WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Now showing 1 - 10 of 90
  • Conference Object
    Speckle Intensity Correlation Distribution Analysis Based on Coincidence Detection for Scattering Medium Characterization
    (IEEE, 2025) Yoldas, Cansu; Kisa, Alperen; Atac, Enes; Karatay, Anil; Dinleyici, Mehmet Salih
    Characterizing a scattering medium is essential for understanding and controlling light propagation, enabling accurate imaging, correlation analysis, and material diagnostics in scientific applications. In this study, the scattering medium has been characterized by examining the spatial distribution of the second-order temporal correlation function of varying speckle patterns obtained under faint-light conditions using a charge-coupled device (CCD) camera. In the proposed method, the exposure time has been utilized as a self-coincidence circuit of the CCD. The spatial statistics of second-order temporal autocorrelation values have been analyzed through power spectral density and radial spatial autocorrelation function. The scattering degree of the medium has been determined using our proposed autocorrelation-based metric. The results from three different media have shown that the method is effective and holds potential for applications such as characterization through speckle imaging.
  • Conference Object
    Citation - WoS: 13
    Automatic HTML Code Generation from Mock-Up Images Using Machine Learning Techniques
    (IEEE, 2019) Asiroglu, Batuhan; Mate, Busra Rumeysa; Yildiz, Eyyup; Nalcakan, Yagiz; Sezen, Alper; Dagtekin, Mustafa; Ensari, Tolga
    The design cycle for a web site starts with creating mock-ups for individual web pages either by hand or using graphic design and specialized mock-up creation tools. The mock-up is then converted into structured HTML or similar markup code by software engineers. This process is usually repeated many more times until the desired template is created. In this study, our aim is to automate the code generation process from hand-drawn mock-ups. Hand drawn mock-ups are processed using computer vision techniques and subsequently some deep learning methods are used to implement the proposed system. Our system achieves 96% method accuracy and 73% validation accuracy.
  • Conference Object
    Outage and Intercept Performance in THz LEO-Ground Communication With Satellite Selection
    (IEEE, 2025) Bakirci, Emre Berker; Ahrazoglu, Evla Safahan; Altunbas, Ibrahim; Erdogan, Eylem
    Satellite communication and THz communication systems are some of the methods that aim to meet the demand of increasing data rates. With an importance growing alongside increasing data amounts, data security is on its way to a position that cannot be neglected when building systems. In this study, it has been shown that secure data transmission can be made possible through the use of THz frequencies in a link between LEO satellites and a ground station. Proposed scenarios data transmission performance have been analyzed. It has been shown that selection transmission have improved both data transmission and security performances.
  • Conference Object
    Performance Evaluation of Filter-Based Gene Selection Methods in Cancer Classification
    (IEEE, 2025) Gokalp, Osman
    With the advances in microarray technology, gene expression levels can be measured efficiently, and this data can be used to solve important problems such as cancer classification. However, microarray data suffers from the high-dimensionality problem and requires dimensionality reduction techniques such as feature selection. This study addresses the cancer classification problem using microarray datasets and comparatively evaluates the performance of different filter-based gene (feature) selection methods. To this end, 11 microarray datasets have been evaluated using 6 different filter methods, and experimental results are presented. According to the findings, the gene selection methods used can improve classification performance by 5% to 30%. Using 5-fold cross-validation, the highest accuracy rates were achieved with 32 genes selected by the gain ratio filter for the Breast and Colon datasets, and with 8 genes selected by the information gain filter for the CNS dataset.
  • Conference Object
    Df-Segdiff: Adiffusion Segmentation Model Using a New Distributed Parallel Computing Algorithm
    (IEEE, 2024) Mi, Hancang; Gan, Hong-Seng; Wang, Xiaoyi; Shimizu, Akinobu; Ramlee, Muhammad Hanif; Unlu, Mehmet Zubeyir
    Brain tumours are among the most life-threatening diseases, and automatic segmentation of brain tumours from medical images is crucial for clinicians to identify and quantify tumour regions with high precision. While traditional segmentation models have laid the groundwork, diffusion models have since been developed to better manage complex medical data. However, diffusion models often face challenges related to insufficient parallel computing power and inefficient GPU utilization. To address these issues, we propose the DF-SegDiff model, which includes diffusion segmentation, parallel data processing, a distributed training model, a dynamic balancing parameter and model fusion. This approach significantly reduces training time while achieving an average Dice score of 0.87, with several samples reaching Dice values close to 0.94. By combining BRATS2020 with the Medical Segmentation Decathlon dataset, we also integrated a comprehensive dataset containing 800 training samples and 53 test samples. Evaluation of the model using Dice, IoU, and other relevant metrics demonstrates that our method outperforms current state-of-the-art techniques.
  • Conference Object
    Outage and Ser Analyses for Dual-Hop Inter-Satellite Thz Communication
    (IEEE, 2024) Ahrazoglu, Evla Safahan; Erdogan, Eylem; Altunbas, Ibrahim
    Inter-satellite links have crucial significance in offering global connectivity and low latency in satellite mega-constellations. In such architectures, system capacity and data-rate can be enhanced by utilizing terahertz (THz) frequencies. Considering the importance of inter-satellite links in mega-constellations and the mounting interest in THz communications, in this study, an inter-satellite THz communication system is examined. In this setup, a low earth orbit (LEO) satellite is deployed to assist transmission between two LEO satellites by using variable-gain amplify-and-forward relaying protocol. The system's performance is analyzed in terms of both outage probability and symbol error rate, and asymptotic outage characteristic is explored. All theoretical findings are verified by Monte-Carlo simulations.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Robust and Energy-Efficient Hardware Architectures for Dizy Stream Cipher
    (IEEE, 2024) Schmid, Martin; Arul, Tolga; Kavun, Elif Bilge; Regazzoni, Francesco; Kara, Orhun
    In the era of ubiquitous computing, efficient and secure implementations of cryptographic hardware are crucial. This paper extends the hardware implementations of a Small Internal State Stream (SISS) cipher, namely DIZY. Previous work shows that DIZY's hardware performance, in terms of area cost and power consumption, is among the best when compared to notable stream ciphers, especially for frame-based encryptions requiring frequent initialization. In this study, we initially optimize the existing hardware implementation and then evaluate the energy efficiency of DIZY. We implement different unrolled versions of DIZY and analyze their energy consumption. Furthermore, we address physical security by integrating masking techniques into the DIZY S-box to protect the implementation against side-channel attacks. We thoroughly investigate the associated overhead and apply optimizations to reduce it, ensuring robust security without compromising efficiency. Our results present a secure, energy-efficient, and lightweight cryptographic hardware design for the stream cipher DIZY, making it suitable for various applications, including Internet of Things (IoT) and embedded systems.
  • Conference Object
    Development of Low-Cost Portable Blood Vessel Imaging System
    (IEEE, 2021) Altay, Ayse; Gumus, Abdurrahman
    As an alternative to high-cost near-infrared (NIR) vascular imaging devices in the market [1], a microcomputerbased, real-time, low-cost, non-contact and safe vascular imaging system has been developed. The higher absorption coefficient of blood from skin and fat, as well as the differences in oxy and deoxyhemoglobin spectra in blood, were helpful factors in the use of the NIR region during the acquisition of vessel images. A device, which uses NIR LED light operated at 850 nm, was designed using optical and electronic components. Image analysis were performed using OpenCV, which is an open-source software library, and data visualization libraries. Tests were carried out to optimize the best imaging conditions for the device. In this study, a portable device design with improved vessel image quality is presented which could potentially be used to assist the health professionals to investigate the abnormalities in the superficial vascular structures at different times during patients' treatments.
  • Conference Object
    Citation - Scopus: 1
    Colorimetric Detection of Creatinine on an Electromechanical Mixing Platform
    (IEEE, 2021) Tarim, E. Alperay; Oksuz, Cemre; Karakuzu, Betul; Tekin, H. Cumhur
    We present an electromechanical mixing platform integrated with a smartphone for colorimetric detection of creatinine using an enzymatic reaction between horseradish peroxidase (HRP) and 3,3',5,5'-Tetramethylbenzidine (TMB). On the developed platform, the color resulting from the reaction between HRP and TMB in a reservoir of a poly(methyl methacrylate) (PMMA) chip is measured using a smartphone camera. With mixing, diluted creatine solutions can be detected in 1 min that can reduce long waiting times of creatinine detection due to enzymatic reactions. Furthermore, smartphone-based colorimetric detection reduces the cost of analysis by eliminating costly equipment for spectrometric measurements without affecting the sensitivity of analysis. We, therefore, think that the presented platform integrated with a smartphone could be used for automatic measurement of creatinine level in the sample by allowing low-cost and rapid analysis, and this would be particularly beneficial for monitoring of chronic kidney disease (CKD) at the point-of-care setting.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    A Metric for Measuring Test Input Generation Effectiveness of Test Generation Methods for Boolean Expressions
    (IEEE, 2021) Ufuktepe, Deniz Kavzak; Ufuktepe, Ekincan; Ayav, Tolga
    The literature includes several methods to generate test inputs for Boolean expressions. The effectiveness of those methods needs to be analyzed by extensive comparisons. To this end, mutation analysis is often benefited by applying a distinctively selected set of mutants on each test generation method. Mutation analysis provides substantive information about the effectiveness of a test suite by indicating the percentage of killed mutants, which is a common metric. However, as we claim and show in this paper, this metric alone is not sufficient to demonstrate the effectiveness of the methods. For a test generation method, the amount of generated test inputs is also an important attribute to evaluate effectiveness. To the best of our knowledge, there is no metric that measures the effectiveness within a scale taking into account several attributes. In this study, we propose a new metric to measure the effectiveness of test input generation methods, which takes into account both the number of killed mutants and the number of test inputs. We demonstrate our new metric on three well-known test input generation methods for Boolean expressions.