Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object A General Predictive Model to Evaluate Daylight Levels of Residential Buildings in the Mediterranean (Next Med) Region(Education and Research in Computer Aided Architectural Design in Europe, 2025) Ekici, B.Conceptual design is one of the most critical phases, as design decisions affect the buildings’ performance throughout their life cycle. Researchers consider various computational methods to achieve effective design proposals. Nevertheless, optimization algorithms are necessary to cope with the complexity and increase the efficiency of design alternatives in various aspects. In sustainable building design, these decisions require computationally expensive processes due to the simulation tasks. Besides, making sustainable design decisions is even more challenging in a Mediterranean climate due to changing conditions throughout the year. Therefore, recent studies frequently consider combining predictive models with optimization algorithms to decrease the burden of expensive simulation time. Relevant works present promising outcomes, yet they are limited to predicting the building performance of specific cases; thus, the proposed predictive models are limited to different design problems. This paper investigates the development of a general machine learning (ML) model to overcome this issue. With this motivation, a parametric test box consisting of twenty parameters related to weather data of twelve Mediterranean (Next Med) countries, space dimensions, vertical/horizontal louvers, and material type is developed using Grasshopper 3d. Moreover, a parametric urban model, which considers eight parameters related to the density of the surrounding buildings, is also created to generate numerous environments. The LadyBug tools simulate the daylight autonomy to generate 12,000 samples. Five different ML models involving artificial neural networks (ANN) are built in Python. Statistical results showed that train and test scores achieved promising outcomes in all ML models. However, when predicting user-defined scenarios not involved in the generated dataset, only ANNs perform generalizable, accurate predictions. The paper discusses the ability of ANN models to accurately predict different design scenarios and locations, and the trustworthiness of the training and test scores based only on collected data. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Conference Object Metacognitive, Cognitive, and Creative Dynamics in the Artificial Intelligence-Aided Design Process(Education and Research in Computer Aided Architectural Design in Europe, 2025) Yazici, G.; Doǧan, F.This study examines the effects of artificial intelligence-aided design processes (AIADP) on cognitive load, creativity, and metacognitive awareness. Within the scope of the study, a one-day face-to-face workshop was organised with twenty-eight architects, including architecture students studying at undergraduate and graduate levels, and the data based on the participants' experiences were analysed using qualitative research methods. The results of the sentiment-based content analysis show that integrating AI tools into the design process reduces cognitive load, supports creative thinking processes, facilitates rapid prototyping and feedback mechanisms, and increases metacognitive awareness. The findings reveal that AI-aided design tools can potentially improve designers' cognitive and creative capacities. The study addresses the effects of AIADP in educational and professional contexts from a local perspective, providing a new perspective on the literature on the integration of AI into design processes. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Article Identification of Turkish Extra Virgin Olive Oils Produced in Different Regions With Volatile Compounds(Innovhub SSI-Area SSOG, 2025) Sevim, Didar; Koseoglu, Oya; Ertan, Hasan; Ozdemir, Durmun; Ulan, MehmetThis study aims to characterize the composition of the volatile compounds in Turkish extra virgin olive oils (EVOOs) produced from three cultivars-Ayvalik, Gemlik, and Memecik-harvested in the South Marmara, South Aegean, and North Aegean regions during the 2014/15 and 2015/16 crop seasons. A total of 135 EVOO samples were obtained using industrial-scale 2-phase and 3-phase extraction systems. These samples were then analyzed using solid-phase microextraction (SPME) coupled with gas chromatography (GC). Among the twelve volatiles identified, trans-2-hexen-1-ol and cis-2-penten-1-ol exhibited the highest levels of abundance across all samples and seasons. Subsequently, 1-penten-3-one, hexanal, and cis-3-hexenyl acetate were identified, and it was determined that these contribute to the green and fruity sensory profile of high-quality olive oil. Two- and three-factor analyses of variance (ANOVA) revealed that volatile concentrations were significantly influenced by variety, harvest season, and extraction system. It is significant that 1-penten-3-one was found to be significantly influenced by both season and variety (p < 0.05), while 1-penten-3-ol exhibited a multifactorial dependency, with significant two-way interactions (season x variety, season x system, variety x system). Furthermore, PLS-DA-based classification successfully distinguished samples according to olive variety, indicating that volatile profiles could serve as reliable markers for authenticity and geographic origin. These findings underscore the potential of using volatile compounds as quality indicators and for geographic labelling in the olive oil industry.Conference Object Differential and Linear Analyses of Dizy Through MILP Modeling(Springer Science and Business Media Deutschland GmbH, 2026) İlter, M.B.; Koçak, O.; Kara, O.; Sulak, F.In this work, we present the first independent security analysis of DIZY, a recently proposed ultra-lightweight stream cipher with two variants: DIZY-80 and DIZY-128. Our analysis focuses on DIZY’s resistance to linear and differential cryptanalysis. We employ a formal technique known as Mixed Integer Linear Programming (MILP), which enables us to model the internal structure of DIZY and search for characteristics that describe how XOR differences or linear masks propagate through the cipher. Specifically, we construct such characteristics to evaluate how many S-boxes become “active” during keystream generation, as this number directly affects the cipher’s resistance to these attacks. Contrary to the designers’ claim that any linear or differential characteristic over 8 rounds must involve at least 20 active S-boxes in DIZY-80 and 22 in DIZY-128, we identify characteristics with only 18 differentially or linearly active S-boxes and 20 linearly active S-boxes, respectively. We mount two distinguishing attacks on each cipher. Our 3-round linear distinguishing attack requires 223 bits of keystream, while the 4-round version requires 235 bits for DIZY-128 and DIZY-80, respectively. Our 2-round differential resynchronization attacks succeed using only the first four bytes of keystream data from approximately 230 and 226 different initializations with chosen initialization vectors (IVs) for DIZY-128 and DIZY-80, respectively. While these attacks do not compromise the full 15-round version of the cipher, they provide valuable insights into the design of DIZY and contribute to a deeper understanding of the security requirements of its diffusion layer. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Article Self-Assembled Peptide Hydrogels with Cell Attachment Motifs for 3D Lung Cancer Model: Evaluation of Cell-Matrix Interactions and Drug Response(John Wiley and Sons Inc, 2026) Sırma Tarım, B.; Tamburaci, S.; Top, A.3D cancer models can mimic the tumor microenvironment, serving as a physiologically relevant platform to investigate the behavior of tumors and test anticancer therapeutics. Although bioactive peptide hydrogels have been widely evaluated for tissue engineering applications, their potential in 3D cancer models has been confirmed in only a few studies. In this study, self-assembling peptide hydrogels containing LDV (IBP1) and LDV and IKVAV cell attachment motifs (IBP2), and the control hydrogel without adhesion units (KLEI) were used for lung cancer modeling. The peptides self-assembled into hydrogels in a cell culture medium with storage moduli of ∼700–1500 Pa. The IBP1 and IBP2 hydrogels enhanced A549 cell proliferation and induced the formation of spheroids with average diameters between ∼70 and ∼150 µm. The cells in KLEI hydrogel with the highest stiffness exhibited mesenchymal-type migration, independent of the cell population, whereas transformation to mesenchymal migration necessitated a specific cell population in the IBP2 hydrogel. The cells in the IBP1 and IBP2 hydrogels with enhanced cell-cell interactions demonstrated higher resistance to docetaxel (DTX). Thus, our results indicate that these bioactive hydrogels can serve as a promising platform for in vitro assessment of cancer mechanisms and drug screening. © 2026 Wiley-VCH GmbH.Article Epigallocatechin Gallate and Punicalagin Combination Reduces Aβ Aggregation and Promotes Neurogenesis in Adult Zebrafish Brain(John Wiley and Sons Inc, 2026) Nazli, D.; Ipekgil, D.; Poyraz, Y.K.; Can, K.; Okmen, I.; Turhanlar-Sahin, E.; Ozhan, G.Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and behavioral alterations. The pathogenesis of AD involves the accumulation of amyloid-beta (Aβ) plaques and the hyperphosphorylated tau proteins, which disrupt neuronal function and trigger neuroinflammation. This study explores the therapeutic potential of epigallocatechin gallate (EGCG) and punicalagin (PU) in mitigating Aβ-induced toxicity using an adult zebrafish model of AD. Our results demonstrate that the EGCG + PU combination significantly reduces Aβ accumulation, protects against cellular damage, suppresses acetylcholinesterase (AChE) activity, and normalizes the expression of amyloidogenic and AD-related genes. Additionally, EGCG + PU treatment alleviates neuroinflammation by suppressing glial activation, including reductions in L-plastin and proinflammatory cytokine expression, while promoting neuronal recovery through mechanisms of neurogenesis and neuroprotection. Notably, the combination treatment restored neuronal density and improved behavioral outcomes by alleviating anxiety- and aggression-like behaviors associated with Aβ toxicity. These results underscore the synergistic neuroprotective effects of EGCG + PU, highlighting their potential as a novel therapeutic approach for mitigating the pathological, behavioral, and inflammatory aspects of AD. © 2026 Wiley Periodicals LLC.Erratum Erratum to “Plasma Proteomic Markers of Interleukin-1β Pathway Associated With Incident Age-Related Macular Degeneration in Persons with AIDS” [Ophthalmol Sci. 2025;5:100794] (Ophthalmology Science (2025) 5(5), (S2666914525000922), (10.1016/J.xops.2025.100794))(Elsevier Inc., 2026) Hunt, P.W.; Olshen, A.B.; Murad, N.; Ambayec, G.C.; Sezgin, E.; Schneider, M.F.; Jabs, D.A.The publisher of this journal would like to note an error in the article “Plasma Proteomic Markers of Interleukin-1β Pathway Associated with Incident Age-Related Macular Degeneration in Persons with AIDS.” An earlier version of Figure 1 was inadvertently published instead of the final revised figure. The correct figure appears below.[Figure presented] © 2025 American Academy of OphthalmologyBook Part Greenmetric Journey of Izmir Institute of Technology: Agile Strategies Towards a Green Campus(Springer Science and Business Media Deutschland GmbH, 2026) Keskin, E.; Ökten, H.E.; Akpinar, İ.; Baran, Y.Recently, there has been growing attention towards sustainable approaches on university campuses through disseminating international evaluation systems, the UI GreenMetric World University Rankings (GM) attracting specific attention in particular. Türkiye is one of the countries where the number of participating universities in GM rises annually at a significant pace. Most of the large-scale university campuses in Türkiye were already built by the 1990s, which led these campuses to adapt themselves to higher standards for sustainability. In this context, Izmir Institute of Technology (IZTECH), a 33-year-old university, has applied for the GM with its Gülbahçe Campus since 2020. This paper aims to reveal IZTECH’s institutional agile sustainability strategy, energetic and collective processes, and good practices in the last five years while examining the outcomes through the GM’s evaluation of six assessment criteria. In this regard, the sustainability practices of IZTECH have been monitored since 2019 and compared to how the developments have improved the GM scores for the past 3 years. This study, focusing on the IZTECH campus through historical, social, educational, and technological perspectives, unveils the barriers between developing and implementing sustainability practices and examines the cohesion between GM scores and annual reports of campus activities for further projections towards a greener campus. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Article A Multidimensional Comparative Analysis of Human Expert vs. AI-Driven Feedback Approaches on Learner-Centered and Collaborative Groups(Routledge, 2026) Yıldız Durak, H.; Onan, A.The aim of this study is to examine the multidimensional effects of AI-based feedback in learner-centered and collaborative learning environments among university students. The study employed a five-group experimental design: two individual learning groups receiving either AI-based feedback(G1) or human expert feedback(G2), two collaborative learning groups receiving either AI(G3) or human expert feedback(G4), and control group(G5). According to the research results, G4 showed the highest level of development in the areas of creative problem solving, internal-external motivation, and critical thinking. G1 was the group with the highest performance, particularly in terms of system interaction, completed activities, and assignments. In contrast, G2 showed the lowest results in terms of both cognitive development and learning analytics. AI-based feedback in collaborative learning environments provided the highest development in cognitive skills, while AI-based in individual work was more effective in increasing system participation. Factorial MANCOVA indicated significant interactions between learning environment and feedback type on posttest outcomes, with strongest effects on self-efficacy, intrinsic motivation, and flexibility. These results show that AI-based feedback has different effects in both individual and collaborative learning contexts. Qualitative thematic analysis highlighted themes of cognitive facilitation, creativity enhancement, feedback quality perceptions, and environment preferences. © 2026 Informa UK Limited, trading as Taylor & Francis Group.Article 3D Magnetic Nanocomposite Aerogel (3D-MANCA) for Humidity Sensing and Dye Adsorption Applications(Institute of Physics, 2026) Shah, N.; Tetik, H.; Lin, D.Introducing magnetic properties to aerogels not only opens new application areas but also enhances their performance in various applications. Herein, we report a novel 3D magnetic agar nanocomposite aerogel (3D-MANCA) with outstanding characteristics such as high porosity, magnetic property, rapid swelling behavior, and a unique stimuli-driven electrical conductivity. Agar and nanocellulose mixture were selected as the matrix material, while magnetic Fe<inf>3</inf>O<inf>4</inf> nanoparticles, CuO nanoparticles, and graphene nanopowder were incorporated as functional additives. 3D-MANCA obtained after a uni-directional freeze casting process exhibited a highly-ordered microporosity. It showed excellent magnetic properties and methylene-blue adsorption capability and a great performance as humidity sensor. © 2026 The Author(s). Published on behalf of The Electrochemical Society by IOP Publishing Limited.