Atılım Academic Archive (Atılım University)
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Earthquake Response Framework With IoT-Based E-Government Services
No full textEarthquakes present a genuine threat to both lives and property, necessitating the minimization of their impact wherever possible. This is especially critical in countries like Iraq, which suffer from inadequate infrastructure. Consequently, this study developed a framework aimed at bolstering Iraq’s current disaster management system to respond to earthquakes. The designation of this system stems from its integration of information and communication technology principles alongside the Internet of things (IoT). The framework’s development was built based on related literature and data collected from websites related to disaster management, including the Ministry of Environment and the Ministry of Communication. The resultant framework was constructed utilizing unified modeling language diagrams, including both use-case and activity diagrams. This endeavor represents one of the few initiatives undertaken in the context of Iraq. Future research endeavors focusing on disaster planning in Iraq and similar contexts may utilize the findings of this study as a foundational resource. © 2026 by Author/s and Licensed by Modestum DOO, Serbia
Policy Frameworks without Practice? Exploring Marine Governance and Climate Integration Challenges in Türkiye
No full textKarlı, Aygün/0000-0003-3588-9789The marine-climate nexus has emerged as a critical frontier in global environmental governance, yet its integration into national policy frameworks remains uneven. This article examines the case of T & uuml;rkiye, a middleincome country with extensive coastlines and increasing exposure to climate risks, to explore how marine and climate governance interact in practice. Drawing on 22 semi-structured interviews with experts from government, civil society, and academia, the study applies thematic analysis to identify six interrelated challenges: (1) the gap between legal frameworks and implementation, (2) crisis-based governance, (3) institutional fragmentation and coordination deficits, (4) dependence on European Union funding and external alignment, (5) societal indifference and limited marine literacy, and (6) the contested discourse of the blue economy. The findings demonstrate that although T & uuml;rkiye has adopted robust legal instruments and aligned with EU standards, enforcement and institutional integration remain weak. Governance is often reactive, fragmented, and externally driven, with limited societal demand for ambitious reforms. These dynamics reflect broader patterns in global marine-climate governance but are compounded by T & uuml;rkiye's context specific political and institutional constraints. The article argues that bridging the persistent policy-practice gap will require stronger institutional coordination, investments in capacity and literacy, and reframing the blue economy as a vehicle for climate adaptation and mitigation rather than narrow economic growth
Multifunctional POSS-Based Nanoparticles Functionalized with Silver, SPIONs, and Rhamnolipid for Antibacterial Applications
No full textNano-engineered materials, particularly those featuring bio-based surface modifications, are emerging as effective tools in combating bacterial infections. In this study, polyhedral oligomeric silsesquioxane (POSS) nanoparticles were functionalized with silver nanoparticles (Ag), superparamagnetic iron oxide nanoparticles (SPIONs), and the biosurfactant rhamnolipid (RL)—either individually or in combination—to evaluate their antibacterial and antibiofilm activities against Staphylococcus aureus ( S. aureus ) and Pseudomonas aeruginosa ( P. aeruginosa ). The modified nanoparticles exhibited sizes ranging from 127 to 227 nm and demonstrated superparamagnetic behavior, offering potential for magnetic targeting. Among the various formulations, the RL-coated, silver- and SPION-decorated POSS nanoparticles (RSMP) exhibited the highest antibacterial efficacy, reducing S. aureus and P. aeruginosa colony growth by approximately 90 % and 66 %, respectively, at a concentration of 0.01 g/L. RSMP nanoparticles also showed strong biofilm inhibition and had the lowest MIC₅₀ values. Notably, these nanoparticles supported the proliferation of human osteoblasts at concentrations up to 0.05 g/L, indicating favorable cytocompatibility. Overall, RSMP nanoparticles present a promising platform for magnetically targetable antibacterial agents, with potential applications in biomedical fields, particularly for managing orthopedic infections. © 2025 Elsevier B.V
QRS (Quality-Reliability-Safety) Complex of Engineering: Its Importance and Necessity in Engineering Education
No full textAlthough quality, reliability and safety are well-known concepts, the importance of these concepts has increased even more considering today's technologies and integrated systems. It is important that these concepts are known by engineers who play an important role in the design of such systems. This article aims to emphasize the importance and necessity of teaching the triple of quality, reliability and safety, expressed with the acronym QRS, in engineering education. In particular, the definitions of these concepts, the relationships between them and the basic issues that should be known by any engineering student regarding these concepts are summarized. Some suggestions are offered to help engineering students gain competence in these subjects. © The Author(s) 202
Distance-Based Estimation Under Progressive Type-I Interval Censoring
No full textMonte Carlo simulation is used to demonstrate improved estimation performance of proposed distance-type estimators for lifetime models under progressive Type-I interval censoring. We propose novel distance-based estimators for lifetime models under progressive Type-I interval censoring. These estimators minimize the discrepancy between observed and model-based conditional failure probabilities using either quadratic or Mahalanobis distances, providing natural alternatives to maximum likelihood estimators (MLEs). Through extensive Monte Carlo simulations, we demonstrate that the Mahalanobis estimator outperforms MLE, particularly under heavy censoring or sparse data. The quadratic estimator also yields competitive results, especially under model misspecification. Two real data examples illustrate the practical advantages of the proposed approach.Natural Sciences and Engineering Research Council of CanadaThis work was supported by an Individual Discovery Grant from the Natural Sciences and Engineering Research Council of Canada
Queue Management Systems in Airport Management: Enhancing Passenger Flow and Operational Efficiency
No full textQueue management systems (QMS) streamline airport operations by determining travel patterns that help manage the passenger flow, reducing wait times, and enhancing operational efficiency. They help optimize queue configurations by real-time data analytics and employing algorithms, working to guide passengers efficiently through the place for check-in, security clearance, and boarding. It leads to a much more pleasant time for the passengers while ensuring better resource utilization and operational planning. This Paper investigates a new queue management system that utilizes advanced technologies like artificial intelligence and real-time data analytics. Such systems enable monitoring of passenger flocking and behavior for adjustability concerning the length of queues and the optimization of service times. The result is an enhanced travel experience and improved airport operational efficiency. The paper takes Singapore Changi Airport as a case study to aid the understanding of how effective management of queues can lead to effective Rose operational efficiency. These findings show that airports can significantly reduce passenger wait times using advanced queue management technologies and enhance the travel experience while facilitating operations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026
From Simulators To Skies: Engineering and Educational Advancements in Pilot Training: a Bibliometric Perspective
No full textThe integration of advanced engineering innovations into pilot training has brought transformative changes to aviation education, emphasizing the role of technologies such as flight simulators, virtual reality (VR), augmented reality (AR), and artificial intelligence (AI). This study employs a bibliometric analysis to explore research trends, influential contributors, and thematic focuses in pilot training from 2000 to 2025, using data from 350 peer-reviewed articles indexed in the Web of Science. Findings reveal a significant rise in publications during the last decade, driven by advancements in simulation technologies, competency-based training, and human factors research. While the field has experienced rapid technological evolution, challenges such as cost barriers, integration complexities, and gaps in long-term performance evaluation remain. This paper highlights emerging trends, including competency-based training and assessment (CBTA) and scenario-based training (SBT) as well as physiological monitoring, offering a comprehensive roadmap for future research and innovation in aviation training
The Effects of Computer-Aided Concept Teaching With the Direct Instruction Model on Concept Acquisition of Students With Intellectual Disabilities
No full textThis study aimed to develop and evaluate a technology-based instructional tool using the Direct Instruction Model (DIM) for teaching geometric concepts - cube, cylinder and cone - to students with mild intellectual disabilities (ID). The 'Shape Finder' application was designed following DIM principles and assessed using a multiple probe design across participants. Four students with mild ID, their three teachers and six special education experts participated. Data collection involved app-based performance metrics, observations and interviews. Results indicated that the Shape Finder effectively supported students' acquisition, retention (up to five weeks), and generalisation of the targeted geometric shapes to real-world objects. Interviews confirmed the application's social validity. The findings highlight that integrating evidence-based instructional models with technology can enhance concept learning for students with mild ID, facilitating both short-term gains and long-term retention. This study underscores the potential of well-designed digital tools in special education to support conceptual understanding and generalisation across contexts.Social Science Citation Inde
Precision Forecasting for Hybrid Energy Systems Using Five Deep Learning Algorithms for Meteorological Parameter Prediction
Full text linkThe intermittent nature of renewable energy sources necessitates accurate power production forecasting to ensure system sustainability and balance between energy supply and demand. Although the deep learning-based meteorological forecasting is significantly studied in literature, most of the current literature applies single-algorithm based on each individual energy source and less multi-algorithm based on comparative studies on multiple architectures as applied to integrated hybrid systems. In addition, most of the research uses the same algorithmic solution to all the meteorological parameters without identifying parameter-specific optimization potential, and recent research is verified on actual future time steps instead of historical train-test split. This study presents a comprehensive comparative analysis of five deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and CNN-LSTM hybrid, for forecasting critical meteorological parameters (wind speed, ambient temperature, and solar radiation) that determine energy output in a wind and solar-based hybrid energy system (HES). Using five years of Istanbul meteorological data (2018-2022), optimal algorithms were systematically identified for each parameter through rigorous hyperparameter optimization and cross-validation. Key results demonstrate that GRU achieves superior performance in wind speed prediction (RMSE: 0.049 m/s, R2: 0.8634) and solar radiation forecasting (RMSE: 0.146 W/m2, R2: 0.6643), while CNN-LSTM excels in ambient temperature prediction (RMSE: 0.011 degrees C, R2: 0.9976). The integrated approach predicted annual hybrid system energy production with 89 % accuracy, demonstrating 0.48 % deviation from observed values. Most significantly, our framework successfully forecasted sixth year (2023) energy production with 1.55 % error, validating its real-world applicability. This research contributes to the methodological advancement of renewable energy forecasting by systematically identifying optimal algorithmic approaches for different meteorological parameters in hybrid systems, thereby supporting the integration of intermittent renewable sources into sustainable energy infrastructures
Promotion of Cooperation in a Co-Evolutionary Pragmatic Agent Multigame Environment
No full textKilic, Hurevren/0000-0002-9058-0365The promotion of cooperation in a co-evolutionary environment where pragmatic agents participate in a multigame setting that contains Prisoner's Dilemma (PD) and SnowDrift (SD) games is investigated. The pragmatic agent conserves its current perspective when successful; otherwise adopts the opposite perspective. Unlike traditional models, this study introduces a setup in which perception and strategy spaces co-evolve in terms of iterative game payoffs. The players are situated in a 2-D square lattice environment and synchronously update their perceptions and strategies after interacting with their immediate neighbors. The ratios of perceptions and strategy are randomly set based on parameters alpha and /3, indicating initial SD and cooperation (C) percentages, respectively. By the end of various simulations, the system's convergent and stable behavior is shown by means, standard deviations, and confidence intervals. The results show that larger (alpha >= 0.5) initial populations of SD agents promote greater cooperation and lead to a dominance of cooperative strategies even for smaller initial C strategies (/3 similar to 0.2). Conversely, when the environment is initially dominated by PD perspectives and defect (D) strategies (alpha = 0.1, /3 = 0.2), it leads to lower levels of cooperation. Depending on the initial ratios of PD/SD and D/C players, cooperative player clusters are not only formed but are also persistent parts of the environment. Finally, we observed that co-evolving PD/SD and D/C environments coupled with pragmatic players lead to a controllable promotion of cooperation even against small initial SD player ratios.Science Citation Index Expande