Yönetim Bilişim Sistemleri Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/68

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Citation - WoS: 12
Citation - Scopus: 13
Assessment of Chromite Liberation Spectrum on Microscopic Images by Means of a Supervised Image Classification
(Elsevier Science Bv, 2017) Camalan, Mahmut; Çavur, Mahmut; Hosten, Cetin
Assessment of mineral liberation spectrum with all its aspects is essential for plant control and optimization. This paper aims to estimate 2D mineral map and its associated liberation spectrum of a particular chromite sample from optical micrographs by using Random Forest Classification a powerful machine-learning algorithm implemented on a user-friendly and an open-source software. This supervised classification method can be used to accurately generate 2D mineral map of this chromite sample. The variation of the measured spectra with the sample size is studied showing that images of 200 particles randomly selected from the optical micrographs are sufficient to reproduce liberation spectrum of this sample. In addition the 2D spectrum obtained with this classification method is compared with the one obtained from the Mineral Liberation Analyzer (MLA). Although 2D mineralogical compositions obtained by the two methods are quite similar microscopic analysis estimates poorer liberation than MLA due to the residual noise (misclassified gangue) generated by the classification. Nevertheless we cannot compare the reliabilities of the two methods as there is not a standard produce yet to quantify the accuracy of MLA analysis. (C) 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 5
Development of a Supervised Classification Method To Construct 2d Mineral Maps on Backscattered Electron Images
(Tubitak, 2020) Camalan, Mahmut; Çavur, Mahmut
The 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.
Citation - Scopus: 28
Land Use and Land Cover Classification of Sentinel 2-A: St Petersburg Case Study
(International Society for Photogrammetry and Remote Sensing, 2019) Çavur, Mahmut; Düzgün, Hafize Şebnem; Kemeç, Serkan; Demirkan, Doğa Çağdaş
Land use and land cover (LULC) maps in many areas have been used by companies, government offices, municipalities, and ministries. Accurate classification for LULC using remotely sensed data requires State of Art classification methods. The SNAP free software and ArcGIS Desktop were used for analysis and report. In this study, the optical Sentinel-2 images were used. In order to analyze the data, an object-oriented method was applied: Supported Vector Machines (SVM). An accuracy assessment is also applied to the classified results based on the ground truth points or known reference pixels. The overall classification accuracy of 83,64% with the kappa value of 0.802 was achieved using SVM. The study indicated that of SVM algorithms, the proposed framework on Sentinel-2 imagery results is satisfactory for LULC maps.
Citation - WoS: 1
Using 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, Mahmut
Areal 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.
Citation - WoS: 1
Yereraltı Maden İşçilerini Gerçek Zamanlı Takip Etmek İçin Rfıd Teknolojisine Dayalı Özgün Bir Entegrasyon Metodolojisi
(Gazi Universitesi, 2018) Çavur, Mahmut
In 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.

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