WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Citation - WoS: 2
Citation - Scopus: 1
94.8 Km-Range Direct Detection Fiber Optic Distributed Acoustic Sensor
(Optica Publishing Group (Formerly OSA), 2019) Uyar, F.; Onat, T.; Unal, C.; Kartaloǧlu, T.; Ozdur, I.; Özbay, E.
This work demonstrates an ultra-long range direct detection fiber optic distributed acoustic sensor which can detect vibrations at a distance of 94.8 km with 10 m resolution along the sensing fiber. © 2023 Elsevier B.V., All rights reserved.
Citation - WoS: 2
Citation - Scopus: 3
94.8 Km-Range Direct Detection Fiber Optic Distributed Acoustic Sensor
(Institute of Electrical and Electronics Engineers Inc., 2019) Uyar, Faruk; Onat, Talha; Unal, Canberk; Kartaloǧlu, Tolga; Ozdur, Ibrahim T.; Özbay, Ekmel
This work demonstrates an ultra-long range direct detection fiber optic distributed acoustic sensor which can detect vibrations at a distance of 94.8 km with 10 m resolution along the sensing fiber. © 2019 Elsevier B.V., All rights reserved.
Adaptive Re-Use of Medieval Caravanserais in Central Anatolia
(Gangemi Editore S P A, 2019) Yoney, Nilufer Baturayolu; Asiliskender, Burak; Urfalioglu, Nur
Kayseri, located at the junction of two major trade routes from northeast to southwest and from southeast to northwest, has been a commercial center for at least 4,000 years. The 23,500 tablets found at the Assyrian trade colony in Kanesh-Karum dating around 2,000 BCE and located 20km from the modern city provide ample proof. The great number and relevant size of Medieval caravanserais around the city as well as commercial buildings at the center indicate that this importance continued. Some of these caravanserais are already in use, albeit with inadequate architectural preservation measures while others are abandoned and/or partially destroyed. Indeed, the preservation, restoration and adaptive re-use of Medieval buildings is a major problematic, bringing out issues and interventions related to lacunae and reintegration, liberation or clearance of additions, structural strengthening with traditional/contemporary technologies, partial reconstruction, consolidation, cleaning and conservation of original building materials, and preventive maintenance. This paper aims to consider the possible presentation and adaptive re-use of Seljukid caravanserais over and inventory of accessible and at least partially preserved examples, focusing on eight case studies from the late 12th and 13th centuries: Karatay Han (1240), Tuzhisar Sultan Han (1232-1236), Eshab-i Kehf Han (before 1235), Cirgalan Han, Saruhan, Agzikarahan (1231-1240), Alayhan and Oresin Han.
AI-Enhanced PV Power Forecasting Using Cloud Thickness and Motion in Kayseri, Türkiye
(Wiley, 2025) Yavuz, Levent; Onen, Ahmet; Awad, Ahmed; Ahshan, Razzaqul; Al-Badi, Abdullah
The incorporation of renewable energy in photovoltaic (PV) systems has made significant progress. The inherent intermittency nature of PV generation, nevertheless poses an obstacle to accurate energy forecasting. Historical PV production plus meteorological data such as temperature, humidity, and atmospheric pressure are largely utilized in present methods of forecasting. However, cloud thickness and dynamics-integrated system, has not been investigated and tested in real-world examples yet.This research seeks to fill this gap in research through the development of a new AI-based PV forecasting model that incorporates cloud thickness, cloud motion, and solar position into the forecasting model. Cloud properties and their impact on solar radiation are computed through a deep learning-based panel-shadowing model. For cloud movement forecasting, a gated recurrent unit (GRU) is used, while multiple convolutional neural networks (CNNs) are used for estimating cloud thickness. These outcomes are then integrated with measurements from environmental sensors to improve the accuracy of the predictions.The system was implemented and tested at Abdullah G & uuml;l University and exhibited a remarkable improvement in forecasting accuracy compared to current models. The results prove that cloud motion and thickness improve the accuracy of PV predictions, which is important for energy market stability and power grid operations.
Akciğer Tümörlü Hastaların PET ve BT Görüntülerinin Çakıştırılıp Birleştirilmesi
(IEEE, 2015) Ayyildiz, Oguzhan; Yilmaz, Bulent; Karacavus, Seyhan; Kayaalti, Omer; Icer, Semra; Eset, Kubra; Kaya, Eser
Image fusion attracts attention in medical field due to complementary behavior and application such as diagnosis and treatment planning. In this study, first positron emission tomography (PET) and computed tomography (CT) images coming from 8 nonsmall cell lung cancer were registered then wavelet and principal component analysis methods were applied to fuse images. According to mutual information metric and nuclear medicine expert wavelet method gave better results when compared to PCA.
Citation - WoS: 7
Citation - Scopus: 12
Ambient Energy Harvesting for Low Powered Wireless Sensor Network Based Smart Grid Applications
(Institute of Electrical and Electronics Engineers Inc., 2019) Faheem, Muhammed Yasir; Ashraf, Muhammad Waqar; Butt, Rizwan Aslam; Raza, Basit; Ngadi, M. A.; Güngör, Vehbi Çağrı
Limited battery lifetime is one of the most critical issues for wireless sensor networks (WSNs)-based smart grid (SG) applications. Recently, ambient energy harvesting (AEH) has been considered to significantly improve the network lifetime of the WSNs-based SG applications. However, extracting a significant amount of energy from the ambient energy resource due to time varying links quality affected by power grid environments is the main issue for WSNs-based applications in SG. In this paper, we propose a novel multi-source energy harvesting mechanisms for WSNs-based SG applications. The propose hybrid ambient energy harvesting framework through the designed circuitry successfully harvests massive power density by capturing the radial electric field (EF) and ambient radio frequency WiFi 2.4GHz band signals present in the vicinity of 500kV power grid station. The design energy harvesting schemes have been implemented on the recently developed routing protocol for SG applications. The experiments using EstiNet9.0, demonstrate that the designed framework is efficient in terms of energy harvesting capabilities to enable a long-lasting lifetime of the WSNs-based smart grid applications. © 2020 Elsevier B.V., All rights reserved.
An Ultra-Low Fabric Capacitive Glove for Real-Time Motion Tracking and Human–computer Interaction
(Institute of Physics, 2025) Başıbüyük, Y.; Mutluç, M.N.; Şavur, Ö.; İçöz, K.
This study presents the development of a wearable glove system that integrates ultra-low-cost, fabric-based capacitive sensors for motion detection and human–computer interaction. The system combines touch and bend sensors fabricated from commercially available silver-coated fabric and silicone acrylic tape, enabling real-time tracking of finger movements via measurable capacitance changes. The glove translates physical gestures into digital commands, facilitating intuitive control in virtual environments. Experimental evaluation demonstrated stable operation across a wide pressure range (10–200 g, equivalent to 1.25–25 kPa), with an unnormalized sensitivity of ∼0.00504 pF g−1 (∼0.0040 pF kPa−1), corresponding to a normalized sensitivity of ∼0.0067 kPa−1 when referenced to the baseline capacitance (C0 ≈ 6 pF). The device exhibited high repeatability over 4000 loading cycles, and minimal signal variation (coefficient of variation, CV < 0.005). Integration with a Unity-based interface enabled low-latency gesture tracking in real time. Each sensor was fabricated for less than $0.05 using simple, scalable methods, without nanomaterials or cleanroom processing. Owing to its affordability, fabrication simplicity, and mechanical robustness, the proposed glove system provides a practical and scalable platform for wearable motion tracking, with strong potential in rehabilitation, assistive technologies, and interactive systems. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Citation - WoS: 1
Analysis of Battery-Powered Sensor Node Lifetime for Smart Grid Applications
(IEEE, 2016) Eris, Cigdem; Gungor, V. Cagri; Boluk, Pinar Sarisaray
Wireless Sensor Networks (WSNs) enable smart grids where sensor nodes monitor and control the important parameters of power grid components. However, energy-aware communication protocols should be developed to extend network lifetime of WSNs in smart grid environments. In this study, the lifetime of wireless sensor nodes has been analyzed for various smart grid environments, such as 500 kV substation, main power control room, and underground network transformer vaults. In addition, the effects of different operation modes of sensor nodes on node lifetime have been reviewed.
Analysis of Power-Law Fin-Type Problems Using Physics Informed Neural Networks
(Sciendo, 2025) Gocer, M.; Coskun, S. B.; Atay, M. T.
This study aims to model the temperature distribution in a single fin subjected to steady one-dimensional heat conduction with nonlinear thermal behavior. For the modeling and solution of the problem, the Physics-Informed Neural Networks (PINNs) architecture was used. The temperature-dependent heat conduction problem and the nonlinear boundary conditions of this problem were formulated with a differential equation. With the help of the PINN architecture, the loss function was minimized in order to reduce the difference between the true value and the predicted value. During this minimization process, the PINN architecture was forced to be consistent with the physical laws. The results obtained after training the PINN architecture exhibit successful performance in terms of accuracy and reliability when compared with the results in the literature. These findings highlight the potential of PINNs as a powerful alternative to conventional methods for solving complex nonlinear heat conduction problems.
Citation - WoS: 3
Citation - Scopus: 4
Analytical Design of Linear Variable Capacitors With Shaped-Finger Comb-Drive Actuators
(Institute of Electrical and Electronics Engineers Inc., 2018) Hah, Dooyoung
Variable capacitors have a broad usage in radio frequency (RF) circuits. Microelectromechanical systems (MEMS) technology can provide variable capacitors with high quality factor and wide tuning range characteristics. One of the design goals for MEMS varactors has been linear capacitance- voltage (C-V) characteristics. To design a linear C-V varactor, a shaped-finger comb-drive actuator is proposed in this paper. The shaped-finger design method, originally developed to obtain linear wavelength-voltage relationships in a tunable optical filter, is modified in this work for a linear C-V varactor, which involves development of a new governing equation. Moreover, conformal mapping is employed in calculation of capacitances, making the whole design process almost all-analytical with the minimum usage of numerical analysis methods. Variable capacitors with the shaped-finger design show linearity factor (LF) - defined as the maximum deviation from the perfect linear relationship - as low as 0.4%, tremendously improved from that of the conventional constant-finger-gap devices (LF: 49.9%). The characteristics of the designed variable capacitor are further investigated through 3-D numerical analysis, and show LF better than 11.5% for the finger thickness in the range between 1 and 10 micrometers. Versatility of the design method is further demonstrated by design of a varactor with linear resonant frequency-voltage (f-V) characteristics for voltage-controlled oscillator (VCO) applications. The developed analytical design method with shaped fingers can find a wide range of applications where comb-drive actuators are used. © 2018 Elsevier B.V., All rights reserved.
Architectural Restoration Projects in Metropolitan Areas: The Case of the Supyo Bridge
(Scuola Pitagora Editrice, 2015) Polimeni, Beniamino
In the last ten years, Asian metropolises have invested large amounts of money in urban renewal projects by encouraging large-scale environmental interventions that re-introduced nature to the cities and promoted a specific identity for the downtown areas. Among these projects, the restoration of the Cheonggyecheon River in Seoul is the most well-known case. The transformation of the river in twenty-nine months from an outdated highway into a multipurpose linear park deserves recognition as a pivotal project in modern urban design. The plan is an outstanding achievement that recovers the biological and social ecology of the city and demonstrates the keen ability of design at the urban scale to generate concrete transformation successfully over vast territories. As an example of a process of urban identity, the creation of this large-scale intervention evokes the historical legacy of the city and has been considered a step towards redeveloping the city's cultural heritage. The construction of a network of pedestrian pathways to connect the historic places and the restoration of the historic monuments are part of a cultural strategy characterized by a long debate of how to restore these areas. In particular, the restoration of two historic bridges Gwangtonggyo and Supyogyo was a highly controversial section of the plan as several interest groups voiced opinions on how to restore historical and cultural sites and their remnants and whether to replace the bridges or not. This article will examine the different restoration strategies designed for the Supyo Bridge ( Supyogyo) that has stood in the Jangchungdan Park since 1965 and, according to the main project, should be relocated in its original position.
Citation - WoS: 7
Citation - Scopus: 4
Artificial Neural Network Modeling and Simulation of In-Vitro Nanoparticle-Cell Interactions
(Amer Scientific Publishers, 2014) Cenk, Neslihan; Budak, Gurer; Dayanik, Savas; Sabuncuoglu, Ihsan
In this research a prediction model for the cellular uptake efficiency of nanoparticles (NPs), which is the rate that NPs adhere to a cell surface or enter a cell, is investigated via an artificial neural network (ANN) method. An appropriate mathematical model for the prediction of the cellular uptake rate of NPs will significantly reduce the number of time-consuming experiments to determine which of the thousands of possible variables have an impact on NP uptake rate. Moreover, this study constitutes a basis for targeted drug delivery and cell-level detection, treatment and diagnosis of existing pathologies through simulating NP-cell interactions. Accordingly, this study will accelerate nanomedicine research. Our research focuses on building a proper ANN model based on a multilayered feed-forward back-propagation algorithm that depends on NP type, size, surface charge, concentration and time for prediction of cellular uptake efficiency. The NP types for in-vitro NP-healthy cell interaction analysis are polymethyl methacrylate (PMMA), silica and polylactic acid (PLA), all of whose shapes are spheres. The proposed ANN model has been developed on MATLAB Programming Language by optimizing a number of hidden layers (HLs), node numbers and training functions. The datasets are obtained from in-vitro NP-cell interaction experiments conducted by Nanomedicine and Advanced Technology Research Center. The dispersion characteristics and cell interactions with different NPs in organisms are explored using an optimal ANN prediction model. Simulating the possible interactions of targeted NPs with cells via an ANN model will be faster and cheaper compared to the excessive experimentation currently necessary.
Citation - WoS: 1
Assessment of Installed Power for Inclined Belt Conveyors Using Genetic Algorithm and Artificial Neural Networks
(Konya Teknik Univ, 2022) Koken, Ekin
In this study, the installed power (P inst , kW) of several inclined belt conveyors operating in the mining industry of Turkey was investigated through two soft computing algorithms (i.e., genetic expression programming (GEP) and artificial neural networks (ANN)). For this purpose, the most crucial belt (i.e., belt length (L), belt width (W), belt inclination (alpha)), operational (i.e., belt speed (Vb) b ) and throughput (Q)) and infrastructural (belt weight (Wb) b ) and idler weight (Wid)) id )) features of 42 belt conveyors were collected for each investigated belt conveyor. The collected data was transformed into a comprehensive dataset for soft computing analyses. Based on the GEP and ANN analyses, two robust predictive models were proposed to estimate the P inst . The performance of the proposed models was evaluated using several statistical indicators, and the statistical evaluations demonstrated that the models yielded a correlation of determination (R2) 2 ) greater than 0.95. Nevertheless, the ANN-based model has slightly overperformed in predicting the P inst values. In conclusion, the proposed models can be reliably used to estimate the P inst for the investigated conveyor belts. In addition, the mathematical expressions of the proposed models were given in the present study to let users implement them more efficiently.
Citation - WoS: 3
Association Rules on Traffic Accident: Case of Ankara
(Ege Univ, Fac Economics & Admin Sciences, 2016) Soylemez, Ismet; Dogan, Ahmet; Ozcan, Ugur
In this study, association rules analysis of the data mining techniques are used for data of traffic accidents in 2010 and some rules are obtained. With this rules, what is the possibility of accident which resulted anybody injured for "different weather conditions (snowy, rainy etc.)", "where the accidents occurred (street, road etc.)" and "way situations (separated road or not)". Different algorithms are used to analyze the association rules. Apriori algorithm is selected for this study and SPSS Clementine 12.0 is used for this algorithm. Firstly, frequency of items are found. Then, items are grouped. In this study, data preprocessing is done and missing values are filled or rejected. In the second phase, outliers are rejected and data type is converted type of 1-0 (binary). In the third phase, Apriori algorithm is applied and results are evaluated.
Citation - WoS: 6
Citation - Scopus: 12
Autonomous UAV Navigation via Deep Reinforcement Learning Using PPO
(IEEE, 2022) Kabas, Bilal
In this paper, a computer vision-based navigation system is proposed for autonomous unmanned aerial vehicles (UAV). The proposed navigation system is based on a deep reinforcement learning-based high-level controller. In this paper, proximal policy optimization (PPO), which is a deep reinforcement learning method, is used to train the artificial neural network in an end-to-end way using a continuous reward function. The proposed method has been tested on images obtained from different modalities (RGB and depth) in simulation environments that are created using Unreal Engine and Microsoft AirSim. For the navigation problem that this work is concerned with, a success rate of 96% has been obtained by using RGB cameras. Since RGB cameras are lighter than depth cameras and the trained artificial neural network has a parameter number less than 170.000, the proposed method is suitable to be deployed in micro aerial vehicles. Code is publicly available*.
Ball Lens Based Mobile Microscope
(Gazi Univ, 2016) Icoz, Kutay
In this paper we report a low cost, simple and mobile microscope based on attachment of a ball lens to a cell phone. The system's noise and parameters affecting the image quality is investigated. The ball lens provides approximately 100X magnification and together with the cell phone's integrated lens and image sensor, 3,4-micron resolution is reached. The field-of-view of the system is 1500x1500 mu m where the price of the ball lens and the holder is less than 10 cents. By using this system as an optical light microscope, we are able to acquire images of micro particles and micro sensors. When combined with image processing methods, this optical system is capable of doing complex analysis as an alternative to commercial optical light microscopes.
Barriers in Sustainable Lean Supply Chain Management: Implementation in SMEs
(Ege Univ, Fac. Economics & Admin. Sciences, 2025) Kazancoglu, Yigit; Takcı, Ebru; Ada, Erhan
As the world undergoes significant transformations in various domains, including technology, energy supply and communication, the idea of sustainability has become a significant issue. This study investigates the barriers to Sustainable Lean Supply Chain (SLSC) management within Small and Medium-Sized Enterprises (SMEs) and explores the structural interrelationships among these barriers. A comprehensive literature review was carried out to recognize critical elements relevant to the research topic, resulting in the identification of fifteen specific elements that account for 85% of the barriers in SLSC management. The DEMATEL method was used to evaluate the significance and influence levels of these factors. Furthermore, structured in-depth interviews were conducted with ten experts representing sectors that constitute 85% of the SMEs operating in Kayseri Organized Industrial Zone (OIZ), Turkey, including metal products, furniture, plastic packaging, construction materials, textiles and food. The findings reveal that strategies represent the most significant barrier to SLSC management in SMEs. The barriers were analyzed in two dimensions: influencing and influenced factors. The primary influencing factor identified was laws, standards, regulations, and legislation while the most significant influenced factor was found supply and suppliers. The study concludes with findings and actionable recommendations for practitioners and decision-makers.
Citation - Scopus: 2
Beyin Bilgisayar Arayüzü Uygulamalari için Dinlenme, Harekete Niyet ve Hareket Ayırma
(Institute of Electrical and Electronics Engineers Inc., 2018) Oztürk, Nedime; Yilmaz, Bulent
Brain-computer interface (BCI) is a system that provides a means to control prosthesis, wheelchair, or similar devices using brain waves without direct motor nervous system involvement. For this purpose, brain waves obtained from multiple electrodes placed on the scalp (EEG, Electroencephalogram) are used. Emotiv Epoc used to obtain EEG signals is a low-cost device and has real-time applications. The aim of this study is the detection of rest, imagination and real movement using EEG signals obtained by Emotiv Epoc headset. As a result, As a result, the data obtained from 39 trials from a female subject were classified resting, motion imagination and movement, according to 97.4% accuracy by using the statistical features of distortion, logarithm energy entropy, energy, Shannon entropy and kurtosis. In this study, it has been shown that this system can be remarkably successful for BCI applications. © 2019 Elsevier B.V., All rights reserved.
Citation - Scopus: 2
Beyin Dalgalari ve Baş Hareketiyle Gerçek Zamanli Robotik Araba Kontrolü
(Institute of Electrical and Electronics Engineers Inc., 2018) Oztürk, Nedime; Yilmaz, Bulent; Onver, Ahmet Yasin
Emotiv Epoc Headset is a portable and low-cost device. In this study, Emotiv Epoc headset was used in order to obtain real-time gyro and EEG signals. The aim of this study was to control a robotic car in real-time by using head movement and opening and closing of the eyes. The maximum and minimum amplitude of the gyro signal, and the ratios of the beta waves of O1 and O2 channel to alpha waves of the same channels were used as threshold values. These threshold values were used to determine the direction of the robotic car. Because of its low-cost and easy implementation, Arduino Uno was used to manage the robotic car. This study has shown that brain waves and head movements can control a device in real time. This system has the potential to be used in neurofeedback and brain-computer interface applications. © 2019 Elsevier B.V., All rights reserved.
Blockchain Based User Management System
(IEEE, 2020) Temiz, Mustafa; Soran, Ahmet; Arslan, Halil; Erel, Hilal
Blockchain is a reliable and transparent structure formed by distributing the data in blocks connected to each other using various cryptography techniques to other points on the network. The difference from the existing database operations is that the authorities and responsibilities do not exist in a single central authority, and that these powers and responsibilities are distributed to the other nodes in the network and the assignment is shared. To provide this, peer to peer network infrastructure is used. However, at this stage, authentication in terms of security is one of the basic security mechanisms. In this study, a user management system which can be integrated with more reliable and current technologies, which is thought to be the solution to speed problems in blockchain, is proposed.

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