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Çavur, Mahmut
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Çavur, Mahmut
M.,Çavur
M. Çavur
Mahmut, Çavur
Cavur, Mahmut
M.,Cavur
M. Cavur
Mahmut, Cavur
cavur, mahmut
Çavur, Mehmet
Cavur, M.
Çavur, M.
M.,Çavur
M. Çavur
Mahmut, Çavur
Cavur, Mahmut
M.,Cavur
M. Cavur
Mahmut, Cavur
cavur, mahmut
Çavur, Mehmet
Cavur, M.
Çavur, M.
Job Title
Email Address
Main Affiliation
Management Information Systems
Management Information Systems
03. Faculty of Economics, Administrative and Social Sciences
01. Kadir Has University
Management Information Systems
03. Faculty of Economics, Administrative and Social Sciences
01. Kadir Has University
Status
Former Staff
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ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
15
LIFE ON LAND
2
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
14
LIFE BELOW WATER
1
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
3
GOOD HEALTH AND WELL-BEING
0
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
4
QUALITY EDUCATION
1
Research Products
2
ZERO HUNGER
2
Research Products
10
REDUCED INEQUALITIES
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
3
Research Products
13
CLIMATE ACTION
0
Research Products
1
NO POVERTY
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
1
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
2
Research Products
5
GENDER EQUALITY
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output
19
Articles
13
Views / Downloads
139/1461
Supervised MSc Theses
3
Supervised PhD Theses
0
WoS Citation Count
82
Scopus Citation Count
132
WoS h-index
5
Scopus h-index
6
Patents
0
Projects
0
WoS Citations per Publication
4.32
Scopus Citations per Publication
6.95
Open Access Source
13
Supervised Theses
3
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| Journal | Count |
|---|---|
| Remote Sensing | 2 |
| Politeknik Dergisi | 2 |
| Journal of Polytechnic | 1 |
| Physical Communication | 1 |
| Powder Technology | 1 |
Current Page: 1 / 3
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19 results
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Now showing 1 - 10 of 19
Article Citation - WoS: 34Citation - Scopus: 45The Geothermal Artificial Intelligence for Geothermal Exploration(Pergamon-Elsevier Science Ltd, 2022) Moraga, J.; Duzgun, H. S.; Cavur, M.; Soydan, H.Exploration of geothermal resources involves analysis and management of a large number of uncertainties, which makes investment and operations decisions challenging. Remote Sensing (RS), Machine Learning (ML) and Artificial Intelligence (AI) have potential in managing the challenges of geothermal exploration. In this paper, we present a methodology that integrates RS, ML and AI to create an initial assessment of geothermal potential, by resorting to known indicators of geothermal areas namely mineral markers, surface temperature, faults and deformation. We demonstrated the implementation of the method in two sites (Brady and Desert Peak geothermal sites) that are close to each other but have different characteristics (Brady having clear surface manifestations and Desert Peak being a blind site). We processed various satellite images and geospatial data for mineral markers, temperature, faults and deformation and then implemented ML methods to obtain pattern of surface manifestation of geothermal sites. We developed an AI that uses patterns from surface manifestations to predict geothermal potential of each pixel. We tested the Geothermal AI using independent data sets obtaining accuracy of 92-95%; also tested the Geothermal AI trained on one site by executing it for the other site to predict the geothermal/non-geothermal delineation, the Geothermal AI performed quite well in prediction with 72-76% accuracy.(c) 2022 Elsevier Ltd. All rights reserved.Conference Object A Robust Microservices Framework for Indoor Tracking System Development(Institute of Electrical and Electronics Engineers Inc., 2024) Hayytbayev, G.; Küçük, K.; Çavur, M.The demand for indoor tracking systems is steadily increasing across various applications. While GPS is effective for outdoor localization, indoor localization presents distinct challenges related to hardware, algorithms, architecture, and infrastructure. Many researchers have focused on developing algorithms or hardware solutions to address these challenges. In response, we designed and implemented a robust, innovative framework utilizing microservices to achieve a scalable, fault-tolerant, flexible, and multi-platform indoor localization system. Our system employs RFID hardware for tracking, with data storage managed by a PostgreSQL database. The architecture incorporates RabbitMQ and the Spring framework, utilizing the Java programming language. The proposed framework was tested using a graphical user interface (GUI) within a metallic underground mine, demonstrating scalability by successfully deploying 7 and 22 RFID readers. The system supports development across various platforms, including web, desktop, and mobile, and is compatible with Mac, Linux, and Windows operating systems. The tracking accuracy was measured at 5.12 meters within a 300-meter metallic mining gallery. Overall, the microservices-based framework proved highly suitable for indoor tracking systems. © 2024 IEEE.Article Citation - WoS: 4Citation - Scopus: 5Development of a Supervised Classification Method To Construct 2d Mineral Maps on Backscattered Electron Images(Tubitak, 2020) Camalan, Mahmut; Çavur, MahmutThe Mineral Liberation Analyzer (MLA) can be used to obtain mineral maps from backscattered electron (BSE) images of particles. This paper proposes an alternative methodology that includes random forest classification, a prospective machine learning algorithm, to develop mineral maps from BSE images. The results show that the overall accuracy and kappa statistic of the proposed method are 97% and 0.94, respectively, proving that random forest classification is accurate. The accuracy indicators also suggest that the proposed method may be applied to classify minerals with similar appearances under BSE imaging. Meanwhile, random forest predicts fewer middling particles with binary and ternary composition, but the MLA predicts more middling particles only with ternary composition. These discrepancies may arise because the MLA, unlike random forest, may also measure the elemental compositions of mineral surfaces below the polished section.Book Part Citation - Scopus: 3Sentinel-1 Sar Verileri Kullanilanarak Maden Kaymalarini ve Deformasyonlarini İzleme [monıtorıng Of Mıne Landslıde And Deformatıon Usıng Sentınel-1 Sar Data](Baski, 2019) Çavur, Mahmut; Camalan, Mahmut; Ketizmen, Hakkı; Ağıtoğlu, SuudIn this study, an original DInSAR method was used to monitor landslides and deformation in a coal mine area. The open-pit mine operation belonging to the Ciner Group in Silopi, Sirnak was selected fort he case study. Between 21 November 2017 and December 31, 2017, 2-month Sentinel-1 data were analyzed every 12 days and interferometric results were obtained. It has been shown that the DInSAR method can be used effectively in order to monitor the mineral movements by using satellite images. The results of the analysis were reported in mm and accuracy analysis was performed on the field. SNAP, Cygwin, and ArcGIS 10.4 software are used for reporting and analysis purposes. The maximum subsidence was measured by radar as 45 mm. The mean subsidence rate of one class was found to be 45 mm as landslide and 46 mm as uplift where cracks most severely developed. The proposed method is an effective method for mining in order to determine the effects that may occur as a result of landslides, displacement, and uplift caused by underground and surface mining.Article Citation - WoS: 1Yereraltı Maden İşçilerini Gerçek Zamanlı Takip Etmek İçin Rfıd Teknolojisine Dayalı Özgün Bir Entegrasyon Metodolojisi(Gazi Universitesi, 2018) Çavur, MahmutIn recent years many companies want to keep track of their employees sources and working machines due to various reasons like security coordination performance monitoring. The purpose and requirements are the main factors that determine the methodology of tracking. The real-time tracking can be determined with high precision in open areas with the global positioning system (GPS). However previous research and developments for indoor tracking have mostly focused on infrared wireless LAN and ultrasonic. In this study a Radio-Frequency Identification (RFID) protocol and interface are integrated into an open source Information Systems (IS) software. A tight coupling methodology is developed for integration of RFID into an open source software. The use of open source software as a common interface also provides better spatial display and analysis capabilities. The tracking algorithm is completely unique original and it is encoded in the Java programming language. In the algorithm the accuracy of locating the proximity direction of miners and whether the RFID tag is on the right and left of the last point of RFID receiver is determined with 20 m accuracy. The system was tested in an underground salt mine. The developed methodology and system are now being commercialized in Turkey.Article Citation - WoS: 11Citation - Scopus: 16Rssi-Based Hybrid Algorithm for Real-Time Tracking in Underground Mining by Using Rfid Technology(Elsevier, 2022) Cavur, Mahmut; Demir, EbubekirKnowing the precise and real-time location of underground mining workers is essential for their health and safety in any emergency. However, the standard Global Positioning System (GPS) is insufficient for such indoor environments as it requires new infrastructure based on different technologies and algorithms. Instead, Radio Frequency Identification (RFID)-based real-time indoor localization systems and a hybrid algorithm are developed. The received-signal-strength (RSS) based positioning techniques are investigated and applied in indoor environments. A unique hybrid approach based on fingerprinting is proposed and developed to solve the disadvantages of the existing techniques. Consequently, the accuracy of this one-of-a-kind algorithm is found to be 2.52 m in an office and 3.13 m in an underground mine. We also compared the proposed hybrid algorithm to the Weighted K-Nearest Neighbor (WKNN). WKNN, on the other hand, has an accuracy of 4.01 m in the office and 4.33 m in underground mining environments. (C) 2022 Elsevier B.V. All rights reserved.Article Citation - WoS: 1Using Random Forest Tree Classification for Evaluating Vertical Cross-Sections in Epoxy Blocks To Get Unbiased Estimates for 3d Mineral Map(Gazi University, 2021) Camalan, Mahmut; Çavur, MahmutAreal mineral maps are constructed from the polished sections of particles that settle to the bottom of epoxy resin. However, heavy minerals can preferentially settle to the bottom, making the polished surface rich in heavy minerals. Therefore, polished sections will become biased estimates of the volumetric (3D) map. The study aims to test whether any vertical cross-section (any section along the settling direction of particles) can be an unbiased estimate of the 3D mineral map of a chromite ore sample. For the purpose of this study, 2D maps of the vertical cross-sections were acquired by using Random Forest classification coupled with image pre- and post-processing tools. Then, 3D mineral maps were converted from 2D maps without assuming stereological errors. The modal mineralogy and particle size distributions predicted from 3D maps were compared with the same features estimated from the particulate sample by XRD and dry sieving analyses, respectively. Any 2D map which yields a modal mineralogy and a size distribution similar to the true analyses was selected as an unbiased estimate of the true 3D map. The results suggest that any vertical cross-section is an unbiased estimate, unlike polished section at which heavier minerals settle preferentially.Master Thesis Gelı̇şmekte Olan Ülkelerde Matematı̇k Başarısını Etkı̇leyen Faktörlerı̇n Araştırılmasında Makı̇ne Öğrenme Teknı̇klerı̇nı̇n Kullanılması: Türkı̇ye, Meksı̇ka, Tayland ve Bulgarı̇stan Örneğı̇(2023) Arpa, Tuba; Çavur, MahmutMatematik tüm eğitim sistemlerinin vazgeçilmez bir parçasıdır. Çünkü matematik, hem günlük yaşamın önemli bir unsuru hem de pek çok meslek ve alan için olmazsa olmaz bir temeli teşkil etmektedir. Bu nedenle, matematik başarısını etkileyen unsurları belirlemenin, ülkelerin gelişimine katkı sağlayacağı söylenebilir. Bu doğrultuda, bu çalışmada PISA 2018 verileri kullanılarak, benzer eğitim sistemi ve ekonomik gelişmişliğe sahip dört ülke olan Türkiye, Bulgaristan, Meksika ve Tayland'ın matematik başarılarını etkileyen faktörleri makine öğrenmesi modelleri ile belirlemek, bu modellerin başarılarını karşılaştırmak amaçlanmıştır. İlgili alanyazında bu amaç için sıklıkla sınıflandırma algoritmaları tercih edildiği görülmektedir. Bu çalışmada hem sınıflandırma hem de regresyon modelleri kullanılmıştır. Çalışmada, regresyon algoritması olarak doğrusal regresyon, destek vektör regresyonu, karar ağacı regresyonu ve rastgele orman regresyonu; sınıflandırma algoritması olarak ise lojistik regresyon, destek vektör sınıflandırması, karar ağacı sınıflandırması ve rastgele orman sınıflandırması kullanılmıştır. Ayrıca, matematik başarısını tahmin etmek için en önemli faktörlerin belirlenmesinde XGradient Boosting algoritması kullanılmıştır. Son olarak, eksik verilerin doldurulmasında, K-Means metodu tercih edilmiştir. Çalışmanın sonuçlarına göre, dört ülke için de matematik başarına en büyük katkı sağlayan değişkenlerin öğrencinin ekonomik, sosyal ve kültürel statüsü, öğrencinin evde sahip olduğu çalışma materyali, öğrencinin sahiplik hissi ve ailenin refah düzeyi olduğu bulunmuştur. Model başarısı açısından hem regresyon hem de sınıflandırma açısından en yüksek başarıya sahip algoritmanın rastgele ormanlar olduğu bulunmuştur. Ayrıca, sınıflandırma algoritmaları ikili ve üçlü sınıflandırma üzerinden incelenmiş, ikili sınıflandırmanın daha yüksek başarıya sahip olduğu görülmüştür. Sonuç olarak, çalışmamızda elde edilen bulgular matematik başarısını tahmin etmede kullanılacak en uygun algoritmanın seçimi v konusunda önemli bir öngörü sunmaktadır. Ayrıca, çalışmanın bulguları, eğitim politikalarının geliştirilmesi ve öğrenci başarısını artırmak için uygulayıcı ve politika yapıcılara önemli iç görüler sağlamaktadır.Article Impacts of the Changes in Agriproduction on Rural Heritage in the Case of Müşküle, Iznik, Turkey(Emerald Group Publishing Ltd, 2025) Ulu, Damla Pilevne; Erkan, Yonca; Alkan Reis, Amine Seyhun; Guvenc, Himmet Murat; Cavur, MahmutPurposeAgriculture is both a constituent and an integral part of rural culture. Therefore, agricultural planning is essential to the conservation of rural heritage. However, this relationship has received limited scholarly attention. Focusing on the rural settlement of M & uuml;sk & uuml;le in Turkey, this research paper reveals the vital role of agricultural planning in sustaining rural architectural heritage.Design/methodology/approachWe examine the settlement's history of agricultural production in relation to national agricultural policies and practices from the early 20th century to the present, analyzing how these shifts have affected the built heritage. The research is a combination of literature review, fieldwork and face-to-face interviews. Aerial images, on-site architectural surveys and interviews were used to identify the features of the built environment. These were followed by in-depth thematic analysis.FindingsWe find that the lack of agricultural planning has led to economic decline among rural households, resulting in the neglect of architectural heritage, abandonment of traditional dwellings and increased rural outmigration. As specialized agricultural products shape the character of rural architecture, changes in production can lead to the removal of heritage-valued building elements, degradation of traditional architectural features and loss of traditional knowledge.Originality/valueThis paper demonstrates the strong link between rural production (i.e. agriproduction) and architectural heritage. It shows how agriproduction shapes rural fabric, plan typologies and building elements and underscores the decisive role of agricultural planning in rural heritage conservation.Article Citation - WoS: 9Citation - Scopus: 12Displacement Analysis of Geothermal Field Based on Psinsar and Som Clustering Algorithms a Case Study of Brady Field, Nevada-Usa(MDPI, 2021) Çavur, Mahmut; Moraga, Jaime; Düzgün, H. Şebnem; Soydan, Hilal; Jin, GeThe availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is -19 mm/yr with an average value of -6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.
