Kerestecioğlu, Feza

Profile Picture
Profile URL
https://hdl.handle.net/20.500.12469/6138
Name Variants
Kerestecioglu F.
K., Feza
Feza Kerestecioğlu
Kerestecioğlu F.
Kerestecioǧlu F.
Kerestecioglu,F.
FEZA KERESTECIOĞLU
Kerestecioğlu, F.
Kerestecioğlu,F.
KERESTECIOĞLU, Feza
KERESTECIOĞLU, FEZA
K.,Feza
Feza KERESTECIOĞLU
Kerestecioğlu, FEZA
Feza, Kerestecioglu
Kerestecioglu,Feza
F. Kerestecioğlu
Kerestecioglu, Feza
Kerestecioğlu, Feza
Keresteci˙oğlu,F.
Kerestecioglu, F.
Job Title
Prof. Dr.
Email Address
[email protected]
Main Affiliation
Computer Engineering
Status
Current Staff
Website
ORCID ID
0000-0001-9722-9458
Scopus Author ID
6603417688
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
AAF-8910-2019

Sustainable Development Goals

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Documents

25

Citations

227

h-index

8

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Documents

22

Citations

156

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Scholarly Output

25

Articles

10

Views / Downloads

6/0

Supervised MSc Theses

1

Supervised PhD Theses

1

WoS Citation Count

96

Scopus Citation Count

158

WoS h-index

6

Scopus h-index

8

Patents

0

Projects

0

WoS Citations per Publication

3.84

Scopus Citations per Publication

6.32

Open Access Source

15

Supervised Theses

2

JournalCount
Adaptive Behavior2
2009 IEEE International Conference on Control Applications1
2013 9th Asian Control Conference (ASCC)1
2018 3rd International Conference on Computer Science and Engineering (Ubmk)1
2018 3rd International Conference on Computer Science and Engineering (UBMK)1
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Now showing 1 - 10 of 25
  • Thumbnail Image
    Article
    Citation - WoS: 2
    Nonuniform Sampling for Detection of Abrupt Changes
    (Birkhauser Boston Inc, 2003) Kerestecioğlu, Feza; Tokat, Sezai
    In this work detection of abrupt changes in continuous-time linear stochastic systems and selection of the sampling interval to improve the detection performance are considered. Cost functions are proposed to optimize both uniform and nonuniform sampling intervals for the well-known cumulative sum algorithm. Some iterative techniques are presented to make online optimization computationally feasible. It is shown that considerable improvement in the detection performance can be obtained by using nonuniform sampling intervals.
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    Conference Object
    Citation - WoS: 8
    Indoor Positioning Using Federated Kalman Filter
    (IEEE, 2018) Aybakan, Tarik; Kerestecioglu, Feza
    In this paper, the performance of a multi-sensor fusion technique, namely Federated Kalman Filter (FKF) is studied in the context of indoor positioning problem. Kalman filters having centralized and decentralized structures are widely used in outdoor positioning and navigation applications. Global Positioning System (GI'S) is the most commonly used system for outdoor positioning/navigation, which cannot be used indoors due to the signal loss. In this study, a decentralized structure for FKF is applied in indoor positioning problem by taking its outdoor navigation performance into consideration. Simulations are perl4med with distance measurements, which are assumed to be calculated by using Received Signal Strength (RSS). Results gathered via different simulations are evaluated as promising for future studies.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 6
    Indoor Positioning Using Federated Kalman Filter
    (Institute of Electrical and Electronics Engineers Inc., 2018) Ayabakan, Tarık; Kerestecioğlu, Feza
    In this paper, the performance of a multi-sensor fusion technique, namely Federated Kalman Filter (FKF) is studied in the context of indoor positioning problem. Kalman filters having centralized and decentralized structures are widely used in outdoor positioning and navigation applications. Global Positioning System (GPS) is the most commonly used system for outdoor positionin/navigation, which cannot be used indoors due to the signal loss. In this study, a decentralized structure for FKF is applied in indoor positioning problem by taking its outdoor navigation performance into consideration. Simulations are performed with distance measurements, which are assumed to be calculated by using Received Signal Strength (RSS). Results gathered via different simulations are evaluated as promising for future studies.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 1
    A Non-Communicating Multi-Robot System With Switchable Formations
    (2013) Cezayirli, Ahmet; Kerestecioğlu, Feza
    We consider connected navigation of autonomous mobile robots with transitions in the group formation. The robots navigate using simple local steering rules without requiring explicit communication among themselves. The formations are achieved by designing proper cost functions and formation transitions are succeeded by switching among these cost functions. The resulting system is proven to be deadlock-free under certain conditions. © 2013 IEEE.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 2
    Citation - Scopus: 8
    Navigation of Autonomous Mobile Robots in Connected Groups
    (IEEE, 2008) Cezayirli, Ahmet; Kerestecioğlu, Feza
    The navigation of autonomous mobile robots as a group is considered in this paper. Definitions adopted from the graph theory are given to characterize the robot group. A local steering strategy is proposed such that when each robot in the group applies this steering scheme the overall result is that the whole group is displaced without losing its connectivity. This is achieved using only limited-range position sensors and without any communication between the robots.
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    Master Thesis
    Anomaly Detection Via Machine Learning
    (Kadir Has Üniversitesi, 2023) ERDEM, GÖRKEM; Kerestecioglu, Feza; Çevik, Mesut
    Retail companies monitor inventory stock levels regularly and manage stock levels based on forecasted sales to sustain their market position. The accuracy of inventory stocks is critical for retail companies to create a correct strategy. Many retail com- panies try to detect and prevent inventory record inaccuracy caused by employee or customer theft, damage or spoilage and wrong shipments. This study is aimed to detect inaccurate stocks using machine learning methods. It uses the real inven- tory stock data of Migros Ticaret A.S¸. of Turkey’s largest supermarket chains. A multiple of machine learning algorithms such as Isolation Forest (IF), Local Outlier Factor (LOF), One-Class Support Vector Machine (OCSVM) were used to detect abnormal stock values. On the other hand, generally, researchers use public data to develop methods, and it is challenging to apply machine learning algorithms to real-life data, especially in unsupervised learning. This thesis shows how to handle real-life data noises, missing values etc. The experimental findings show the perfor- mances of machine learning methods in detecting anomalies in low and high level inventory stock.
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    Article
    Circular Formations of Non-Communicating Robot Groups Via Local Strategies
    (Sage Publications Ltd, 2023) Kerestecioglu, Feza; Sen, Uemit; Isikver, Cagri; Goktekin, Ahmet
    Local strategies, which are based on cost minimization, to achieve circular formations of autonomous robot groups are presented. It is assumed that the group members have no communication capabilities or any means of interchanging information among themselves, and that they can only rely on their sensors, which provide relative positions of their nearby group members. It is verified on simulations that via appropriately defined cost functions arc, arc-triangle and circle formations are obtained, which can be maintained during navigation.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 2
    Active Reconfigurable Control of a Submarine With Indirect Adaptive Control
    (2003) Demirci, Ufuk; Kerestecioğlu, Feza
    An indirect adaptive controller is designed for submersibles. The design is developed using a linearized MIMO model of a submarine. Standard recursive least squares estimation method is used to estimate the parameters. Depth and pitch angle of the submarine is controlled by means of the well-known indirect self-tuning method. In case of a system fault estimated parameters of the submarine model have been used to update the controller coefficients.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 7
    Fault Tolerant Control With Re-Configuring Sliding-Mode Schemes
    (2005) Demirci, Ufuk; Kerestecioğlu, Feza
    In this paper a controller design method for linear MIMO systems is presented which a sliding mode controller is reconfigured in case of system faults. Faults are detected with the residual vector generated from a standard linear observer. Once a fault has been detected the fault distribution matrix can be obtained and used to update the corrective or equivalent control parts of the sliding mode controller. As a result fault tolerant adaptive controllers keep the system performance within acceptable limits or at least avoids the system to wind-up. © TÜBITAK.
  • Thumbnail Image
    Article
    Citation - WoS: 14
    Citation - Scopus: 15
    RSSI-Based Indoor Positioning via Adaptive Federated Kalman Filter
    (IEEE-Inst Electrical Electronics Engineers Inc, 2022) Ayabakan, Tarik; Kerestecioglu, Feza
    In this paper, federated Kalman filter (FKF) is applied for indoor positioning. Position information that is multi-laterated from the distance information obtained using the received signal strengths collected from several access points are processed in a FKF to estimate the position of the target. Two approaches are presented to adjust the information-sharing coefficients of FKF using online measurements. The data collected on a test bed composed of four access points are used to assess and compare the performances of the proposed algorithms. It is shown that the estimation error can be improved considerably by adjusting the information-sharing coefficients online.