Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - Scopus: 2miRcorrNetPro: Unraveling Algorithmic Insights Through Cross-Validation in Multi-Omics Integration for Comprehensive Data Analysis(Institute of Electrical and Electronics Engineers Inc., 2023-12-05) Ünlü Yazici, Miray; Yousef, Malik; Marron, J. S.; Bakir-Güngör, Burcu; Yazici, Miray UnluHigh throughput -omics technologies facilitate the investigation of regulatory mechanisms of complex diseases. Along this line, scientists develop promising tools and methods to extend our understanding at the molecular and functional levels. To this end, miRcorrNet tool performs integrative analysis of MicroRNA (miRNA) and gene expression profiles via machine learning (ML) approach to identify significant miRNA groups and their associated target genes. In this study, we propose miRcorrNetPro tool, which extends miRcorrNet by tracking group scoring, ranking and other information through the cross-validation iterations. Heatmap visualizations enable deep novel insights into the collective behavior of clusters of groups in cellular signaling and hence facilitate detection of potential biomarkers for the disease under investigation. Although miRcorrNetPro is designed as a generic tool, here we present our findings and potential miRNA biomarkers for Breast Cancer (BRCA). The miRcorrNetPro tool and all other supplementary files are available at https://github.com/Miray-Unlu/miRcorrNetPro. © 2024 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 1Traffic Light Management Systems Using Reinforcement Learning(Institute of Electrical and Electronics Engineers Inc., 2022-09-07) Can, Sultan Kubra; Thahir, Adam Rizvi; Cos¸kun, Mustafa; Güngör, Vehbi Çağrı; Coskun, MustafaWhile reducing traffic congestion and decrease the number of traffic accidents in the intersections, most of the traffic light management approaches cannot adapt well to fast changing traffic dynamics and growing demands of the intersections with modern world developments. To overcome this problem, adaptive traffic controllers are developed, and detectors and sensors are added to systems to enable adoption and dynamism. Recently, reinforcement learning has shown its capability to learn the dynamics of complex environments, such as urban traffic. Although it was studied in single junction systems, one of the problems was the lack of consistency with how the real world system works. Most of the systems assume that the environment is fully observable or actions would be freely executed using simulators. This study aims to merge usefulness of reinforcement learning methods with real-world traffic constraints. Comparative performance evaluations show that the reinforcement learning algorithm (Advantage Actor-Critic (A2C)) converges well while staying stable under changing traffic dynamics. © 2022 Elsevier B.V., All rights reserved.Conference Object The Relationship Between TSH Levels, Maternal Characteristics and Racial Group of the Aneuploidy Screening(Institute of Electrical and Electronics Engineers Inc., 2022-09-07) Soylemez, Ummu Gülsüm; Kaymakçalan, Hande; Härkönen, Juho; Bakir-Güngör, Burcu; Celebiler, Hande KaymakcalanFirst-trimester maternal screening is a widely used test for detecting fetal aneuploidies and neural tube defects for over two decades. Human chorionic gonadotropin hormone (beta-hCG) and pregnancy-associated plasma protein A (PAPP-A) are two serum biomarkers that are analyzed in this screening. The thyroid hormone is a critical hormone for normal pregnancy and fetal development. During the first half of pregnancy, placental and fetal development depends on the thyroid hormone levels in the mother. Therefore, thyroid abnormalities in the mother can result in unfavorable pregnancy outcomes such as intrauterine growth restriction, miscarriage, hypertensive disorders, premature birth, and an increase in the risk of low IQ in the newborn. In this study, we analyzed the first-trimester screening data collected from 410 pregnant women who were seen at Yale University Hospital Prenatal Unit; and checked for possible correlations of TSH levels with maternal characteristics, racial group PAPP-A MoM levels. © 2022 Elsevier B.V., All rights reserved.Conference Object The Effect of Different Classifiers on Recursive Cluster Elimination in the Analysis of Transcriptomic Data(Institute of Electrical and Electronics Engineers Inc., 2023-10-11) Bulut, Nurten; Bakir-Güngör, Burcu; Qaqish, Bahjat F.; Yousef, MalikGene expression data with limited sample size and a large number of genes are frequently encountered in genetic studies. In such high-dimensional data, identification of genes that distinguish between disease states is a challenging task. Feature selection (FS) is a useful approach in dealing with high dimensionality. Support Vector Machines Recursive Cluster Elimination (SVM-RCE) is a technique for FS in high-dimensional data. The SVM-RCE approach has been utilized for identification of clusters of genes whose expression levels correlate with pathological state. A key step in SVM-RCE is the use of an SVM classifier to assign an area under the curve (AUC) score to each gene cluster based on its ability to predict class labels. In this study, we investigate the use of alternative classifiers in the cluster-scoring step. Specifically, we compare Support Vector Machines, Random Forest, XgBoost, Naive Bayes, and linear logistic regression. In addition to AUC score performance evaluation, the algorithms are compared in terms of the number of selected genes at different levels of clustering and in terms of the running time. © 2023 Elsevier B.V., All rights reserved.Article Citation - WoS: 40Citation - Scopus: 49Spatio-Temporal Rich Model-Based Video Steganalysis on Cross Sections of Motion Vector Planes(Institute of Electrical and Electronics Engineers Inc., 2016-07) Taşdemir, K.; Kurugöllü, F.; Sakir Sezer, S.; Sezer, SakirA rich model-based motion vector (MV) steganalysis benefiting from both temporal and spatial correlations of MVs is proposed in this paper. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this paper. First, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring MVs for longer distances. Therefore, temporal MV dependency alongside the spatial dependency is utilized for rigorous MV steganalysis. Second, unlike the filters previously used, which were heuristically designed against a specific MV steganography, a diverse set of many filters, which can capture aberrations introduced by various MV steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in the previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-Temporal range and provides a better cover model. The proposed method is tested against the most prominent MV steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in MV steganalysis field, including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads. © 2016 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 5Sliding Mode Control of a Switched Reluctance Motor Drive With Four-Switch Bi-Directional DC-DC Converter for Torque Ripple Minimization(Institute of Electrical and Electronics Engineers Inc., 2020-09) Ates, Ertugrul; Tekgun, Burak; Ablay, GünyazIn this paper, a method to drive switched reluctance motors (SRM) with a modular four-switch bidirectional DC-DC converter and an H-bridge is proposed. The DC-DC converter operates as a buck or a boost converter with constant frequency to control each phase current while the H-bridge inverter switches only twice in a period to adjust the polarity of the phase voltage. Sliding mode control is designed to have fast and robust current control in the DC-DC converter. The sliding surface equation which is derived for all operation modes including buck and boost modes in motoring and regenerating conditions is defined with the estimated inductor current. The proposed drive system eliminates the bulk DC-capacitors and allows one to adjust the bus voltage individually for all phases. Moreover, the proposed system topology works with only one high-frequency switching device in the DC-DC conversion stage rather than two in conventional drives which provides a simpler current control and reduced switching losses. © 2020 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 2Sliding Window and Filterbank Utilization on Riemannian Geometry(Institute of Electrical and Electronics Engineers Inc., 2022-08-08) Altindis, Fatih; Yilmaz, BulentRiemannian geometry-based signal processing approaches on EEG signals provides similar decoding performance compared to state-of-the-art methods. However, Riemannian geometry framework requires predefine EEG signal epoch that is to be used in the analysis. Sliding window approach that operates in Riemannian geometry proposed to enable use of EEG signals without constrained by the record length. Decoding performance of tangent space mapping was increased more than 6% in overall accuracy compared the previous study's results. Instead of using single band-pass filter, utilization of filterbank is proposed to increase decoding performance. Distance based Riemannian classifier's overall performance were increased by 5% compared to standard Riemannian geometry approach. © 2022 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 8Short Term Electricity Load Forecasting: A Case Study of Electric Utility Market in Turkey(Institute of Electrical and Electronics Engineers Inc., 2015-04) Ishik, Muhammed Yasin; Göze, Tolga; Ozcan, Ihsan; Güngör, Vehbi Çağrı; Aydin, Zafer; Yasin, MuhammedWith the recent developments in energy sector, the pricing of electricity is now governed by the spot market where a variety of market mechanisms are effective. After the new legislation of market liberalization in Turkey, competition-based on hourly price has received a growing interest in the energy market, which necessitated generators and electric utility companies to add new dimensions to their scope of operation: short-term load and price forecasting. The field has several opportunities though not free from challenges. The dynamic behavior of the market price has caused the electric load to become variable and non-stationary. Furthermore, the number of nodes, in which the load must be predicted, is not constant anymore and can no longer be estimated by experts alone. In this competitive scenario, statistical forecasting methods that can automatically and accurately process thousands of data samples are essential. The purpose of this study is to demonstrate the importance of short-term load forecasting, how it has received a growing interest in Turkey and to propose an artificial neural network that can forecast the short term electricity load. Through detailed performance evaluations, we demonstrate that our forecasting method is capable of predicting the hourly load accurately. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 10Security and Privacy Challenges, Solutions, and Open Issues in Smart Metering: A Review(Institute of Electrical and Electronics Engineers Inc., 2021-09-15) Win, Lae Lae; Tonyali, SametThe traditional power grid becomes ‘smart’ when it is combined with the communication and information technology. Along with smart grid, the traditional meter is replaced with smart meter. Smart meters play an important role in energy consumption reporting and, thereby, billing. Besides smart meters, the smart grid communication network is composed of heterogeneous devices that are communicating through public networks. Therefore, smart metering communications are susceptible to cyber-attacks and privacy breaches which are still under debating. This paper gives a brief overview of smart grid, smart metering, and the communication networks. Then, the privacy and security requirements of the smart grid network are derived. The various kind of cyber-attacks are discussed, after that, the different schemes and approaches that have been proposed in previous papers are reviewed. Lastly, the open issues on security and privacy of smart grid metering communications are highlighted. © 2022 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 3Citation - Scopus: 4Seamless Mobile Data Offloading in Heterogeneous Wireless Networks Based on IEEE 802.21 and User Experience(Institute of Electrical and Electronics Engineers Inc., 2014-04) Tüzünkan, Firat A.; Güngör, Vehbi Çağrı; Zeydan, Engin; Ileri, Ömer; Ergüt, SalihThe increase on smartphone usage has brought the burden of data traffic with it. Operators are looking for cost-effective solutions to overcome the problem of 3G infrastructure for high contention traffic scenarios. Several schemes were offered to save the moment, and they brought some extra costs including deploying femtocell or WiMax, LTE, LTE-Advanced systems along with their expensive equipment. On the other hand, operators are expanding their networks with 802.11 technologies such that they can exploit the free-band communication. Meaning the data traffic can handover between WLAN and UMTS interchangeably. By using NS-2 simulator, we implemented IEEE 802.21 WG's Media Independent Handover (MIH) module by combining with Channel Quality Indicator (CQI) values collected from user equipment (UE) and observed a recovered throughput for both medium. We found that there is a tradeoff among energy efficiency, delay tolerance and cost. Furthermore, in this study, we integrated a Quality of Experience (QoE) metric during real-time handover decision process so that with this type of collaborative solution, an operator will be unique in terms of user happiness and heterogeneous network management. © 2021 Elsevier B.V., All rights reserved.