WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Article A Novel Hypercube-Based Approach To Overlay Design Algorithms on Topic Distribution Networks(Gazi Univ, 2022) Yumusak, Semih; Hassanpour, Reza; Layazali, Sina; Oztoprak, Kasim; Hassanpour, Reza; Yazılım MühendisliğiData communication in peer-to-peer (P2P) network requires a fine-grained optimization for memory and processing to lower the total energy consumption. When the concept of Publish/subscribe (Pub/Sub) systems were used as a communication tool in a P2P network, the network required additional optimization algorithms to reduce the complexity. The major difficulty for such networks was creating an overlay design algorithm (ODA) to define the communication patterns. Although some ODAs may perform worse on a high-scale, some may have better average/maximum node degrees. Based on the experimentation and previous works, this study designed an algorithm called the Hypercube-ODA, which reduces the average/maximum node degree for a topic connected Pub/Sub network. The Hypercube-ODA algorithm creates the overlay network by creating random cubes within the network and arranging the nodes with the cubes they belong to. In this paper, the details of the proposed Hypercube algorithm were presented and its performance was compared with the existing ODAs. Results from the experiments indicate that the proposed method outperforms other ODA methods in terms of lower average node degree (lowering the average node degree by up to 60%).Article Citation - WoS: 1Using Text Mining for Research Trends in Empirical Software Engineering(Gazi Univ, 2021) Tokdemir, GulThis paper intends to examine the research trends in Empirical Software Engineering domain within the last two decades using text mining. It studies published articles in the relevant literature with an emphasis on abstracts of 10658 articles published in the literature on Experimental Software Engineering domain. Using a probabilistic topic modelling technique (Latent Dirichlet Allocation), it brings forward the main topics of research within this domain. By further analysis, the paper evaluates the changes of focus in published works in the last two decades and depicts the recent trends in research content wise. Through a timely comparison, it portrays the alteration of interest within empirical software engineering research and proposes a future research agenda to develop an advanced field, beneficial both for academics and practitioners.Article Citation - WoS: 2Citation - Scopus: 2Analysis of Heat Transfer Enhancement in Tubes With Capsule Dimpled Surfaces and Al2o3-Water Nanofluid(Turkish Soc thermal Sciences Technology, 2022) Ibrahim, Mahmoud Awni A. Haj; Turkoglu, Hasmet; Yapici, Ekin Ozgirgin; Haj Ibrahim, Mahmoud Awni A.This study aims to numerically investigate and evaluate the enhancement of heat transfer by new capsule dimples on tube surfaces for flow of water and Al2O3-water nanofluid with different concentrations, under uniform surface heat flux. The originality of this work lies in combining two passive heat transfer enhancement methods such as geometrical improvements and nanofluids together. Capsule dimples with different depths were considered. Al2O3- water nanofluid was modeled as a single-phase flow based on the mixture properties. The effects of dimple depth and nanoparticle concentrations on Nusselt number, friction factor and performance evaluation criteria (PEC) were studied. Numerical computations were performed using ANSYS Fluent commercial software for 2000-14000 Reynolds number range. It was found that when laminar, transient and fully developed turbulent flow cases are considered, increase in the dimple depth increases the Nusselt number and friction factor for both pure water and Al2O3-water nanofluids cases. Also, the friction factor increases as dimple depth increases. Results show that increase in PEC is more pronounced in the laminar region than in the transition region, it starts to decrease for turbulent flows. For nanofluid, PEC values are considerably higher than pure water cases. The variation of PEC for capsule dimpled tubes are dependent on flow regimes and dimple depths. Increasing the nano particle volume concentration and dimple depth in laminar flows increase the PEC significantly.Article Line-Of Rate Construction for a Roll-Pitch Gimbal Via a Virtual Pitch-Yaw Gimbal(Tubitak Scientific & Technological Research Council Turkey, 2021) Cifdaloz, OguzhanIn this paper, a method to construct the line of sight rate of a target with a roll-pitch gimbal and tracker is described. Construction of line-of-sight rate is performed via utilizing a virtual pitch-yaw gimbal. Kinematics of both the roll-pitch and pitch-yaw gimbals are described. A dynamical model for the roll-pitch gimbal is developed, and a nested control structure is designed to control the angular rates and line of sight angles. A kinematic model of the tracker is developed and a tracker controller is designed to keep the target in the field of view. Conversion equations between roll-pitch and pitch-yaw gimbal configurations are provided. Finally, constructed line of sight rates are compared to true line of sight rates via simulations. Obtained results indicate that the constructed line of sight rates pertaining to a target satisfactorily converge to the actual line of sight rates.Article Citation - WoS: 4Citation - Scopus: 5An Algebraic Stability Test for Fractional Order Time Delay Systems(Ramazan Yaman, 2020) Baleanu, Dumitru; Ozyetkin, Munevver MineIn this study, an algebraic stability test procedure is presented for fractionalorder time delay systems. This method is based on the principle of eliminatingtime delay. The stability test of fractional order systems cannot be examineddirectly using classical methods such as Routh-Hurwitz, because such systemsdo not have analytical solutions. When a system contains the square roots ofs, it is seen that there is a double value function of s. In this study, a stabilitytest procedure is applied to systems including ps and/or different fractionaldegrees such as s where 0 < α < 1, and αǫR. For this purpose, the integerorder equivalents of fractional order terms are first used and then the stabilitytest is applied to the system by eliminating time delay. Thanks to the proposedmethod , it is not necessary to use approximations instead of time delay termsuch as Pad´e. Thus, the stability test procedure does not require the solutionof higher order equations.Article Citation - WoS: 3Citation - Scopus: 3Filter Design for Small Target Detection on Infrared Imagery Using Normalized-Cross Layer(Tubitak Scientific & Technological Research Council Turkey, 2020) Demir, H. Seckin; Akagunduz, ErdemIn this paper, we introduce a machine learning approach to the problem of infrared small target detection filter design. For this purpose, similar to a convolutional layer of a neural network, the normalized-cross-correlational (NCC) layer, which we utilize for designing a target detection/recognition filter bank, is proposed. By employing the NCC layer in a neural network structure, we introduce a framework, in which supervised training is used to calculate the optimal filter shape and the optimum number of filters required for a specific target detection/recognition task on infrared images. We also propose the mean-absolute-deviation NCC (MAD-NCC) layer, an efficient implementation of the proposed NCC layer, designed especially for FPGA systems, in which square root operations are avoided for real-time computation. As a case study we work on dim-target detection on midwave infrared imagery and obtain the filters that can discriminate a dim target from various types of background clutter, specific to our operational concept.Article Citation - WoS: 13Citation - Scopus: 16Modeling the Impact of Temperature on Fractional Order Dengue Model With Vertical Transmission(Ramazan Yaman, 2020) Defterli, OzlemA dengue epidemic model with fractional order derivative is formulated to an-alyze the effect of temperature on the spread of the vector-host transmitted dengue disease. The model is composed of a system of fractional order differ-ential equations formulated within Caputo fractional operator. The stability of the equilibrium points of the considered dengue model is studied. The cor-responding basic reproduction number R alpha 0 is derived and it is proved that if R alpha 0 < 1, the disease-free equilibrium (DFE) is locally asymptotically stable. L1 method is applied to solve the dengue model numerically. Finally, numerical simulations are also presented to illustrate the analytical results showing the influence of the temperature on the dynamics of the vector-host interaction in dengue epidemics.Article Citation - WoS: 5Citation - Scopus: 5Vessel Segmentation in Mri Using a Variational Image Subtraction Approach(2014) Saran, Ayşe Nurdan; Nar, Fatih; Saran, MuratVessel segmentation is important for many clinical applications, such as the diagnosis of vascular diseases, the planning of surgery, or the monitoring of the progress of disease. Although various approaches have been proposed to segment vessel structures from 3-dimensional medical images, to the best of our knowledge, there has been no known technique that uses magnetic resonance imaging (MRI) as prior information within the vessel segmentation of magnetic resonance angiography (MRA) or magnetic resonance venography (MRV) images. In this study, we propose a novel method that uses MRI images as an atlas, assuming that the patient has an MRI image in addition to MRA/MRV images. The proposed approach intends to increase vessel segmentation accuracy by using the available MRI image as prior information. We use a rigid mutual information registration of the MRA/MRV to the MRI, which provides subvoxel accurate multimodal image registration. On the other hand, vessel segmentation methods tend to mostly suffer from imaging artifacts, such as Rician noise, radio frequency (RF) inhomogeneity, or partial volume effects that are generated by imaging devices. Therefore, this proposed method aims to extract all of the vascular structures from MRA/MRI or MRV/MRI pairs at the same time, while minimizing the combined effects of noise and RF inhomogeneity. Our method is validated both quantitatively and visually using BrainWeb phantom images and clinical MRI, MRA, and MRV images. Comparison and observer studies are also realized using the BrainWeb database and clinical images. The computation time is markedly reduced by developing a parallel implementation using the Nvidia compute unified device architecture and OpenMP frameworks in order to allow the use of the method in clinical settings.Article Citation - WoS: 7Citation - Scopus: 10Extending a Sentiment Lexicon With Synonym-Antonym Datasets: Swnettr Plus(Tubitak Scientific & Technological Research Council Turkey, 2019) Genc, Burkay; Sever, Hayri; Saglam, FatihIn our previous studies on developing a general-purpose Turkish sentiment lexicon, we constructed SWNetTR-PLUS, a sentiment lexicon of 37K words. In this paper, we show how to use Turkish synonym and antonym word pairs to extend SWNetTR-PLUS by almost 33% to obtain SWNetTR++, a Turkish sentiment lexicon of 49K words. The extension was done by transferring the problem into the graph domain, where nodes are words, and edges are synonym- antonym relations between words, and propagating the existing tone and polarity scores to the newly added words using an algorithm we have developed. We tested the existing and new lexicons using a manually labeled Turkish news media corpus of 500 news texts. The results show that our method yielded a significantly more accurate lexicon than SWNetTR-PLUS, resulting in an accuracy increase from 72.2% to 80.4%. At this level, we have now maximized the accuracy rates of translation-based sentiment analysis approaches, which first translate a Turkish text to English and then do the analysis using English sentiment lexicons.Article Citation - WoS: 1Citation - Scopus: 3Identifying Criminal Organizations From Their Social Network Structures(Tubitak Scientific & Technological Research Council Turkey, 2019) Genc, Burkay; Sever, Hayri; Cinar, Muhammet SerkanIdentification of criminal structures within very large social networks is an essential security feat. By identifying such structures, it may be possible to track, neutralize, and terminate the corresponding criminal organizations before they act. We evaluate the effectiveness of three different methods for classifying an unknown network as terrorist, cocaine, or noncriminal. We consider three methods for the identification of network types: evaluating common social network analysis metrics, modeling with a decision tree, and network motif frequency analysis. The empirical results show that these three methods can provide significant improvements in distinguishing all three network types. We show that these methods are viable enough to be used as supporting evidence by security forces in their fight against criminal organizations operating on social networks.