WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 2Citation - Scopus: 2Tuning the Solid Phase Fluorescence Emission From Long Wavelength Visible To Near-Infrared in Oxazol-5 Derivatives: Structure–property Relationship, Theoretical and Experimental Studies(Springer, 2023) Nazlı, İbrahim Hanif; Yakalı, Gül; Topkaya, Derya; İzmirli, Merve; Uzun, Sema Demirci; Alp, SerapMost of the fluorescent molecules among organic π-conjugated materials show blue or green emission in the solid phase but few of them emit red-shifted visible and near-infrared light in the material science. To create molecules emitting for this feature, two π-conjugated oxazol-5-one derivatives containing donor (OCH3) and acceptor groups (NO2) were synthesized. Their optical and charge-transport properties were investigated through experimental and theoretical methods including the single crystal X-ray crystallography, Hirshfeld Surface Analysis, photophysical studies and Density Functional Theory (DFT), respectively. In addition, FT-IR, 1H-NMR, 13C-NMR spectroscopy, cyclic voltammetry (CV) measurements were performed. According to our results, both molecules may provide the significant pathway of development of long wavelength visible and red emissive features in solid phase with the aggregation induced enhanced emission (AIEE) properties particularly in the fields of OLEDs, optical communication, defence and bioimaging.Article Citation - WoS: 15Citation - Scopus: 15The Effect of Strain Rate on the Compression Behavior of Additively Manufactured Short Carbon Fiber-Reinforced Polyamide Composites With Different Layer Heights, Infill Patterns, and Built Angles(Springer, 2023) Zeybek, Mehmet Kaan; Güden, Mustafa; Taşdemirci, AlperPrevious studies on the fused deposition modelling (FDM) processed short carbon fiber/Polyamide 6 (PA6) matrix composites and neat PA6 have mostly concentrated on the quasi-static mechanical properties. Present study focused on the strain rate-dependent deformation behavior of a short carbon fiber-reinforced PA6 (Onyx) and neat PA6, produced in different layer heights, infill patterns and built angles. As compared with PA6, Onyx showed a higher compression stress at all strain rates investigated. A layer height of 0.2 mm in PA6 specimens promoted a better bonding between [0/90°] infill layers; hence, a higher flow stress than 0.2 mm layer height specimens, while 0.2 mm layer height induced a higher porosity in Onyx specimens, leading to a lower flow stress. The porosities in Onyx [0/90°] infill specimens were due to the constraining effect of 0/90° fiber layers. Changing infill pattern from a [0/90°] to a concentric one decreased porosity at the same layer height and hence increased the compressive flow stress. The highest compressive strength was found in the specimens with the loading axis 90 and 0° to [0/90°] infill plane. The lowest strength was, however, determined in the specimens with the loading axis 30 and 60o to [0/90°] infill plane in quasi-static loading. However, the specimens with the loading axis of 60, 45, 30 and 0° exhibited a brittle behavior in high strain rate loading (1500 s−1). The specimens with the loading axis of 45° had the lowest fracture stress and strain in the high strain rate loading. This signified the importance of loading angle at high strain rates. Finally, the rate sensitivities of PA6 and Onyx specimens were shown to be similar, showing a matrix dominated deformation. However, the strain rate jump tests indicated a slightly higher rate sensitivity of Onyx specimens at quasi-static strain rates (10−3-10−1 s−1).Article Citation - Scopus: 3Cut-In Maneuver Detection With Self-Supervised Contrastive Video Representation Learning(Springer, 2023) Nalçakan, Yağız; Baştanlar, YalınThe detection of the maneuvers of the surrounding vehicles is important for autonomous vehicles to act accordingly to avoid possible accidents. This study proposes a framework based on contrastive representation learning to detect potentially dangerous cut-in maneuvers that can happen in front of the ego vehicle. First, the encoder network is trained in a self-supervised fashion with contrastive loss where two augmented videos of the same video clip stay close to each other in the embedding space, while augmentations from different videos stay far apart. Since no maneuver labeling is required in this step, a relatively large dataset can be used. After this self-supervised training, the encoder is fine-tuned with our cut-in/lane-pass labeled datasets. Instead of using original video frames, we simplified the scene by highlighting surrounding vehicles and ego-lane. We have investigated the use of several classification heads, augmentation types, and scene simplification alternatives. The most successful model outperforms the best fully supervised model by ∼ 2% with an accuracy of 92.52%Article Citation - WoS: 3Citation - Scopus: 4Development of Textured Lead-Free Nbt-Based Piezoelectric Materials in a Matrix, Synthesized by an Alternative Route, Via Templated Grain Growth(Springer, 2023) Çoban Tetik, Hatice Şule; Suvacı, Ender; Avcı, A. Murat; Adem, Umut; Karakaya, MerveIn this study, (1−x)(K0.5Bi0.5TiO3-BaTiO3)−xNa0.5Bi0.5TiO3 KBT:BT = 2:1 where x = 0.8 (KBT-BT-NBT) (001) textured lead-free piezoelectric ceramics were fabricated using BT template by templated grain growth with tape casting. Unlike the commonly used matrix preparation method, which is the calcination of all raw materials in one step, the matrix phase was prepared in a different way by first preparing KBT, BT and NBT powders separately and then by calcining the mixtures of these powders, so that effect of the matrix, synthesized by this alternative route, on texture development properties was evaluated. In addition, the effect of BT template content on the grain orientation with different sintering temperature and time, structure evolution, phase stability and piezoelectric properties were investigated to assess the materials’ actuating performance. The highest Lotgering factor of 81% was achieved for the textured ceramics with 10 wt% BT templates sintered at 1150 °C for 48 h. Compared to the one-step synthesis method, similar Lotgering factor values were obtained at lower sintering temperatures in the matrix, synthesized by the alternative 2-step method. The highest piezoelectric constant, remnant polarization, strain value and depolarization temperature were also obtained from the same sample, as ~ 190 pC/N, 30 kV/cm, 25% at 50 kV/cm and ~ 165 °C, respectively. The results show that the textured, lead free K0.5Bi0.5TiO3-BaTiO3-Na0.5Bi0.5TiO3 (KBT-BT-NBT) ceramics that are developed by using the matrix, synthesized by the alternative 2-step method, can be very promising lead-free electroceramics for high performance actuator applications.Article Citation - WoS: 2Citation - Scopus: 2Assessment of Future Water Demand in a Semiarid Region of Turkey: a Case Study of Tahtali–seferihisar Basin(Springer, 2023) Karahan, S. M.; Elçi, ŞebnemWater is a vital resource for society and nature, and its scarcity has consequences in all aspects of existence. Today, issues including the inability to preserve the status of existing water resources and excessive water withdrawal are causing the amount of water to diminish day by day. Furthermore, factors such as urbanization and industrialization, population growth, water quality degradation owing to agricultural pesticides, and climate change, all have a negative impact on water supplies. A basin-based water management analysis was carried out in this study by applying the "Integrated Water Resources Management" strategy to the Tahtalı–Seferihisar sub-basin in Turkey, where water stress is expected in the future. Using the WEAP (Water Evaluation and Planning System) model, the hydrological (precipitation, flow, evaporation) data of important water resources for the basin and Izmir (Tahtalı, Seferihisar, Ürkmez, and Kavakdere Dams) were used to predict the availability of water resources in the future, and several possible scenarios for water demands/supplies were analyzed. The water budget balances projected in 2050 have been calculated by considering six different scenarios: Reference Scenario, Report Consumption Scenario, Optimistic Case Scenario, Pessimistic Case Scenario, Return Flow Scenario, and Various Forecast Scenario. The water balances that can be obtained in each scenario under various situations were computed and compared. For all considered scenarios, unmet water demand in the basin is found to be significant (157.52 hm3 in the Optimistic Case Scenario and 373.16 hm3 in the Pessimistic Case Scenario).Article Citation - WoS: 11Citation - Scopus: 12Investigation of the Best Possible Methods for Wind Turbine Blade Waste Management by Using Gis and Fahp: Turkey Case(Springer, 2022) Öztürk, Samet; Karipoğlu, FatihThe aim of this study is to present the status and projections of wind turbine blade retirement in Turkey; to investigate the number of retiring WT blades in the regional, manufacturer, and material aspects; and to discuss the management methods for retired WT blades. To determine the best possible wind turbine blade waste management methods for Turkey, a combined application of Geographical Information Systems (GIS) and the Fuzzy Analytical Hierarchy Process (FAHP) is used in this study. It is found that around nine thousand WT blades will become waste between 2020 and 2039 in Turkey, corresponding to around 80,500 tons of waste. On average, 52,325 tons of glass/carbon and 28,175 tons of polymers will be accumulated between 2020 and 2039 from wind turbine blades. More than half of the WT blade waste will come from two WT manufacturers, namely, Enercon and Nordex. Aegean and Marmara regions will provide 74% of the blade waste, where 33% of them will be 2 MW and 2.5 MW sizes of WT blades. Furthermore, a case study is applied to Izmir city to demonstrate the results of FAHP for finding the best available method to dispose of WT blades. The results show that using blade waste as filling material is the best alternative, while waste-to-energy is the last favorable option for blade waste management. Finally, sensitivity analyses are applied to demonstrate the robustness of the results for the inclusion of new alternatives and the bias of experts’ judgments.Article Citation - WoS: 14Citation - Scopus: 18The use of video clickstream data to predict university students’ test performance: A comprehensive educational data mining approach(Springer, 2022) Yürüm, Ozan Raşit; Taşkaya Temizel, Tuğba; Yıldırım, SonerVideo clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students’ test performance with two consecutive experiments. The first experiment was performed as an exploratory study with 22 university students using a single test performance measure and basic statistical techniques. The second experiment was performed as a conclusive study with 16 students using repeated measures and comprehensive data mining techniques. The findings show that a positive correlation exists between the total number of clicks and students’ test performance. Those students who performed a high number of clicks, slow backward speed or doing backwards or pauses achieved better test performance than those who performed a lower number of clicks, or who used fast-backward or fast-forward. In addition, students’ test performance could be predicted using video clickstream data with a good level of accuracy (Root Mean Squared Error Percentage (%RMSE) ranged between 15 and 20). Furthermore, the mean of backward speed, number of pauses, and number/percentage of backwards were found to be the most important indicators in predicting students’ test performance. These findings may help educators or researchers identify students who are at risk of failure. Finally, the study provides design suggestions based on the findings for the preparation of video-based lectures.Article Citation - WoS: 16Citation - Scopus: 13Energy storage performance of nitrogen-doped reduced graphene oxide/co-doped polyaniline nanocomposites(Springer, 2022) Altınışık, Hasan; Getiren, Bengü; Çıplak, Zafer; Soysal, Furkan; Yıldız, NurayThe design and exploration of carbon-based electrode materials have become highly significant for developing supercapacitor technology, which has attracted considerable attention in energy storage systems. Here, nitrogen-doped reduced graphene oxide (N-rGO) – Polyaniline (PANI) nanocomposites were synthesized by a facile two-step method in which in situ polymerization of aniline monomer was performed on hydrothermally synthesized N-rGO nanosheets in DBSA and H2SO4 medium for co-doping of PANI chains. The effects of various acid concentrations (DBSA:H2SO4 0.5 − 0.25:1 n/n) and N-rGO:aniline ratios (N-rGO:aniline 1:4–10 m/m) used in the preparation of the electrode material on the capacitive properties were investigated. It is found that the co-doped N-rGO-PANI nanocomposites exhibit a high specific capacitance of 346.3 F g− 1 at 1 A g− 1, remarkable rate capacity (99.9%, 1–10 A g− 1) and excellent cycle stability at 5 A g− 1 (81.3%, 5000 cycles) in a two-electrode system. As a result, constructing co-doped PANI chains and N-doped rGO provided a viable and simple way to improve the capacitive performances of supercapacitors.Article Soft Error Vulnerability Prediction of Gpgpu Applications(Springer, 2022) Topçu, Burak; Öz, IşılAs graphics processing units (GPUs) evolve to offer high performance for general-purpose computations in addition to inherently fault-tolerant graphics applications, soft error reliability becomes a significant concern. Fault injection provides a method of evaluating the soft error vulnerability of target programs. Since performing fault injection experiments for complex GPU hardware structures takes impractical times, the prediction-based techniques to evaluate the soft error vulnerability of general-purpose GPU (GPGPU) programs based on metrics from different domains get crucial for both HPC developers and GPU vendors. In this work, we propose machine learning (ML)-based prediction frameworks for the soft error vulnerability evaluation of GPGPU programs. We consider program characteristics, hardware usage and performance metrics collected from the simulation and the profiling tools. While we utilize regression models to predict the masked fault rates, we build classification models to specify the vulnerability level of the GPGPU programs based on their silent data corruption (SDC) and crash rates. Our prediction models achieve maximum prediction accuracy rates of 95.9, 88.46, and 85.7% for masked fault rates, SDCs, and crashes, respectivelyArticle Label-Free Retraining for Improved Ground Plane Segmentation(Springer, 2022) Uzyıldırım, Furkan Eren; Özuysal, MustafaDue to increased potential applications of unmanned aerial vehicles over urban areas, algorithms for the safe landing of these devices have become more critical. One way to ensure a safe landing is to locate the ground plane regions of images captured by the device camera that are free of obstacles by deep semantic segmentation networks. In this paper, we study the performance of semantic segmentation networks trained for this purpose at a particular altitude and location. We show that a variation in altitude and location significantly decreases network performance. We then propose an approach to retrain the network using only a new set of images and without marking the ground regions in this novel training set. Our experiments show that we can convert a network’s operating range from low to high altitudes and vice versa by label-free retraining.