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Biomimetic nanocoating of bone plates [Kemik Plakalarinda Biyomimetik Nanokaplamalar]

Aydin R.S.T. | Uyanik S.

Conference Object | 2017 | 2016 20th National Biomedical Engineering Meeting, BIYOMUT 2016

Infection and nonunion following fracture fixation remain as unsolved problems of orthopaedic surgery. This condition may lead to implant failures and necessitate further surgical interventions, ending up with increased morbidity and treatment costs. In this study, 316L stainless steel bone plates were coated with stronsiyum containing bone like hydroxyapaptite (HA) (1. Layer) and silver enriched polylactic acid coating (2. Layer). Thus, firstly, 2.0 mm. routinely used fracture fixation plates were first coated by immersing strontium containing simulated body fluid (×10) in order to nanocoat with HA layer. Then, plates will be coate . . .d with Ag enriched PLA and their surface properties will were characterized. © 2016 IEEE Daha fazlası Daha az

Real-time control based on NARX neural network of hexarotor UAV with load transporting system for path tracking

Altan A. | Aslan O. | Hacioglu R.

Conference Object | 2018 | 2018 6th International Conference on Control Engineering and Information Technology, CEIT 2018

The control of equipment such as camera gimbal, Vertical Take-Off and Landing (VTOL) and Load Transporting System (LTS) on Unmanned Aerial Vehicle (UAV) with its own flight control directly affects the performance of the mission in tasks such as tracking the target along the specified path and leaving payloads on the targets specified in the dangerous areas. In this study, neural network based real-time control of a hexarotor UAV is performed so that the payloads on the targets determined by path tracking can be left with minimum error. The Nonlinear AutoRegressive eXogenous (NARX) model of the UAV is obtained after the flight data . . .are passed through the pre-processing, feature extraction and feature selection stages. The obtained neural network model is embedded in the flight control card to realize real time path tracking of the UAV. The three payloads in the cubic structure are both transported by the originally designed LTS and left with the help of LTS to targets on the path. Environmental testing is conducted taking into account the limitations of the physical properties of the LTS and specified path tracking on the autonomously moving UAV, and the impact on proposed NARX control algorithm's mission performance is examined. © 2018 IEEE Daha fazlası Daha az

Online dead body detection experiment with an unmanned underwater vehicle [Bir insansiz sualti araci ile çevirimiçi ceset tanilama deneyi]

Berik M. | Kartal S.K.

Conference Object | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this study, real-time online body detection under water was conducted using an unmanned underwater observation tool. According to the underwater position of the vehicle, data from the vehicle camera is provided to identify different body parts of a body in a real-time video stream. Here we present an approach for underwater human body detection based on the use of highly educated classifiers. The algorithm's performance in real time video shooting of the car is optimized to reduce the false positive rate by aiming to identify a corpse part of each picture frame. According to the results obtained, it was ensured that the corpse pa . . .rts were successfully detected under changing conditions with incorrect positive perception. Algorithms were developed using the Pyhton program. © 2018 IEEE Daha fazlası Daha az

Classification of power quality events signals with pattern recognition methods by using Hilbert transform and genetic algorithms [Güç kalitesi bozulma sinyallerinin hilbert dönüşümü ve genetik algoritmalar kullanilarak örüntü tanima yöntemleri ile siniflandirilmasi]

Karasu S. | Sarac Z.

Conference Object | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this study, instantaneous envelope, phase and frequency series are obtained by Hilbert transform for Power Quality (PQ-Power Quality) disturbances signals. Rms, Thd, energy, entropy and statistical properties are applied to these series. With the wrapper feature selection approach, a set of features is obtained that has a small number of feature subset and a high performance from 36 features. Genetic Algorithm (GA) is used as a search algorithm and the classifier algorithm is K nearest neighborhood (KNN). Support Vector Machines (SVM) for selected features are also used in the classification step. The learning algorithm is obtain . . .ed as KNN, the model performance that classifies PQ classes with 99.07%. The number of feature sets is 8. In addition, performance under noisy data is also tested to show that the generated model has a generalized structure. © 2018 IEEE Daha fazlası Daha az

Simulation of Parkinsonian Basal nuclei with network motifs

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.1 - 4

Nowadays, neurodegenerative diseases which affect human life quite negatively with motor, cognitive and psychiatric disorders are becoming widespread. One of the most common neurodegenerative disorder is Parkinson's disease. Recent electrophysiological experiments have shown that Basal Ganglia, a special region in the midbrain, is related to Parkinsonism. Beta frequency oscillations, which are important symptoms of Parkinson's disease, emerge intensively in Globus Pallidus and Subtalamus nuclei. In this study, anatomical connections of Globus Pallidus and Subtalamus are constructed computationally, and the cellular properties that g . . .ive rise to emergence of beta oscillations are investigated. © 2017 IEEE Daha fazlası Daha az

Cell Master: A Versatile and User-Friendly Educational Software for Simulation of Neuronal Dynamics [Cell Master: Nöronal Dinamiklerin Simülasyonu için Çok Yönlü ve Kullanici Dostu Bir Egitim Yazilimi]

Ozcan Z. | Kayikçioglu I. | Yildirim O. | Köse C. | Kayikçioglu T.

Conference Object | 2018 | 2018 Medical Technologies National Congress, TIPTEKNO 2018 , pp.1 - 4

In this study, A user-friendly, versatile and easily accessible educational software design was done by using NEURON hoc programming in order to investigate the dynamics, biophysical properties of nerve cells and their responses to various stimulation. With the help of interfaces which prepared for users to be assisted visually, it is aimed to be able to easily perform almost any application desired. This software allows users to perform their simulations without the need to write any code. Considering the features given in detail in the study, it has been suggested to use the software in neuroscience education. © 2018 IEEE.

Ultrasonic signal delay determination for distance estimation in underwater space [Sualti Uzaylarda Mesafe Kestirimi İçin Ultrasonik İşaret Gecikmesinin Belirlenmesi]

Onur, Tuğba Özge | Hacıoğlu, Rıfat

Proceedings | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.1 - 4

Reverberation and multipath propagation afîect the accuracy of time of flight (TOF) estimation in confined underwater medium. In this paper, time delay has been estimated by obtaining the transmitted signal and first echo signal from measured signal acquised by using a wideband transducer with 5 MHz central frequency. Cross-correlation (CC) and generalized cross-correlation (GCC) methods have been applied to the obtained signals and their performances have been compared. The results show that GCC method has better performance for time delay estimation in confined underwater medium where multipath propagation and reverberation are se . . .vere. © 2017 IEEE Daha fazlası Daha az

Prediction of the optimal threshold value in DF relay selection schemes based on artificial neural networks

Kara, Ferdi | Kaya, Hakan | Erkaymaz, Okan | Öztürk, Ertan

Proceedings | 2016 | Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016 , pp.1 - 4

In wireless communications, the cooperative communication (CC) technology promises performance gains compared to traditional Single-Input Single Output (SISO) techniques. Therefore, the CC technique is one of the nominees for 5G networks. In the Decode-And-Forward (DF) relaying scheme which is one of the CC techniques, determination of the threshold value at the relay has a key role for the system performance and power usage. In this paper, we propose prediction of the optimal threshold values for the best relay selection scheme in cooperative communications, based on Artificial Neural Networks (ANNs) for the first time in literatur . . .e. The average link qualities and number of relays have been used as inputs in the prediction of optimal threshold values using Artificial Neural Networks (ANNs): Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) networks. The MLP network has better performance from the RBF network on the prediction of optimal threshold value when the same number of neurons is used at the hidden layer for both networks. Besides, the optimal threshold values obtained using ANNs are verified by the optimal threshold values obtained numerically using the closed form expression derived for the system. The results show that the optimal threshold values obtained by ANNs on the best relay selection scheme provide a minimum Bit-Error-Rate (BER) because of the reduction of the probability that error propagation may occur. Also, for the same BER performance goal, prediction of optimal threshold values provides 2dB less power usage, which is great gain in terms of green communication. © 2016 IEEE Daha fazlası Daha az

Computer-assisted diagnosis of vertebral column diseases by adaptive neuro-fuzzy inference system

Uzun, Rukiye | İşler, Yalçın | Erkaymaz, Okan | Kocadayı, Yasemin

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this study, a clustering algorithm based on adaptive neural fuzzy inference system (ANFIS) was used for computer-assisted diagnosis of the vertebral column disorder from machine learning databases of UCI (University of California Irvine). Features of pelvic incidence, pelvic tilt and lumbar lordosis angle given in this dataset was applied to the inputs of the algorithm. The performance of algorithm was evaluated using mean square error and regression coefficient criteria to discriminate patients with vertebral column disease from healthy subjects. As a result, the classification performance of 90.82% was obtained by using the gen . . .erated model of ANFIS. © 2018 IEEE Daha fazlası Daha az

A survey on security threats and authentication approaches in wireless sensor networks

Karakaya A. | Akleylek S.

Conference Object | 2018 | 6th International Symposium on Digital Forensic and Security, ISDFS 2018 - Proceeding2018-January , pp.1 - 4

Wireless sensor networks (WSN) are networks in which data obtained by observing the environment by a large number of sensors deployed in a specific area are sent securely to other sensors or centers in the network. These networks have the abilities of being not connected to a central node, self-managing and healing, not being connected to a specific network topology, multi-way routing, preserving the integrity and confidentiality of data, and being robust. Today's ongoing work: designing sensors that are resistant to harsh weather conditions, reducing energy consumption, designing low-cost sensors with high capacities, and making da . . .ta flow faster and safer. The data obtained from the sensors must be transmitted safely to the target. Wireless sensor networks have a large number of attack types (Sybil, Wormhole, Sinkhole, etc.) that threaten data flow. While designing security policies, a general structure is aimed at eliminating some or all of the attacks. For this reason, policies based on information security principles such as privacy, integrity, availability, authentication and non-repudiation have been developed. In this paper, current problems are assessed in the security of wireless sensor networks, and authentication security policies are discussed. © 2018 IEEE Daha fazlası Daha az

Similarity based anisotropic diffusion filter [Benzesime dayali Yön Bagimli Yayinim Filtresi]

Tanyeri U. | Incetas M.O. | Demirci R.

Conference Object | 2016 | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings , pp.1401 - 1404

Different filter methods to reduce noises occurred during image capture have been developed. One of the most effective image filters is diffusion filter. However, the major drawback of conventional diffusion filter is user-dependent. While noises are reduced with conductance coefficient arbitrarily selected, edge pixels are perceived such as noise. In this study, a novel anisotropic diffusion filter using similarity values obtained with the distance of each pixel to its neighbors has been proposed. Initially, similarity values of all image pixels are computed, and then they are used as conductance coefficients in diffusion filter. T . . .he mentioned value above is user dependent for conventional diffusion and it is constant for all pixels. On the other hand, it is made adaptive and eliminated user intervention with suggested approach. Developed method has been tested with different noise variances of images and experimental results have been compared with conventional diffusion filter. © 2016 IEEE Daha fazlası Daha az

Classification of power quality disturbances by using ensemble technique [Güç Kalitesi Bozulmalarinin Birlikte Çalişma Yöntemi ile Siniflandirilmasi]

Karasu S. | Başkan S.

Conference Object | 2016 | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings , pp.529 - 532

In this paper, 11 different power quality disturbances were automatically detected by using statistical features with wavelet transform and norm entropy techniques. The best of the created features were selected with forward selection algorithm. Performance of classification algorithms, Support Vector Machines (SVM), Multi Layer Perceptron (MLP), k Nearest Neighbor (KNN) and random subspace KNN (Sub-KNN) which is an ensemble method, were examined. Consequently, the best classification accuracy of 99.3% was achieved by using Sub-KNN and it was appeared that compared to other methods, this algorithm was more robust against the noise. . . .© 2016 IEEE Daha fazlası Daha az

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