WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article On the Strengths and Weaknesses of Virtual Reality in Distance Estimation in AEC Domain: A Meta-Analysis of Literature 2014–2024(Springer Science and Business Media Deutschland GmbH, 2026) Kasalı, Altuğ; Doğan, Fehmi; Çevik, A.; Kasali, A.; 02.02. Department of Architecture; 02. Faculty of Architecture; 01. Izmir Institute of TechnologyVirtual reality (VR) became the most used extended reality system in architecture, engineering, and construction domains. It offers advantages through its immersive and interactive interface. There is, however, a need to investigate both its strengths and weaknesses especially in relation to the claim that it is a close surrogate for real-world performances. This study reports the findings of a meta-analysis on distance estimation (DE) in VR. Distance estimation, essential for spatial perception, remains to be a problem in VR even with advanced head-mounted displays. The study questions whether VR can match the real-world performance in DE to highlight its shortcomings as well as its potentials. The meta-analysis includes 77 pieces of data from 29 studies and investigates whether DE accuracy has improved and how DE interacts with task type, task environment, and target range. The results indicate VR is still underperforming in DE, head-mounted display’s weight is the significant factor, and task type and task environment significantly interact with DE. We conclude VR needs to be specifically tailored regarding the needs of practitioners in architecture and engineering industry and that it is not yet a substitute for real-world performances. © The Author(s) 2025.Conference Object Citation - WoS: 1Citation - Scopus: 3Structural Performance of R/C Buildings in 2023 Kahramanmaraş Earthquakes Under the Lens of Hassan Index(Springer Science and Business Media Deutschland GmbH, 2024) Dönmez, Cemalettin; Yesilyurt, Cennet; Gozun, Uveys; Ozturk, Baki; Donmez, Cemalettin; 01. Izmir Institute of Technology; 03. Faculty of Engineering; 03.03. Department of Civil EngineeringStarting with the 1999 Kocaeli Earthquake, seismic damage indices have been developed to quantify damage potential. The late Professor Mete Sozen played a significant role in this endeavor by introducing the Hassan Index, which is an indirect measure of the robustness of structures. Its calculation is straightforward, given the vertical structural element dimensions at ground level. Various earthquakes worldwide, from Taiwan to Chile, have provided opportunities to assess its effectiveness across diverse building practices and earthquake characteristics. Following the February 2023 Kahramanmaras Earthquakes, a reconnaissance team was dispatched to gather field data to observe the damages through the lens of the Hassan Index. The study extended to cover all major city and town centers, studying around 250 reinforced concrete buildings with 2-16 stories. These buildings were all constructed after the 2000s. Hence, the data set sheds light on the performance of Turkish construction practices after the commencement of the 1998 Turkish Building code and the following earthquake regulations. By evaluating the newly gathered data alongside the existing dataset, a basis is established to consider the Hassan Index as a preliminary design index rather than solely as a seismic damage index.Conference Object Citation - WoS: 2Citation - Scopus: 6Discussion on the Causes of the Observed Damages in the 2023 Kahramanmaraş Earthquakes(Springer Science and Business Media Deutschland GmbH, 2024) Dönmez, Cemalettin; Comlekoglu, Hakki Gurhan; Ozturk, Baki; Donmez, Cemalettin; 01. Izmir Institute of Technology; 03. Faculty of Engineering; 03.03. Department of Civil EngineeringThe devastating earthquakes in February 2023 in south-east Turkiye demonstrated that the Turkish built environment does not meet the needed performance. The frequency of earthquakes in Turkiye calls for urgent organization to upgrade the existing structures and avoid the repetition of deficient applications. Hence, it is necessary to identify the causes of the damage. The presented study concentrated on a subset of the existing inventory built under the governance of 1998 and later Turkish Earthquake Codes. Following the earthquakes in Kahramanmaras, Turkiye, a reconnaissance study was conducted to understand the causes of the damage incurred. The extensive study covered all the major city and town centers, specifically concentrating on the 2- to 16-story reinforced concrete buildings. The first impression of the data gathered indicates significant detailing imperfections. Poor drift control, inferior layout preferences, and non-structural detailing issues are the other suspects. The observed damage and the current seismic regulation requirements will be critically discussed to form a basis for possible future improvements to the seismic code.Article Citation - WoS: 1Citation - Scopus: 1Enhancing the Sustainable Protein Extraction Process From Black Cumin Seed Cake Press for Eco-Friendly Protein Supplements(Springer Science and Business Media Deutschland GmbH, 2025) Uzuner, Sibel; Uzuner, Sibel; Uzuner, S.; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyFinding new protein sources is essential to meet the global population’s needs. Nigella sativa (black cumin) seeds and the residual cake left after oil cold pressing contain valuable nutritional compounds, including proteins, phenolics, essential amino acids, and various bioactive compounds. In the literature, the structural characteristics and functional properties of proteins from black cumin seeds have been extensively studied. However, there are limited reports on the use of emerging extraction technologies for extracting soluble proteins from black cumin seed cake press (BCSCP). Therefore, two distinct extraction techniques—microwave (MW) and ultrasonication (US)—were assessed for their effectiveness in extracting soluble proteins from BCSCP. The aim of this study was to investigate the effects of various operational conditions on protein extraction yield and functional properties of proteins extracted from BCSCP. The maximum protein yield (27.04%) was achieved using a 10% solid/liquid ratio (SLR) at 33 °C for a 30-min extraction time with the US extraction technique. After ultrafiltration, the protein yield increased to 33.83%, showcasing the predominance of sarcosine (17.18 g/100 g), glutamine (11.63 g/100 g), and proline (33.46 g/100 g) amino acids. The water-holding capacity (WHC), oil-holding capacity (OHC), foam capacity (FC), and foam stability (FS) of the BCSCP isolate were found to be 5.4 ± 0.3 g/g, 9.4 ± 0.0 g/g, 43.6 ± 6.4%, and 39.0 ± 4.7%, respectively. The study revealed that US is a suitable extraction process for obtaining soluble proteins from BCSCP with favorable functional properties. Further studies are needed to evaluate the bioavailability and health impacts of bioactive peptides in order to develop food applications. © The Author(s) 2024.Conference Object Citation - WoS: 1Citation - Scopus: 1Gpprmon: Gpu Runtime Memory Performance and Power Monitoring Tool(Springer Science and Business Media Deutschland GmbH, 2024) Öz, Işıl; Öz,I.; 01. Izmir Institute of Technology; 03.04. Department of Computer Engineering; 03. Faculty of EngineeringGraphics Processing Units (GPUs) perform highly efficient parallel execution for high-performance computation and embedded system domains. While performance concerns drive the main optimization efforts, power issues become important for energy-efficient GPU executions. While performance profilers and architectural simulators offer statistics about the target execution, they either present only performance metrics in a coarse kernel function level or lack visualization support that enables performance bottleneck analysis or performance-power consumption comparison. Evaluating both performance and power consumption dynamically at runtime and across GPU memory components enables a comprehensive tradeoff analysis for GPU architects and software developers. This paper presents a novel memory performance and power monitoring tool for GPU programs, GPPRMon, which performs a systematic metric collection and offers useful visualization views to track power and performance optimizations. Our simulation-based framework dynamically collects microarchitectural metrics by monitoring individual instructions and reports achieved performance and power consumption information at runtime. Our visualization interface presents spatial and temporal views of the execution. While the first demonstrates the performance and power metrics across GPU memory components, the latter shows the corresponding information at the instruction granularity in a timeline. Our case study reveals the potential usages of our tool in bottleneck identification and power consumption for a memory-intensive graph workload. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Article Citation - WoS: 1Citation - Scopus: 1Valorization of Black Carrot Pomace and Pea Powder for Co-Production of Polygalacturonase and Pectin Lyase(Springer Science and Business Media Deutschland GmbH, 2025) Uzuner, Sibel; Uzuner, S.; Sezgin, H.T.; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyPectic enzyme groups, particularly polygalacturonase and pectin lyase, are vital components of a high-value microbial enzyme category widely employed in applications within the fruit juice and wine industries. The exploration of alternative carbon and nitrogen sources remains crucial for enhancing enzyme production while reducing costs. This study evaluates the impact of carbon (black carrot pomace) and nitrogen (pea protein) loading on fermentable sugar content, protein content, and enzyme activities during both batch and fed-batch cultivation. Additionally, three distinct valorization techniques—thermal (steam), thermochemical (steam assisted with dilute acid), and microwave-assisted with dilute acid pretreatments—were assessed for their effectiveness in hydrolyzing black carrot pomace as a carbon source. The findings indicate that microwave-assisted dilute acid, coupled with enzymatic saccharification, resulted in the highest fermentable sugar production (0.493 g/g), achieving an 87.3% conversion yield. Pea protein demonstrated more favorable outcomes with the highest polygalacturonase activity (20.50 ± 0.52 U/L) and pectin lyase activity (46.44 ± 3.45 U/L) compared to whey protein and yeast extract used as nitrogen sources. Meanwhile, the highest polygalacturonase and pectin lyase activity, along with the highest total protein content (52.25 ± 0.06 mg/L), was recorded under the same culture conditions, reaching 164.34 ± 2.26 and 188.22 ± 1.72 U/L, respectively, after 72 h, representing approximately 1.18- and 1.34-fold increases from the batch system. Consequently, these results prove that fed-batch cultivation, utilizing black carrot pomace hydrolyzate as a feeding substrate and pea protein as a nitrogen source, significantly increases polygalacturonase and pectin lyase activity compared to batch cultivation. © The Author(s) 2024.Conference Object Citation - Scopus: 1Classification of Turkish and Balkan House Architectures Using Transfer Learning and Deep Learning(Springer Science and Business Media Deutschland GmbH, 2024) Yönder,V.M.; Çavka, Hasan Burak; Doğan, Fehmi; Apaydın, Mehmet Serkan; Yönder, Veli Mustafa; Apaydın,M.S.; Doğan,F.; 02.02. Department of Architecture; 02. Faculty of Architecture; 01. Izmir Institute of Technology; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of EngineeringClassifying architectural structures is an important and challenging task that requires expertise. Convolutional Neural Networks (CNN), which are a type of deep learning (DL) approach, have shown successful results in computer vision applications when combined with transfer learning. In this study, we utilized CNN based models to classify regional houses from Anatolia and Balkans based on their architectural styles with various pretrained models using transfer learning. We prepared a dataset using various sources and employed data augmentation and mixup techniques to solve the limited data availability problem for certain regional houses to improve the classification performance. Our study resulted in a classifier that successfully distinguishes 15 architectural classes from Anatolia and Balkans. We explain our predictions using grad-cam methodology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Article Citation - WoS: 70Citation - Scopus: 59First Measurement of Large Area Jet Transverse Momentum Spectra in Heavy-Ion Collisions(Springer Science and Business Media Deutschland GmbH, 2021) Karapınar, Güler; Karapınar, Güler; CMS Collaboration; 01. Izmir Institute of TechnologyJet production in lead-lead (PbPb) and proton-proton (pp) collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV is studied with the CMS detector at the LHC, using PbPb and pp data samples corresponding to integrated luminosities of 404 ?b?1 and 27.4 pb?1, respectively. Jets with different areas are reconstructed using the anti-kT algorithm by varying the distance parameter R. The measurements are performed using jets with transverse momenta (pT) greater than 200 GeV and in a pseudorapidity range of |?| < 2. To reveal the medium modification of the jet spectra in PbPb collisions, the properly normalized ratio of spectra from PbPb and pp data is used to extract jet nuclear modification factors as functions of the PbPb collision centrality, pT and, for the first time, as a function of R up to 1.0. For the most central collisions, a strong suppression is observed for high-pT jets reconstructed with all distance parameters, implying that a significant amount of jet energy is scattered to large angles. The dependence of jet suppression on R is expected to be sensitive to both the jet energy loss mechanism and the medium response, and so the data are compared to several modern event generators and analytic calculations. The models considered do not fully reproduce the data. [Figure not available: see fulltext.] © 2021, The Author(s).