19 Pandemic? Acceptance and Use by Turkish Academics
No full textThe COVID-19 pandemic necessitated a rapid transition to online education, presenting adaptation challenges for faculty members unfamiliar with distance education methodologies. Certain institutions have demonstrated greater efficacy owing to prior experience in this domain. This study investigates faculty acceptance and utilisation of mandatory distance education employing the UTAUT2 model, with age and gender as moderating variables, analysed through structural equation modelling. Data from 3631 participants were collected using a 25-item scale encompassing seven subdimensions: performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit and price value. The research assessed the impact of these dimensions on behavioural intention and usage, with gender moderating several relationships, while age did not exhibit a significant moderating effect. The findings, consistent with the extant literature, suggest that training and experience in distance education could enhance acceptance and utilisation among faculty members.The Scientific and Technological Research Council of Turkiye (TUEBITAK) [120K209]This project was funded by The Scientific and Technological Research Council of Turkiye (TUEBITAK) [Project Grant #120K209].Social Science Citation Inde
Advanced Restoration Management Strategies in Smart Grids: the Role of Distributed Energy Resources and Load Priorities
No full textAhmadi, Bahman/0000-0002-1745-2228; Ozdemir, Aydogan/0000-0003-1331-2647Fast restoration following long outages is a challenge in the smart city management process. It is necessary to accurately characterize the real operating conditions of the system for optimal restoration. This study focuses on two key factors of a practical distribution system restoration. The first factor is cold load pickup (CLPU), which commonly occurs after an outage and is caused by thermostatically controlled loads. A time-dependent CLPU is modeled to accurately describe the restored load behaviors. The second factor is the effect of the distributed generators (DG), energy storage systems (ESSs), and load priority factors on the system's restoration process. To address this challenge, a robust optimization model is proposed that fully considers the effect of DG, and ESS units and uncertainty of CLPU. The proposed models are tested on the IEEE 33-node and 69-node test systems using the Advanced Grey Wolf Algorithm (AGWO). The simulation scenarios are designed to uncover optimal scheduling strategies for the restoration process corresponding to each Pareto solution of a previous study. The results are discussed for several distinct initial conditions. Moreover, a comparative evaluation is done, contrasting the outcomes achieved through the AGWO algorithm with those stemming from alternative heuristic methods.EU [957682]; The Scientific and Technological Research Council of Turkey TUBITAKThe funding for this research is provided by the EU HORIZON 2020 project SERENE, grant agreement No 957682, and the "117E773 Advanced Evolutionary Computation for Smart Grid and Smart Community" project, conducted under the 1001 Project framework organized by "The Scientific and Technological Research Council of Turkey TUBITAK".Science Citation Index Expande
Strategic Analysis of E-Trade Platforms in Automotive Spare Part Sector: a T-Spherical Fuzzy Perspective
No full textChatterjee, Prasenjit/0000-0002-7994-4252; Aytekin, Ahmet/0000-0002-1536-7097; Korucuk, Selcuk/0000-0003-2471-1950; Pamucar, Dragan/0000-0001-8522-1942E-trade platforms are software applications that enable businesses to conduct online sales and manage their digital storefronts. These platforms provide a range of tools and features to facilitate the creation, operation, and management of an online business. This study comprehensively evaluates e-trade platforms within the automotive spare parts industry, examining various critical aspects to identify the optimal platform. The evaluation includes an in-depth analysis of the current state of the platforms, exploration of potential strategies and approaches for improvement, and identification and analysis of challenges and barriers. To address these issues, the study employs problem-solving within the framework of expert evaluations based on criteria defined by an extensive literature review. T-Spherical fuzzy (T-SF) subjective weighting approach and T-SF-weighted aggregated sum product assessment (WASPAS) method are used for this purpose. The analysis reveals that "security" is the most crucial criterion, with Amazon emerging as the most prominent e-trade platform. The findings indicate that prioritizing security, discounts, and delivery time will enable e-commerce platforms to gain a competitive edge. The study evaluates international e-commerce platforms, identifying weaknesses in critical business areas key competitive advantage factors, and offering forward-thinking recommendations. This research has significant implications for the rapid and effective development of logistical partnerships with e-trade platforms across various industries. Additionally, it serves as a foundational basis and template for future research in the ecommerce sector, particularly within the automotive spare parts industry.Science Citation Index Expande
Revitalizing Tourism Research
No full textBuckley, Ralf/0000-0003-0442-5818Social Science Citation Inde
A New Quantum-Enhanced Approach To Ai-Driven Medical Imaging System (Vol 28 , 213 , 2024)
No full textScience Citation Index Expande
Integration of Emerging Technologies in Tourism and Hospitality Curriculum: an International Perspective
No full textThis paper investigates the status of emerging technologies, how they can be integrated into the curriculum, the skills students can acquire through these technologies, and the employment opportunities they create in the tourism and hospitality industry. In the study, a content analysis was conducted on the curriculum of 65 undergraduate tourism and hospitality management programs, followed by an analysis of data from 28 academics to explore the role of emerging technologies in the curriculum. We have observed six core topics. Technology courses had the lowest proportion. We further observe four categories of skills that emerging technologies may provide students, highlighting their potential to shape future career opportunities. Building on these findings, the current study contributes to the literature by linking these skill sets - digital and technological, theoretical, operational, and managerial - to emerging job roles such as virtual reality tour designers, competent tourism developers, and AI-driven marketing specialists. Furthermore, the study identifies the domains where emerging technologies have the most relevance and outlines which purpose they may be included in the tourism and hospitality curriculum as a course. Thus, it forwards previous studies emphasizing the importance of emerging technologies. The study also suggests the implications for the literature, practice, and public policies.Social Science Citation Inde
Inequality, Post-Covid Inflation and Incomes Policy in a Two Household Sfc Model for the Uk Economy
No full textBu tez, gelir çatışması teorisi perspektifinden enflasyon ve gelir eşitsizliği arasındaki etkileşime odaklanarak Birleşik Krallık ekonomisinde COVID sonrası enflasyonunun dinamiklerini incelemektedir. Çalışma, Birleşik Krallık ekonomisine yönelik uyarlanmış ilk iki-haneli Stok-Alım Tutarlı (SFC) modelini sunarken eşitsizlik ve enflasyon dinamiklerini analiz etmek için kapsamlı bir çerçeve sağlamaktadır. Modelin sağladığı bulgular, interaktif politika simülasyonları ve eğitim uygulamalarını mümkün kılan yenilikçi bir R Shiny tabanlı araç olan UK-SFC Uygulaması'nın geliştirilmesiyle daha da güçlendirilmiştir. Bulgular, bölüşüm dinamikleriyle yönlendirilen gelir taleplerinin enflasyonist baskılarda merkezi bir rol oynadığını ve gelir politikası tasarımının kritik önemini göstermektedir. Simülasyon sonuçları, gelir eşitsizliğini ele alacak şekilde iyi tasarlanmış bir gelirler politikasının, hem enflasyonu hem de gelir eşitsizliğini aynı anda azaltabileceğini göstermektedir. Araştırma, enflasyon ve eşitsizliği ele almak için gelir politikasının çift yönlü bir mekanizma olarak benimsenmesini savunmaktadır ve etkili ekonomik sonuçlar elde etmede, etkin gelirler politikalarının kritik önemini vurgulamaktadır.This thesis examines the dynamics of post-COVID inflation in the UK economy, focusing on the interplay between inflation and income inequality through the lens of income conflict theory. It introduces the first two-household Stock-Flow Consistent (SFC) model tailored to the UK economy, providing a comprehensive framework for analyzing inequality and inflation dynamics. The model's insights are further enhanced by the development of the UK-SFC App, an innovative R Shiny-based tool enabling interactive policy simulations and educational applications. The findings reveal that income claims, driven by distributive dynamics, play a central role in inflationary pressures and demonstrate the critical role of incomes policy design. Simulation results indicate that an incomes policy, when well-designed by addressing income inequality, may simultaneously reduce inflation and income inequality. The research advocates for the adoption of incomes policy as a dual mechanism to address both inflation and inequality, by emphasizing the critical importance of effective incomes policies in achieving effective economic outcomes
Processor Design and Application of Futuristic
No full textMany devices consist of low-power processor. Quantum-dot-cellular-automata (QCA) based processor designs provide enhanced performance compared with conventional metal-oxide-semiconductor (MOS) based processors. Nanocomputing-based processors are often energy-efficient. We have developed Nanotechnology QCA-based different subcomponents of processor such as 2-to-4 decoder, 3-to-8 decoder, Delay Flip-flop (D-FF), and sequence counter. A potential energy proof has been measured in the 2-to-4 decoder design. The synthesis approach algorithm has been presented for all designs. Further, the potential energy calculation results show for 2-to-4 decoder. According to the synthesis results 2-to-4 decoder has improved 82.3% cell count, 86% area, and 85% latency over previous work. Comparing the primitive results with the prior one, results improved by 64% and 76% in terms of cell count and area in the design of the 3-to-8 decoder. Among the different components of the processor is D-FF, which has an improvement of 66.37% in cell counts and 62.5% in area over the prior design. Primitive results have improved, including latency, cell count, and area, showing the proposed processor design is comparable to lowpower devices and high speed. In terms of balance power, the proposed subcomponent of the processor will benefit low power device.Emerging Sources Citation Inde
Miniaturized Soft Growing Robots for Minimally Invasive Surgeries: Challenges and Opportunities
No full textAdvancements in assistive robots have significantly transformed healthcare procedures in recent years. Clinical continuum robots have enhanced minimally invasive surgeries, offering benefits to patients such as reduced blood loss and a short recovery time. However, controlling these devices is difficult due to their limited accuracy in three-dimensional deflections and challenging localization, particularly in confined spaces like human internal organs. Consequently, there has been growing research interest in employing miniaturized soft growing robots, a promising alternative that provides enhanced flexibility and maneuverability. In this work, we extensively investigated issues concerning their designs and interactions with humans in clinical contexts. We took insights from the open challenges of the generic soft growing robots to examine implications for miniaturization, actuation, and biocompatibility. We proposed technological concepts and provided detailed discussions on leveraging existing technologies, such as smart sensors, haptic feedback, and artificial intelligence, to ensure the safe and efficient deployment of the robots. Finally, we offer an array of opinions from a biomedical engineering perspective that contributes to advancing research in this domain for future research to transition from conceptualization to practical clinical application of miniature soft growing robots.TUBITAK [121C145]This work is funded by TUBITAK within the scope of the 2232-B International Fellowship for Early Stage Researchers Program Number 121C145.Emerging Sources Citation Inde
Strategic Tour Operator Selection in the Tourism Sector Using a Quantum Picture Fuzzy Rough Set-Based Multi-Criteria Decision-Making Approach
No full textTour operator selection is critical for ensuring high-quality services, customer satisfaction, and sustainable tourism development. However, traditional decision-making methods often fail to address the complexities and uncertainties involved in this process. This study introduces a robust decision-making framework that integrates quantum picture fuzzy rough sets (QPFR) with advanced Multi-Criteria Decision-Making (MCDM) techniques to enhance the evaluation and selection of tour operators. The methodology incorporates QPFR, the Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess and rank seven prominent tour operators in the Turkish tourism sector. The evaluation is based on 16 comprehensive criteria: quality, safety, environmental impact, authenticity, and economic contribution. Expert inputs and artificial intelligence techniques were utilized to ensure the model's reliability and accuracy. The findings reveal that the proposed model effectively minimizes uncertainties, provides consistent rankings, and highlights the critical importance of specific criteria in decision-making. Sensitivity analysis confirms the robustness of the results, demonstrating the model's applicability to dynamic and complex decision-making contexts. This study offers theoretical contributions and practical insights for decision-makers, emphasizing the value of integrating advanced computational methods to support sustainable tourism development.Science Citation Index Expande