Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - Scopus: 1PCB Component Recognition With Semi-Supervised Image Clustering(IEEE, 2021-06-09) Unal, Ahmet Emin; Tasdemir, Kasim; Bahcebasi, AkifClassification of surface mounted devices plays an important role on automated inspection systems of printed component board production. Limited number of publicly available datasets which the components are labeled and high intraclass variance in these datasets causes the supervised approches to be inefficient. In this study a deep learning method, enhanced with an unsupervised clustering system, which uses a small set of labeled data is proposed. The method compared with the current studies and the supervised systems. Most optimized setting reached high accuracy results by outrunning current classification methods.Conference Object Graph-Based Biomedical Knowledge Discovery(IEEE, 2024-05-15) Altuner, Osman; Bakir-Gungor, Burcu; Bakal, GokhanThe digitalization process is progressing at a very high speed all over the world. While this situation provides many conveniences in today's life, it also brings along a problem such as analyzing and processing the huge digital data. This also applies to published academic studies. In this sense, the process of evaluating each study to access previously unknown information within the studies requires a very laborious process. For this reason, in this study, the publications obtained for the target diseases were analyzed by text analysis processes and converted into a graph structure that enables the linking of meaningful terms through biomedical relationships. On the dense graph structure obtained, binary biomedical entities with important links such as treats, causes, associated_with were queried. The entity pairs obtained according to the query results were also confirmed by manual search method and proved to be real connections. In this study, retrieval of known biomedical entities with the proposed approach solved the time-consuming manual search problem. There is also the potential to obtain unknown/unexplored possible new relationships (e.g., therapeutic, causal, etc.) with multiple binary linking patterns.Conference Object Citation - WoS: 6Citation - Scopus: 14Autonomous UAV Navigation via Deep Reinforcement Learning Using PPO(IEEE, 2022-05-15) Kabas, BilalIn 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*.Article Citation - Scopus: 2Vs (30) Tabanlı Yerel Zemin Koşulları Ve Deprem Hasar İlişkisi: Van-Abdurrahmangazi Örneği(TMMOB Chamber of Geological Engineers, 2021-12-31) Aykaç, Zeynep; Akin, Muge K.; Çabalar, Ali FiratIn order to minimize the disaster risk caused by earthquakes, not only province and district-based studies, but also studies covering small areas such as neighborhoods and villages should be carried out. In this study, Abdurrahmangazi Neighborhood, one of the districts that was severely damaged by two earthquakes that took place on 23 October and 09 November 2011 in the province of Van, was examined. The building conditions and the ground conditions in the study area where the quarter is located have been considered together. Shear wave velocity (V<inf>s</inf>) was used to determine the dynamic behavior of soils. The borehole data obtained in the study area were evaluated and the shear wave velocities were determined by using 5 different empirical relations developed by some researchers for the relationship between SPT-N and V<inf>s</inf> . Using these, V<inf>S(30)</inf> values were determined and ground classifications were made according to the National Earthquake Hazard Reduction Program (NEHRP-2000), EUROCODE-8, the Regulation on Buildings to be Built in Earthquake Zones (DBYBHY-2007). In addition, the new earthquake regulations is Turkey Earthquake Building Regulations (TBDY-2018) were also considered. The building damage conditions and the ground conditions in the area where the quarter is located were evaluated together. It was determined that the building damages after earthquakes were caused by structural deficiencies and building quality for this neighborhood, regardless of the ground conditions, and damage distributions were interpreted accordingly. © 2022 Elsevier B.V., All rights reserved.Conference Object Akciğer Tümörlü Hastaların PET ve BT Görüntülerinin Çakıştırılıp Birleştirilmesi(IEEE, 2015-10) Ayyildiz, Oguzhan; Yilmaz, Bulent; Karacavus, Seyhan; Kayaalti, Omer; Icer, Semra; Eset, Kubra; Kaya, EserImage 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.Conference Object Population Specific Classification of Colorectal Cancer With Meta-Analysis of Metagenomic Data(Institute of Electrical and Electronics Engineers Inc., 2023-10-11) Temiz, Mustafa; Yousef, Malik; Bakir-Güngör, BurcuAdvances in next-generation sequencing and '-omics' technologies makes it possible to characterize the human gut microbiome. While some of these microorganisms are important regulators of our immune system, modulation of the microbiota leads to a variety of diseases. Colorectal cancer (CRC), the third most common cancer worldwide, is caused by genetic mutations, environmental conditions, and abnormalities in the gut microbiota. Using various machine learning methods and meta-analysis techniques, this study aims to build a classification model that can help in CRC diagnosis by analyzing metagenomic datasets of different populations obtained at the species level. Using 8 different countries and 9 different metagenomic datasets, 3 different meta-analyzes are performed: within-population, cross-population, and one population is selected for testing and the rest is used as a training dataset (LODO). For CRC classification, 4 different classification algorithms (Random Forest (RF), Logitboost, Adaboost, and Decision Tree (DT)) are used. The best performance among these methods was obtained with the Random Forest algorithm with an AUC of 0.98 by using JP for the training data set and JPN populations for the test data set in the cross-population performance evaluation. © 2023 Elsevier B.V., All rights reserved.Article Gazlaştırma Tesisi Odun Atığı ve Sivas Kangal Linyit Kömürünün Boya Adsorpsiyonunda Kullanım Olanaklarının Araştırılması(Chamber of Mining Engineers of Turkey, 2020-12-01) Kırma, Ramazan; Sarikaya, Musa; Top, S.; Uçkun, Şükrü; Timür, İrfanIn this study, the usage possibilities of wood waste obtained from Gebze MDF and Particle Board Gasification Plant preliminary studies and Sivas Kangal lignite coal as absorbents were investigated. In this way, it was aimed both to evaluate the wastes and to prevent environmental pollution with materials that are cheaper and easier to obtain. The structure and surface properties of wood waste and coal samples crushed and ground to -75 µm size and used as adsorbent were investigated by XRD, SEM and BET analyses. In addition, samples have been characterized by elemental, ash, moisture, volatile matter and fixed carbon analyses. In the experiments, methylene blue (MM) with the formulation of C<inf>16</inf>H<inf>18</inf>CIN<inf>3</inf>S.xH<inf>2</inf>O was used. The effects of temperature, mixing time and concentration parameters on MM adsorption were investigated. Langmuir isotherms were created for different temperatures at optimum concentrations. As a result, it has been revealed that lignite coal and wood waste can be used as adsorbent. A 10 ppm MM for lignite coal and 3 ppm MM for wood waste were determined to be ideal concentrations for adsorption. © 2022 Elsevier B.V., All rights reserved.Conference Object MRD Biyoçip İçin Görüntü İşleme Temelli Sinyal Elde Etme Metodu(IEEE, 2019-04) Uslu, Fatma; Icoz, Kutay; Tasdemir, KasimThe response of the cancer patients to chemotherapy treatment varies from person to person. For some patients cancer cells are resistant to treatment and these cells can relapse again which is known as minimal residual disease. A microfluidic-based biochip capable of monitoring minimal residual disease is under development by our research group. The role of the biochip is to capture the target cells, which were separated by immunomagnetic beads on micro square tiles. Then biochips are imaged using a bright field optical microscope and it is planned to perform image-processing methods to detect the target cells, immunomagnetic beads and micro tiles. In this work the current progress of image processing methods for differentiating the immunomagnetic beads and micro tiles is presented.Article Atatürk’ün Esir Aldığı Yunan General Nikolaos Trikupis ve Talas Üsera Garnizonu(Sabit Dokuyan, 2023-06-26) Karataş, Murat; Metin, MehmetAfter the First World War, especially with the support of England, the Greek army invaded Anatolian lands on the way to realize Megali Idea (Greater Greece). The regular army of the Turkish Grand National Assembly established on the Western Front dealt the final blow to the Greek army with The Great Offensive and the Battle of the Commander –in-Chief. In addition to the Greek soldiers captured in the wars before this victory, many Greek soldiers, as well as the commander –in-chief of the Greek army, General Trikupis, and her entourage were also captured after the said victory. As the number of prisoners increased rapidly after The Great Offensive and the Battle of the Commander –in-Chief, the captive officers were transferred to Afyon, Kırşehir and Kayseri. Other military and civilian prisoners were transferred to different parts of Anatolia. Greek prisoners of war were kept in the prisoner garrisons until the implementation of the document on the mutual release of prisoners signed between the states of Turkey and Greece at the Lausanne Peace Conference. Only Greek Officers remained in Talas Prisoner Garrison, one of these prisoner garrisons. The Talas Prisoner Garrison was inspected twice by international Committee of the Red Cross. The delegation prepared reports on the condition of the prisoners and the garrison. In this study, the captivity of General Trikupis on the battlefield, the Talas Prisoner Garrison and situation of the captive Greek officers staying here, the aid of the Red Crescent Society to the prisoners will be emphasized. The Study was planned to be prepared by making use archival resources, memoirs, newspapers and copyright-reviewed works. © 2023 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 3İki Durumlu Bir Beyin Bilgisayar Arayüzünde Özellik Çıkarımı ve Sınıflandırma(Institute of Electrical and Electronics Engineers Inc., 2016-10) Altindis, Fatih; Yilmaz, BulentBrain Computer Interface (BCI) technology is used to help patients who do not have control over motor neurons such as ALS or paralyzed patients, to communicate with outer world. This work aims to classify motor imageries using real-time EEG dataset, which was published by Graz University, Austria. The dataset consists of two-channel EEG signals of right-hand movement imagery and left-hand movement imagery of 8 subjects. There are a total of 120 motor imagery trials (60 left and 60 right) EEG signals recorded from each subject. EEG signals are filtered and feature vectors were extracted that consist of 24, 32 and 40 relative band power values (RBPV). In this work, feature vectors classified by three different methods, linear discriminant analysis (LDA), K nearest neighbor (KNN) and support vector machines (SVM). Results show that best performance was achieved by 24 RBPV feature vector and LDA classification method. © 2017 Elsevier B.V., All rights reserved.
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