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https://hdl.handle.net/20.500.12511/11384

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The impact of climate change on construction activity performance
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Oruç, Sertaç; Dikbaş, Hüseyin Attila; Gümüş, Berkin; Yücel, İsmail
There are specific construction operations that require weather forecast data to make short-term decisions regarding construction; however, most resource-related decision making and all project management plans must be carried out to anticipate weather conditions beyond the capabilities of the currently available forecasting technologies. In this study, a series of single- and multi-risk analyses were performed with 9 km grid resolution over Turkiye using combinations of weather and climate variables and their threshold values which have an impact on the execution and performance of construction activities. These analyses will improve the predictability of potential delays, enable the project to be scheduled on a future-proof basis by considering the calculated normal and periodic predictions on the grid scale, and serve as a dispute resolution tool for related claims. A comprehensive case study showcasing the methodology and illustrating its application shows that the project duration is expected to be extended because of the impact of climate on both historical and future periods. While the original project duration was 207 days, when climate effects were considered, the optimum mean and median values increased to 255 and 238 days, respectively, for the historical period. The optimum duration mean and median change to 239 days by the end of the century, according to the SSP5-8.5 scenario, if the construction schedules consider climate change. The change in duration was mainly due to rising temperatures, which increased winter workability and reduced summer workability. However, if the historical practices are carried over to future schedules, the mean and median increase to 258 days and 244 days, respectively, which may cause unavoidable direct, indirect, or overhead costs.
Nonlocal effects of antibiotic-resistance-causing mutations reveal an alternative region for targeting on FtsW-penicillin-binding protein 3 complex of haemophilus influenzae
(American Chemical Society, 2023) Alhamwi, Almotasem Belah; Atılgan, Canan; Şensoy, Özge
[Abstract Not Available]
Cyber-WISE: A cyber-physical deep wireless indoor positioning system and digital twin approach
(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Karakuşak, Muhammed Zahid; Kıvrak, Hasan; Watson, Simon; Özdemir, Mehmet Kemal
In recent decades, there have been significant research efforts focusing on wireless indoor localization systems, with fingerprinting techniques based on received signal strength leading the way. The majority of the suggested approaches require challenging and laborious Wi-Fi site surveys to construct a radio map, which is then utilized to match radio signatures with particular locations. In this paper, a novel next-generation cyber-physical wireless indoor positioning system is presented that addresses the challenges of fingerprinting techniques associated with data collection. The proposed approach not only facilitates an interactive digital representation that fosters informed decision-making through a digital twin interface but also ensures adaptability to new scenarios, scalability, and suitability for large environments and evolving conditions during the process of constructing the radio map. Additionally, it reduces the labor cost and laborious data collection process while helping to increase the efficiency of fingerprint-based positioning methods through accurate ground-truth data collection. This is also convenient for working in remote environments to improve human safety in locations where human access is limited or hazardous and to address issues related to radio map obsolescence. The feasibility of the cyber-physical system design is successfully verified and evaluated with real-world experiments in which a ground robot is utilized to obtain a radio map autonomously in real-time in a challenging environment through an informed decision process. With the proposed setup, the results demonstrate the success of RSSI-based indoor positioning using deep learning models, including MLP, LSTM Model 1, and LSTM Model 2, achieving an average localization error of <= 2.16 m in individual areas. Specifically, LSTM Model 2 achieves an average localization error as low as 1.55 m and 1.97 m with 83.33% and 81.05% of the errors within 2 m for individual and combined areas, respectively. These outcomes demonstrate that the proposed cyber-physical wireless indoor positioning approach, which is based on the application of dynamic Wi-Fi RSS surveying through human feedback using autonomous mobile robots, effectively leverages the precision of deep learning models, resulting in localization performance comparable to the literature. Furthermore, they highlight its potential for suitability for deployment in real-world scenarios and practical applicability.
Yerel yönetimlerde elektronik ihale (E-İhale) süreçleri ve yapı bilgi modellemesi (YBM) entegrasyonu
(2022) Pınar, Ömer Galip
Ülkemizde, diğer devlet kurumlarında olduğu gibi, yerel yönetimlerde de her türlü mal ve hizmet alımı yöntemlerinde de yapılan ihaleler için, Türkiye Elektronik Kamu Alımları Platformu (EKAP) adı verilen bir uygulama kullanılmaktadır. Özellikle yerel yönetimlerde hizmet çeşitliliğinin tek bir kurumda toplanması ve söz konusu taleplere hızlı bir şekilde cevap verilmesi zorunluluğu ortaya çıkması sonucu bu süreçlerin hızlı ve sağlıklı bir şekilde çözülmesi gerekmektedir. Yapılan bu çalışma kapsamında da EKAP konusunda uzmanların yapmış olduğu çalışmalar incelenmiş, yapılan literatür araştırması sonucu bunlara örnek verilmiştir. Yerel yönetimlerde yapılan çalışmaların ise daha çok geleneksel yöntemler ile yürütüldüğü gözlemlenmiş, özellikle belediyelerde EKAP sistemi ile entegre edilebilecek bir YBM uygulaması ile öncelikle proje yönetimlerinin daha profesyonel yapılacağı görülmüştür. Bu uygulamaların sağlıklı bir şekilde entegre edilebilmesi durumunda, sonuçlarının nasıl olacağına dair örnekler çalışma içerisinde paylaşılmıştır. Ayrıca pilot bir uygulama ile söz konusu çalışmaların desteklenebileceği ve sahadaki uygulama sonuçları ile yapılan akademik açıklamaların birbiri ile örtüşeceği görülmüştür.
Impacts of climate change on extreme climate indices in Türkiye driven by high-resolution downscaled CMIP6 climate models
(MDPI, 2023) Gümüş, Berkin; Oruç, Sertaç; Yücel, İsmail; Yılmaz, Mustafa Tuğrul
In this study, the latest release of all available Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models with two future scenarios of Shared Socio-Economic Pathways, SSP2-4.5 and SSP5-8.5, over the period 2015–2100 are utilized in diagnosing climate extremes in Türkiye. Coarse-resolution climate models were downscaled to a 0.1° × 0.1° (~9 km) spatial resolution using the European Centre for Medium-Range Weather Forecasts Reanalysis 5-Land (ERA5-Land) dataset based on three types of quantile mapping: quantile mapping, detrended quantile mapping, and quantile delta mapping. The temporal variations of the 12 extreme precipitation indices (EPIs) and 12 extreme temperature indices (ETIs) from 2015 to 2100 consistently suggest drier conditions, in addition to more frequent and severe precipitation extremes and warming temperature extremes in Türkiye, under the two future scenarios. The SSP5-8.5 scenario indicates more severe water stress than the SSP2-4.5 scenario; the total precipitation decreases up to 20% for Aegean and Mediterranean regions of Türkiye. Precipitation extremes indicate a decrease in the frequency of heavy rains but an increase in very heavy rains and also an increasing amount of the total precipitation from very heavy rain days. Temperature extremes such as the coldest, warmest, and mean daily maximum temperature are expected to increase across all regions of Türkiye, indicating warming conditions by up to 7.5 °C by the end of the century. Additionally, the coldest daily maximums also exhibit higher variability to climate change in the subregions Aegean, Southeastern Anatolia, Marmara, and Mediterranean regions of Türkiye while the mean daily maximum temperature showed greater sensitivity in the Black Sea, Central Anatolia, and Eastern Anatolia regions.
Applications of data mining algorithms for customer recommendations in retail marketing
(Nova Science Publishers, Inc., 2022) Delice, Elif; Polatlı, Lütviye Özge; Düzdar Argun, İrem; Tozan, Hakan
In recent years, researchers have highlighted how large volumes of data can be transformed into information to determine customer behaviors, and data mining applications have become a major trend. It has become critical for organizations to use a tool for understanding the relationships between data to protect their marketplace by increasing customer loyalty. Thanks to data mining applications, data can be processed and transformed into information, and in this way, target audiences can be determined while developing marketing strategies. This chapter aims to increase the market share with products specific to the customer portfolio, introduce strategic marketing tools for retaining old customers, introduce effective methods for acquiring new customers, and increase the retail sales chart, based on purchasing habits of customers. The data set was collected under pandemic conditions during the COVID-19 process and analyzed to support retail businesses in their online shopping orientation. By examining the local customer base, it was assumed that the customer group would display similar behaviors in online or teleordering methods, customer identification and order estimation were made to follow an effective sales policy. Segmentation was performed with data mining applications, and the grouped data were separated according to their similarities. The data set consisting of demographic characteristics and various product information of the enterprise's customers were analyzed with Decision Tree and Random Forest, which are data mining methods, the best performing algorithm in the data set was selected by comparing the performance of the methods. As a result of the findings, appropriate suggestions were given to the business to determine the purchasing tendencies of the customers and to increase the level of effectiveness in sales-marketing strategies. In this way, materials were presented to assist the enterprise in developing strategies to increase the number of sales by taking faster and more accurate action by avoiding the time and expense that would be lost by the trial-error method.
Finite element spine models and spinal instruments: A review
(World Scientific Publishing Co Pte Ltd, 2022) Akıncı, Saliha Zeyneb; Arslan, Yunus Ziya
There is considerable biomechanics literature on finite element modeling and analysis of the spine. To accurately mimic the biomechanical behavior of the vertebral column, a generated computational model has to include anatomical structures that are consistent with physiological reality. In this review article, we focused on the finite element spine models that have been developed by various approaches in the literature. Firstly, the anatomical features of the spine and the spinal components have been briefly explained. We then focused on the modeling stages of vertebrae, ligaments, facet joints, intervertebral discs, and spinal instruments. With this paper, we expect to provide a comprehensive resource regarding the modeling preferences used in spine modeling.
RSS-based wireless LAN indoor localization and tracking using deep architectures
(MDPI, 2022) Karakuşak, Muhammed Zahid; Kıvrak, Hasan; Ateş, Hasan Fehmi; Özdemir, Mehmet Kemal
Wireless Local Area Network (WLAN) positioning is a challenging task indoors due to environmental constraints and the unpredictable behavior of signal propagation, even at a fixed location. The aim of this work is to develop deep learning-based approaches for indoor localization and tracking by utilizing Received Signal Strength (RSS). The study proposes Multi-Layer Perceptron (MLP), One and Two Dimensional Convolutional Neural Networks (1D CNN and 2D CNN), and Long Short Term Memory (LSTM) deep networks architectures for WLAN indoor positioning based on the data obtained by actual RSS measurements from an existing WLAN infrastructure in a mobile user scenario. The results, using different types of deep architectures including MLP, CNNs, and LSTMs with existing WLAN algorithms, are presented. The Root Mean Square Error (RMSE) is used as the assessment criterion. The proposed LSTM Model 2 achieved a dynamic positioning RMSE error of 1.73 m, which outperforms probabilistic WLAN algorithms such as Memoryless Positioning (RMSE: 10.35 m) and Nonparametric Information (NI) filter with variable acceleration (RMSE: 5.2 m) under the same experiment environment.
Machine learning-based analysis of glioma grades reveals co-enrichment
(MDPI, 2022) Garbulowski, Mateusz; Smolinska, Karolina; Çabuk, Uğur; Yones, Sara A.; Celli, Ludovica; Yaz, Esma Nur; Barrenäs, Fredrik; Diamanti, Klev; Wadelius, Claes; Komorowski, Jan
Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for gliomas is The Cancer Genome Atlas (TCGA). However, such big cohorts should be processed with caution and evaluated thoroughly as they can contain batch and other effects. Furthermore, biological mechanisms of cancer contain interactions among biomarkers. Thus, we applied an interpretable machine learning approach to discover such relationships. This type of transparent learning provides not only good predictability, but also reveals co-predictive mechanisms among features. In this study, we corrected the strong and confounded batch effect in the TCGA glioma data. We further used the corrected datasets to perform comprehensive machine learning analysis applied on single-sample gene set enrichment scores using collections from the Molecular Signature Database. Furthermore, using rule-based classifiers, we displayed networks of co-enrichment related to glioma grades. Moreover, we validated our results using the external glioma cohorts. We believe that utilizing corrected glioma cohorts from TCGA may improve the application and validation of any future studies. Finally, the co-enrichment and survival analysis provided detailed explanations for glioma progression and consequently, it should support the targeted treatment.
The differentiation of parental satisfaction with the spatial features of public primary schools: The case of Pendik, Istanbul
(Konya Technical University, 2021) Yılmaz, Cengiz; Pakoz, Muhammed Ziya
Purpose The present study aims to examine the change of parents' satisfaction with the spatial features of public primary schools according to personal, residential, school, and neighbourhood characteristics and to measure to what extent the spatial features explain the overall satisfaction with primary schools. Design/Methodology/Approach Firstly, the study area was divided into 4 clusters by hierarchical clustering method. In proportion to the number of students in each cluster, an online survey was conducted with 807 parents in 19 public primary schools in Pendik between 5-27 May 2020. Personal and residential characteristics obtained from the survey results and school and neighbourhood characteristics obtained from secondary sources were cross-tabulated with the levels of satisfaction on 19 spatial characteristics of the schools. Later, these 19 spatial features were reduced to two basic dimensions with the principal component analysis, and the level of explanation of these dimensions on the overall school satisfaction was revealed by multiple regression analysis. Findings The level of satisfaction of parents with the spatial characteristics of primary schools differs significantly according to personal (15 out of 19), residential (5 out of 19), school (14 out of 19), and neighbourhood (10 out of 19) characteristics. In addition, the parents' satisfaction regarding the spatial adequacies of the primary school has a determinant effect on the overall satisfaction of the parents with the primary school. The most effective factors in the overall satisfaction of parents from primary school are "size of sports fields" and "size of activity spaces". Research Limitations/Implications Similar studies in different cases (both in rural and urban areas), different time periods, and for different education levels should be repeated to compare the results. Social/Practical Implications This research indicates that spatial characteristics should be taken into account in determining the priority improvements starting from the sports fields and activity spaces of schools. Originality/Value The present study evaluates the spatial adequacies of public primary schools and associates it with urbanization and urban planning. It is expected to contribute to the studies to increase the quality of spatial dimensions of primary schools, and consequently urban life quality.
Integrative analysis of axolotl gene expression data from regenerative and wound healing limb tissues
(Nature Research, 2019) Sibai, Mustafa; Parlayan, Cüneyd; Tuğlu, Pelin; Öztürk, Gürkan; Demircan, Turan
Axolotl (Ambystoma mexicanum) is a urodele amphibian endowed with remarkable regenerative capacities manifested in scarless wound healing and restoration of amputated limbs, which makes it a powerful experimental model for regenerative biology and medicine. Previous studies have utilized microarrays and RNA-Seq technologies for detecting differentially expressed (DE) genes in different phases of the axolotl limb regeneration. However, sufficient consistency may be lacking due to statistical limitations arising from intra-laboratory analyses. This study aims to bridge such gaps by performing an integrative analysis of publicly available microarray and RNA-Seq data from axolotl limb samples having comparable study designs using the "merging" method. A total of 351 genes were found DE in regenerative samples compared to the control in data of both technologies, showing an adjusted p-value < 0.01 and log fold change magnitudes >1. Downstream analyses illustrated consistent correlations of the directionality of DE genes within and between data of both technologies, as well as concordance with the literature on regeneration related biological processes. qRT-PCR analysis validated the observed expression level differences of five of the top DE genes. Future studies may benefit from the utilized concept and approach for enhanced statistical power and robust discovery of biomarkers of regeneration.

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