WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Start date: 2021Language: search.filters.language.tr

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Now showing 1 - 9 of 9
  • Conference Object
    High Performance and Resource Efficient Low Density Parity Check Decoder Design
    (IEEE, 2025-06-25) Unal, Burak
    Low Density Parity Check (LDPC) codes have gained popularity in communication systems due to their capacity-approaching error correction performance. In this study, a highperformance LDPC decoding algorithm with extremely low resource usage is proposed. Among the hard decision class of LDPC decoders, Gallager B (GaB) provides high-performance hardware due to its computational simplicity. However, GaB suffers from poor error-correction performance. In this study, a new intrinsic computation technique for GaB called Intrinsic Gallager B (IGaB) is introduced to improve error correction performance. Our simulation results show that the IGaB algorithm provides better error correction performance compared with GaB. GaB and IGaB algorithms are implemented on Field Programmable Gate Array (FPGA) to compare hardware performance.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 2
    Fine Tuning DeepSeek and Llama Large Language Models with LoRA
    (IEEE, 2025-06-25) Uluirmak, Bugra Alperen; Kurban, Rifat
    In this paper, Low-Rank Adaptation (LoRA) finetuning of two different large language models (DeepSeek R1 Distill 8B and Llama3.1 8B) was performed using the Turkish dataset. Training was performed on Google Colab using A100 40 GB GPU, while the testing phase was carried out on Runpod using L4 24 GB GPU. The 64.6 thousand row dataset was transformed into question-answer pairs from the fields of agriculture, education, law and sustainability. In the testing phase, 40 test questions were asked for each model via Ollama web UI and the results were supported with graphs and detailed tables. It was observed that the performance of the existing language models improved with the fine-tuning method.
  • Article
    Tax Compliance Behaviour and Lab Experiments: A Literature Review
    (Maliye Bakanligi, 2021) Demirtas, Burak Kagan
    The purpose of this article is to conduct a literature review of the papers based on laboratory experiments to analyze tax evasion behaviors of individuals. Although experimental studies in economics have become more and more important day by day, there are almost no publications on experimental economics in the Turkish literature. The studies are examined especially in terms of experimental designs because this study also aims to increase awareness about laboratory experiments. This review also discusses the criticism of laboratory experiments and concludes that the results obtained from laboratory experiments are important and it would be beneficial to support them with field experiments.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Prediction of Type 2 Diabetes Using Metagenomic Data and Identification of Taxonomic Biomarkers
    (IEEE, 2024-05-15) Temiz, Mustafa; Kuzudisli, Cihan; Yousef, Malik; Bakir-Gungor, Burcu
    Nowadays, different molecular levels of -omics data on diseases are generated and analyzing these data with machine learning methods is one of the popular research topics. Among these data, the use of metagenomic data to facilitate the diagnosis, detection and treatment of diseases is increasing day by day. Type 2 diabetes (T2D) is a chronic disease characterized by insulin resistance and progressive dysfunction of pancreatic beta cells. While the number of people with diabetes is increasing by around 8% annually, the cost of treating the disease is rising by 18% per year. Therefore, the number of studies on the diagnosis, development and progression of T2D is increasing over time. The aim of this study is to achieve higher machine learning performance by using fewer metagenomic features and to achieve better classification performance by reducing computational costs. In this study, we compare the performance of three different methods using T2D-related metagenomic data. First, the MetaPhlAn tool is used to calculate the taxonomic species and their relative abundances in each sample. The SVM-RCE, RCE-IFE and microBiomeGSM tools used in this study are methods that perform classification by grouping and scoring features and are known to work well on complex datasets. In this study, the best results were obtained with the RCE-IFE tool with an AUC of 0.72 with an average of 125 features information. In addition, key taxonomic species identified by these tools as associated with T2D are presented in comparison to the literature.
  • Conference Object
    Citation - Scopus: 1
    PCB Component Recognition With Semi-Supervised Image Clustering
    (IEEE, 2021-06-09) Unal, Ahmet Emin; Tasdemir, Kasim; Bahcebasi, Akif
    Classification 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, Gokhan
    The 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: 6
    Citation - Scopus: 14
    Autonomous UAV Navigation via Deep Reinforcement Learning Using PPO
    (IEEE, 2022-05-15) Kabas, Bilal
    In 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
    3D Sampling of K-Space With Non-Cartesian Trajectories in MR Imaging
    (Gazi Univ, Fac Engineering Architecture, 2025-02-03) Dundar, Mehmet Sait; Gumus, Kazim Z.; Yilmaz, Bulent
    This study presents an innovative approach to 3D k-space sampling in MR imaging using non-Cartesian concentric shell trajectories. The method involves 32 concentric shells of varying radii, allowing for rapid data acquisition through undersampling techniques. Simulations using IDEA software demonstrate that this approach can fill the k-space in less than one second, a significant time reduction compared to traditional FLASH sequences that can take 3-4 minutes. The concentric shell model enhances imaging efficiency by minimizing artifacts and ensuring uniform k-space filling, leading to higher resolution and faster scans. This technique shows promise for clinical applications, particularly in dynamic imaging scenarios such as acute stroke and pediatric radiology, where speed and precision are critical. As illustrated in Figure A, the concentric shell trajectories enable uniform k-space filling, significantly reducing scan times and improving image quality. These results are based on the simulations conducted with IDEA software.
  • Article
    An Opportunity for Nuri Demirağ the National Development Party the Transition to Multiparty Life in Turkey
    (Osman Kose, 2023) Karatas, Murat; Solak, Yeter
    The political life in Turkey during the period of 1923-1945 showed a single-party characteristic. Turkey, which did not enter the Second World War in 1939-1945, faced some negativities brought by the war both during and after the war. These negativities have had a compelling effect on the government to switch to a multi-party system with the effect of external and internal factors. Nuri Demira & gbreve; founded the National Development Party while he was preparing to take a step towards a multiparty system in Turkey, forced by both domestic and foreign conditions. Although the party could not show an active presence in our political life, its establishment made an important contribution to the establishment of democracy culture and the Despite all the efforts of Nuri Demira & gbreve; as the founder and chairman of the party, the inconsistency in the party and the evaluation of party activities from the wrong points led to the party's indifference in political life. In 1957, the existence of the National Development Party in our political life came to an end quietly due to the fact that the party committee could not convene after the death of the party chairman, Nuri Demira & gbreve;.In this sense, our study aims to contribute to the literature by aiming to discuss the political adventure of the National Development Party, which stands at an important point in terms of the democratization process in our political life, and to reveal the role of its founder, Nuri Demirag, in this process.