Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Understanding the Impact of Deep Learning Models on Building Information Modeling Systems: a Study on Generative Artificial Intelligence Tools †(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Yönder,V.M.The power of the relationship between building information modeling (BIM) systems and advanced artificial intelligence models holds considerable weight for users of BIM. This relationship allows the generation, analysis, and deduction of insights from substantial construction digital data. This research explores the relationship between generative artificial intelligence (generative AI), deep neural nets, and the BIM systems, including its users. This study examines the correlation between generative artificial intelligence and BIM methodology by conducting a case study. Furthermore, this paper investigates the conceptual and practical use of generative AI components (e.g., text-to-image models, diffusion networks, deep neural networks, large language model, and generative adversarial network) in BIM systems via bibliometric analysis. © 2023 by the author.Article Citation - Scopus: 4An Investigation of Shopping Mall Design Requirements †(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Çavka,H.B.Shopping malls may be considered as controversial structures since they sometimes fail to comply with the expectations of the project stakeholders throughout the project life cycle. New mall projects often attract the attention of people since such a structure has a potential to reshape the neighborhood it is located in; however, the impact is usually negative. On the other hand, the parties involved in mall projects may be subject to criticism from both the public and the industry during the design, construction, and operation. In this study we conducted semi-structured interviews with five managers of an international company that provides real estate services worldwide, and mainly focuses on managing shopping centers within the context of Turkiye. During the interviews, we collected insights on shopping mall design and criteria that have an impact on the operational success or failure. We analyzed the interview data to understand the shopping mall design requirements from the experts’ perspectives. We summarized our investigation under three main categories as location, shop and brand mix, and design. Analyzed data indicates that the requirements and use of shopping malls evolve and change over time. The change is driven by things such as changing habits and expectations of the users and new marketing approaches. Understanding such changes is essential for designers and investors to propose new design approaches and space compositions in order to be able to adapt to the changes. Through our analysis of the collected data, we provided insights on requirements and new trends that affect the design of malls. As further explained in this paper, our analysis indicates a number of important topics during design such as the need to design to fit ever-changing spatial needs, providing feel-good environment for users, correct placement of spaces and stores related to each other, designing circulation that supports commercial activities, and designing with a consideration of operation and maintenance. According to the collected data, the trend of shopping mall design is towards integration of hybrid uses, free forms, more open spaces, increased emphasis on gastronomy, and enabling socializing while leveraging technology and being more sustainable. © 2023 by the author.Article Citation - Scopus: 1Strategy for Revalorization of Cheese Whey Streams To Produce Phenyllactic Acid †(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Meruvu,H.Cheese whey (CW) is the residual liquid waste from cheese manufacturing industries, and it is rich in diverse nutrients with the potential for usage as a growth matrix for sustaining lactic acid bacteria (LAB) fermentation. Lactic acid (LA), phenyllactic acid (PLA), and their derivatives are green chemicals that can be produced by LAB metabolism with the revalorization of CW. LA and PLA are known for their antimicrobial properties, immunoregulatory functions, and production of biobased polymers (biodegradable plastics) like poly lactic acid and poly-phenyl lactic acid; hence, they find numerous applications in agricultural/food-based, pharmaceutical, biochemistry, or medical fields, as well as in antibiotic supplements in livestock feeds for animal husbandry. Herewith, we discuss our experimental strategy/concept (that can be implemented) for the microbial fermentation of cheese whey streams using robust LAB co-cultures to produce 3-PLA through sequential steps, adding a note upon their possible applications hereof. It is proposed that various food matrices, like raw cow milk, fermented cow milk, and fermented table olives, will be screened for the isolation of robust lactic acid bacteria that can be used as starter cultures for the fermentation of cheese whey liquids for producing augmented levels of LA and/or PLA. Moreover, we discuss the feasibility of practically producing PLA using an orchestrated assemblage of simple procedures, viz., isolating robust LAB strains from natural food matrices, tailoring LAB growth using a selective medium sustenance, adopting adaptive evolution procedures for improving resistance to higher temperatures and tolerance to lactic acid and/or cheese whey (low-cost substrate), and using FTIR and HPLC tools for analyzing the PLA content produced. Two Lactobacillus isolates (CM30_001 and CMW_10−3), sourced from raw cow milk and fermented cow milk whey, were found to produce 3-PLA contents of 39 mg/L and 32 mg/L in batch fermentation, using this proposed strategy. © 2023 by the author.Article Citation - WoS: 5Citation - Scopus: 6Effect of Graphene Nanoplatelet Content on Mechanical and Elevated-Temperature Tribological Performance of Self-Lubricating Ze10 Magnesium Alloy Nanocomposites(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Kandemir,S.; Yöyler,S.; Kumar,R.; Antonov,M.; Dieringa,H.Magnesium (Mg) and graphene in alloy formulations are of paramount importance for lightweight engineering applications. In the present study, ZE10 Mg-alloy-based nanocomposites reinforced with graphene nanoplatelets (GNPs) having a thickness of 10–20 nm were fabricated via ultrasound-assisted stir casting. The effect of GNP contents (0.25, 0.5, and 1.0 wt.%) on the microstructure, Vickers hardness, and tensile properties of nanocomposites was investigated. Further, tribological studies were performed under a ball-on-disc sliding wear configuration against a bearing ball counterbody, at room and elevated temperatures of 100 °C and 200 °C, to comprehend temperature-induced wear mechanisms and friction evolution. It was revealed that the GNP addition resulted in grain coarsening and increased porosity rate of the Mg alloy. While the composites exhibited improved hardness by 20–35% at room temperature and 100 °C, a minor change was observed in their hardness and tensile yield strength values at 200 °C with respect to the GNP-free alloy. A notable improvement in lowering and stabilizing friction (coefficient of friction at 200 °C~0.25) and wear values was seen for the self-lubricating GNP-added composites at all sliding temperatures. The worn surface morphology indicated a simultaneous occurrence of abrasive and adhesive wear mode in all samples at room temperature and 100 °C, while delamination and smearing along with debris compaction (tribolayer protection) were the dominant mechanisms of wear at 200 °C. Inclusively, the results advocate steady frictional conditions, improved wear resistance, and favorable wear-protective mechanisms for the Mg alloy–GNP nanocomposites at room and elevated temperatures. © 2024 by the authors.Article Citation - Scopus: 20Estrus Detection and Dairy Cow Identification With Cascade Deep Learning for Augmented Reality-Ready Livestock Farming(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Arıkan, İ.; Ayav, T.; Seçkin, A.Ç.; Soygazi, F.Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming. © 2023 by the authors.Article Citation - WoS: 3Citation - Scopus: 3Assessment of Mutual Variation of Near-Surface Air Temperature, Land Surface Temperature and Driving Urban Parameters at Urban Microscale(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Gerçek,D.; Güven,İ.T.The Urban Heat Island (UHI) effect is of critical concern for cities’ adaptation to climate change. The UHI effect shows substantial intra-urban variation at the city microscale, causing disparities in thermal comfort and energy consumption. Therefore, air temperature assessment should be prioritized for effective heat mitigation and climate adaptation. However, meteorological stations’ spatial distribution is far from meeting the scale that the UHI and its driving parameters operate. This limitation hampers demonstrating the intra-city variability of UHI and its origin of sources; for example, most studies employ Land Surface Temperature (LST), usually without demonstrating the relationship between UHI and LST. The current body of knowledge on urban climate implies a much better understanding and more detailed information on the spatial pattern of UHI and the driving factors to provide decision-makers with tools to develop effective UHI mitigation and adaptation strategies. In an attempt to address the adequacy of the use of LST and UPs in describing the intra-city variability of UHI, this study investigates the relationship between LST daytime and nighttime, and air temperature (Ta) daytime and nighttime, and driving urban parameters (UPs) of UHI together. Although it is well recognized that the intensity of the UHI is characterized by Ta, particularly at night, so-called nocturnal UHI, the use of remotely sensed LST is common, owing to the lack of spatially detailed Ta data in cities. Our findings showed that nocturnal UHI is weakly correlated with nighttime LST with a Pearson correlation (r) of 0.335 at p > 0.05 and that it is not correlated with daytime LST for the case study, highlighting the need for Ta observations for representing the intra-urban variation of nocturnal UHI. Among UPs, Sky View Factor (SVF), Building Volume Density (BVD), and Road Network Density (RND) explained 69% of the variability of Ta nighttime that characterizes nocturnal UHI. Therefore, UPs that performed well in estimating nocturnal UHI may be used in the absence of densely distributed Ta measurements. In a further investigation of the urban cooling phenomenon based on UHI diurnal changes, a particular region with high nighttime temperatures spoiled the Ta daytime and nighttime coherence. This region is characterized by high Mean Building Height (MBH), BFD, and BVD that re-emits heat, low SVF that prevents urban cooling, and high RND that releases extra heat at night. These particular UPs can be of prior interest for urban cooling. The present study, exploring the relationships of LST and Ta in a diurnal context, offers a further understanding of the preference of LST, Ta, or UPs to characterize UHI. Ta, in relation to major causative factors (UPs), provides insights into addressing the localities most vulnerable to the UHI effect and possible strategies targeting heat mitigation for sustainability and climate change resilience. © 2023 by the authors.