Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Now showing 1 - 10 of 49
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Oscillator Phase Noise Impact on Monostatic/Bistatic Space-Borne Sub-THz ISAR
    (IEEE, 2025-05-21) Bekari, Ali; Gashinova, Marina; Bekar, Muge; Martorellai, Marco; Antonioni, Michail; Bekar, Ali; Martorella, Marco; Antoniou, Michail
    This study develops an oscillator phase noise model and analyzes its effects on the performance of spaceborne monostatic and bistatic Inverse Synthetic Aperture Radar (B-ISAR) systems operating at the sub-THz band. The B-ISAR study is of current importance as it can provide a basis for distributed space-based ISAR to enable persistent co-operative space domain awareness (Co-SDA).
  • Conference Object
    Enhancing Complex Disease Group Scoring with Mirgedinet: A Multi-Algorithm Machine Learning Framework Based on the GSM Approach
    (IEEE, 2025-06-25) Qumsiyeh, Emma; Bakir-Gungor, Burcu; Yousef, Malik
    Integrating biological prior knowledge for disease gene associations has shown significant promise in discovering new biomarkers with potential translational applications. This work investigates the application of a multi-algorithm machine learning framework based on the Grouping-Scoring-Modeling (G-S-M) approach for improving the prediction of complex diseases. The study identifies the primary gene and miRNA interactions in various complex diseases with the help of miRGediNET, which is a machine-learning based tool that integrates data from three biological databases. Traditional methods have only focused on independence between features; the G-S-M method focuses on aggregating genes based on biological interactions, pinpointing the scoring of gene groups for a disease, and modeling its predictive capability using advanced machine learning algorithms. In this research paper, seven algorithms, including Support Vector Machine, Decision Tree, and CatBoost, were applied to eight datasets extracted from the GEO database. This framework proved very robust in ranking gene clusters, thus predicting critical biomarkers while doing 100-fold randomized cross-validation within the evaluation. The results indicate this approach's high potential for refining disease and supporting research for choosing the best algorithm that can provide biological insights and computational advances.
  • Conference Object
    Exploring Microbiome Signatures in Autism Spectrum Disorder via Grouping-Scoring Based Machine Learning
    (IEEE, 2025-06-25) Temiz, Mustafa; Ersoz, Nur Sebnem; Yousef, Malik; Bakir-Gungor, Burcu
    The rapid increase in omic data production increased the importance of machine learning (ML) methods to analze these data. In particular, the use of metagenomic data in the diagnosis, prognosis and treatment of diseases is becoming widespread. Autism Spectrum Disorder (ASD) is a neurodevelopmental disease that occurs in early childhood and continues lifelong. The aim of this study is to increase ML performance, reduce computational costs and achieve successful classification performance using a small number of metagenomic features. In addition, disease prediction is performed; ASD associated biomarkers are determined using the microBiomeGSM on metagenomic data. Classification is performed at three different taxonomic levels (genus, family and order) using the relative abundance values of species. The best performance metric (0.95 AUC) was obtained at the order taxonomic level using an average of 416 features with microBiomeGSM. The identified ASD-related taxonomic species are presented.
  • Conference Object
    Symmetric Electret-Based Vibration Energy Harvesters With Curved-Beam Hinges
    (IEEE, 2023-05-28) Hah, Dooyoung
    Broadband power spectral characteristics are desirable in vibration energy harvesters, and it can be achieved by employing curved-beam hinges, which exhibit force-displacement nonlinearity. Via numerical analysis by using stochastic differential equations and colored-noise inputs, this study shows that a symmetric configuration of the curved-beam hinges in electret-based harvesters can produce higher (up to 8% more) power outputs than an asymmetric one. It also presents that the harvesters with curved-beam hinges can produce higher (up to 4.4 times) power outputs than those with straight hinges when the vibration magnitude is 0.05g.
  • Conference Object
    Structural Integrity Analysis of a Two-Pole Synchronous Reluctance Machine With Non-Circular Shaft
    (IEEE, 2023-06-14) Tekgun, Didem; Tekgun, Burak; Alan, Irfan
    This paper investigates the structural strength of a 6-inch diameter, two-pole, 4 kW line start synchronous reluctance machine (LS-SynRM) designed with a new non-circular shaft structure that serves as a pump motor. Flux paths on the rotor are widened while narrowing down the shaft of the motor on the q- axis to improve the motor efficiency. By using this method, a wider path is created for the flux in the d-axis. As a result, the inductance in the d-axis, the ratio of inductance between the d-axis and q-axis (referred to as saliency ratio), and the difference in inductance between the d-axis and q-axis are all amplified. To evaluate the structural strength of the machine, a series of analyses are conducted, including modal, harmonic, and static examination on the rotor using ANSYS Structural. The findings indicate that to prevent redundant deformations and undesirable vibrations because of resonance, the maximum safe limit for shaft size reduction is determined as 8 mm.
  • Conference Object
    Citation - WoS: 30
    Citation - Scopus: 38
    Software Defined Communication Framework for Smart Grid to Meet Energy Demands in Smart Cities
    (IEEE, 2019-04) Faheem, Muhammad; Umar, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Ngadi, Md. Asri; Gungor, Vehbi Cagri
    In smart cities, the electricity is an essential component since it preserves a certain level of residents' life quality and provisions the entire spectrum of their economic activities. Thus, a smart way is essential to develop cities without disregarding energy issues. In this scope, the smart grid paradigm offers power supply in an efficient, sustainable and economical manner with minimal impact on the environment and can meet the future energy demands. However, real-time monitoring and control of the smart grid (SG) for continuous and quality-aware power supply in smart cities (SCs) is challenging and requires an advanced quality of service (QoS)-aware communication framework. In this context, this research aims to present a novel data-gathering scheme by using the Internet of software-defined mobile sinks (SDMSs) and wireless sensor networks (WSNs) in the smart grid. The extensive simulation results conducted through the EstiNet9.0 indicate that the designed scheme outperforms existing approaches and achieves its defined goals for events-drive applications in the SG.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 6
    Single and Double Side Comb-Shaped Patch Antenna Design Evolved From Rectangular Shape for Reduced Sized Antenna Applications
    (IEEE, 2020-11-18) Baydar, Huseyin; Aslan, Melih; Kilic, Veli Tayfun
    This paper reports single and double side comb-shaped patch antennas to be used in reduced-sized antenna applications. The proposed antenna designs are evolved from regular rectangular shape antennas. The designed single and double side comb-shaped antennas were investigated in a complete set of study together with the rectangular shape antenna that resonates at 5 GHz frequency. Reflection coefficient (S-11) parameter of the designed comb-shaped antennas and the rectangular antenna were calculated together with three-dimensional (3D) directivity patterns in simulations for different arm lengths, arm widths, and arm numbers of the comb-shaped antennas. Results show that with the comb-shaped antennas it is possible to shift the resonance frequency of a regular rectangular shape antenna to a frequency lower than its half without enlarging the foot-print area or with the smaller foot-print area. Also, resonance frequency change and peak directivity variations at resonance frequencies of the antennas with geometrical parameters of the antennas were calculated, too. The findings indicate that due to the large number of geometrical parameters that come with the nature of the comb shape, comb-shaped antennas provide more flexibility while constructing an antenna.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Sensorless Position and Speed Control of IPMSM With Sliding Mode Observer and Voltage Signal Injection
    (IEEE, 2021) Ates, Ertugrul; Tekgun, Burak; Ablay, Gunyaz
    A sensorless control approach based on a sliding mode observer for predicting the rotor position and speed is studied in this work. For predicting the motor speed and position, the sliding mode observer followed by a phase locked loop is formulated by means of the back EMF model. The voltage signal injection method is utilized for accurate estimation in zero or low speed region. Numerical simulation results are provided for an 8-pole IPMSM, which shows that the motor speed and position in zero or low-speed region are accurately estimated with the designed observer and voltage signal injection approach.
  • Conference Object
    Range-Based Wireless Sensor Network Localization by a Circumnavigating Mobile Anchor Without Position Information
    (IEEE, 2024-06-11) Guler, Samet
    Typical range-based wireless sensor network (WSN) localization approaches aim at estimating the sensor node positions by using a set of anchors with known positions. In some applications, assuming the knowledge of the anchors' positions may be impractical, and estimation of the sensors' positions in an arbitrary fixed frame may be sufficient. Considering such scenarios, we propose a WSN localization algorithm by single mobile anchor without self location information. The mobile anchor obtains distance measurements from the sensors while tracking a custom trajectory which is shown to improve the localization performance over time for high signal-to-noise ratio cases. By utilizing two stationary reference nodes within the WSN, the proposed framework generates sensor node position estimation up to translation and rotation with sufficient precision in the absence of global positioning aids. We foresee that the proposed framework can demonstrate benefits in several WSN applications ranging from internet-of-things to service robotics.
  • Conference Object
    Citation - WoS: 11
    Citation - Scopus: 20
    ROI Detection in Mammogram Images Using Wavelet-Based Haralick and Hog Features
    (IEEE, 2018-12) Tasdemir, Sena Busra Yengec; Tasdemir, Kasim; Aydin, Zafer; Yengec Tasdemir, Sena Busra
    Digital mammography is a widespread medical imaging technique that is used for early detection and diagnosis of breast cancer. Detecting the region of interest (ROI) helps to locate the abnormal areas, which may be analyzed further by a radiologist or a CAD system. In this paper, a new classification method is proposed for ROI detection in mammography images. Features are extracted using Wavelet transform, Haralick and HOG descriptors. To reduce the number of dimensions and eliminate irrelevant features, a wrapper-based feature selection method is implemented. Several feature extraction methods and machine learning classifiers are compared by performing a leave-one-image-out cross-validation experiment on a difficult dataset. The proposed feature extraction method provides the best accuracy of 87.5% and the second-best area under curve (AUC) score of 84% when employed in a random forest classifier.