WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Article Vessel Segmentation in MRI Using a Variational Image Subtraction Approach(Tubitak Scientific & Technological Research Council Turkey, 2014) Nar, Fatih; Saran, Ayse Nurdan; 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 Outputs Bounds for Linear Systems with Repeated Input Signals: Existence, Computation and Application to Vehicle Platooning(Tubitak Scientific & Technological Research Council Turkey, 2018) Schmidt, Klaus Werner; Saglam, Harun BugraThis paper investigates the effect of repeated time-limited input signals on the output excursion of stable, linear time-invariant systems. It is first shown that the maximum norm of the output signal remains bounded if the repeated input signals are separated by a nonzero dwell time. Then a novel method for computing a tight bound on the output signal norm is proposed. The setting of the paper is motivated by a vehicle platooning application, where vehicles repeatedly open/close gaps in order to perform lane changes. The developed method analyzes driving safety by computing a bound on the spacing error between vehicles when performing repeated open/close gap maneuvers.Article General Formulation of the Scattered Matter Waves by a Quantum Shutter(Tubitak Scientific & Technological Research Council Turkey, 2009) Umul, Yusuf Z.The scattering process of matter waves by a quantum shutter is investigated by using the spectrum integral representation. The scattered fields are expressed in terms of the Fresnel function. It is shown that the obtained equation gives the Moshinsky function for a one dimensional problem of the plane wave. Also a general integral representation is derived for two dimensional problems. The scattering of matter waves for some special wave-packets are examined analytically and numerically.Article Effects of Routing Algorithms on Novel Throughput Improvement of Mobile Ad Hoc Networks(Tubitak Scientific & Technological Research Council Turkey, 2012) Preveze, Barbaros; Safak, AyselA cognitive method called most congested access first (MCAF), minimizing the packet loss ratio and improving the throughput of a multihop mobile WiMAX network, is proposed. MCAF combines both the time division multiple access and the orthogonal frequency division multiple access methods. MCAF additionally uses spectral aid and buffer management methods, which air proposed in this paper, to manage both spectrum. access and packets in the buffers. By using these novel methods, real-time video and voice packet transmission is achieved, data packet loss rate is minimized, and the system throughput per node is improved. Effects of fastest path and ant colony routing algorithms on throughput improvement methods are investigated. It is shown that the fastest path routing algorithm, provides higher throughput values than the ant colony routing algorithm.Article Adaptive Decision Fusion Based Framework for Short-Term Wind Speed and Turbulence Intensity Forecasting: Case Study for North West of Turkey(Tubitak Scientific & Technological Research Council Turkey, 2017) Dinckal, Cigdem; Toreyin, Bechet Ugur; Kucukali, Serhat; Din Çkal, ÇigdemIn this paper, an online learning framework called adaptive decision fusion (ADF) is employed for short-term wind speed and turbulence intensity forecasting by use of wind speed data for each season for the city of Izmit, located in the northwest of Turkey. Fixed-weight (FW) linear combination is derived and used for comparison with ADF. Wind speeds and turbulence intensities are predicted from the existing wind speed data and computed turbulence intensities, respectively, using the ADF and FW methods. Simulations are carried out for each season and the results are tested on mean absolute percentage error criterion. It is shown that the proposed model captured the system dynamic behavior and made accurate predictions based on the seasonal wind speed characteristics of the site. The procedure described here can be used to estimate the local velocity and turbulence intensity in a wind power plant during a storm.Article A Switching Inverse Dynamics Controller for Parallel Manipulators around Drive Singular Configurations(Tubitak Scientific & Technological Research Council Turkey, 2016) Ider, Sitki Kemal; Ozdemir, MustafaDespite many advantages, parallel manipulators are known to possess drive singularities where the control of one or more degrees of freedom is lost. Around these singular configurations, the required actuator forces grow unbounded. Previous efforts in the literature put forward singularity-consistent trajectory planning and singularity robust modification of the dynamic equations as a solution to this problem. However, this previous method is applicable only for the open-loop operation of the manipulator, whereas initial configuration errors, external disturbances, and modeling errors should necessarily be taken into account in a closed-loop sense in real-life applications. With this aim, a switching inverse dynamics controller is proposed in this study for the trajectory tracking control of parallel manipulators as they pass through drive singular configurations. Simulations of the application of the developed controller result in good tracking performance, even in the presence of modeling errors, while the actuator efforts remain bounded and continuous in the neighborhood of the singularity.Article Citation - WoS: 4Citation - Scopus: 6Et ve Balık Eti Hanehalkı Talebinin Mevsimselliği: Bir Kentsel Alan Örneği(Tubitak Scientific & Technological Research Council Turkey, 2005) Klasra, Mushtaq Ahmad; Fidan, HalilBu çalışma, Almost Ideal Demand System (AIDS)'i kullanarak, farklı mevsimlerde et ve balık için hane halkı talebine etkili faktörlerin tahmininde çıkarımlarda bulunmaktadır. Anket verileri kullanılarak, bütçe payı, talebin fiyat elastikiyeti, çapraz elastikiyet ve balık ve et için harcamalar, eşitlikler sistemi ile tahmin edilmiştir. Özellikle, Kurban Bayramı dönemlerinde bütçe paylarında artış olması durumu et ve balık tüketiminin mevsimsel etkisini inceleyen bu çalışmanın temel sonucu olmuştur. Bunun ötesinde, kentsel alanda yaşayan insanlar, hamsi hariç, fiyat artışlarına karşı duyarlı oldukları bulunamamıştır. Bu çalışma, politika yapıcıları, üreticiler ve pazarlama uzmanlarının izleyecekleri politikalarda etkili kaynak kullanımlarının düzenlenmesine, bu sonuçların onlara yardımcı olabilmesi bakımından önemlidir.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: 10Citation - Scopus: 15Detection of Hand Osteoarthritis From Hand Radiographs Using Convolutional Neural Networks With Transfer Learning(Tubitak Scientific & Technological Research Council Turkey, 2020) Erbay, Hasan; Maras, Hadi Hakan; Ureten, KemalOsteoarthritis is the most common type of arthritis. Hand osteoarthritis leads to specific structural changes in the joints, such as asymmetric joint space narrowing and osteophytes (bone spurs). Conventional radiography has traditionally been the primary method of visualizing these structural changes and diagnosing osteoarthritis. We aimed to develop a computerized method that is capable of determining the structural changes seen in radiography of the hand and to assist practitioners in interpreting radiographic changes and diagnosing the disease. In this retrospective study, transfer-learning-based convolutional neural networks were trained on a randomly selected dataset containing 332 radiography images of hands from an original set of 420 and were validated with the remaining 88. Multilayer convolutional neural network models were designed based on a transfer learning method using pretrained AlexNet, GoogLeNet, and VGG-19 networks. The accuracies of the models were 93.2% for AlexNet, 94.3% for GoogLeNet, and 96.6% for VGG-19. The sensitivities of these models were 0.9167 for AlexNet, 0.9184 for GoogLeNet, and 0.9574 for VGG-19, while the specificity values were 0.9500, 0.9744, and 0.9756, respectively. The performance metrics, including accuracy, sensitivity, specificity, and precision, of our newly developed automated diagnosis methods are promising in the diagnosis of hand osteoarthritis. Our computer-aided detection systems may help physicians in interpreting hand radiography images, diagnosing osteoarthritis, and saving time.Article Citation - WoS: 2Citation - Scopus: 4A New Systematic and Flexible Method for Developing Hierarchical Decision-Making Models(Tubitak Scientific & Technological Research Council Turkey, 2015) Beldek, Ulas; Leblebicioglu, Mehmet Kemal; Lebleb Iciog lu, Mehmet Kemal; Belde, UlaşThe common practice in multilevel decision-making (DM) systems is to achieve the final decision by going through a finite number of DM levels. In this study, a new multilevel DM model is proposed. This model is called the hierarchical DM (HDM) model and it is supposed to provide a flexible way of interaction and information flow between the consecutive levels that allows policy changes in DM procedures if necessary. In the model, in the early levels, there are primary agents that perform DM tasks. As the levels increase, the information associated with these agents is combined through suitable processes and agents with higher complexity are formed to carry out the DM tasks more elegantly. The HDM model is applied to the case study 'Fault degree classification in a 4-tank water circulation system'. For this case study, the processes that connect the lower levels to the higher levels are agent development processes where a special decision fusion technique is its integral part. This decision fusion technique combines the previous level's decisions and their performance indicator suitably to contribute to the improvement of new agents in higher levels. Additionally, the proposed agent development process provides flexibility both in the training and validation phases, and less computational effort is required in the training phase compared to a single-agent development simulation carried out for the same DM task under similar circumstances. Hence, the HDM model puts forward an enhanced performance compared to a single agent with a more sophisticated structure. Finally, model validation and efficiency in the presence of noise are also simulated. The adaptability of the agent development process due to the flexible structure of the model also accounts for improved performance, as seen in the results.