Oğuz Ekim, Pınar

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Profile URL
https://hdl.handle.net/20.500.14365/6888
Name Variants
Eki̇m, Pınar Oğuz
Ekim, Pınar Oğuz
Oguz Ekim, Pinar
Job Title
Email Address
pinar.ekim@ieu.edu.tr
Main Affiliation
05.06. Electrical and Electronics Engineering
Status
Current Staff
Website
ORCID ID
0000-0003-1860-4526
Scopus Author ID
36608964400
Turkish CoHE Profile ID
62217BCD60CAC025
Google Scholar ID
bkixXI0AAAAJ
WoS Researcher ID
ABB-8456-2020
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Pinar_Oguz_Ekim.jpg (11.39 KB)

Sustainable Development Goals

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DECENT WORK AND ECONOMIC GROWTH
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INDUSTRY, INNOVATION AND INFRASTRUCTURE
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10

REDUCED INEQUALITIES
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PARTNERSHIPS FOR THE GOALS
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RESPONSIBLE CONSUMPTION AND PRODUCTION
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7

AFFORDABLE AND CLEAN ENERGY
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NO POVERTY
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GENDER EQUALITY
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CLIMATE ACTION
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QUALITY EDUCATION
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LIFE BELOW WATER
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ZERO HUNGER
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LIFE ON LAND
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PEACE, JUSTICE AND STRONG INSTITUTIONS
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CLEAN WATER AND SANITATION
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GOOD HEALTH AND WELL-BEING
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SUSTAINABLE CITIES AND COMMUNITIES
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Documents

23

Citations

257

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Documents

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Citations

183

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Scholarly Output

19

Articles

5

Views / Downloads

33/174

Supervised MSc Theses

4

Supervised PhD Theses

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WoS Citation Count

63

Scopus Citation Count

112

WoS h-index

4

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4

Patents

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Projects

2

WoS Citations per Publication

3.32

Scopus Citations per Publication

5.89

Open Access Source

5

Supervised Theses

4

JournalCount
ELECO 2019 - 11th International Conference on Electrical and Electronics Engineering2
2021 8Th Internatıonal Conference on Electrıcal And Electronıcs Engıneerıng (Iceee 2021)1
2024 IEEE 15th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 20241
2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 2045621
2Nd Internatıonal Congress on Human-Computer Interactıon, Optımızatıon And Robotıc Applıcatıons (Hora 2020)1
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Now showing 1 - 10 of 18
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 4
    Face Detection, Tracking and Recognition With Artificial Intelligence
    (Institute of Electrical and Electronics Engineers Inc., 2021) Tekkok S.C.; Soyunmez M.E.; Bostanci B.; Ekim P.O.
    Due to the COVID-19 pandemic, the face masks are mandatory everywhere so it might be beneficial to automatize the detection and tracking of whether people wear a mask or not with the help of the computer vision. Furthermore, it can be implemented on mobile robots as well. Additionally, face recognition of people is discussed with two different techniques which are based on neural networks and eigenface approach in this study. Hence, a complete system which can be used with mobile platforms has been achieved with the proposed procedure. © 2021 IEEE.
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    Conference Object
    Citation - Scopus: 1
    Pallet Detection and Docking With Autonomous Forklift;
    (Institute of Electrical and Electronics Engineers Inc., 2024) Keser, Alperen; Ekim, P.O.
    Pallet handling operations in factories and warehouses are vital to ensure continuity and increase productivity. These operations using forklifts face some difficulties in terms of time, cost and efficiency. One way to circumvent these problems is to use mobile autonomous robots. However, autonomous robots may also experience difficulties in such operations. One of these difficulties is autonomous docking. Completion of the docking operation in the desired time, working with good precision and not exceeding the determined cost values are still issues in the field of robotics. The main goal of this study is to provide an easily integrated and low-cost solution for problems frequently encountered in the field of robotics, such as docking and pallet detection in autonomous forklifts. The difference of the image processing mechanism, developed for the pallet detection, is that the sensor used is a low-cost depth camera. The planner has been designed in an easily manipulable way and the requiered precision for picking the pallet have been achieved with a cross-track error of ±3 cm or less, and orientation error of ±4° or less. Performance of the developed system has been tested in a simulation environment on a non-holonomic, tricycle forklift. © 2024 IEEE.
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    Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    The Application of Kalman Filter for Lead-Acid Battery State of Charge Estimation
    (IEEE, 2021) Tekkok, Sercan Cagdas; Bostanci, Bekir; Soyunmez, Mehmet Emre; Oğuz Ekim, Pınar
    Battery systems are crucial part of the most applications which are mobile and have electronic components from autonomous mobile robots to mobile phones. Hence, it is important to keep track of the state of the battery and its health in order to make these devices reliable and also protect the battery from over discharges and overcharges. There are different methods to estimate it but not all of them applicable for mobile systems. Thus, this study discusses and compares three methods that can be used for mobile applications and batteries that are under continuous use. The coulomb counting method, the linear counting model and the extended Kalman filter with nonlinear battery model are tested with both simulated and real data with a lead acid battery.
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    Conference Object
    Citation - Scopus: 1
    The Ekf Based Localization and Initialization Algorithms With Uwb and Odometry for Indoor Applications and Ros Ecosystem
    (Institute of Electrical and Electronics Engineers Inc., 2020) Oguz-Ekim P.; Bostanci B.; Tekkok S.C.; Soyunmez E.
    This paper will cover some extension modules over the Turtlebot3 libraries using ultra-wideband (UWB) sensors and propose a solution to the initialization problem along with the localization problem. The Turtlebot3 already has an algorithm named move base for autonomous drive, which uses Light Detection and Ranging (LiDAR) and odometry to localize itself and avoid obstacles. However, it suffers from autonomous initialization. Therefore, ranging data from UWB sensors are used to take the initial pose of the robot to eliminate the initialization problem and advance the move base algorithm to be more robust. This data is also used in the Extended Kalman Filter (EKF) along with odometry to localize the robot. To enable wide-spread adoption, we provide an open source implementation of our algorithms and modules for the robot operating system (ROS) for real environment. Furthermore, we create an open source simulation environment for applications, which use UWB, LiDAR, and odometry data. © 2020 IEEE.
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    Article
    Citation - WoS: 24
    Citation - Scopus: 32
    Machine Learning Approaches for Municipal Solid Waste Generation Forecasting
    (Mary Ann Liebert, Inc, 2021) Oğuz Ekim, Pınar
    Municipal solid waste (MSW) generation forecasting can be considered as the biggest challenge of integrated solid waste management systems, particularly for developing countries where data collection is limited. In this study, three different machine learning algorithms, namely backpropagation neural network (BPNN), support vector regression (SVR), and general regression neural network, were applied for different countries. Comparative evaluation of these different algorithms based on gross domestic product, domestic material consumption, and resource productivity were given through the optimum solution. Moreover, the algorithms were tested for the case of Turkey. The results of this study are expected to represent a general outline for stakeholders of Turkey for improving MSW management strategies all over the country, and these results can be extended to similar developing countries across the world. It can be concluded that BPNN and SVR methods can be applied successfully for the case of Turkey and other countries across the world to predict the MSW generation, whereas BPNN is slightly better. If the input and output variables are identified well, machine learning approaches can give a good projection for waste generation, and this projection can be utilized for different countries. Furthermore, the developing countries with missing data can develop more realistic strategies for MSW management by not relying solely on international databases such as Eurostat to forecast MSW generation.
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    Master Thesis
    Browser-Based Lightweight Cross-Platform Web Control System for Autonomous Robots Operating With Ros
    (İzmir Ekonomi Üniversitesi, 2023) Söyünmez, Mehmet Emre; Eki̇m, Pınar Oğuz
    Her geçen gün otonom robotlar hayatımızda daha da yaygınlaşmakta. Çoğunlukla lojistik ve ağır üretim hatlarıyla başlayan, ancak şimdi hastanelerden havalimanlarına, kafeteryalardan kütüphanelere ve hatta insanların evlerine kadar her sektörde ve tesiste kullanılmaktadırlar. İlk başlarda bir robotu kullanmak için herhangi bir standart bulunmaksızın, her robot geliştirici kendi sistemini oluşturup kendi robotlarında kullanmakta veya diğer geliştiricilerden satın almaktaydı. Ancak son zamanlarda Robot İşletim Sistemi (ROS) yaygın bir araç haline geldi. En büyük şirketler bile robotlarında ROS'u kullanmaya başladı. Öte yandan robotları uzaktan kontrol etmek, robot üzerindeki ROS sistemine başka bir bilgisayardan SSH gibi bir iletişim protokolü ile bağlanmayı gerektiriyor ve ardından robotu komut satırından çalıştırmak ya da emir vermek gerekiyordu, ki bu da belirli bir oranda Linux bilgisi gerektirmekte. Bu sorunu çözmek için şirketler, köprü görevi görecek uzaktan bir bilgisayarda çalışacak uygulamalar geliştirmeye başladılar. Ancak bununla birlikte, bu uzaktan cihazın belirli gereksinimlere sahip olmasını gerektiriyor, örneğin Windows işletim sistemine sahip olması, 4 GB RAM'e sahip olması, yönetici erişimi olması vb. Bunun üstesinden gelmek için, ROS ile çalışan robotları her türlü cihaz ya da işletim sistemiyle, tarayıcı çalıştırabilen herhangi eski bir dizüstü bilgisayar, cep telefonu veya akıllı saat gibi, saf JavaScript kullanarak kontrol etmek için tarayıcı tabanlı hafif ve çapraz platformlu bir sistem oluşturmayı hedeflemekteyim
  • Thumbnail Image
    Conference Paper
    Citation - WoS: 1
    Tracking neighborhood closed-loop pumped hydro storage potential
    (IEEE Computer Society, 2023) Ouedraogo, Kiswendsida Elias; Oğuz Ekim, Pınar; Demirok, Erhan
    Worldwide, energy is at the center of the socio-economical, geopolitical, and climate crises. For this reason, governments, businesses, and communities are promoting green energy to boost their energy resilience and energy independence sustainably. However, the bottleneck of replacing fossil fuel power plants entirely with intermittent renewable energy remains the high cost of energy storage systems. The study explored the existence of megawatt-hours scale closed-loop pumped hydro storage reservoirs near communities' centers. A MATLAB algorithm has been developed to detect pairs of reservoirs with one, four, and nine hectares each, and a head of one to three hundred meters, corresponding to an energy capacity of 20 to 540 megawatt hours per pair. For the three cities studied, (Banfora / Burkina, Syracuse / New York, Manisa / Turkey) the results revealed the existence of more than 10.000 megawatt-hours storage capacity in each city which meets or exceeds the need of the communities. Therefore, a 100% renewable energy power grid that is resilient, and reliable, can be achieved faster by adopting distributed closed-loop pumped hydro storage which is likely to attract a large number of smaller investors. © 2023 IEEE.
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    Research Project
    Kapalı Alanlarda Kullanılan Otonom Yer Araçları için Yer Bulma, Haritalandırma ve Güzergâh Planlama Yapabilen Cihaz Tasarımı ve Gelistirilmesi
    (2022) Ekim, Pınar Oğuz
    Otonom sistemler son yıllarda insan için tehlikeli uygulamalarda veya insanla is birligi içinde oldukları alanlarda oldukça önem kazanmıstır. Bu uygulamaların pek çogunda otonom sistemin bulundugu yeri tespit etmesi, çevresinin haritasını çıkartması ve de bu bilgilere dayanarak görevine uygun olan güzergâhı planlaması önemli alt problemler olarak karsımıza çıkmaktadır. Farklı sensörlerden gelen bilgilerin güvenilir ve verimli bir sekilde birlestirilmesinin, konum bulma ve daha birçok robotik sorununun çözümüne yardımcı olmaktadır. Çünkü bir sensör belirli çevresel kosullar altında ölçüm alamadıgında digeri hata yayılımını azaltmak için kullanılabilir. Buna ek olarak, bir sensörün hata özellikleri, farklı özelliklere sahip baska bir sensörün kullanılması ile düzeltilebilir. Sensör füzyonunun önemi yaygın olarak bilinmesine ragmen, yeni gelistirilen sensör teknolojileri ve uyumlu algoritmalar henüz kapsamlı bir sekilde çalısılmamıstır. Bu nedenle projemizde özellikle Odometre, UWB ve de Lidar sensörlerinden gelen bilgiler harmanlanmıstır. Algoritmalar Python ve C dilleri ile gelistirilmis ve ROS aracılıgı ile gerçek zamanlı olarak donanımlardan gelen bilgileri isleyebilmisler. 5 cm-10 cm konumlandırma hassasiyetinde oldukça gürbüz bir sistem ortaya çıkarılmıstır.
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    Conference Object
    Localization With Particle Filter Based on Odometer and Uwb
    (IEEE, 2020) Oğuz Ekim, Pınar
    In this paper, the particle filter structure that uses odometer and Ultra-wide band (UWB) sensors for positioning autonomous ground vehicles used in confined spaces was investigated. Accordingly, UWB sensor packages written for Turtlebot3 libraries are mentioned. The positioning algorithm has been evaluated both in simulation environment using Robot Operating System (ROS) and in real test environment. Positioning accuracy is sufficient for practical applications, but as the number of reference sensors increases, results with better precision are obtained.
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    Conference Object
    Citation - WoS: 9
    Citation - Scopus: 16
    The Lidar and Uwb Based Source Localization and Initialization Algorithms for Autonomous Robotic Systems
    (Institute of Electrical and Electronics Engineers Inc., 2019) Bostanci B.; Tekkok S.C.; Soyunmez E.; Oguz-Ekim P.; Yeganli F.
    This paper covers the source localization algorithm based on the least squares techniques and the squared range measurements obtained from ultra-wide band (UWB) sensors to locate the robot in an indoor environment. Additionally, the initialization algorithm which is based on light detection and Ranging (LiDAR) scans is proposed. It takes the advantage of the estimated location to find the initial orientation of the robot with respect to the previously obtained map. Thus, the crucial problem of the autonomous initialization and localization in robotics is solved. To enable wide-spread adoption, we provide an open source implementation of our algorithms and the modules for the robot operating system (ROS) for real environment. Furthermore, an open source simulation environment is created for applications which employ UWB/LiDAR data. © 2019 Chamber of Turkish Electrical Engineers.