Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Uzun, Sevda(77)
- Merdan, Mehmet(73)
- Duran, Celal(54)
- Ozdes, Duygu(50)
- Baltaci, Cemalettin(45)
- Kaygusuz, Abdullah(45)
- Kulakaç, Nurşen(39)
- Ashyralyyev, Charyyar(38)
- Karsli, Orhan(37)
- Demir, Selim(36)
- Öztürk, Serkan(36)
- Dokuz, Abdurrahman(35)
- Turan, Ibrahim(35)
- Araz, Onur(33)
- Kandemir, Raif(31)
- Sipahi, Ferkan(30)
- Topal, Fevzi(30)
- Kurt, Kemal(28)
- Peker, Iskender(28)
- Arslan, Mehmet(27)
- Baltacı, Cemalettin(27)
- Maden, Nafiz(27)
- Ozturk, Samet(27)
- Aydin, Aydanur(26)
- Vural, Alaaddin(26)
- Bayrakdaroglu, Serdar(25)
- Kurnaz, Muammer(25)
- Reis, Hatice Catal(25)
- Akar, Zeynep(24)
- Aydin, Faruk(24)
- Gücer, Mehmet Ali(24)
- Topal, Meryem(24)
- Yolcu, Halil(24)
- Yücel, Cem(24)
- Anaç, Halil(23)
- Kankal, Murat(23)
- Ürkek, Bayram(23)
- Aliyazicioglu, Yuksel(22)
- Günen, Mehmet Akif(22)
- Tuncer, Metin(22)
Yayınlar
- MakaleYalnız künye2022Scopus SJRQ2Proportional control moment gyroscope for two-wheeled self-balancing robot
Ünker, Faruk
A two-wheeled self-balancing robot is considered for investigating the responses of a control moment gyroscope powered by a proportional controller to prevent the robot rollover against the constant inertia forces because of accelerations of the wheels of the robot. The amplitudes of the frequency equations related to the required angular momentum of flywheels with an optimum controller gain were also found. A simulation model of the robot using computer-aided engineering software (RecurDyn) is built to verify the equations of a Lagrangian model. The results of both obtained from the Lagrangian and that from RecurDyn simulations are analyzed comparatively, in which the proportional control loop reduces the required flywheel speeds Ω of gyros and keeps the robot in a very small amplitude of a stable sinusoidal motion in the upright position.
AtıfScopus23WoS12
İncele - Kitap BölümüYalnız künye2022Symptom and Life Quality Management in Oncology Patients
Demir Doğan, Melike
Quality of life is a multidimensional concept. Therefore, its assessment includes many parameters ranging from happiness and well-being of individuals to environmental quality and ecological structures. A good symptom management is associated with less symptom formation and thus with a better quality of life. Non-pharmacological interventions typically include various psychosocial, behavioral and environmental strategies that can complete traditional treatment to increase the quality of life for cancer patients.
AtıfScopus2OpenAlex2İncele - MakaleAçık Erişim2022Scopus SJRQ2A new cryptic species of the Darevskia parvula group from NE Anatolia (Squamata, Lacertidae)
Arribas, Oscar; Candan, Kamil; Kurnaz, Muammer; Kumlutaş, Yusuf; Caynak, Elif Yıldırım; Ilgaz, Çetin
In this study, we re-examine the Darevskia parvula group comprehensively using morphology, osteology and mitochondrial phylogeny, and describe a new endemic species from Turkey: Darevskia tuniyevisp. nov. A total of 257 adult specimens were evaluated for external morphology (scalation and biometry) with univariate (descriptive statistics and ANOVA with post-hoc tests) and multivariate (Discriminant Analysis and ANOSIM) analyses. In parallel, osteological data and molecular analyses using three DNA markers (mitochondrial 16S rRNA and Cyt-b, nuclear Rag-1) were used to complete the description of the new taxon. The molecular phylogenetic analyses indicated that the D. parvula group is composed of three taxa as D. parvula, D. adjarica and D. tuniyevisp. nov., and showed that D. adjarica and D. tuniyevisp. nov. are reciprocal sister taxa. On the other hand, D. adjarica is morphologically very different from other two forms, while D. parvula is hardly distinguishable externally from D. tuniyevisp. nov. Therefore, we can consider that D. parvula and D. tuniyevisp. nov. are cryptic species. These two cryptic species retain their primitive morphology within the group, while D. adjarica has changed, perhaps due to different bioclimatic conditions in its Pleistocene refuge and current area.
AtıfScopus14WoS11OpenAlex11İncele - MakaleYalnız künye2022Scopus SJRQ2InSiNet: a deep convolutional approach to skin cancer detection and segmentation
Reis, Hatice Catal; Turk, Veysel; Khoshelham, Kourosh; Kaya, Serhat
Cancer is among the common causes of death around the world. Skin cancer is one of the most lethal types of cancer. Early diagnosis and treatment are vital in skin cancer. In addition to traditional methods, method such as deep learning is frequently used to diagnose and classify the disease. Expert experience plays a major role in diagnosing skin cancer. Therefore, for more reliable results in the diagnosis of skin lesions, deep learning algorithms can help in the correct diagnosis. In this study, we propose InSiNet, a deep learning-based convolutional neural network to detect benign and malignant lesions. The performance of the method is tested on International Skin Imaging Collaboration HAM10000 images (ISIC 2018), ISIC 2019, and ISIC 2020, under the same conditions. The computation time and accuracy comparison analysis was performed between the proposed algorithm and other machine learning techniques (GoogleNet, DenseNet-201, ResNet152V2, EfficientNetB0, RBF-support vector machine, logistic regression, and random forest). The results show that the developed InSiNet architecture outperforms the other methods achieving an accuracy of 94.59%, 91.89%, and 90.54% in ISIC 2018, 2019, and 2020 datasets, respectively. Since the deep learning algorithms eliminate the human factor during diagnosis, they can give reliable results in addition to traditional methods. Graphical abstract: [Figure not available: see fulltext.]
AtıfScopus170WoS313OpenAlex160
İncele - MakaleYalnız künye2022Scopus SJRQ3The Effect of Surface Morphology of Silver Nanoparticles on the Selectivity of Styrene Epoxidation
Sarlblylk, Oǧuz Yunus
Catalytic materials at the nanoscale level have an enormous impact on sustainable environmental protection, which is important for the future. Therefore, the researchers will intensively carry out the design of catalytic materials with well-ordered surface structures. In more detail, morphology-controlled nanoparticles have special interactions with the reactants that increase catalytic performance and influence the selectivity for catalytic reactions. For those reasons, obtaining specifically surface structure-tuned nanocrystals having different surface arrangements is a significant priority that promises the best model relationship between well-oriented surface structure and catalytic performance. In this study, silver nanocrystals shaped with cubes, truncated octahedrons, and octahedrons were produced. Their catalytic behaviors were examined as an innovation for epoxidation/oxidation reactions of styrene in mild conditions. The morphological and surface characterizations of nanocrystals were determined by analytical and instrumental methods such as high-resolution transmission electron microscopy energy dispersive X-ray (HR-TEM-EDX), X-ray diffraction (XRD), as well as inductively coupled plasma mass spectroscopy optical emission spectrometry (ICP-OES), and gas chromatography-mass spectrometry (GC-MS). According to the results, nanoparticles having different surface-facets fractions can be employed to increase the selectivity of styrene epoxide.
AtıfScopus3WoS3OpenAlex3İncele - MakaleYayıncıda açık erişim2022Scopus SJRQ3Information theory and machine learning based authentication of flaxseed oil using portable and handheld vibrational spectroscopy sensors
Aykas, Didem-Peren; Menevseoglu, Ahmed; Gunes, Nurhan
Flaxseed oil is one of the popular edible oils, and its adulteration has become a concern because of its high commodity value. Therefore, there is a need to detect adulterated flaxseeds with a rapid, non-invasive, and simple method to keep the quality of flaxseed oil. This study aimed to develop a machine learning algorithm and information theory to detect adulterated flaxseed oils by vibrational spectroscopy units combined with chemometrics. Oil spectra were collected with portable/handheld vibrational spectroscopic units and analyzed using conditional entropy, support vector machines (SVM), and soft independent modeling of class analogy (SIMCA) to generate classification models to identify the pureness of oils and partial least square regression (PLSR) to predict the adulterant levels and fatty acid distributions. Conditional entropy showed that two or three wavenumbers/shifts could discriminate the oils using machine learning algorithms with an accuracy of over 95%. SIMCA models determined the oils with an interclass distance (ICD) over 1.1. Specifically, the Fourier transform mid-infrared (FT-MIR) unit provided the best classification of the oils with ICD over 4.9. All instruments showed good performance in predicting fatty acids and adulteration levels with rval≥0.89 and standard error prediction (SEP) ≤1.7%. Overall, these portable/handheld units showed great potential for rapid, simple, and non-invasive monitoring to identify adulterated flaxseed oils.
AtıfScopus7WoS7OpenAlex7İncele - MakaleAçık Erişim2022Scopus SJRQ3Phytoremediation ability of Helichrysum arenarium plant for Au and Ag: case study at Demirören village (Gümüşhane, Turkey)
Vural, Alaaddin; Safari, Semaneh
It was investigated ability of Helichrysum arenarium plant, in phytoextraction, phytostabilization, and phytoremediation in this study. Soil and plant samples were collected from the Demirören alteration site which has the potential of gold mineralization and analyzed for gold and silver. When the results of the analysis were evaluated, it was determined that the gold and silver contents in the soil did not show compatibility with the gold and silver contents of the plants grown at the same point. It was concluded that the high gold and silver concentrations in the plants are related to the hydrothermal alteration and weathering at the point where the plants grow. For investigation of phytoremediation ability of the plant, translocation factor (TF), bio-concentration factor (BCF), and bioaccumulation factor (BAF) were calculated. The values of TF, BAF, and BCF for Ag are equal 0.33, 0.043, and 0.13 and for Au are equal 2.04, 0.59, and 0.29, respectively. So, obtained data show that Helichrysum arenarium is not appropriate for phytoextraction and phytostabilization of gold and silver in this case, but H. arenarium can be used in phyto-mining and for biogeochemical exploration of gold. Considering that the gold and silver concentrations in the developed soil in the study area are low concentrations, it is predicted that a similar study will yield satisfactory-interesting results when it is made in plants grown on the gold mineralization/enrichment areas.
AtıfScopus9WoS9OpenAlex11İncele - MakaleYalnız künye2022Scopus SJRQ3Roza: a new and comprehensive metric for evaluating classification systems
Melek, Mesut; Melek, Negin
Many metrics such as accuracy rate (ACC), area under curve (AUC), Jaccard index (JI), and Cohen’s kappa coefficient are available to measure the success of the system in pattern recognition and machine/deep learning systems. However, the superiority of one system to one other cannot be determined based on the mentioned metrics. This is because such a system can be successful using one metric, but not the other ones. Moreover, such metrics are insufficient when the number of samples in the classes is unequal (imbalanced data). In this case, naturally, by using these metrics, a sensible comparison cannot be made between two given systems. In the present study, the comprehensive, fair, and accurate Roza (Roza means rose in Persian. When different permutations of the metrics used are superimposed in a polygon format, it looks like a flower, so we named it Roza.) metric is introduced for evaluating classification systems. This metric, which facilitates the comparison of systems, expresses the summary of many metrics with a single value. To verify the stability and validity of the metric and to conduct a comprehensive, fair, and accurate comparison between the systems, the Roza metric of the systems tested under the same conditions are calculated and comparisons are made. For this, systems tested with three different strategies on three different datasets are considered. The results show that the performance of the system can be summarized by a single value and the Roza metric can be used in all systems that include classification processes, as a powerful metric.
AtıfScopus7WoS8OpenAlex9İncele - MakaleYalnız künye2022Scopus SJRQ1Optimization of multiple tuned mass dampers for a two-span continuous railway bridge via differential evolution algorithm
Araz, Onur; Kahya, Volkan
The study aims at proposing a methodology for optimization of multiple tuned mass dampers (MTMD) in reducing the multi-resonance vibrations of continuous bridges due to moving train loads. The equations of motion for time-domain analysis are derived for obtaining train-induced vibrations of a two-span continuous railway bridge with equipped MTMD-1 and MTMD-2 devices when the vehicle-bridge interaction (VBI) is considered. The bridge and the train are modeled as a Bernoulli-Euler beam with constant section and a series of moving sprung masses of identical length, respectively. To reduce the multiple resonance vibrations of a two-span continuous railway bridge, the MTMD-1 and MTMD-2 are tuned to the first mode and the second mode of the bridge, and they are attached to the midspan of each span, respectively. The optimum parameters of the both MTMD systems are investigated using the differential evolution (DE) method. The criterion chosen to obtain the optimum parameters is the minimization of the first two resonance peaks of the bridge. The influence of the different mass ratios and the number of TMD units in the MTMD system on the optimum parameters of the both MTMD systems and corresponding displacement responses of the bridge are also investigated. The results show that the VBI effect does not have much effect on the resonant train speeds and the control performance of TMDs. Therefore, the optimum parameters of TMDs can be obtained quickly by modeling the train as a series of moving forces for the vibration control of railway bridges.
AtıfScopus33WoS32OpenAlex33İncele - MakaleYalnız künye2022Scopus SJRQ1Robust copy-move detection in digital audio forensics based on pitch and modified discrete cosine transform
Ustubioglu, Beste; Küçükuğurlu, Büşranur; Ulutas, Guzin
Copy-move forgery is one of the most widely used methods in the field of audio forensic because it is difficult to detect and convenient to apply. However, post-processing operations applied to forged speech to hide traces of forgery make detection of forensic more difficult. In this study, we propose a robust method for detection and localization of the audio copy-move forgery using modified discrete cosine transform (MDCT). For this purpose, we first divide the speech recording into voiced and unvoiced parts by extracting a pitch sequence from the speech recording. After the determination of voiced parts, we extract MDCT coefficients from them and take the mean of the transpose of the coefficient matrix as the feature. These MDCT features are very robust against commonly used post-processing operations (especially audio compressing). Euclidean distance (ED) is applied to compute the similarities between the features. The voiced parts, which give minimum ED are determined as copy-move audio parts. Also, two separate databases (Pitch-based and Voice Activity Detection (VAD-based) are created during the work to evaluate the performance of the proposed method because there is no common database in the field of audio forensic in the literature. Experiment results show that the proposed method gives better results for detection and localization of audio copy-move forgery on different databases compared to other studies in the literature. The proposed method is also robust against common post-processing operations such as noise addition, filtering operation, and especially compression operation.
AtıfScopus22WoS17OpenAlex23İncele - MakaleAçık Erişim2022Scopus SJRQ1Zircon U[sbnd]Pb geochronology and petrology of the tholeiitic gabbro from the Kovanlık (Giresun) area: Constraints for the Late Cretaceous bimodal arc magmatism in the Eastern Pontides Orogenic Belt, NE Turkey
Temizel, İrfan; Arslan, Mehmet; Abdioğlu Yazar, Emel; Aslan, Zafer; Kaygusuz, Abdullah; Baki Eraydın, Tuğba
Mafic intrusions of the Eastern Pontides Orogenic Belt (EPOB) in NE Turkey are found rarely in varying ages, sizes and compositions. Of these, tholeiitic gabbro stocks, namely Kovanlık gabbro, consist of pyroxene gabbro and minor hornblende gabbro with a mainly granular texture. The pyroxene gabbro contains plagioclase, clino- and ortho-pyroxene, olivine, and Fe[sbnd]Ti oxides, whereas the hornblende gabbro includes mainly plagioclase, hornblende, rarely biotite and Fe[sbnd]Ti oxides. The clinopyroxene compositions of the pyroxene gabbro exhibit arc-related tholeiitic magmas. The Kovanlık gabbroic rocks have high U/Yb zircon ratios, implying continental arc-related tectonic settings. Zircon U[sbnd]Pb dating on the Kovanlık gabbro yielded a concordia age of ~92 Ma (Turonian). Petrochemically, the gabbroic rocks have a tholeiitic character and show arc- and MORB-like signatures. The gabbroic rocks show positive Rb, Ba, K, Pb, Sr, Ti and negative Nb, Ce, Nd, Hf, Zr anomalies in N-MORB normalized diagrams. The chondrite-normalized REE plots of the rocks show flat to feeble right-dipping REE patterns (LaN/LuN = 0.94–2.56) with positive Eu anomalies (EuN/Eu* = 1.15–2.14; except for two pyroxene gabbro samples). The gabbroic rocks have 87Sr/86Sr(i) ratios (0.704533 to 0.706265), εNd(i) values (4.04–4.85), 206Pb/204Pb (18.56–18.68) and 207Pb/204Pb (15.61–15.64) ratios. Low Nb/La and Nb/Y ratios, as well as high Sr/Yb and Ba/Rb ratios, indicate that source regions were modified by slab-derived fluids and/or melts. The obtained zircon dating, isotopic and geochemical data, as well as regional geology, revealed that the tholeiitic mafic magma derived from a spinel-lherzolite mantle at a relatively shallow depth, and the Kovanlık gabbro in the EPOB represents one of the first mafic intrusions of Late Cretaceous bimodal arc magmatism related to the roll-back of the northwards subducting Tethys oceanic plate.
AtıfScopus19WoS17OpenAlex20İncele - MakaleYalnız künye2022Scopus SJRQ1A decision support tool for the student–supervisor allocation problem of postgraduate programs
Bahadır Şimşek, Ahmet
The stable supervisor-student allocation (SSA) is crucial in the success of the research at the postgraduate education. The difference of SSA from the well-known student-project allocation (SPA) problem is that it moves the determination of the research topic to after the allocation, thus allowing the student and the lecturer to discuss the research topic. In the education systems of developing countries where decision support systems are not prevalent, the student–lecturer allocation is performed manually with a greedy approach, which can result in unstable matches. In this study, we propose a multi-objective binary model that allows decision-makers to shift between three main allocation strategies with a trade-off parameter. We test the model with a real dataset of a postgraduate program in Turkey. Experiments show that the model can successfully implement different strategies, and there can also be more than one breaking point between strategies. Also, we transform the model into a decision support tool that provides easy use to the decision-maker and reports the solutions of the trade-off parameter sensitivity analysis. The tool reports the level of satisfaction for each strategy at different breakpoints, allowing the decision-maker to see its options.
AtıfScopus6WoS3OpenAlex5İncele - MakaleAçık Erişim2022Scopus SJRQ1COVID-DSNet: A novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and Chest X-Ray images
Reis, Hatice Catal; Turk, Veysel
COVID-19 (SARS-CoV-2), which causes acute respiratory syndrome, is a contagious and deadly disease that has devastating effects on society and human life. COVID-19 can cause serious complications, especially in patients with pre-existing chronic health problems such as diabetes, hypertension, lung cancer, weakened immune systems, and the elderly. The most critical step in the fight against COVID-19 is the rapid diagnosis of infected patients. Computed Tomography (CT), chest X-ray (CXR), and RT-PCR diagnostic kits are frequently used to diagnose the disease. However, due to difficulties such as the inadequacy of RT-PCR test kits and false negative (FN) results in the early stages of the disease, the time-consuming examination of medical images obtained from CT and CXR imaging techniques by specialists/doctors, and the increasing workload on specialists, it is challenging to detect COVID-19. Therefore, researchers have suggested searching for new methods in COVID- 19 detection. In analysis studies with CT and CXR radiography images, it was determined that COVID-19-infected patients experienced abnormalities related to COVID-19. The anomalies observed here are the primary motivation for artificial intelligence researchers to develop COVID-19 detection applications with deep convolutional neural networks. Here, convolutional neural network-based deep learning algorithms from artificial intelligence technologies with high discrimination capabilities can be considered as an alternative approach in the disease detection process. This study proposes a deep convolutional neural network, COVID-DSNet, to diagnose typical pneumonia (bacterial, viral) and COVID-19 diseases from CT, CXR, hybrid CT + CXR images. In the multi-classification study with the CT dataset, 97.60 % accuracy and 97.60 % sensitivity values were obtained from the COVID-DSNet model, and 100 %, 96.30 %, and 96.58 % sensitivity values were obtained in the detection of typical, common pneumonia and COVID-19, respectively. The proposed model is an economical, practical deep learning network that data scientists can benefit from and develop. Although it is not a definitive solution in disease diagnosis, it may help experts as it produces successful results in detecting pneumonia and COVID-19.
AtıfScopus36WoS22OpenAlex36İncele - MakaleAçık Erişim2022Automatic prediction of covid-19 from chest-computed tomography (CT) images using deep learning architectures; [Derin öğrenme mimarilerini kullanarak göğüs BT görüntülerinden otomatik Covid-19 tahmini]
Turk, Veysel; Catal Reis, Hatice; Kaya, Serhat
Machine learning has been actively used in disease detection and segmentation in recent years. For the last few years, the world has been coping with the Coronavirus disease 2019 (COVID-19) pandemic. Chest-computerized tomography (CT) is often a meaningful way to detect and detect patients with possible COVID-19. This study aims to classify COVID-19 and non-COVID-19 chest-CT images using deep learning (DL) algorithms and investigate whether we can achieve successful results in different parameters using four architectures. The study was performed on proved positive COVID-19 CT images, and the datasets were obtained from the GitHub public platform. The study evaluated four different deep learning architectures of VGG16, VGG19, LeNet-5, and MobileNet. The performance evaluations were used with ROC curve, recall, accuracy, F1-score, precision, and Root Mean Square Error (RMSE). MobileNet model showed the best result ; F1 score of 95%, the accuracy of 95%, the precision of 100%, recall of 90%, AUC of 95%, and RMSE of 0.23. On the other hand, VGG 19 model gave the lowest performance; F1 score of 90%, the accuracy of 89%, the precision of 90%, recall of 90%, AUC of 89%, and RMSE of 0.32. When the algorithms' performances were compared, the highest accuracy was obtained from MobileNet, LeNet-5, VGG16, and VGG19, respectively. This study has proven the usefulness of deep learning models to detect COVID-19 in chest-CT images based on the proposed model framework. Therefore, it can contribute to the literature in Medical and Engineering in COVID-19 detection research.
AtıfScopus2OpenAlex2
İncele - MakaleYalnız künye2022Scopus SJRQ2Effect of different objective functions on control performance of tuned mass damper for a high-rise building considering soil–structure interaction
Araz, Onur; Ozturk, Kasif Furkan; Cakir, Tufan
This paper deals with the optimization of the tuned mass damper (TMD) with different objective functions for high-rise building under earthquake motions considering soil–structure interaction (SSI). A study is conducted to search for the TMD that outperforms five objective functions (i.e., OF-1–OF-5) containing combinations of the structural responses and foundation responses. The main goal of the present study is to evaluate and compare the control performance of these five objective functions. The optimum parameters of TMD are obtained by particle swarm algorithm (PSA) to minimize the acceleration transfer function. To determine the dynamic response of a 40-story building under the influence of SSI, six different foundation soil conditions and eight different earthquake records are considered. The results show that the SSI effects on the dynamic response of the high-rise building resting on relatively soft soil types such as SD and SE are of critical importance. It is shown that the effectiveness of the optimum TMD designed by OF-1 is better than the others in suppressing the peak response values for all soil types. After OF-1, the best performances are obtained for OF-3 and OF-5 which yield approximately the same effectiveness. It is also found that different earthquake records, soil types and objective functions are very effective on the effectiveness of TMD.
AtıfScopus22WoS22OpenAlex25İncele - MakaleAçık Erişim2022Scopus SJRQ240Ar–39 Ar dating, whole-rock and Sr-Nd isotope geochemistry of the Middle Eocene calc-alkaline volcanic rocks in the Bayburt area, Eastern Pontides (NE Turkey): Implications for magma evolution in an extension-related setting
Kaygusuz, Abdullah; Yücel, Cem; Aydınçakır, Emre; Gücer, Mehmet Ali; Ruffet, Gilles
Discussions continue about whether Middle Eocene magmatism in the Eastern Pontides is associated with collision or subduction. This paper presents new whole-rock geochemistry, Sr-Nd isotopic and 40Ar-39Ar age data for Middle Eocene volcanic rocks from the Bayburt area of the Eastern Pontides (NE Turkey) to investigate their sources and evolutionary history. The new 40Ar–39Ar ages reveal that these volcanic rocks erupted between 44.6 ± 0.1 Ma and 43.5 ± 0.1 Ma, within the Lutetian (Middle Eocene). The studied volcanic rocks are composed of basalt, andesite, basaltic andesite and minor dacite lava and pyroclastic rocks. These rocks consist of plagioclase, amphibole, pyroxene, olivine, biotite, sanidine and minor quartz phenocrysts with Fe-Ti oxides. They have microlithic, hyalo-microlithic, porphyritic and rarely glomeroporphyritic textures. The volcanic rocks have low to high-K calc-alkaline affinities. They display enrichment in large-ion lithophile elements and depletion in high-field strength elements with high Th/Yb ratios, which indicate that the magmas forming the volcanic rocks were derived from lithospheric mantle sources enriched by mostly slab-derived fluids in the spinel stability field. 87Sr/86Sr(i) values vary between 0.70485 and 0.70551 and 143Nd/144Nd(i) values vary between 0.51255 and 0.51267. These data correspond to the mantle array on the isotope ratio diagram. The main solidification processes consist of fractional crystallization with minor assimilation. In light of the data obtained in this study together with data from previous studies, petrogenetic character of the Middle Eocene magmas from the southern parts of the Eastern Pontides may be explained by melting of an enriched lithospheric mantle source initially metasomatized by subduction fluids in a post-collisional extensional-related tectonic setting.
AtıfScopus17WoS14OpenAlex20İncele - MakaleAçık Erişim2022Scopus SJRQ1A countrywide analysis of 27 solar power plants installed at different climates
Ozden, Talat
The world is still heavily using nonconventional energy sources, which are worryingly based on carbon. The step is now alternative energy sources hoping that they will be more environmentally friendly. One of the important energy conversion forms by using these sources is photovoltaic solar systems. These type of power plants is on the increase in everyday on the world. Before investment a solar power plant in a specified region, a techno-economic analyse is performed for that power plant by using several meteorological data like solar irradiance and ambient temperature. However, this analyses generally lacks evaluation on effects of climatic and geographical conditions. In this work, 5 years of data of 27 grid-connected photovoltaic power plants are investigated, which are installed on seven different climate types in Turkey. Firstly, the power plants are categorized considering the tilt angles and Köppen–Gieger climate classification. The performance evaluations of the plants are mainly conducted using monthly average efficiencies and specific yields. The monthly average efficiencies, which were classified using the tilts and climate types were from 12 to 17%, from 12 to 16% and from 13 to 15% for tilts 30°/10°, 25° and 20°, respectively. The variation in the specific yields decrease with elevation as y(x) = − 0.068x + 1707.29 (kWh/kWp). As the performances of photovoltaic systems for some locations within the Csb climatic regions may relatively lower than some other regions with same climate type. Thus, techno-economic performance for PVPP located in this climate classification should be carefully treated.
AtıfScopus6WoS2OpenAlex8İncele - MakaleAçık Erişim2022Scopus SJRQ1Seismic performance of a high-rise building by using linear and nonlinear methods
Çavdar, Özlem
In this paper, the seismic behavior of the existing reinforced concrete tall building is investigated by using the linear and nonlinear dynamic methods. The selected existing reinforced concrete structure was designed according to Turkey Seismic Code-2007. The performance analysis according to the Turkey Building Earthquake Code-2019 is realized in a 41-story reinforced concrete shear wall-framed structure in Istanbul where active fault lines are located. For high-rise building, firstly, spectrum analysis according to mode superposition methods of linear computational methods used within the scope of strength-based design is performed. Turkey Building Earthquake Code-2019 advises a nonlinear deformation-based design approach to determine more accurately the behavior of high-rise building, as in the earthquake regulations of other developed countries. In addition, the nonlinear time history analyses of building were performed. At the end of the study, torsional irregularity is seen on the normal floors and intermediate floor; stiffness irregularity was found on second floors. In addition, it has been observed in some of the oblique columns of the building that load bearing capacities were exceeded due to creep, axial compressive loads and severe damages occurred. According to the Turkey Building Earthquake Code-2019, the high-rise reinforced concrete shear wall building is not expected to satisfy life safety performance levels under design earthquake.
AtıfScopus5WoS3OpenAlex6İncele - MakaleYalnız künye2022Scopus SJRQ2A note on linear non-Newtonian Volterra integral equations
Güngör, Nihan
In this study, the Volterra integral equations are defined in the non-Newtonian calculus with the aid of ∗ -integral. The focus of this study is obtaining the solution of linear non-Newtonian integral equations. The ∗ -resolvent kernel method, successive approximations method and Adomian decomposition method are applied for solving non-Newtonian integral equations in the non-Newtonian sense. Some numerical examples are presented to explain the procedure of these methods. Finally, a model that describes a type of the exponential growth model is proposed in the sense of non-Newtonian calculus as an example.
AtıfScopus8WoS8OpenAlex7İncele - MakaleYalnız künye2022Scopus SJRQ1Early Cambrian S-type granites in the Sakarya Zone, NE Turkey: A record for transition from subduction to post-collisional extension deduced from U-Pb zircon age and Nd-Hf isotopes
Karsli, Orhan; Sengün, Firat; Dokuz, Abdurrahman; Aydin, Faruk; Kandemir, Raif; Kristoffersen, Magnus; Santos, Jose Francisco; Hofmann, Mandy; Duygu, Levent
Cadomian realms have recently received much attention in the Alpine-Mediterranean orogenic belts, with discontinuous outcrops extending from the Alps to the Istanbul Zone, Menderes Massif, Taurides in Turkey and Iran as well. However, they have not been identified in the Sakarya Zone, northern Turkey to date. Here, we present, for the first time, zircon U-Pb geochronology, zircon Hf-isotopes and trace elements as well as whole-rock geochemistry and Nd-isotopes from the Karamese metagranitoid in the Yusufeli (Artvin) area, NE Turkey. The zircon U-Pb age data demonstrate that the Karamese metagranitoid intruded into the Precambrian basement units in the Early Cambrian (ca. 534-530 Ma). Zircon overgrowths in the Karamese metagranitoid interpreted as a result of metamorphic overprint yielded ages of 328 Ma. This age indicates that the Sakarya Zone experienced the Variscan metamorphic events at 328 Ma. The Early Cambrian metagranitoid shows that some rocks in the basement of the Sakarya Zone date back to Precambrian in age. The Karamese metagranitoid is an S-type granite, with high modal content of muscovite (similar to 10%). The samples show highly peraluminous [A/CNK = molar Al2O3/(CaO + K2O + Na2O) = 1.34-1.58] and medium-K calc-alkaline geochemical affinities. The Karamese metagranitoid displays low REE concentrations and a slight positive Eu anomaly and show slightly light REEs and LILEs enrichments, and HFSEs depletions. The samples have negative epsilon(Nd)(t) of -4.76 to -2.90 and epsilon(Hf) (t) of -4.75 to -1.08 values. These geochemical-isotopic characteristics reveal that the Karamase metagranitoid originated through fluid-absent muscovite dehydration melting of heterogeneous metasedimentary source rocks (mostly greywacke), with a minor input of juvenile mafic melt. We argue that the Early Paleozoic metagranitoids along the eastern Sakarya Zone is an expression of crustal thinning in the Cadomian orogenic belt in northern Gondwana, with the tectonic turnover from convergent margin to crustal extension possibly induced by break-off of Tornquist oceanic lithosphere which is a branch of Iapetus Ocean during Early Cambrian.
AtıfScopus16WoS14OpenAlex15İncele