WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653

Browse

Filters

2021 - 2026779

Settings

Start date: 2021Scopus Q: search.filters.scopusQuartile.Q1

Search Results

Now showing 1 - 10 of 779
  • Corrigendum
  • Article
    A Multi-Scenario Evaluation of Adaptive Fuzzy Logic Algorithms for Intelligent Traffic Signal Management in Urban Intersections
    (Nature Portfolio, 2026) Dvorsky, Jiri; Martinovic, Jan; Shaheen, Sumaira; Riaz, Muhammad Bilal; Qadri, Syed Shah Sultan Mohiuddin; Slaninova, Katerina
    The article presents a performance analysis of the advanced adaptive control systems of traffic lights that are based on the advanced fuzzy logic. They include Modified Intuitionistic Fuzzy Logic Algorithm (MIFLA) and the Modified Interval Type-2 fuzzy logic (MIT2FL) at a four-leg intersection. In this article, there is an integration of these fuzzy models with the SUMO platform with respect to the weaknesses of the traditional fixed-time traffic lights, particularly in rapidly urbanizing areas. This will be to achieve a real-time dynamic control system. The simulation matrix was a grid of the nine scenarios in which the performance of the controllers was assessed to some extent, depending on the traffic and directional imbalances. The results reveal that the MIT2FL is more effective than the MIFLA and the Modified Webster benchmark. MIT2FL is less divergent, has shorter queuing times, and is more flexible. This occurs when the demand is high, and the traffic conditions are not proportional. This work is significant because it provides fuzzy logic controllers that can deal with uncertainty. It also creates a benchmarking model of a typical multi-scenario. Moreover, it gives the opportunity for reproducibility of the findings in real traffic implementation. The innovations will assist in making the city smarter and easier to move around. They manage congestion, delays, and improve the sustainability of smart traffic control.
  • Article
    A Covering Tour-Based Inventory Routing Framework for Humanitarian Logistics
    (Springer, 2026) Kanik, Zehra B.; Uzgören Kazanç, H. Cansın; Soysal, Mehmet; Coelho, Leandro C.; Kazanc, H. Cansin Uzgoren
    In post-disaster situations, swiftly delivering humanitarian assistance to victims amid chaos and uncertainty poses a significant challenge in practice. Furthermore, efficient distribution of restricted resources, effective inventory control, and optimal resource allocation remain imperative priorities for humanitarian organizations that strive to meet urgent needs under adverse conditions. This study proposes a two-echelon Covering Inventory Routing Problem (CIRP) that integrates the Inventory Routing Problem (IRP) and the Covering Tour Problem (CTP) to support decision-making in the distribution of medical kits in post-disaster humanitarian logistics. A scenario-based probabilistic Mixed-Integer Linear Programming (MILP) model is introduced to decrease costs while adequately addressing unpredictable demand. The applicability of the model was assessed through scenario analysis and a case study. In addition, a three-phase matheuristic algorithm is proposed to solve the CIRP. The results demonstrate that integrating IRP and CTP in a two-echelon structure improves both cost efficiency and the reach of aid delivery under uncertainty. The use of a static-dynamic inventory approach, together with coordinated routing, effectively minimizes emergency shipments and adapts to fluctuating demand, providing valuable support for decision-making in real-time humanitarian contexts. The three-phase matheuristic achieved cost reductions of over 70% relative to the model's incumbent solution within the first hour on large-scale instances, highlighting its practical use in accelerating decision-making amid post-disaster uncertainty.
  • Article
    An Uncertainty-Gated Neuro-Symbolic Framework for High-Coverage Topic Modeling and Trend Analysis in Scholarly Corpora with LLM Assistance
    (IEEE-Inst Electrical Electronics Engineers Inc, 2026) Demir, Onur; Saran, Murat
    The rapid growth of scientific literature demands scalable methods that can track research evolution, yet density-based topic models such as BERTopic systematically exclude low-density documents as outliers, obscuring emerging and niche research areas. We propose a Neuro-Symbolic, Uncertainty-Gated Framework that recovers these outliers through geometric centroid reassignment and an ontological entropy gate derived from the Computer Science Ontology (CSO), routing only genuinely ambiguous cases to a local Large Language Model (Qwen2.5-14B via Ollama). A controlled ablation study demonstrates that centroid reassignment provides the largest coverage gain (+ 22.9 percentage points (pp)), the CSO entropy gate preserves niche-topic integrity, and selective LLM routing adds an additional + 5.9 pp. On 12,535 Turkish computer engineering theses (TR-CS; 2001-2025), the full pipeline raises coverage from 75.5% +/- 1.2 % (Bare BERTopic) to 95.7% +/- 0.4% (five-seed means) while maintaining competitive coherence (NPMI = 0.112 +/- 0.006) and cross-seed stability (AMI = 0.832 +/- 0.015), at similar to 15x fewer LLM calls than a fully generative Pure-LLM baseline. Mann-Kendall trend tests on the high-coverage series identify 69 statistically significant trends (FDR q < 0.05), and cross-corpus validation on similar to 200K arXiv CS abstracts confirms that the architecture generalizes beyond the primary dataset. The framework offers a reproducible, cost-effective solution for monitoring scientific developments in rapidly evolving fields.
  • Article
    On Multiplicative Fractional Operators of Hadamard and Katugampola Types in G-Calculus and Related Hermite-Hadamard Inequalities
    (World Scientific Publ Co Pte Ltd, 2026) Abdeljawad, Thabet; Lakhdari, Abdelghani; Jarad, Fahd; Budak, Hüseyin; Alqudah, Manar A
    This paper explores the extension of classical fractional operators to the framework of G-calculus, a non-Newtonian calculus in which differentiation and integration are defined via multiplicative analogs of their classical counterparts. We begin by recalling key concepts from both fractional calculus and G-calculus. Next, we revisit the recently introduced multiplicative Riemann-Liouville fractional operators and extend the multiplicative Riemann-Liouville fractional derivative to arbitrary order alpha > 0. Building on this foundation, we introduce multiplicative versions of the Hadamard and Katugampola fractional integrals and derivatives. Finally, we establish Hermite-Hadamard inequalities for both newly defined integrals.
  • Article
    A User-Centric Domain-Adaptive Quality Model for Benchmarking Generative AI Systems
    (Institute of Electrical and Electronics Engineers Inc., 2026) Esirik, Buse Erol; Gokalp, Ebru
    Generative AI (GenAI) systems operate across diverse application domains where quality priorities shift dynamically in response to user expectations and contextual requirements. This variability calls for a comprehensive quality model that enables stakeholder-driven weight recalibration to support product evaluation and selection. However, existing approaches do not simultaneously account for GenAIspecific attributes, user-centric quality priorities, and domain-adaptive evaluation mechanisms. To bridge this gap, this study proposes the User-Centric Generative AI Quality Model (UC-GAIQM), a domainadaptive framework in which Analytic Hierarchy Process (AHP) weights can be recalibrated to reflect quality priorities across different application scenarios and user profiles. The proposed model was developed through a mixed-methods, three-phase research design. In the first phase, a Systematic Literature Review (SLR) and Multivocal Literature Review (MLR) established the theoretical foundation. In the second phase, a quantitative survey of active GenAI users (n = 111) validated eight quality dimensions through exploratory and confirmatory factor analysis (alpha = 0.94, KMO = 0.88, CFI = 0.943). In the third phase, a three-round expert-driven Delphi study confirmed the structural validity of the model (Kendall's W = 0.84), and an AHP study demonstrated the weight recalibration mechanism. UC-GAIQM comprises eight quality dimensions and thirty sub-dimensions aligned with key ISO/IEC standards, the NIST AI Risk Management Framework, and the EU AI Act. The results demonstrate that the proposed model facilitates dynamic, context-sensitive evaluation of GenAI products by enabling quality priority adaptation across application domains.
  • Article
    A Metaverse-Based Fully Immersive Training for Temporomandibular Joint: A Pilot Study
    (Wiley, 2026) Ozcelik, Erol; Ekici, Saliha Zerdali; Basmaci, Fulya; Cagiltay, Nergiz Ercil; Kilicarslan, Mehmet Ali
    Objective Understanding the temporomandibular joint (TMJ) can be challenging with conventional methods, as its complex anatomy, comprising the articular disc, mandibular condyle, and temporal bone, requires detailed visualisation. Traditional approaches like textbooks and static images often fall short, whereas modern tools such as 3D modelling and virtual reality (VR) offer more effective alternatives. Metaverse technology further enhances this by creating interactive, immersive and collaborative learning environments that simulate real-world experiences. While VR is increasingly used in dental education, research on fully immersive metaverse-based learning remains limited.Methods In this pilot study, a custom metaverse environment was developed to teach TMJ concepts. Then, the effectiveness of conventional and metaverse-based teaching methods in improving dental students' understanding of the TMJ was evaluated experimentally. A randomised trial was conducted with 120 first-year dental students, divided into three groups: classical lecturing, metaverse-based training and a combination of both.Results Findings indicate that students in the metaverse and combined groups outperformed those in the classical lecturing group, with no significant difference between the two metaverse-involved groups.Conclusions This suggests that for highly complex anatomical structures like the TMJ, metaverse-based training alone may be sufficient, eliminating the need for additional traditional instruction. The study highlights the metaverse's potential to enhance dental education by providing a fully 3D, interactive learning experience.
  • Article
    Women’s Labor Force Participation After Disasters: The Case of Nurdağı, Türkiye, Following Kahramanmaraş Earthquakes
    (Wiley, 2026) Orhan, Ezgi; Wein, Anne M.; Kroll, Cynthia A.
    Economic functionality is essential for the recovery of cities and communities following disasters. A crucial factor in reducing business disruptions and guaranteeing their continuity is the capacity of employees to resume work. Facilitating the reintegration of employees into the workforce can expedite their post-disaster recovery process and assist the impacted communities in their recuperation. Nevertheless, when women encounter numerous challenges in returning to the workforce, the share of women's employment declines. This study aims to elucidate the challenges and expectations of women living in the region directly impacted by the February 6, 2023, Kahramanmaraş earthquakes regarding their participation in the post-disaster job market. Nurdağı town in Gaziantep province, where the impacts of the February 6th earthquakes are evident, was selected as the case study. One year later, a survey was administered to 375 women living in a Nurdağı container city. The study explores earthquake damages and losses to their homes and workplaces, their migration status post-disaster, the challenges faced in labor market participation, and their expectations for employment. The responses clarify specific barriers to women's labor force participation in the first year following the earthquakes and the type of programs that could help overcome the difficulties faced. While state-sponsored temporary work programs facilitate women's employment in the short run, these jobs may not align with skills and prior work experience and do not address the longer-term needs for women seeking stable, permanent income-generating positions. Amid extensive destruction, the establishment of a secure living environment had become the most basic need, while gender-specific supports are also important in restoring women's labor force participation, including psychological treatment options, programs to assist with the care of children and other dependents, and vocational development. The study highlights considerations when providing support for both employees and recovering businesses after a disaster.
  • Article
    Sustainable Development Solutions Network (SDSN) Reports Between 2018 and 2023: Malmquist Index Analysis for the Performance of OECD Countries
    (Wiley, 2026) Kalemci, R. Arzu; Unsal, Mehmet Guray; Alp, Ihsan; Celik, Busra Agan; Dalkilic, Altay Ogulcan; Agan Celik, Busra
    In 2015, the United Nations (UN) adopted the 17 Sustainable Development Goals (SDGs), calling for urgent action to end poverty, reduce inequality, and secure a sustainable future. Within this global agenda, the commitment of the Organization for Economic Co-operation and Development (OECD) is particularly significant given its institutional capacity and international influence. This study examines Sustainable Development Solutions Network (SDSN) reports for 2018-2023 using the Malmquist Productivity Index (MPI) as an alternative performance measurement tool. The MPI allows assessment of annual changes in total factor productivity and efficiency differences across OECD members. Rather than directly measuring absolute progress toward the SDGs, the analysis evaluates relative efficiency dynamics among countries in transforming sustainability-related indicators over time. The results provide comparative insights into how OECD countries improve or deteriorate in their relative sustainability performance within the observed period. The results show that OECD countries display uneven progress, with some improving while others stagnate or decline, and reveal persistent disparities in efficiency and productivity. By providing a dynamic and comparative evaluation, the study contributes to quantitative SDG monitoring and offers insights for policymakers seeking to enhance sustainable development strategies.
  • Article
    Messaging Brand Experience: Brand Ethicality, Brand Trust, Brand Attitudes
    (Taylor & Francis Ltd, 2026) Ozsacmaci, Bulent; Kilic, Tamer; Dursun, Tolga; Celik, Suleyman
    Messaging applications (e.g. WhatsApp/Telegram/Signal-type platforms) have become high-frequency touchpoints within integrated marketing communications. This study examines how the brand experience of messaging applications translates into brand attitudes through two parallel mechanisms: perceived brand ethicality and brand trust. We theorize that ethicality and trust serve as communication signals that arise from interface-level design and governance choices, such as plain-language privacy notices, granular consent flows, visible encryption and reliability cues, and third-party assurances. Using survey data from active messaging users, we validated the measurement model via CFA and tested a parallel-mediation structure with bootstrapped indirect effects. Results indicate that messaging brand experience exerts a positive direct effect on brand attitudes and significant indirect effects through both brand ethicality and brand trust, confirming that persuasion in messaging hinges on credibility and transparency signals embedded in the journey. Robustness checks across alternative specifications support these findings. Theoretically, the paper integrates behavioural foundations of persuasion with corporate communication by reframing governance artefacts as source/message credibility cues that shape ethical inferences and risk reduction. Managerially, the results recommend making ethical and reliability signals salient within messaging flows, aligning privacy-by-default language with value propositions, and orchestrating assurance elements across channels to improve attitudes and downstream performance.