TR-Dizin İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396

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3D Sampling of K-Space With Non-Cartesian Trajectories in MR Imaging
(Gazi Univ, Fac Engineering Architecture, 2025) Dundar, Mehmet Sait; Gumus, Kazim Z.; Yilmaz, Bulent; 01. Abdullah Gül University
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.
Citation - WoS: 4
Citation - Scopus: 4
All-Polymer Ultrasonic Transducer Design for an Intravascular Ultrasonography Application
(Tubitak Scientific & Technological Research Council Turkey, 2019) Hah, Dooyoung; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
Intravascular ultrasonography (IVUS), a medical imaging modality, is used to obtain cross-sectional views of blood vessels from inside. In IVUS, transducers are brought to the proximity of the imaging targets so that high-resolution images can be obtained at high frequency without much concern of signal attenuation. To eliminate mechanical rotation rendered in conventional IVUS, it is proposed to manufacture a transducer array on a flexible substrate and wrap it around a cylindrical frame. The transducer of consideration is a capacitive micromachined ultrasonic transducer (CMUT). The whole device needs to be made out of polymers to be able to endure a high degree of bending (radius: 1 mm) Bending of the devices leads to considerable changes in the device characteristics, including resonant frequency and pull-in voltage due to geometrical dimension changes and stress induced. The main purpose of this work is to understand the effect of bending on the device characteristics by means of finite element analysis. Another objective of the work is to understand the relationships between such an effect and the device geometries. It is learned that the bending-induced stress depends strongly on anchor width, membrane thickness, and substrate thickness. It is also learned that resonant frequency and pull-in voltage become lower in most cases because of using a flexible substrate in comparison to those of the device on a rigid substrate. Bending-induced stress increases the spring constant and hence increases resonant frequency and pull-in voltage, although this effect is relatively weaker. For most of the device geometries, pull-in voltage is too high for the polymer material to endure. This is the main drawback of the all-polymer CMUT. In order to meet the design goal of 20 MHz resonant frequency, the membrane radius has to be smaller than 7.7 mu m for a thickness of 3 mu m.
Citation - WoS: 2
Citation - Scopus: 2
Analysis of Optical Gyroscopes With Vertically Stacked Ring Resonators
(Tubitak Scientific & Technological Research Council Turkey, 2021) Hah, Dooyoung; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
Without any moving part, optical gyroscopes exhibit superior reliability and accuracy in comparison to mechanical sensors. Microring-resonator-based optical gyroscopes emerged as alternatives for bulky conventional Sagnac interferometer sensors, especially attractive for applications with limited footprints. Previously, it has been reported that planar incorporation of multiple resonators does not bring about improvement in sensitivity for a given area because the increase in Sagnac phase accumulation does not outrun the increase of area. Therefore, it was naturally suggested to consider vertical stacking of ring resonators because then, the resonators can share the same footprint. In this work, sensitivity performances of such configurations with vertically stacked microring resonators are analyzed and compared to that of a basic (single-resonator) configuration. Through comprehensive study, it is learned that the sensitivity performance of the devices with vertically-stacked resonators (either with a single bus waveguide or with two bus waveguides) does not exceed that of the basic sensor device (single resonator with one bus waveguide), i.e. the basic structure is yet to be remained as the most efficient configuration.
Citation - Scopus: 5
A Comparative Study to Estimate the Mode I Fracture Toughness of Rocks Using Several Soft Computing Techniques
(Murat Yakar, 2023) Köken, E.; Kadakci Koca, Tümay; 01. Abdullah Gül University; 02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği; 02. Mühendislik Fakültesi
Fracture toughness is an important phenomenon to reveal the actual strength of fractured rock materials. It is, therefore, crucial to use the fracture toughness models principally for simulating the performance of fractured rock medium. In this study, the mode-I fracture toughness (KIC) was investigated using several soft computing techniques. For this purpose, an extensive literature survey was carried out to obtain a comprehensive database that includes simple and widely used mechanical rock parameters such as uniaxial compressive strength (UCS) and Brazilian tensile strength (BTS). Several soft computing techniques such as artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), gene expression programming (GEP), and multivariate adaptive regression spline (MARS) were attempted to reveal the availability of these methods to estimate the KIC. Among these techniques, it was determined that ANN presents the best prediction capability. The correlation of determination value (R2) for the proposed ANN model is 0.90, showing its relative success. In this manner, the present study can be declared a case study, indicating the applicability of several soft computing techniques for the evaluation of KIC. However, the number of samples for different rock types should be increased to improve the established predictive models in future studies. © 2023 Elsevier B.V., All rights reserved.
Citation - WoS: 1
Citation - Scopus: 1
The Comparison of Fragility Curves of Moment-Resisting and Braced Frames Used in Steel Structures Under Varying Wind Load
(Turkish Chamber Civil Engineers, 2025) Ozalp, Abdulkadir; Gokdemir, Hande; Ciftci, Cihan; 01. Abdullah Gül University; 02.03. İnşaat Mühendisliği; 02. Mühendislik Fakültesi
In this study, the performance of two different steel structure types (moment-resisting frame and braced frame) under wind loading was compared by addressing the fragility curves of these structure types. To perform this comparison, the dimensions of the members of these structural systems were first determined. Then, nonlinear static pushover analyses were conducted to assess the performance levels of each frame type. After applying these analyses, time-history analyses were performed with 100 different wind loads for each varying equivalent mean wind speed. Afterwards, the probability of exceeding the predetermined structural performance limits of the structure types was determined using Monte Carlo simulation method. Finally, the results of the simulation method were used to adapt the maximum likelihood estimation method to obtain the fragility curves of the structures. To conclude, it has been revealed that the material cost of the structure doubles when diagonal elements are used, but the wind speed required for a 100% collapse probability to occur in the braced frame is twice as high compared to the moment-resisting frame.
Enlightening the Molecular Mechanisms of Type 2 Diabetes With a Novel Pathway Clustering and Pathway Subnetwork Approach
(Tubitak Scientific & Technological Research Council Turkey, 2022) Bakir-Gungor, Burcu; Yazici, Miray Unlu; Goy, Gokhan; Temiz, Mustafa; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik Fakültesi; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
Type 2 diabetes mellitus (T2D) constitutes 90% of the diabetes cases, and it is a complex multifactorial disease. In the last decade, genome-wide association studies (GWASs) for T2D successfully pinpointed the genetic variants (typically single nucleotide polymorphisms, SNPs) that associate with disease risk. In order to diminish the burden of multiple testing in GWAS, researchers attempted to evaluate the collective effects of interesting variants. In this regard, pathway-based analyses of GWAS became popular to discover novel multigenic functional associations. Still, to reveal the unaccounted 85 to 90% of T2D variation, which lies hidden in GWAS datasets, new post-GWAS strategies need to be developed. In this respect, here we reanalyze three metaanalysis data of GWAS in T2D, using the methodology that we have developed to identify disease-associated pathways by combining nominally significant evidence of genetic association with the known biochemical pathways, protein-protein interaction (PPI) networks, and the functional information of selected SNPs. In this research effort, to enlighten the molecular mechanisms underlying T2D development and progress, we integrated different in silico approaches that proceed in top-down manner and bottom-up manner, and presented a comprehensive analysis at protein subnetwork, pathway, and pathway subnetwork levels. Using the mutual information based on the shared genes, the identified protein subnetworks and the affected pathways of each dataset were compared. While most of the identified pathways recapitulate the pathophysiology of T2D, our results show that incorporating SNP functional properties, PPI networks into GWAS can dissect leading molecular pathways, and it could offer improvement over traditional enrichment strategies.
An Evaluation of the Rural Landscapes as Heritage From Habitus Perspective
(Geleneksel Yayincilik Ltd Stl, 2024) Elagoz Timur, Bahar; Asiliskender, Burak; 01. Abdullah Gül University; 05.01. Mimarlık; 05. Mimarlık Fakültesi
Rural heritage areas consist of natural and built environments produced concerning local and traditional life practices, production -consumption habits, and intangible values of societies. This environment is created vernacularly using local materials and construction techniques due to the topographical features where it is built and is in contact with local users. For this reason, it is valuable to explain the meaning of vernacular architecture to understand its users and the habitus that emerges from it. Historical rural settlements, which have found their place in conservation theories over time, attract attention with their traditional and vernacular architecture.These areas, called "rural landscape as heritage" by definition developed by ICOMOS-IFLA, are accepted as a whole with their tangible and intangible components such as natural, archaeological, and architectural. Today, plenty of research is about integrated conservation issues of rural landscape heritages. The study, differently from theirs, plans to discuss the rural landscapes through habitus. It is possible to interpret the vernacular architecture produced in rural landscapes by understanding its user and the habitus in which it emerges. Moreover, there is a dynamic link between the traditional rural areas and the habitus of societies that produce and are produced by their daily lifestyles, traditions, collective memories, and histories. The habitus, which is always transformed, begins to adapt its environment to the change by this link. In this changing process, effects such as industrialization, technological developments, and globalization threaten rural landscapes to lose their authentic values. The first step in the conservation of rural landscapes lies in understanding these areas and their values and making change predictable. From this point of view, this study questions the role of habitus in the formation and life cycle of rural heritage. The research and the hypothesis created aim to contribute to the studies about sustainable living in rural landscapes by revealing the structuring effect of the habitus between the rural landscapes and their natural, built, and socio-cultural environments. In the study, the method developed from the literature to understand rural landscapes and their dynamics without studying the case is presented for use in rural landscape heritage conservation studies. Habitus connects the natural, tangible, and intangible components of rural landscapes by the balance it creates and contributes to the formation and maintenance of the spirit of place. In order to understand this balance and draw attention to holistic conservation approaches, the network of relations has been tried to be revealed in detail. Within the scope of the study, the definition of habitus was explained through the environment and practices, and its relationship with the rural landscape was conveyed through a single structure and settlement. The transition of living heritage is inevitable, but when it cannot be managed according to international regulations, the consequences will be the loss of rural heritage, which represents societies' traditional lifestyles. The proposed approach needs to be customized and re-established for each different rural landscape heritage site. Because each heritage site is unique and has its own conservation problems. It is critical to raise awareness about the effects of habitus change in rural landscapes and their management and to emphasize the importance of creating resilient rural heritage areas that can accompany change by preserving authentic values.
Citation - WoS: 1
Citation - Scopus: 2
Investigation of Hydrogen Diffusion Profile of Different Metallic Materials for a Better Understanding of Hydrogen Embrittlement
(Gazi Univ, 2023) Kapci, Mehmet Fazil; Bal, Burak; 01. Abdullah Gül University; 02.06. Makine Mühendisliği; 02. Mühendislik Fakültesi
In this study, hydrogen diffusion profiles of different metallic materials were investigated. To model hydrogen diffusion, 1D and 2D mass diffusion models were prepared in MATLAB. Iron, nickel and titanium were selected as a material of choice to represent body-centered cubic, facecentered cubic, and hexagonal closed paced crystal structures, respectively. In addition, hydrogen back diffusion profiles were also modeled after certain baking times. Current results reveal that hydrogen diffusion depth depends on the microstructure, energy barrier model, temperature, and charging time. In addition, baking can help for back diffusion of hydrogen and can be utilized as hydrogen embrittlement prevention method. Since hydrogen diffusion is very crucial step to understand and evaluate hydrogen embrittlement, current set of results constitutes an important guideline for hydrogen diffusion calculations and ideal baking time for hydrogen back diffusion for different materials. Furthermore, these results can be used to evaluate hydrogen content inside the material over expensive and hard to find experimental facilities such as, thermal desorption spectroscopy.
Citation - Scopus: 2
Investigation of Peroxidase-Like Activity of Flower-Shaped Nanobiocatalyst From Viburnum Opulus L. Extract on the Polymerization Reactions
(Turkish Chemical Society, 2024) Kalayci, Berkant; Kaplan, Naime; Mirioglu, Muge; Dadi, Seyma; Öçsoy, Ismail; Göktürk, Ersen; 01. Abdullah Gül University
Here, we report the effects of peroxidase-mimicking activity of flower shaped hybrid nanobiocatalyst obtained from Viburnum-Opulus L. (Gilaburu) extract and Cu2+ ions on the polymerization of phenol and its derivatives (guaiacol and salicylic acid). The obtained nanoflowers exhibited quite high catalytic activity upon the polymerization of phenol and guaiacol. The yields and the number average molecular weights of the obtained polymers were significantly high. Due to solubility issue of salicylic acid in aqueous media, polymerization of salicylic acid resulted in very low yields. Free-horseradish peroxidase (HRP) enzyme is known to be losing its catalytic activity at 60 °C and above temperatures. However, the synthesized nanoflowers exhibited quite high catalytic activity even at 60 °C and above reaction temperatures. This provides notable benefits for reactions needed at high temperatures, and it is very important to use these kinds of nanobiocatalysts for both scientific studies and industrial applications. © 2024 Elsevier B.V., All rights reserved.
Citation - WoS: 1
Citation - Scopus: 2
Investigation of the Interaction of Adipose-Derived Mesenchymal Stem Cells With Ε-Polycaprolactone and EGG White Scaffolds
(Gazi Univ, 2023) Oztel, Olga N.; Yilmaz, Hilal; Isoglu, I. Alper; Allahverdiyev, Adil; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
The development of three-dimensional (3D) cell culture models is becoming increasingly important due to their numerous advantages over conventional monolayer culture. This study aimed to examine the interaction of adipose tissue-derived mesenchymal stem cells (AD-MSCs) with scaffolds composed of e-polycaprolactone (e-PCL) and egg white. In our study, e-PCL and egg white scaffolds were produced from their monomers by tin octoate catalyzed and heat polymerization, respectively. Characterization of e-PCL was carried out by Gel Permeation Chromatography (GPC), Fourier Transform Infrared Spectrophotometry (FTIR), Proton Nuclear Magnetic Resonance (H-NMR), Differential Scanning Calorimetry (DSC) and Scanning Electron Microscopy (SEM). AD-MSCs labeled with red fluorescent CellTracker CM-DiI were cultured on egg white and e-PCL scaffolds for 12 days. Cell viability was determined using 3-(4.5Dimethylthiazol-2yl)-2.5-diphenyltetrazolium bromide (MTT) and nitric oxide (NO) level was evaluated for toxicity. The results showed that the number of AD-MSCs in the egg white scaffold increased periodically for 12 days compared to the other groups. Although the number of ADMSCs in the e-PCL scaffold increased until day 6 of the culture, the number of cells started to decrease after day 6. These results were associated with the toxic effect of lactic acid release on cells resulting from the decomposition of e-PCL scaffolds through catabolic reactions. Therefore, these results indicated that the egg white scaffold enhanced and maintained cell adhesion and cell viability more than the e-Polycaprolactone scaffold and could be used as a scaffold in tissue engineering studies involving stem cells.
Citation - WoS: 8
Citation - Scopus: 10
Lung Cancer Subtype Differentiation From Positron Emission Tomography Images
(Tubitak Scientific & Technological Research Council Turkey, 2020) Ayyildiz, Oguzhan; Aydin, Zafer; Yilmaz, Bulent; Karacavus, Seyhan; Senkaya, Kubra; Icer, Semra; Kaya, Eser; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
Lung cancer is one of the deadly cancer types, and almost 85% of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation of two subtypes of NSCLC, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). The major advances in understanding the effects of therapy agents suggest that future targeted therapies will be increasingly subtype specific. We obtained positron emission tomography (PET) images of 93 patients with NSCLC, 39 of which had ADC while the rest had SqCC. Random walk segmentation was applied to delineate three-dimensional tumor volume, and 39 texture features were extracted to grade the tumor subtypes. We examined 11 classifiers with two different feature selection methods and the effect of normalization on accuracy. The classifiers we used were the k-nearest-neighbor, logistic regression, support vector machine, Bayesian network, decision tree, radial basis function network, random forest, AdaBoostM1, and three stacking methods. To evaluate the prediction accuracy we performed a leave-one-out cross-validation experiment on the dataset. We also considered optimizing certain hyperparameters of these models by performing 10-fold cross-validation separately on each training set. We found that the stacking ensemble classifier, which combines a decision tree, AdaBoostM1, and logistic regression methods by a metalearner, was the most accurate method for detecting subtypes of NSCLC, and normalization of feature sets improved the accuracy of the classification method.
Citation - Scopus: 21
Lyapunov Exponent Enhancement in Chaotic Maps With Uniform Distribution Modulo One Transformation
(Akif AKGUL, 2022) Ablay, Günyaz; 01. Abdullah Gül University
Most of the chaotic maps are not suitable for chaos-based cryptosystems due to their narrow chaotic parameter range and lacking of strong unpredictability. This work presents a nonlinear transformation approach for Lyapunov exponent enhancement and robust chaotification in discrete-time chaotic systems for generating highly independent and uniformly distributed random chaotic sequences. The outcome of the new chaotic systems can directly be used in random number and random bit generators without any post-processing algorithms for various information technology applications. The proposed Lyapunov exponent enhancement based chaotic maps are analyzed with Lyapunov exponents, bifurcation diagrams, entropy, correlation and some other statistical tests. The results show that excellent random features can be accomplished even with one-dimensional chaotic maps with the proposed approach. © 2023 Elsevier B.V., All rights reserved.
Citation - WoS: 2
Citation - Scopus: 3
Magnetic Separation of Micro Beads and Cells on a Paper-Based Lateral Flow System
(Gazi Univ, 2023) Farooqi, Muhammed Fuad; Icoz, Kutay; 01. Abdullah Gül University
Paper based lateral flow systems are widely used biosensor platforms to detect biomolecules in a liquid sample. Proteins, bacteria, oligonucleotides, and nanoparticles were investigated in the literature. In this work we designed a magnetic platform including dual magnets and tested the flow of micron size immunomagnetic particles alone and when loaded with cells on two different types of papers. The prewetting conditions of the paper and the applied external magnetic field are the two dominant factors affecting the particle and cell transport in paper. The images recorded with a cell phone, or with a bright field optical microscope were analyzed to measure the flow of particles and cells. The effect of prewetting conditions and magnetic force were measured, and it was shown that in the worst case, minimum 90% of the introduced cells reached to the edge of the paper. The paper based magnetophoretic lateral flow systems can be used for cell assays.
Citation - WoS: 1
Citation - Scopus: 2
Metacognitive Monitoring and Mathematical Abilities: Cognitive Diagnostic Model and Signal Detection Theory Approach
(Turkish Education Assoc, 2021) Basokcu, Oguz Tahsin; Guzel, Mehmet Akif; 01. Abdullah Gül University; 06. İnsan ve Toplum Bilimleri Fakültesi; 06.02. Psikoloji
Besides various in-class assessments, there exist some standardized assessment tools that are administered in several countries, such as PISA (Programme for International Student Assessment) and TIMMS (Trends in International Mathematics and Science Study). The questions' contents, type of responding, grading, and the analyses in these large-scale tests have been diversified in years. In this study, it was aimed to identify the abilities that are measured at PISA mathematics test in a single testing procedure and by utilizing the methods of analyses of Cognitive Diagnostic Model (CDM) as well as Signal Detection Theory (SDT), which have not been used so far in the assessment of these abilities. Therefore, a randomly selected sample of 6th-grade students (N=230) in Izmir was tested with a PISA-equivalent 12-item mathematics test, where the items are graded dichotomously (correct vs. incorrect). CDM estimates were calculated by using the Deterministic Input Noisy Output and Gate (DINA) Model. The participants were asked to report whether they thought they could solve the question correctly, guess even if they thought they could not solve the question, and then, rate their confidence levels on the correctness of their answers in turn so as to allow us to measure their "metacognitive monitoring performance" with the SDT method, which refers to the ability to differentiate correct and incorrect responses. In short, a better metacognitive monitoring performance was obtained by measuring how well once could differentiate their correct and incorrect responses with the observation of they prefer reporting and then giving high confidence levels to the actually correct responses and prefer passing to give an answer yet rate lower confidence levels to the actually incorrect responses given as pure guesses. The results showed that CDM fits well to the assessment of PISA test and those who were better at the ability of "reasoning and developing strategies" in particular among four possible abilities detected with CDM ("representing and communicating", "mathematization", "reasoning and developing strategies", "using symbolic and technical language") had also better metacognitive monitoring performance. The present study, therefore, contributes to the research that investigates what features the ability of better differentiating correct and incorrect responses are actually linked. Based on the results, it is suggested that a better metacognitive monitoring ability is linked to having a better ability of "reasoning and developing strategies" in particular. Additionally, it is suggested that measuring metacognitive monitoring performance at PISA -or even any other possible tests- with the SDT calculation method, that has a relatively straightforward testing procedure, may yield various estimates for the students' abilities measured at the test as well as their related higher-order abilities.
Citation - WoS: 3
Citation - Scopus: 3
MicroRNA Prediction Based on 3D Graphical Representation of RNA Secondary Structures
(Tubitak Scientific & Technological Research Council Turkey, 2019) Sacar Demirci, Muserref Duygu; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
MicroRNAs (miRNAs) are posttranscriptional regulators of gene expression. While a miRNA can target hundreds of messenger RNA (mRNAs), an mRNA can be targeted by different miRNAs, not to mention that a single miRNA might have various binding sites in an mRNA sequence. Therefore, it is quite involved to investigate miRNAs experimentally. Thus, machine learning (ML) is frequently used to overcome such challenges. The key parts of a ML analysis largely depend on the quality of input data and the capacity of the features describing the data. Previously, more than 1000 features were suggested for miRNAs. Here, it is shown that using 36 features representing the RNA secondary structure and its dynamic 3D graphical representation provides up to 98% accuracy values. In this study, a new approach for ML-based miRNA prediction is proposed. Thousands of models are generated through classification of known human miRNAs and pseudohairpins with 3 classifiers: decision tree, naive Bayes, and random forest. Although the method is based on human data, the best model was able to correctly assign 96% of nonhuman hairpins from MirGeneDB, suggesting that this approach might be useful for the analysis of miRNAs from other species.
Modified Self-Adaptive Local Search Algorithm for a Biobjective Permutation Flow Shop Scheduling Problem
(Tubitak Scientific & Technological Research Council Turkey, 2019) Alabas Uslu, Cigdem; Dengiz, Berna; Aglan, Canan; Sabuncuoglu, Ihsan; 01. Abdullah Gül University
Interest in multiobjective permutation flow shop scheduling (PFSS) has increased in the last decade to ensure effective resource utilization. This study presents a modified self-adaptive local search (MSALS) algorithm for the biobjective permutation flow shop scheduling problem where both makespan and total flow time objectives are minimized. Compared to existing sophisticated heuristic algorithms, MSALS is quite simple to apply to different biobjective PFSS instances without requiring effort or time for parameter tuning. Computational experiments showed that MSALS is either superior to current heuristics for Pareto sets or is incomparable due to other performance indicators of multiobjective problems.
Citation - Scopus: 4
Network Intrusion Detection Based on Machine Learning Strategies: Performance Comparisons on Imbalanced Wired, Wireless, and Software-Defined Networking (SDN) Network Traffics
(Turkiye Klinikleri, 2024) Hacilar, Hilal; Aydin, Zafer; Güngör, Vehbi Çağrı; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik Fakültesi
The rapid growth of computer networks emphasizes the urgency of addressing security issues. Organizations rely on network intrusion detection systems (NIDSs) to protect sensitive data from unauthorized access and theft. These systems analyze network traffic to detect suspicious activities, such as attempted breaches or cyberattacks. However, existing studies lack a thorough assessment of class imbalances and classification performance for different types of network intrusions: wired, wireless, and software-defined networking (SDN). This research aims to fill this gap by examining these networks’ imbalances, feature selection, and binary classification to enhance intrusion detection system efficiency. Various techniques such as SMOTE, ROS, ADASYN, and SMOTETomek are used to handle imbalanced datasets. Additionally, eXtreme Gradient Boosting (XGBoost) identifies key features, and an autoencoder (AE) assists in feature extraction for the classification task. The study evaluates datasets such as AWID, UNSW, and InSDN, yielding the best results with different numbers of selected features. Bayesian optimization fine-tunes parameters, and diverse machine learning algorithms (SVM, kNN, XGBoost, random forest, ensemble classifiers, and autoencoders) are employed. The optimal results, considering F1-measure, overall accuracy, detection rate, and false alarm rate, have been achieved for the UNSW-NB15, preprocessed AWID, and InSDN datasets, with values of [0.9356, 0.9289, 0.9328, 0.07597], [0.997, 0.9995, 0.9999, 0.0171], and [0.9998, 0.9996, 0.9998, 0.0012], respectively. These findings demonstrate that combining Bayesian optimization with oversampling techniques significantly enhances classification performance across wired, wireless, and SDN networks when compared to previous research conducted on these datasets. © 2024 Elsevier B.V., All rights reserved.
Citation - WoS: 2
Citation - Scopus: 2
The Nexus of Leadership, Political Empowerment, and Social Mobilization: The Case of the July 15 Coup Attempt in Turkey
(Seta Foundation, 2020) Donmez, Rasim Ozgur; Timur, Kasim; Lloyd, Fatma Armagan Teke; 01. Abdullah Gül University; 06. İnsan ve Toplum Bilimleri Fakültesi; 06.01. Siyaset Bilimi ve Uluslararası İlişkiler
This study analyzes the mutually empowering relations between Turkish President Recep Tayyip Erdogan and his followers, and how Erdogan's charismatic leadership and image functioned to galvanize his followers on the night of July 15, 2016, when large numbers of them mobilized against the attempted coup. The article has three sections. The first is a theoretical discussion which sheds light on the concept and the underlying mechanisms of political empowerment and its effects on the relationships between leaders and followers. The second section evaluates Erdogan's characteristics and ruling style, which was instrumental in motivating resistance to the abortive coup. Finally, the third section analyzes the various means by which Erdogan was able to inspire the masses to mobilize against the armed junta through interviews and observations.
Citation - WoS: 4
Citation - Scopus: 5
Noise-Assisted Multivariate Empirical Mode Decomposition Based Emotion Recognition
(Istanbul Univ-Cerrahapasa, 2018) Ozel, Pinar; Akan, Aydin; Yilmaz, Bulent; 01. Abdullah Gül University
Emotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms. Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD). Despite its various benefits, EMD has several drawbacks: it is intended for univariate data; it is prone to mode mixing; and the number of local extrema must be enough before the EMD process can begin. To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals. Emotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms. Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD). Despite its various benefits, EMD has several drawbacks: it is intended for univariate data; it is prone to mode mixing; and the number of local extrema must be enough before the EMD process can begin. To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals.
Optimizing Parameters for Efficient Computation With Fully Homomorphic Encryption Schemes
(Tubitak Scientific & Technological Research Council Turkey, 2025) Karaagac, Cavidan Yakupoglu; Rohloff, Kurt; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik Fakültesi
In this study, we aim to provide a parameter selection approach for the BFVrns scheme, one of the prominent fully homomorphic encryption (FHE) schemes. Selecting parameters for lattice-based FHE schemes poses a practical challenge for both experts and nonexperts. To solve this problem, we introduce a hybrid approach that combines theoretical approach with experimental analysis. First, we employ regression analysis to examine the impact of parameters on both performance and security. The varying behavior of FHE parameters in terms of performance, security, and ciphertext expansion factor (CEF) makes parameter selection more challenging. To address this issue, we employ a multi-objective optimization algorithm to determine the optimal parameter set for performance, CEF, and security simultaneously. As a result of this optimization, we obtain an improved parameter set that enhances performance at a given security level while ensuring correctness and resistance to lattice-based attacks, maintaining at least 128-bit security. Our results achieve an average similar to 5x reduction in CEF and generally better performance compared to the parameter sets in a previous BFVrns study. Our approach serves as a semi-automated parameter selection method for the PALISADE homomorphic encryption library, a widely recognized FHE library. This study sets a precedent for other FHE libraries.

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