Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
Browse
4512 results
Search Results
Conference Object Zero Carbon Buildings: A Realistic Approach to Climate Adaptation(Springer International Publishing AG, 2026) Harputlugil, Gülsu UlukavakClimate change continues to be a priority on the agendas of countries and governments today. The approach to this issue can gain significant importance in parallel with the severity of the effects caused by the climate crisis in different regions of the world. To minimize the destruction that climate change will cause over the next 50 years, climate adaptation and mitigation strategies are among the leading strategies of all countries. At this point, it is evident that the decisions made within the framework of the Paris Climate Agreement and the annual United Nations Climate Change Conference (COP) meetings are extremely guiding and accurate. However, within the framework of these agreements, it is necessary to develop strategies that will ensure the adaptation of existing buildings, as well as new buildings, to achieve the 2050 targets defined for the building sector. This study will discuss strategies to minimize the impacts that buildings constructed in the past decade and those that will be constructed in the next decade will face as part of the existing building stock in 2050. There is a need to evaluate the measures that can be taken today to ensure that buildings constructed according to current regulations, which can be labelled as nearly zero-energy/carbon buildings, are resilient in the 2050 and 2080 scenarios. Within the framework of this study, 2050 and 2080 climate scenarios will be examined, and suggestions will be presented by discussing how adaptable building stock can be achieved in terms of resilience.Article Queue-Responsive Adaptive Signal Control vs. Webster Optimization: A Multi-Criteria Simulation Assessment at a Signalized Intersection(MDPI, 2026) Albdairi, Mustafa; Almusawi, AliTraffic signal control at signalized intersections plays a key role in mitigating urban congestion, reducing vehicle emissions, and improving road safety. This study examines three signal control strategies at a four-approach isolated intersection simulated using the Simulation of Urban Mobility (SUMO) microscopic traffic simulator: a baseline fixed-time plan, a Webster-optimized fixed-time plan, and a queue-responsive adaptive controller implemented through the Traffic Control Interface (TraCI). The strategies were evaluated under balanced traffic demand of 600 vehicles per hour per approach over a 3600 s simulation period. Performance was assessed using eight indicators related to mobility, environmental impact, and safety, including average delay, travel time, queue length, network speed, throughput, CO2 emissions, fuel consumption, and time-to-collision events. The results indicate that the adaptive controller produced the greatest improvements, reducing delay by 14.3%, travel time by 13.6%, CO2 emissions by 9.3%, fuel consumption by 9.4%, and TTC conflicts by 11.2%, while increasing network speed by 47.9%. The Webster-optimized plan achieved moderate improvements, lowering delay by 4.8% and fuel consumption by 5.0% without additional infrastructure requirements. Overall, the findings suggest that both signal re-timing and queue-responsive adaptive control can enhance intersection performance, with the preferred approach depending on available infrastructure and implementation costs.Article Navigating Fear and Recklessness: Lawyers’ Perspectives on Courageous Client Behaviours in the Rights-Seeking Process(Routledge Journals, Taylor & Francis Ltd, 2026) Sert, Ozgur; Kılıç, Tamer; Mert, Ibrahim Sani; Bayramoğlu, GökbenCourage is often central to rights seeking. Drawing on Aristotelian virtue ethics and socio-psychological perspectives, this qualitative study examines how Turkish lawyers interpret and manage clients' courage, from cowardice to recklessness, during litigation. Semi-structured written interviews with 46 practising lawyers were analysed thematically in MAXQDA24. Participants largely saw courage as pivotal to sustaining claims, especially when supported by education, financial resources, and robust social ties. Social pressure and reputational risks frequently dampened courage, prompting early withdrawal. Lawyers portrayed cowardly clients as anxious and hesitant, courageous clients as calibrated risk-takers, and reckless clients as bold but imprudent, and tailored their guidance, accordingly, offering reassurance, structure, or caution. Situating these dynamics within Turkiye's collectivist, high-uncertainty-avoidant context, the study advances cross-cultural legal psychology and highlights the value of emotional intelligence and mental health awareness in legal practice.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, KaterinaThe 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 UzgorenIn 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 A Machine-Learning-Based Multi-Hazard GIS-AHP Framework for Wind Turbine Siting under Earthquake-Landslide Coupling(IOP Publishing Ltd, 2026) Dincer, Ali Ersin; Demir, Abdullah; Ozturk, Sevki; Kalpakci, Volkan; Dilmen, OmerThis study presents a machine-learning-based multi-hazard geographical information system (GIS)-analytical hierarchy process (AHP) framework for wind turbine siting that explicitly accounts for the coupled effects of earthquake and landslide hazards. The primary innovation lies in the development of a conditional weighting algorithm that integrates machine-learning-derived hazard assessments with structural engineering logic. Landslide susceptibility is first modeled using a random forest classifier trained on a comprehensive inventory of historical landslide data and 12 geo-environmental conditioning factors, producing a high-resolution susceptibility map with excellent predictive performance (AUC = 0.86). Feature importance analysis indicates that slope, hydrological indices, and geological conditions are the dominant controls on landslide occurrence. This data-driven map is then integrated with earthquake hazard zones and additional environmental and technical constraints within a GIS-AHP framework to generate a comprehensive wind turbine suitability assessment. Results show that explicitly accounting for earthquake-landslide coupling leads to a nearly 20% reduction in high and very high suitability areas, accompanied by an expansion of low and moderate suitability zones, highlighting the limitations of single-hazard planning approaches. The main contribution of this study lies in advancing renewable energy planning through the explicit integration of interdependent natural hazards, demonstrating how earthquake-resistant foundation strategies can simultaneously mitigate landslide risks.Article A Left-Definite Non-Integer-Order Dissipative Operator(Springer Nature, 2026) Ugurlu, EkinIn this paper we consider a non-integer (fractional)-order nonselfadjoint boundary-value problem so that the fractional-order equation is a kind of left-definite equation. We construct a dissipative operator in a Sobolev space H-1(a,b) and we introduce several results on the spectral properties of the related operators. In particular, we construct an inverse operator with the aid of the Dirac-delta function and we apply Krein's theorem to the inverse operator which is compact having a nuclear imaginary component.Article Enhanced Mapping of Rainfall Induced Landslide Susceptibility Using a Deep Feedforward Neural Network with Soft Computing(Techno-Press, 2026) Zhu, Licai; Akagic, Amila; Nanehkaran, Yaser A.; Pusatli, Tolga; Mahmud, Elkhan; Jian, DongThe presented study attempted to propose enhanced rainfall-induced landslide susceptibility mapping method by using the Deep Feedforward Neural Network (DFNN) which is developed for analysis the non-liner feature detection in landslide susceptibility analysis. To evaluate our approach, a comprehensive dataset of triggering factors was compiled, encompassing historical landslide occurrences with total of 107 records, rainfall data, geological information, seismicity, human-activities, and topographic attributes. Through rigorous training and testing procedures, the DFNN demonstratedsuperior ability for generalization and superior performance. The effectiveness of the selected method is demonstrated on the data from the Zanjan County, known for its diverse geographical, geological, and hydrological characteristics, which are pivotal factors in mapping of landslide susceptibility. Results showcased a substantial enhancement in the accuracy of mapping of rainfall-induced landslide susceptibility for the Zanjan County, which is compared with benchmark learning classifiers. According to the results of the study, it appeared that the northeastern and southwestern area of the Zanjan County can be deemed to have a high to very-high risk of landslide occurrence, which is validated via benchmark classifiers. The western part of the Zanjan County was observed to have a very low to low risk.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, MuratThe 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 Refocus on Planning and Positive Refocusing Mediate the Relationship Between Cognitive Flexibility and Psychological Resilience(Springer, 2026) Mungan, Özlem; Torun Yazihan, NaksidilCognitive flexibility is one of the most important indicators of mental health and is a cognitive process at the heart of psychological resilience. The more cognitively flexible individuals are, the more likely they are to use adaptive emotion regulation strategies, which in turn increases their psychological resilience, according to the results of the current study. This study highlights the value of fostering cognitive flexibility and adaptive emotion regulation strategies to promote psychological resilience, and provides practical insights for practitioners. For future studies, training programmes designed to improve cognitive flexibility may have downstream benefits for emotion regulation and resilience-for example, cognitive behavioural therapy, rational-emotional therapy and mindfulness-based interventions, which are known to improve cognitive flexibility, may be particularly effective in promoting adaptive emotional responses.