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Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Now showing 1 - 10 of 1351
  • Article
    Widening the Moral Circle: Perceived Responsibility and Guilt as Mediators of Moral Expansiveness and pro-Environmental Behavior
    (Springer, 2026) Sari, Erkin; Coskun, Muhammet; Cingoz-ulu, Banu; Candanoglu, Inci
    Previous research has shown that moral constructs, such as personal norms, play a significant role in shaping individuals' pro-environmental engagement. However, the specific influence of moral expansiveness on such behaviors has received limited attention in the existing literature. This study aims to investigate the relationship between moral expansiveness and pro-environmental engagement within the Turkish context, which is particularly vulnerable to the impacts of climate change. It specifically examines the mediating roles of perceived environmental responsibility and environmental guilt to better understand the mechanisms underlying this association. In total, 244 undergraduate students (167 women, 76 men, 1 did not state; Mage = 21.95, SDage = 2.58) participated in the current study in exchange for course credit. Findings indicated that moral expansiveness indirectly predicted pro-environmental behaviors through both perceived environmental responsibility and environmental guilt, although its direct effect was not significant. Perceived environmental responsibility and environmental guilt both significantly predicted pro-environmental behaviors. Additionally, individuals with more left-leaning political views reported higher levels of pro-environmental behavior. This study highlights how broader moral concern can support sustainability, while contributing to the inclusion of non-Western contexts in environmental psychology.
  • Conference Object
    Web-Based Comparative Analysis Framework for Metaheuristic Optimization Algorithms: A Unified Educational Approach
    (Institute of Electrical and Electronics Engineers Inc., 2026) Durmus, Ali; Eryasar, Selin; Kurban, Rifat
  • Article
    Unsettled Grounds, Enduring Bonds: A Literature Review on Employee Engagement during Organizational Change
    (Routledge Journals, Taylor & Francis Ltd, 2026) Abbas, Alhamzah F.; Ahmed, Ayesha; Usman, Muhammad; Shah, Syed Haider Ali
    This systematic review critically examines how employee engagement is conceptualized and operationalized within the context of organizational change, aiming to uncover prevailing themes, highlight conceptual inconsistencies, and identify gaps in the literature to advance understanding in evolving organizational settings. Guided by the the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA framework, the study analyzes 29 peer-reviewed journal articles published between 2006 and 2025, retrieved from the Scopus database, employing thematic synthesis and citation mapping to explore both organizational and individual-level influences on engagement during change. The findings reveal a dual-level framework: at the organizational level, leadership, organizational support, communication, and cultural and contextual dynamics play a central role, while at the individual level, psychological and emotional factors, behavioral patterns, attitudes toward change, and opportunities for skill development and career progression are key drivers. This review contributes by clarifying conceptual boundaries, identifying underexplored dimensions, and providing actionable insights for leaders and HR practitioners to sustain and enhance employee engagement during periods of organizational transition.
  • Conference Object
    Unified Control: Managing Multiple PLCs Through a Single HMI Interface via MODBUS RTU Protocol
    (Institute of Electrical and Electronics Engineers Inc., 2026) Aykut, Ercan; Yavuz, Izzet; Erdogan, Kubra; Benli, Sena Nur; Mumcu, M. Cihat
  • Article
    Surface Integrity and Tool Wear in S2-GFRP Milling: Experimental and Statistical Evaluation of Cutting Parameters and DLC and TiAlN Tool Coatings
    (Springer London Ltd, 2026) Danisman, Sengul; Yilmaz, Cagatay; Ersoy, Emin; Kesriklioglu, Sinan
    In this study, the surface integrity of S2-glass fiber-reinforced polymer (S2-GFRP) composites during milling with carbide cutters was investigated using a two-phase experimental design, focusing on surface roughness (Ra), burr area, and tool wear (VB). In the first phase, using a Taguchi L9 design, the effects of coating type (uncoated, TiAlN, DLC), spindle speed (2000-6000 rpm), and feed rate (0,15-0,25 mm/rev) on Ra and burr area were evaluated. In this short machining range where tool wear was negligible, the optimal combination yielding the lowest Ra (approximate to 0.97 mu m) and the minimum burr area (approximate to 231 mm & sup2;) was determined to be 4000 rpm, 0,15 mm/rev, and the DLC-coated tool. Regarding the effect of tool material on Ra, the DLC-coated tool provided approximately 4 and 2 times better results than the uncoated and TiAlN-coated tools, respectively. In the second phase, experiments extended up to 130 passes with this optimal parameter set showed that Ra increased significantly with increasing VB, and the burr area exhibited threshold-like behavior. In particular, a sudden increase in Ra and the burr area was observed when the VB approximate to threshold of approximately 100 mu m was exceeded; partial regression analyses confirmed different burr-formation tendencies in the low- and high-wear regimes. The results reveal that DLC coating initially provides superior performance in S2-GFRP milling, but surface degradation accelerates after the critical VB threshold.
  • Article
    Predicting Respiratory Infection and Symptoms Development Using Gene Set Enrichment Scores and Machine Learning
    (Elsevier Sci Ltd, 2026) Aydin, Zafer; Isik, Yunus Emre
    Recent advancements in precision medicine enable personalized predictions grounded in individual-level genetic data. However, relying solely on a single type of data can decrease prediction accuracy and limit the biological interpretability of the resulting models. Incorporating predefined genetic knowledge, such as derived gene sets, can improve performance and provide deeper biological insights for complex diseases, including respiratory infections. This study aimed to evaluate the usability of enrichment scores (ES), calculated using gene sets from the Molecular Signatures Database (MSigDB), as a feature representation for machine learning models to predict respiratory viral infections and symptom development. In addition, the proposed feature representation approach was extensively compared with the de facto gene-level expression representation. A total of 36,834 predefined gene sets were compiled from the MSigDB, and their ES values were calculated. Experiments used the GSE73072 dataset from Gene Expression Omnibus, containing gene expression profiles before and after virus exposure. Various machine learning and feature selection algorithms were applied to ES-based and probe-level feature sets. The results showed that both feature representation approaches achieved an area under the precision-recall curve (AUPRC) value greater than 0.90 for all tasks. Compared with the Respiratory Viral DREAM Challenge leaderboard phase, our models showed a 14.8% improvement in pre-exposure predictions (T0) and a 17.4% improvement in symptom classification. Using enrichment scores as a feature representation generally resulted in better performance than probe-level representation when predicting respiratory infections and symptom development. Identifying key gene sets through feature selection and comparing them with essential genes for respiratory viruses enabled a more comprehensive analysis, providing deeper insights into the pathways that contribute to these predictions.
  • Conference Object
    Retrieval-Augmented Generation for Technical Intelligence in Aerospace and Defense Systems
    (Institute of Electrical and Electronics Engineers Inc., 2026) Yener, Fehmi; Duman, Merve; Bakal, Gokhan
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  • Article
    From Agility to Advocacy: Exploring How Gender Moderates the Impact of Social Media Agility on Brand Trust and Influencing Behavior
    (Palgrave Macmillan Ltd, 2026) Bozkurt, Sıddık; Gligor, David; Hollebeek, Linda D.; Sarp, Serap
    This research investigates the effect of perceived social media agility (P-SMA) on customers' influencing behavior, a theoretical subset of engagement behavior, with brand trust acting as a mediator and gender (male/female) as a moderator. It also explores how these relationships differ across age groups. Two online surveys were conducted: Study 1 with 165 younger participants and Study 2 with 178 adults. Using PROCESS Macro Models 4 and 7, we tested direct, mediated, and moderated mediation effects. Both studies found that P-SMA enhances brand trust, which subsequently mediates its influence on customer behavior. Study 2 confirmed these results, showing that gender moderates the relationship between P-SMA and both brand trust and influencing behavior, with stronger effects observed among females (vs. males) in both samples. The findings highlight the importance of tailoring social media strategies to gender-based engagement patterns. Crafting content and interaction styles that foster trust can improve influence and advocacy, especially when agility is a key element of the brand's digital presence. This research integrates P-SMA, brand trust, and customer influence behavior within a moderated mediation model. Using two age-diverse samples, it shows gender shapes reactions to brand agility, while age differences remain non-significant across both datasets.