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

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Comparing Image Similarity Methods for Face Images
(Institute of Electrical and Electronics Engineers Inc., 2021) Örnek, Ahmet Haydar; Çelik, Mustafa; Alper, Ozan Can
In order to realize real-time computer vision projects we need to avoid time consuming operations such as more inference for deep learning. Our current application uses face images to decide whether there is a mask on the face so as to prevent unhealthy situations in view of epidemic. Since frames are sequentially coming it is necessary to eliminate similar frames to avoid more inference. We show how to measure a similarity between two frames by comparing traditional and deep learning based methods in this study. This study shows that deep learning based method is more efficient than traditional methods when comparing images. © 2021 IEEE.
Citation - Scopus: 3
Cost Analysis of Electric Vehicle Charging Stations and Estimation of Payback Periods With Artificial Neural Networks
(Institute of Electrical and Electronics Engineers Inc., 2023) Olcay K.; Cetinkaya N.
In this study, the current number of electric vehicles charging stations (EVCS) and the projected increase in their numbers for two different scenarios, as outlined in the literature, have been analyzed, taking into consideration all kinds of charging station costs, to determine their payback periods. Cost calculations and revenue projections have been conducted based on the high growth scenario for charging stations to establish their respective payback periods. Artificial neural networks (ANN) were developed using these data, and payback periods were predicted according to the medium growth scenario. An equation was formulated using the current numbers of electric vehicles and the growth rates specified in the literature to determine the number of electric vehicles in the near future. Moreover, the energy consumption of electric vehicles currently utilized in the automotive industry was identified using the data obtained. All of these data were employed in the training of artificial neural networks. The source of income covering the charging station costs is derived from electricity sales made at the stations. The calculated payback periods based on the number of charging stations per vehicle provided in the study and the forecasts made using artificial neural networks indicate that the charging station payback periods will significantly decrease in the future, warranting careful consideration of the initial costs. © 2023 IEEE.
Citation - Scopus: 3
Localization Using Two Different Imu Sensor-Based Dead Reckoning System
(Institute of Electrical and Electronics Engineers Inc., 2024) Toy, I.; Durdu, A.; Yusefi, A.
Dead reckoning estimates the current position, speed, and direction of moving objects using known position information. Localization determines an object's location on the map, categorized into human and vehicle localization. Autonomous vehicles rely on accurate vehicle localization for effective task execution. While Global Navigation Satellite System (GNSS) is a popular method, weak or absent signals can pose challenges. This study utilizes Inertial Measurement Unit (IMU) sensors for localization, integrating a second IMU to enhance accuracy. Fusing data from two IMU sensors, a dead reckoning system achieves 1.02 degrees and 1.41 meters errors in rotation and translation with a single IMU, and 1.01 degrees and 1.04 meters with two IMUs, respectively. © 2024 IEEE.
Citation - Scopus: 4
Thermal Characteristics, Stability, and Degradation of Pvc Composites and Nanocomposites
(Springer Science and Business Media Deutschland GmbH, 2024) Özsin, G.; Kılıç, M.; Kırbıyık, Kurukavak, Ç.; Varol, E.
PVC composites are frequently and widely used in numerous engineering applications because they offer a cost-effective and versatile solution with improved mechanical, thermal, and barrier properties for various applications. Investigating the thermal characteristics, thermal stability, and thermal degradation of PVC-based composites is essential to ensure their optimal performance, safety, and durability in polymer material science. The current study briefly explains the thermal properties and degradation mechanism of PVC and then focuses are placed on the composites with PVC matrix. In particular, the thermal characteristics of different composite formulations and strategies based on different reinforcements were presented and compared within each strategy and in between. This overview will help to gain a profound understanding of the current state of PVC-based composites and nanocomposites in the context of thermal properties and thermal degradation to determine the best formulation, processing processes, and conditions of such composite materials. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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