01. Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed

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30 Ekim 2020 Ege Denizi Depreminin Kabuk Deformasyonuna Etkisinin Tusaga-aktif Verileri ile İncelenmesi
(Gumushane University, 2024) Baş, İ.Ç.; Abbak, R.A.
The TUSAGA-Active (Turkish National Continuous Operating Reference System) is available for commercial and academic studies with 168 fixed GNSS (Global Navigational Satellite Systems) stations. Its capability to provide high-accuracy data facilitate to monitor deformations in engineering structures resulting from crustal movements. On October 30, 2020, an earthquake with a magnitude of ML = 6.6 (MW = 6.9) struck the Aegean Sea at 14.51 local time. The aim of the study is that TUSAGA-Active stations located within the earthquake-affected area are thoroughly examined to detect any crustal deformations caused by this seismic event. As part of this analysis, deformation directions and magnitudes were determined for stations AYD1, CESM, DIDI, IZMI, KIKA, and SALH. RINEX data from 15 days before the earthquake date and 11 days after were processed using CSRS-PPP (Canadian Spatial Reference System Precise Point Positioning Service) and OPUS (Online Positioning User Service), which are internet-based GNSS services. The results of this analysis revealed that the CESM station experienced the most significant displacement, averaging 57.39 mm in the north direction according to the CSRS-PPP service. Similar results were obtained from the OPUS service data. © 2024, Gumushane University. All rights reserved.
3b T1 Ağırlıklı Mr Görüntülerinde Atlas Tabanlı Hacim Ölçüm Yöntemini Kullanarak Alzheimer Hastalığının Teşhisi
(Gazi Univ, 2022) Öziç, Muhammet Üsame; Ekmekci, Ahmet Hakan; Özşen, Seral; Barstuğan, Mücahid; Yıldoğan, Aydın Talip
Alzheimer Hastalığı yaşlılık ile beraber başlayan bir beyin hastalığıdır. Hastalığın teşhisi, takibi ve ilgili beyin bölgelerinin ölçümleri yüksek çözünürlüklü üç boyutlu yapısal manyetik rezonans görüntüleri ile yapılabilmektedir. Bu çalışmada, OASIS veri tabanından alınan 70 Alzheimer 70 Normal 3B T1 ağırlıklı MR görüntüleri üzerinde 116 subkortikal bölgenin hacimsel ölçümünü yapabilecek atlas tabanlı bir hacim ölçüm ve sınıflandırma modeli tasarlanmıştır. Ölçülen değerler her bir denekte gri madde, parankim, total beyin hacmi ile bölünerek normalizasyon işlemi yapılmıştır. Böylece ham ölçülen değerler dahil olmak üzere 140x116 matris boyutlu 4 farklı veri kümesi elde edilmiştir. Veri kümeleri entropi, t-test, roc, Bhattacharyya, Wilcoxon özellik derecelendirme yöntemleri ile en anlamlı özellikten en anlamsız özelliğe doğru derecelendirilmiştir. Derecelendirilen veriler her döngüde sırasıyla birleştirilmiş, lineer ve rbf kernel kullanan destek vektör makinelerine 10-kat çapraz geçerleme ile verilerek sınıflandırma işlemi yapılmıştır. Tüm senaryolar analiz edilerek, en az özellikle en iyi sonucu veren küme, özellik derecelendirme ve sınıflandırma metodu ortaya konulmuştur. Normalizasyon ve özellik derecelendirme yöntemlerinin sınıflandırma sonucuna etkisi incelenmiştir. Deneysel işlemler sonucunda roc özellik derecelendirme tabanlı lineer destek vektör makinesi, total beyin hacmi normalizasyonlu 107 özellik kullanarak %95.71 hassasiyet, %94.29 özgüllük, %95.00 doğruluk, 0.95 eğri altında kalan alan değerleri ile en yüksek oranları vermektedir.
A 3d U-Net Based on Early Fusion Model: Improvement, Comparative Analysis With State-Of Models and Fine-Tuning
(Konya Teknik Univ, 2024) Kayhan, Beyza; Uymaz, Sait Ali
Multi-organ segmentation is the process of identifying and separating multiple organs in medical images. This segmentation allows for the detection of structural abnormalities by examining the morphological structure of organs. Carrying out the process quickly and precisely has become an important issue in today's conditions. In recent years, researchers have used various technologies for the automatic segmentation of multiple organs. In this study, improvements were made to increase the multi-organ segmentation performance of the 3D U-Net based fusion model combining HSV and grayscale color spaces and compared with state-of-the-art models. Training and testing were performed on the MICCAI 2015 dataset published at Vanderbilt University, which contains 3D abdominal CT images in NIfTI format. The model's performance was evaluated using the Dice similarity coefficient. In the tests, the liver organ showed the highest Dice score. Considering the average Dice score of all organs, and comparing it with other models, it has been observed that the fusion approach model yields promising results.
6 Şubat 2023'te Pazarcık ve Elbistan Merkezli 7,7 ve 7,6 Büyüklüğündeki Depremlerin Hatay Bölgesindeki Termal Sularda Olası Radon Anomalilerine Etkisi
(2023) Acar, Merve; Satılmış, Halimenur; Atav, Ülfet; Manisa, Kaan; Bozdağ, Ayla; Erdoğan, Mehmet
Bu proje kapsamında, 6 Şubat 2023?te Pazarcık ve Elbistan merkezli 7,7 ve 7,6 büyüklüğündeki depremlerin ve sonrasında oluşan artçı depremlerin Hatay bölgesindeki yeraltısularında (termal ve kaynak suları) olası radon anomalileri üzerine etkileri araştırılmıştır. Radon konsantrasyonu ölçümleri AlphaGUARD PQ 2000PRO radon detektörü ile gerçekleştirilmiştir. Elde edilen verilere göre 2 lokasyonda önemli radon anomalilerinin olduğu gözlenmiştir. Bu anomalilere 6 Şubat tarihli depremlerin etkisi olabileceği gibi sonrasında gerçekleşen çok sayıdaki artçı depremlerin de etkisi olabilir. Bu anomalilerden ilki Hamamat kaplıcasını besleyen kaynakta gözlenmiştir. Bu kaynakta, 7 Mayıs 2023 tarihinde Topboğazı-Kırıkhan?da meydana gelen 4,9 ML büyüklüğündeki artçı deprem öncesinde radon seviyesinde 4 kat artış gözlenirken sonrasında ise bir azalış gözlenmiştir. Diğer anomali ise Tahtaköprü lokasyonundan alınan kaynakta gözlenmiş olup bu kaynaktaki radon seviyesinde de 28 Nisan tarihinde Hatay-Samandağ?da meydana gelen 4,2 ML büyüklüğündeki deprem öncesi gerçekleştirilen ölçümde yaklaşık 5 kat artış gözlenirken sonrasında da yaklaşık 4 kat gibi bir azalış gözlenmiştir. Bu iki kaynakta gözlenen radon anomalileri ile bu kaynaklar civarında meydana gelen 4,9 ve 4,2 ML büyüklüğündeki depremler arasında bir ilişki olabilir. Dolayısıyla kısıtlı verilere ragmen bu iki anomali 28 Nisan tarihinde Hatay-Samandağ?da meydana gelen 4,2 ML ve 7 Mayıs tarihinde Topboğazı-Kırıkhan?da meydana gelen 4,9 ML büyüklüğündeki artçı depremlerin bir ön işaretçisi olarak yorumlanabilir. Ayrıca bu iki kaynakta uzun süreli radon ölçümlerinin gerçekleştirilmesi olası depremler öncesi bir öncü işaretin gözlenmesi bakımından önemli olabilir.
891–1924 Yıllarında “assomptıon‟un augustġnlerġ” tarġkatının eskġġehġr merkezlġ mġsyonerlġk faalġyetlerġ
(2012) Aydın, Mehmet
Assomption‘un Augustinleri''tarikatının Eskişehir‘deki misyonerlik faaliyetleri, genelde Assomptionistlerin Anadolu‘daki misyon faaliyetlerine bağlı olarak yürütülmüştür. Bu tarikatın başlangıçtaki amacı, Fransa‘yı yeniden Hıristiyanlaştırmaktır. Bu amaçla Emmanuel d‘Alzon (1810–1880), 1845‘te ''Assomption‘un Augustinleri''veya''Assomptionist''tarikatını kurmuştur. Tarikatın ismini, D‘Alzon‘un görev yaptığı Nime Şehrindeki Assomption kolejinden aldığı tahmin edilmektedir. Assomptionist''tarikatı 1864 de Roma tarafından tanınmıştır. ''Assomptionist''ismi, Hz. Meryem‘in göğe çıkışına olan inancın bir ifadesi olarak verilmiştir. Bu inanç, Katolik kilisesi mensupları arasında XIII. yüzyıldan beri yaygın olmakla beraber, 1950 yılında Papa XII. Pie tarafından dogma olarak ilan edilmiştir. Böylece Katolik kilisesi Meryem‘in günahsız hamileliğini ve onun göğe yükselişini kendileri için manevi bir feyz kaynağı olarak benimsemişlerdir. Anahtar kelimeler: Misyon, Assumption, Meryem, Katolik, Papa.
Aber Analysis of Ris-Aided Ssk Schemes Over Ricean Fading Channels
(2022) Canbilen, Ayşe Elif; Ates, Alper
Reconfigurable intelligent surface (RIS) is a promising technology to meet the needs of next-generation wireless communication techniques that enhance the quality of service by effectively adjusting the phases of the signals through a reflective surface. On the other side, space shift keying (SSK), as one of the typical index modulation (IM) techniques, provides data transmission by using only the information of the active transmitting antenna index instead of applying traditional modulation methods. In this study, two of the RIS-assisted SSK schemes are studied to take potential benefits of both RIS and SSK techniques, and the average bit error rate (ABER) performance is investigated over Ricean fading channels. The activated transmitter antenna for each transmission instant is detected by utilizing the maximum likelihood (ML) detection algorithm at the receiver side. The ABER performance of the proposed RIS-based systems in proportion to the increasing number of reflecting elements and Ricean-K factor is presented by both theoretical derivations and computer simulations. The obtained results show that the Ricean-K parameter and the number of reflective elements on the RIS have an undeniable effect on the system performance.
Academic Graph: a Literature Review System
(Institute of Electrical and Electronics Engineers Inc., 2022) Çataltaş, M.; Yumuşak, S.; Oztoprak, K.
As the number of academic publications increase, preparing a literature review becomes more challenging. This paper introduces an automated literature review support system to ease the literature review process for academia with reference graphs, abstract and full document summaries, paper clusters by keywords, abstracts, and abstract summaries combined. The output of the proposed system may ease exploring the state-of-the-art research. © 2022 IEEE.
Citation - WoS: 1
Academic Text Clustering Using Natural Language Processing
(2022) Taşkıran, Fatma; Kaya, Ersin
Accessing data is very easy nowadays. However, to use these data in an efficient way, it is necessary to get the right information from them. Categorizing these data in order to reach the needed information in a short time provides great convenience. All the more, while doing research in the academic field, text-based data such as articles, papers, or thesis studies are generally used. Natural language processing and machine learning methods are used to get the right information we need from these text-based data. In this study, abstracts of academic papers are clustered. Text data from academic paper abstracts are preprocessed using natural language processing techniques. A vectorized word representation extracted from preprocessed data with Word2Vec and BERT word embeddings and representations are clustered with four clustering algorithms.
The Accessibility of Public Transportation Stops: Istanbul Case
(2023) Levend, Sinan; Öztaşkın, Dilara
The study emphasizes the importance of creating a sustainable public transportation system that people can use comfortably. This sustainable transportation approach aims to deliver transportation plans focused on people, society and space. Developing public transportation systems that contribute to social equality by appealing to all segments of society and reducing traffic density has become one of the main objectives of transportation plans. Ensuring the accessibility of public transportation stops is a crucial aspect of achieving this objective. In this context, the study examines the accessibility of public transportation stops in Istanbul. For the accessibility measurements of public transportation stops, the study uses the Service Areas Analysis tool in the ArcGIS program's Network Analyst extension, a geographical information system-based software program. The analysis results indicate that approximately 90% of the population can reach the stops of rubber-tyred public transportation types (one of the public transportation types in Istanbul) within a five-minute walking distance. However, the ratio of the population that can reach rail system stations and maritime transportation piers within a five-minute walking distance is only approximately 3%. Accordingly, it can be seen that the Istanbul transportation system depends heavily on the rubber-tyred public transportation system.
Citation - WoS: 1
Accuracy Assessment Toward Merging of Terrestrial Laser Scanner Point Data and Unmanned Aerial System Point Data
(2023) Karasaka, Lütfiye; Erdal, Kasım; Makineci, Hasan Bilgehan
Terrestrial Laser Scanning (TLS) techniques are widely preferred for 3D models of small and large objects, buildings, and historical and cultural heritages. However, sometimes relying on a single method for 3D modelling an object/structure is insufficient to arrive at a solution or meet expectations. For example, Unmanned Aerial Systems (UAS) provide perspective for building roofs, while terrestrial laser scanners provide general information about building facades. In this research, several facades of a selected building could not be modelled using terrestrial laser scanning, and UAS was used to complete the missing data for 3D modelling. The transformation matrix, a linear function, is created to merge different data types. In the transformation matrix, the scale was found to be 1:1.012. The accuracy analysis of the produced 3D model was also made by comparing the spatial measurements taken from different building facades and the differences in the measurement values obtained from the 3D model and calculating statistically. According to the accuracy analysis results, the Root Mean Square Error (RMSE) value is approximately 3 cm. The results of the accuracy research, which are within the 95% confidence interval with the three-sigma rule, are approximately 2 cm as RMSE. As a result of the study, it was determined that the data obtained from UAV photogrammetry and the data obtained by the TLS technique could be combined, and the integrated 3D model obtained can be used more efficiently.
Accurate Edge Detection With Support of Reflectance Transformation Imaging
(Institute of Electrical and Electronics Engineers Inc., 2022) Kaya, Burhan; Durdu, Akif
Reflectance Transformation Imaging (RTI) is a method of photographing an object that reveals details that are invisible to the naked eye. The input of RTI consists of a series of images captured by a fixed positioned camera and each illuminated from a known and different direction by lights. Reflection Transform Imaging is widely used to produce quality models from multi-light image data. It is frequently preferred for various studies in the field of cultural heritage. For the first time in this paper, the RTI photographing method has been used outside of its traditional using way. It is used to solve the well-known problem of edge detection. Reflection transform cannot be used actively, because it is difficult to create an RTI experimental environment in daily life. However, under certain conditions, the approaches mentioned in this paper will be used in daily life, from the analysis of images in every field. In this paper, the ideas that it can be applied in every partially controlled area that needs high resolution object detection are discussed. With the method mentioned in this statement, a new approach has been proposed and proven based on RTI basics for edge and corner detections. © 2022 IEEE.
Citation - WoS: 3
Citation - Scopus: 4
Achievable Rate Analysis for Two-Way Relay Non-Orthogonal Multiple Access Systems
(IEEE, 2021) Özdemir, Özgür
This paper investigates the performance of a non-orthogonal multiple access (NOMA) based two-way relaying system where the users want to exchange independent messages with the help of a decode-and-forward relay. We consider transmission over three phases where the first and second phases are allocated to the transmissions of the users and after detection the relay applies superposition coding and transmits the network encoded symbol to the users in the third phase. Exact analytical expressions are derived to characterize the achievable average rate of the system over independent Rayleigh fading channels. Computer simulations are also presented to confirm the theoretical analysis. Analytical and simulation results show that the proposed three-phase two-way relaying scheme with NOMA outperforms the two-phase and four-phase NOMA-based two-way relaying scenarios in terms of achievable average rate.
Citation - Scopus: 1
Achievable Rate of Noma-Based Cooperative Communication Systems With Best Relay Selection Over Cascaded Rayleigh Fading Channels
(IEEE, 2020) Özdemir, Özgür
In this paper, the achievable rate analysis of NOMA-based cooperative communication systems with best relay selection is studied. The cascaded Rayleigh fading channels are considered since investigations have shown that cascaded channel structure agree better with mobile network models such as inter-vehicular communication systems. A cooperative network where a source terminal communicates with a destination directly and through a selected relay among K relays is considered and the achievable average rate of this system using NOMA is found by computer simulations. The obtained results for cascaded Rayleigh fading channels in case of decode and forward protocol have shown that the average rate is decreased as the cascading degree increases. It has been also seen that for a given cascading degree the average rate performance of the system is increased when the number of total relays is increased.
An Adaptive and Hybrid State of Charge Estimation Method Integrating Sequence-To Learning and Coulomb Counting for Li-Ion Based Energy Storage Systems
(Konya Teknik Univ, 2025) Cımen, Halıl
For safe and long-lasting operation of Li-ion batteries used in electric vehicles and electric grid applications, the State of Charge (SOC) of the battery cell must be estimated with high accuracy. However, due to the uncertainty in environmental conditions and the complex nature of battery chemistry, SOC estimation still presents a significant challenge. In this study, an adaptive and hybrid method for SOC estimation of a Li-ion battery cell is proposed. Convolutional Neural Network (CNN) based Sequence-to-point learning architecture is used to estimate the initial SOC values at specific time intervals. In order to increase the estimation accuracy, a multi-scale CNN architecture is designed, and useful features are captured. The obtained estimation values are integrated with the partial coulomb counting method to increase the accuracy. In addition, the proposed model adaptively updates the estimation weights with the help of the estimation error data obtained during the full charging of the batteries. The proposed model is tested on the LG 18650HG2 dataset. The results prove that the proposed model is 23% more accurate than benchmark models at 25°C and 55.5% more accurate at 0°C.
Addressing Time Delays in Blood Glucose Regulation for T1DM Using a PD Controller and Smith Predictor Method
(Institute of Electrical and Electronics Engineers Inc., 2025) Kurnaz, Ender; Aydogdu, Omer
Diabetes Mellitus, particularly Type 1 Diabetes (T1DM), is a condition where the pancreas does not produce enough insulin, causing abnormal Blood Glucose (BG) levels. Proper BG regulation is essential for managing T1DM and preventing related complications. In this research, a hybrid method that integrates the PD controller and Smith Predictor is employed to tackle the issue of time delays in blood glucose regulation for T1DM patients. This study compares two control strategies: a Proportional-Derivative (PD) controller and the Smith Predictor, both of which address time delays inherent in glucose monitoring and insulin delivery systems. The PD controller parameters are determined using MATLAB Simulink's PID Tuner, and the system's transfer function was derived through System Identification. The time response analysis of both control methods shows that while their rise times are similar, the Smith Predictor offers a significant reduction in delay and peak times. © 2025 Elsevier B.V., All rights reserved.
Adrenal Tumor Classification on T1 and T2-Weighted Abdominal Mr Images
(Institute of Electrical and Electronics Engineers Inc., 2019) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Adrenal tumors occur on adrenal glands and can be malignant. Adrenal glands consist of cortex and medulla. If cortex or medulla produce hormones extremely, the hormonal unbalance situation arises. This situation causes adrenal tumor occurrence on adrenal glands. In this study, adrenal tumors on T1 and T2-weighted MR images were classified by the SVM algorithm. Before the classification stage, different feature extraction algorithms and filtering methods were used for preprocessing. The classification results that were obtained by four different methods were evaluated on five different evaluation metrics as sensitivity, specificity, accuracy, precision, and F-score. The best classification performance was obtained with Method 2 on T1-weighted MR (Magnetic Resonance) images where the sensitivity, specificity, accuracy, precision, and F-score metrics were obtained as 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. © 2019 IEEE.
The Adsorption of Cr(vi) and Organic Matter by New Generation Pyrolysis Char
(2021) Kalem, Merve; Yel, Esra; Arıkan, Zafer
Waste vehicle tires (WT) and high density polyetylene (HDPE) were pyrolyzed at 300, 500 and 700°C by slow pyrolysis. Solid product (pyrolysis char) were collected and pyrolysis char was used as adsorbent for COD and Cr(VI) removal. The char samples were characterized by BET, EDS, SEM and XRD analysis. Based on the BET, SEM and XRD results of the char samples, WT 700 can be used as adsorbents for Cr (VI) and organic material adsorptions. Cr(VI) and COD removal efficiency of char adsorbent were investigated. In the adsorption experiments, char was used as 0.1-0.5 g/100 mL doses and at 50°C and 80°C adsorption temperatures. The effects of adsorption temperature and char dosage on the adsorption efficiency were invesitigated. The maximum Cr(VI) adsorption capacity of this new generation char was found to be 14.09 mg/g for 80°C adsorption temperatures. 0.5 g/100 mL adsorbent dose was bettter in COD and Cr (VI) removals. The correlation of PSD1 (pseudo first order kinetic model) was better than PSD2 (pseudo second order kinetic model) for all doses. The Temkin and Langmuir isotherms were better isotherm for COD and Cr(VI) removals, respectively. A new approach were present to evaluation of waste HDPE and waste tires with this study.
Citation - Scopus: 2
Advanced Applications of Green Materials for Gas Separation and Storage
(Elsevier, 2020) Kırbıyık Kurukavak, Çisem; Kuş, Mahmut
Extraordinary increase in global energy demand and supply, thus the environmental pollution, is one of the most important problem for today’s modern life. Gas separation and storage applications are closely related to control of the greenhouse gas and to use of clean and renewable energy. The development of green materials with desired combination properties and corresponding methods for target applications, which can minimize the environmental impact by using renewable sources has been having a growing attention over the last decades. Green and eco-friendly techniques, also called as “green chemistry, " focus on the processes and products, which reduce the use of hazardous substances and nonrenewable sources. Membrane separation, absorption, and physical adsorption for gas separation, purification, and storage are considered to be energy-efficient, low-cost, renewable, and environmental-friendly for a sustainable future. In this section, we highlight the details of these green techniques in gas separation and storage applications. © 2021 Elsevier Ltd. All rights reserved.
Citation - Scopus: 2
Advanced Applications of Green Materials in Bioelectronics Applications
(Elsevier, 2020) Yılmaz, Tuğbahan; Kuş, Mahmut
Green materials have great potential to become a primary research area for bioelectronic integration. Over the last three decades, bioelectronic applications have been getting great interest due to their low cost, flexible, nontoxic, large-volume electronic components that are sustainable, biocompatible, biodegradable, and bioresorbable. Therefore the versatility of bioelectronics applications, such as organic field-effect transistors and biosensors, promises a bright future. This chapter will highlight recent progress in the natural materials and some of their applications in bioelectronics devices. The key strategies and the forecast perspectives of this research field are also briefly summarized. © 2021 Elsevier Ltd. All rights reserved.
Advanced Oxidation Processes for Degradation of Pharmaceuticals Used During Covid-19 Pandemic
(Elsevier, 2023) Ramirez, I.; Mariam, E.; Kumar, A.; Yanardağ, D.; Villaseñor-Basulto, D.L.; Garcia-Huante, Y.G.; Ordaz, A.
The COVID-19 pandemic impacted public health, the economy, and the environment worldwide. During the pandemic, high demand for prescribed pharmaceuticals to treat COVID-19 and other consequential illnesses was observed, including antiviral, corticosteroids, antidepressants, analgesics, and antibiotics. The excessive use of these pharmaceutical compounds provoked new concerns regarding their presence in water bodies. Although the concentrations of these compounds in water are in trace levels (e.g., ng L−1 in most cases), the scientific community has classified them as emerging contaminants of paramount importance. Wastewater and drinking water systems have been encouraged and, in some cases, required to remove these emerging contaminants. Among various treatment techniques, advanced oxidation processes (AOPs) are potential technologies to degrade and remove these contaminants. AOPs represents a broad group of treatment processes for oxidizing compounds that are typically resistant to conventional redox processes. In this chapter, the impact of COVID-19 on water systems is discussed to understand the current circumstances of associated pharmaceutical compounds. We explore the effectiveness of AOPs from the lens of removing these organic molecules. In addition, we provide an overview of the current methods for the detection and quantification of pharmaceutical compounds against COVID-19 in wastewater. The information presented in this chapter has the potential to help engineers, scientists, and public health professionals navigate how AOPs can be used for degradation of pharmaceuticals in water. © 2024 Elsevier Inc. All rights reserved.

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