Smart Cities in the Global Context: Geographical Analyses of Regional Differentiations
Tijjani, Kabeer Saleh | Sarıkaya Levent, Yasemin | Levent, Tolga
The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring regional differentiations in smart city development. This study aims to examine how smart cities differentiate, especially through associations between regions and smart city dimensions. This study utilises data from the IMD Smart City Index 2023 and applies a multi-step methodology based on the United Nations’ geographic regions, employing geographical and statistical analyses. The findings reveal distinct regional differentiations, highlighting a clear Global North–Sou...
Investigation and Implementation of New Technology Wearable Mobile Laser Scanning (WMLS) in Transition to an Intelligent Geospatial Cadastral Information System
Yiğit, Abdurahman Yasin | Ulvi, Ali | Yakar, Murat
The human population is constantly increasing throughout the world, and accordingly, construction is increasing in the same way. Therefore, there is an emergence of irregular and unplanned urbanization. In order to achieve the goal of preventing irregular and unplanned urbanization, it is necessary to monitor the cadastral borders quickly. In this sense, the concept of a sensitive, up-to-date, object-based, 3D, and 4D (4D, 3D + time) cadastral have to be a priority. Therefore, continuously updating cadastral maps is important in terms of sustainability and intelligent urbanization. In addition, due to the increase in urbanization, it has become necessary to update the cadastral information system and produce 3D cadastral maps. However, since there are big problems in data collection in urb...
Transfusion Reactions in Paediatric Patients; Hemovigilance Data from a Tertiary Hospital
Fatma Durak | Özlem Tezol
Objective: This study aimed to define transfusion-related adverse reactions (TRs) observed in paediatric patients at a university hospital in Turkey. Methods: The data from the archive of the Mersin University Hospital Blood Centre, spanning the period between August 2017 and August 2024, were subjected to retrospective analysis. The descriptive and clinical characteristics of paediatric patients who received blood transfusions and were recorded using the haemovigilance reporting system were subjected to analysis. The findings were presented in the form of descriptive statistics. Results: Over a seven-year period, 34 TRs were reported, yielding an overall incidence of 1.12‰(95% CI: 0.79–1.55‰; 34/30,265). The reaction rate was 0.84‰(95% CI: 0.45–1.42‰; 12/14,329) for erythrocyte c...
An Adaptive Underwater Image Enhancement Framework Combining Structural Detail Enhancement and Unsupervised Deep Fusion
Kahveci, Semih | Avaroğlu, Erdinç
The underwater environment severely degrades image quality by absorbing and scattering light. This causes significant challenges, including non-uniform illumination, low contrast, color distortion, and blurring. These degradations compromise the performance of critical underwater applications, including water quality monitoring, object detection, and identification. To address these issues, this study proposes a detail-oriented hybrid framework for underwater image enhancement that synergizes the strengths of traditional image processing with the powerful feature extraction capabilities of unsupervised deep learning. Our framework introduces a novel multi-scale detail enhancement unit to accentuate structural information, followed by a Latent Low-Rank Representation (LatLRR)-based simplifi...
GIS-Based Multi-Criteria Analysis for Urban Afforestation Planning in Semi-Arid Cities
Ulvi, Ali | Yiğit, Abdurahman Yasin
Urban forests are very important for the environment and for people, especially in semi-arid cities where there is not much greenery. This makes heat stress worse and makes the city less livable. This paper presents a comprehensive geospatial methodology for selecting afforestation sites in the expanding semi-arid urban area of Şanlıurfa, Turkey, characterized by minimal forest cover, rapid urbanization, and extreme weather conditions. We identified nine ecological and infrastructure criteria using high-resolution Sentinel-2 images and features from the terrain. These criteria include slope, aspect, topography, land surface temperature (LST), solar radiation, flow accumulation, land cover, and proximity to roads and homes. After being normalized to make sure they were ecologically relevant...
Explainable Sinkhole Susceptibility Mapping Using Machine-Learning-Based SHAP: Quantifying and Comparing the Effects of Contributing Factors in Konya, Türkiye
Iban, Muzaffer Can
Sinkholes, naturally occurring formations in karst regions, represent a significant environmental hazard, threatening infrastructure, agricultural lands, and human safety. In recent years, machine learning (ML) techniques have been extensively employed for sinkhole susceptibility mapping (SSM). However, the lack of explainability inherent in these methods remains a critical issue for decision-makers. In this study, sinkhole susceptibility in the Konya Closed Basin was mapped using an interpretable machine learning model based on SHapley Additive exPlanations (SHAP). The Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) algorithms were employed, and the interpretability of the model results was enhanced through SHAP analysis. Among the c...
Morphological Characteristics of Grapevine Cultivars and Closed Contour Analysis with Elliptic Fourier Descriptors
Demir, Bünyamin
Morphology is the most visible and distinct character of plant organs and is accepted as one of the most important tools for plant biologists, plant breeders and growers. A number of methods based on plant morphology are applied to discriminate in particular close cultivars. In this study, image processing analysis was used on 20 grape cultivars (“Amasya beyazı“, “Antep karası“, “Bahçeli karası”, “Çavuş“, “Cevşen“, “Crimson“, “Dimrit“, “Erenköy beyazı“, “Hafızali“, “Karaşabi“, “Kırmızı“, “İzabella (Isabella) “, “Morşabi“, “Müşgüle“, “Nuniya“, “Royal“, “Sultani çekirdeksiz (Sultanina)“, “Yalova incisi“, “Yerli beyazv“, “Yuvarlak çekirdeksiz“) to classify them. According to image processing analysis, the longest and the greatest projected area values were observed in “Antep karası“ cultivar....
Capturing the Experience: How Digital Media Affects Memory Retention in Museum Education
Say, Fuat Serkan | Öztürk, İsmail Yavuz
This study investigates the effects of digital media usage, specifically photo-taking and video recording, on memory retention in the context of museum education. Utilizing a quasi-experimental design, this research involved three groups, each exposed to different conditions: observation without media use, photo-taking, and video recording. A total of 120 university students who participated in the study were divided randomly into groups balanced by working memory capacity. Immediate and delayed recall tests were conducted to assess short-term memory and long-term retention. The results reveal that participants who merely observed the objects exhibited considerably better memory performance compared to those who used digital media. This result is consistent with the cognitive offloading hy...
Moringa oleifera Lam. as a bioflocculant for harvesting microalgae grown on agricultural wastewaters for feed production
Eker-Develi, Elif | Tekdal, Dilek
Harvesting impacts the costs of microalgae production and affects the characteristics of the final product. Therefore, this study evaluated Moringa oleifera seed powder (MP) as a bioflocculant compared to two chemicals (Aluminium Sulphate—AS and Iron Chloride—IC) to harvest a mixed microalgae culture (Chlorella vulgaris and Desmodesmus sp.) grown on digestate. MP was the most stable flocculant but resulted in the lowest harvesting efficiency of 75%, compared to 94% for AS and 100% for IC. Process parameters such as pH, duration of mixing, grinding method for obtaining the powder, and granulometry had no significant effect on the harvesting efficiency of MP, reinforcing that this is a robust flocculant. The use of a water extraction step increased the harvesting efficiency of MP to ...
Smart Cities in the Global Context: Geographical Analyses of Regional Differentiations
Tijjani, Kabeer Saleh | Sarıkaya Levent, Yasemin | Levent, Tolga
The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring regional differentiations in smart city development. This study aims to examine how smart cities differentiate, especially through associations between regions and smart city dimensions. This study utilises data from the IMD Smart City Index 2023 and applies a multi-step methodology based on the United Nations’ geographic regions, employing geographical and statistical analyses. The findings reveal distinct regional differentiations, highlighting a clear Global North–Sou...
Smart Cities in the Global Context: Geographical Analyses of Regional Differentiations
Tijjani, Kabeer Saleh | Sarıkaya Levent, Yasemin | Levent, Tolga
The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring regional differentiations in smart city development. This study aims to examine how smart cities differentiate, especially through associations between regions and smart city dimensions. This study utilises data from the IMD Smart City Index 2023 and applies a multi-step methodology based on the United Nations’ geographic regions, employing geographical and statistical analyses. The findings reveal distinct regional differentiations, highlighting a clear Global North–Sou...
Automating an Encoder–Decoder Incorporated Ensemble Model: Semantic Segmentation Workflow on Low-Contrast Underwater Images
Bektaş, Jale
Numerous methods have been proposed for semantic segmentation and the state-of-the-art part is likely to be incorporated by deep learning-based methods which show a salient performance. This study addresses the challenge of semantic segmentation in low-contrast imbalanced under water images. Moreover, it employs nine model fusions as a downstream workflow task using encoder–decoder architectures with Dice Loss and Focal Loss training focusing on the imbalance data. Afterwards, the most effective two encoder–decoder fusion models, Res34+Unet and VGG19+FPN, by 0.592%, 0.590% mIoU on average and by 0.510%, 0.491% F1-score yielded better performance, respectively, than other models. Using a weight-optimization algorithm, the ensemble model with recreated IoU results improves the accuracy for b...
Assessment of Groundwater Potential Zones Utilizing Geographic Information System-Based Analytical Hierarchy Process, Vlse Kriterijumska Optimizacija Kompromisno Resenje, and Technique for Order Preference by Similarity to Ideal Solution Methods: A Case Study in Mersin, Türkiye
Çelik, Mehmet Özgür | Kuşak, Lütfiye | Yakar, Murat
The indiscriminate use of surface water has heightened the demand for groundwater supplies. Therefore, it is critical to locate potential groundwater sources to develop alternative water resources. Groundwater detection is tremendously valuable, as is sustainable groundwater management. Mersin, in southern Türkiye, is expected to confront drought shortly due to increased population, industry, and global climate change. The groundwater potential zones of Mersin were determined in this study by GIS-based AHP, VIKOR, and TOPSIS methods. Fifteen parameters were used for this goal. The study area was separated into five categories. The results show that the study area can be divided into “Very High” zones (4.98%, 5.94%, 7.96%), followed by “High” zones (10.89%, 10.32%, 16.50%), “Moderate” zones...
A novel cosmopolitan species of blue diatoms
Eker-Develi, Elif
Specimens of a new species of blue diatoms from the genus Haslea Simonsen were discovered in geographically distant sampling sites, first in the Canary Archipelago, then North Carolina, Gulf of Naples, the Croatian South Adriatic Sea, and Turkish coast of the Eastern Mediterranean Sea. An exhaustive characterization of these specimens, using a combined morphological and genomic approach led to the conclusion that they belong to a single new to science cosmopolitan species, Haslea silbo sp. nov. A preliminary characterization of its blue pigment shows similarities to marennine produced by Haslea ostrearia, as evidenced by UV–visible spectrophotometry and Raman spectrometry. Life cycle stages including auxosporulation were also observed, providing data on the cardinal points of this s...
Machine Learning for Out-of-Sample Prediction of Industry Portfolio Returns Within Multi-Factor Asset Pricing Models
Duran, Esra Sarıoğlu | Korkmaz, Turhan
Accurately predicting asset returns remains a central challenge in finance, with significant implications for portfolio optimization and risk management. In response to the challenge, this study evaluates the predictive performance of machine learning algorithms in estimating excess returns of U.S. industry portfolios, within the out-of-sample prediction framework of the Fama–French three-, four-, five- and six-factor asset pricing models. In the analysis, Support Vector Regression, Multilayer Perceptron, Linear Regression, and k-Nearest Neighbor were employed using monthly return data from 1992 to 2022, covering 5-, 10-, 12-, 17-, 30-, 38-, 48-, and 49-portfolio configurations composed of NYSE, AMEX, and NASDAQ-listed firms. The findings reveal that support vector regression achie...
Spatiotemporal Agricultural Drought Assessment and Mapping Its Vulnerability in a Semi-Arid Region Exhibiting Aridification Trends
Iban, Muzaffer Can
Agricultural drought, increasingly intensified by climate change, poses a significant threat to food security and water resources in semi-arid regions, including Türkiye’s Konya Closed Basin. This study evaluates six satellite-derived indices—Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI), Evapotranspiration Condition Index (ETCI), and Soil Moisture Condition Index (SMCI)—to monitor agricultural drought (2001–2024) and proposes a drought vulnerability map using a novel Drought Vulnerability Index (DVI). Integrating Moderate Resolution Imaging Spectroradiometer (MODIS), Climate Hazards Center InfraRed Precipitation with Station (CHIRPS), and Land Data Assimilation System (FLDAS) datasets, the DVI combin...