TR-Dizin İndeksli Yayınlar Koleksiyonu

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

Browse

Now showing 1 - 13 of 13

Citation - WoS: 1
Citation - Scopus: 2
Complementary Medicines Used in Ulcerative Colitis and Unintended Interactions With Cytochrome P450-Dependent Drug-Metabolizing Enzymes
(Tubitak Scientific & Technological Research Council Turkey, 2022) Sen, Alaattin
Ulcerative colitis (UC) is an idiopathic, chronic inflammatory disease with multiple genetic and a variety of environmental risk factors. Although current drugs significantly aid in controlling the disease, many people have led to the application of complementary therapies due to the common belief that they are natural and safe, as well as due to the consideration of the side effect of current drugs. Curcumin, cannabinoids, wheatgrass, Boswellia, wormwood and Aloe vera are among the most commonly used complementary medicines in UC. However, these treatments may have adverse and toxic effects due to unintended interactions with drugs or drug-metabolizing enzymes such as cytochrome P450s; thus, being ignorant of these interactions might cause deleterious effects with severe consequences. In addition, the lack of complete and controlled long-term studies with the use of these complementary medicines regarding drug metabolism pose additional risk and unsafety. Thus, this review aims to give an overview of the potential interactions of drug-metabolizing enzymes with the complementary botanical medicines used in UC, drawing attention to possible adverse effects.
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
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: 3
An Asymptotic-Numerical Hybrid Method for Singularly Perturbed System of Two-Point Reaction-Diffusion Boundary-Value Problems
(Tubitak Scientific & Technological Research Council Turkey, 2019) Cengizci, Suleyman; Natesan, Srinivasan; Atay, Mehmet Tank
This article focuses on the numerical approximate solution of singularly perturbed systems of second-order reaction-diffusion two-point boundary-value problems for ordinary differential equations. To handle these types of problems, a numerical-asymptotic hybrid method has been used. In this hybrid approach, an efficient asymptotic method, the so-called successive complementary expansion method (SCEM) is employed first, and then a numerical method based on finite differences is applied to approximate the solution of corresponding singularly perturbed reaction-diffusion systems. Two illustrative examples are provided to demonstrate the efficiency, robustness, and easy applicability of the present method with convergence properties.
Citation - WoS: 1
Citation - Scopus: 1
Existence Results for a Class of Boundary Value Problems for Fractional Differential Equations
(Tubitak Scientific & Technological Research Council Turkey, 2021) Dogan, Abdulkadir
By application of some fixed point theorems, that is, the Banach fixed point theorem, Schaefer's and the LeraySchauder fixed point theorem, we establish new existence results of solutions to boundary value problems of fractional differential equations. This paper is motivated by Agarwal et al. (Georgian Math. J. 16 (2009) No.3, 401-411).
Citation - Scopus: 5
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
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.
Study of Helical Antenna Endowing Short Wire Length and Compact Structure for High-Frequency Operations and Its Exclusive Manufacturing Process
(Tubitak Scientific & Technological Research Council Turkey, 2023) Aslan, Melih; Sik, Kaan; Güzelkara, Izzet; Özdür, Ibrahim Tuna; Kilic, Veli Tayfun
In this paper a study of a helical antenna resonating at high-frequency (HF) band with a very compact structure is reported. The designed antenna's S11 parameter magnitude change with frequency was calculated for different geometrical parameters. For each case, first, only a single parameter was changed. Then for a fair comparison, multiple parameters were changed simultaneously while the total wire length was set to be constant. Also, shifts in resonance frequencies and variations in -10 dB bandwidths were investigated. Our results show that resonance behaviour changes distinctively with the geometrical parameters and it allows shortening of the antenna wire length. For the designed antenna, the resonances shift to lower frequencies and -10 dB bandwidths around the resonances decrease as the winding wire thickness, number of turns, and turn radius increase. Whereas as the turn spacing increases the resonances shift to higher frequencies and -10 dB bandwidths widen, although the total wire length of the antenna increases. To verify the simulation results, the designed antenna was fabricated with an exclusive manufacturing process and characterized. The measurement results are in good agreement with the simulation results. It demonstrates the feasibility of the proposed manufacturing technique, which is new in the literature and enables accurate and rigid antenna fabrication with simple and low-cost steps.
Optimizing Parameters for Efficient Computation With Fully Homomorphic Encryption Schemes
(Tubitak Scientific & Technological Research Council Turkey, 2025) Karaagac, Cavidan Yakupoglu; Rohloff, Kurt
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.
Existence of Positive Solutions for Nonlinear Multipoint P-Laplacian Dynamic Equations on Time Scales
(Tubitak Scientific & Technological Research Council Turkey, 2020) Dogan, Abdulkadir
In this paper, we investigate the existence of positive solutions for nonlinear multipoint boundary value problems for p-Laplacian dynamic equations on time scales with the delta derivative of the nonlinear term. Sufficient assumptions are obtained for existence of at least twin or arbitrary even positive solutions to some boundary value problems. Our results are achieved by appealing to the fixed point theorems of Avery-Henderson. As an application, an example to demonstrate our results is given.
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
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.
Solutions to Nonlinear Second-Order Three-Point Boundary Value Problems of Dynamic Equations on Time Scales
(Tubitak Scientific & Technological Research Council Turkey, 2019) Dogan, Abdulkadir
In this paper, we consider existence criteria of three positive solutions of three-point boundary value problems for p-Laplacian dynamic equations on time scales. To show our main results, we apply the well-known Leggett-Williams fixed point theorem. Moreover, we present some results for the existence of single and multiple positive solutions for boundary value problems on time scales, by applying fixed point theorems in cones. The conditions we used in the paper are different from those in [Dogan A. On the existence of positive solutions for the one-dimensional p-Laplacian boundary value problems on time scales. Dynam Syst Appl 2015; 24: 295-304].
Citation - WoS: 1
Citation - Scopus: 1
Prediction of Preference and Effect of Music on Preference: A Preliminary Study on Electroencephalography from Young Women
(Tubitak Scientific & Technological Research Council Turkey, 2019) Yilmaz, Bulent; Gazeloglu, Cengiz; Altindis, Fatih
Neuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is investigated. The second aim was to develop an approach in the prediction of preference using only brain signals. In this work, 19-channel EEG signals were recorded and two experimental paradigms were implemented: no music/silence and rhythmic, loud music using a headphone, while viewing women shoes. For each 10-sec epoch, normalized power spectral density (PSD) of EEG data for six frequency bands was estimated using the Burg method. The effect of music was investigated by comparing the mean differences between music and no music groups using independent two-sample t-test. In the preference prediction part sequential forward selection, k-nearest neighbors (k-NN) and the support vector machines (SVM), and 5-fold cross-validation approaches were used. It is found that music did not affect like decision in any of the power bands, on the contrary, music affected dislike decisions for all bands with no exceptions. Furthermore, the accuracies obtained in preference prediction study were between 77.5 and 82.5% for k-NN and SVM techniques. The results of the study showed the feasibility of using EEG signals in the investigation of the music effect on purchasing behavior and the prediction of preference of an individual.
Citation - WoS: 2
Citation - Scopus: 2
Analysis of Optical Gyroscopes With Vertically Stacked Ring Resonators
(Tubitak Scientific & Technological Research Council Turkey, 2021) Hah, Dooyoung
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 - 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
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.

Browse

Browsing TR-Dizin İndeksli Yayınlar Koleksiyonu by Scopus Q "Q2"