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Date of Conference: 16-19 May 2016 Conference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016 In this paper, we study multi-class classification of tweets, where we introduce highly efficient dimensionality reduction techniques suitable for online processing of high dimensional feature vectors generated from freely-worded text. As for the real life case study, we work on tweets in the Turkish language, however, our methods are generic and can be used for other languages as clearly explained in the paper. Since we work on a real life application and the tweets are freely worded, we introduce text correction, normalization and root finding algorithms. Although text processing and classification are highly important due to many applications such as emotion recognition, advertisement selection, etc., online classification and regression algorithms over text are limited due to need for high dimensional vectors to represent natural text inputs. We overcome such limitations by showing that randomized projections and piecewise linear models can be efficiently leveraged to significantly reduce the computational cost for feature vector extraction from the tweets. Hence, we can perform multi-class tweet classification and regression in real time. We demonstrate our results over tweets collected from a real life case study where the tweets are freely-worded, e.g., with emoticons, shortened words, special characters, etc., and are unstructured. We implement several well-known machine learning algorithms as well as novel regression methods and demonstrate that we can significantly reduce the computational complexity with insignificant change in the classification and regression performance.

Date of Conference: 2-5 May 2018 In this paper, we study online nonlinear data regression and propose a highly efficient long short term memory (LSTM) network based architecture. Here, we also introduce on-line training algorithms to learn the parameters of the introduced architecture. We first propose an LSTM based architecture for data regression. To diminish the complexity of this architecture, we use an energy efficient operator (ef-operator) instead of the multiplication operation. We then factorize the matrices of the LSTM network to reduce the total number of parameters to be learned. In order to train the parameters of this structure, we introduce online learning methods based on the exponentiated gradient (EG) and stochastic gradient descent (SGD) algorithms. Experimental results demonstrate considerable performance and efficiency improvements provided by the introduced architecture.

Medical Technologies National Congress (TIPTEKNO) -- NOV 08-10, 2018 -- Magusa, CYPRUS WOS: 000467637600004 In this paper, a post-operative recurrence estimation tool called Sorbellini's nomogram for the kidney cancer patients showing no metastates is introduced and a novel application for mobile devices based on this model is developed for the physician's follow up procedures. The TNM stage, tumor size, nuclear (Fuhrman) grade, the existance of necrosis and vascular invasion are employed as the input parameters for this software to predict the recurrence probability in mentioned patients. Finaly, the performance analyses are carried out to verify the reliability of the application. Biyomedikal Klinik Muhendisligi Dernegi, Izmir Katip Celebi Univ, Biyomedikal Muhendisligi Bolumu

3rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEG, WOS: 000459847400034, Bone drilling operation is widely used method in surgery. This operation must be done with hight care. In the case of failur some demage might be happened. In this paper a new technich is presented. By this method 1,5 mm precision is optained., BMBB, Istanbul Teknik Univ, Gazi Univ, ATILIM Univ, Int Univ Sarajevo, Kocaeli Univ, TURKiYE BiLiSiM VAKFI

UF-EMG test, in which non-invasive uroflowmetry (UF) and electromyography (EMG) signals are simultaneously recorded, is frequently used in children diagnosed with lower urinary tract dysfunction disease (AUSD) and its treatment. In the literature, independent (single) UF signals and integrated (dual) UF-EMG signals are graded many times but there is no classification study of UF-EMG integrated signals with Artificial Neural Networks (ANN), although studies have been done to classify UF signals with ANN. In this paper, it was aimed to classify the UF-EMG signals recorded from pediatric patients during the UF-EMG tests in Urodinami Center of Gulhane Education and Research Hospital using ANN. 773 (80%) of the 967 patients with an average age of 8 were used for training and 194 (20%) were used for the test. In YSA, the contribution of the features obtained from the EMG signals played a crucial role and was the main reason to improve the signal classification from 58% to 84.02%. The new classification method created by the obtained data does facilitate the interpretation of UF-EMG results for the clinical personnel in diagnosis, follow-up and treatment of patients. It is also aimed that the pediatric patients living in regions with less access to health care can be treated by providing an early and easy preliminary diagnostic tool., Günümüzde çocuklarda alt üriner sistem disfonksiyonu (AÜSD) hastalıklarının teşhisinde ve tedavinin takibinde, girişimsel olmayan (noninvaziv) üroflovmetri (UF) ve elektromiyografi (EMG) sinyallerinin eşzamanlı olarak kaydedildiği UF-EMG testi sıklıkla kullanılmaktadır. Literatürde, bağımsız UF sinyalleri ve UF-EMG sinyalleri birçok defa derecelendirilmiş, UF sinyallerinin Yapay Sinir Ağları (YSA) ile sınıflandırılmasına dair çalışmalar yapılmış olmasına rağmen, UF-EMG sinyallerinin birlikte kullanıldığı YSA ile sınıflandırma çalışması bulunmamaktadır. Bu çalışmada, Gülhane Eğitim ve Araştırma Hastanesi Ürodinami Merkezinde, pediatrik hastalara uygulanan UFEMG testleri sırasında kaydedilen sinyallerin YSA kullanılarak sınıflandırılması amaçlanmıştır. Yaş ortalaması 8 olan 967 hasta verisinden 773 adedi (%80) eğitim, 194 adedi (%20) ise test amaçlı kullanılmış, YSA’da EMG sinyallerinden elde edilen özniteliklerin katkısı başarı oranının %58‘den %84,02 seviyelerine gelmesini sağlamıştır. Elde edilen veriler ile oluşturulan yeni sınıflandırma metodu hastaların tanı, takip ve tedavisinde sağlık personelinin UF-EMG sonuçlarını yorumlamasında kolaylık sağlamayı; sağlık hizmetine ulaşma imkânı daha az olan bölgelerdeki çocuk hastalara, daha erken ve kolay ön tanı konularak uygun tedaviye yönlendirme imkânı sağlamayı hedeflemektedir.

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100575 Large scale dictionaries such as wordnets are one of the important structures used in natural language processing. Wordnet is a comprehensive dictionary containing semantic relations including synonyms, antonyms, etc. In this paper, we try to extract Hypernym-Hyponym relations which are one of the main parts of WordNet. For this aim, we used Wikipedia, Contemporary Dictionary of Turkish and Wiktionary as corpora. We used Finite State Machines for developing several rules for Hypernym-Hyponym extraction. Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100213 Superpixel based methods have recently shown success in scene segmentation and labeling. In scene labeling, a superpixel algorithm is used first to segment the image into visually consistent small regions; then several feature descriptors are computed and classification is performed for each superpixel. In this paper, Kernel Codebook Encoding (KCB) of superpixel features is proposed. In KCB feature vectors are mapped to multiple codewords in a soft manner, instead of the usual hard quantization. The weights assigned to the codewords are determined by a kernel distance function. KCB method is used for encoding of SIFT features in SuperParsing image parsing algorithm. The developed approach is tested on the SIFT Flow dataset consisting of 2,688 images and 33 classes, and achieves 2.7% increase in parsing accuracy over SuperParsing. Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100519 Along with the widespread use of technology, there have been many studies on human-computer relation recently. Study of the effects of computer systems on human education can be shown as an example of this. In this paper, a reliable and real time tangible user interface system developed for the air drum game which is used both for game and computer based training programs is presented. A user can perform a play action in six different directions using electronic drum sticks. A developed algorithm detects the direction of moving stick by processing sensor data taken from these sticks. Information about the stick which is moved and its direction are sent to the sound system to play the sound file of the relevant drum instrument. In this way the user is presented with a realistic drum experience. The developed system has been tested by different users in real world and its performance has been reported. The results verify the reliability and usability of the electronic drum game. Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY, WOS: 000413813100200, In this paper, the performance of direct current informative subcarrier intensity modulation (DCI-SIM) which is proposed to enhance the power efficiency of subcarrier intensity modulation (SIM) is investigated in visible light communication. The BER performance of DCI-SIM is compared with SIM, pulse amplitude modulation (PAM) and, enhanced unipolar orthogonal frequency division multiplexing (eU-OFDM) for different spectral efficiencies. Using analytical derivations and simulation results, we show that the DCI-SIM is the most power efficient modulation technique among others, and that the power efficiency increases with the spectral efficiency. Furthermore, we optimize the constellation of 64-DCI-SIM and present the results., Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100251 The Internet and social media provide a major source of information about people's opinions. Due to the rapidly growing number of online documents, it becomes both time-consuming and hard task to obtain and analyze the desired opinionated information. Sentiment analysis is the classification of sentiments expressed in documents. To improve classification perfromance feature selection methods which help to identify the most valuable features are generally applied. In this paper, we compare the performance of four feature selection methods namely Chi-square, Information Gain, Query Expansion Ranking, and Ant Colony Optimization using Maximum Entropi Modeling classification algorithm over Turkish Twitter dataset. Therefore, the effects of feature selection methods over the performance of sentiment analysis of Turkish Twitter data are evaluated. Experimental results show that Query Expansion Ranking and Ant Colony Optimization methods outperform other traditional feature selection methods for sentiment analysis. Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

In this paper, a computationally efficient method is proposed for modeling the indoor visible light communications (VLC) channels using a non-sequential ray tracing technique. We created three dimensional realistic simulation environment to depict indoor scenarios specifying the geometry of the indoor environment, the objects inside, the reflection characteristics of the surface materials as well as the characteristics of the transmitter and receiver. We then compute the received optical power and the delay of direct/indirect rays which are used to obtain the channel impulse response (CIR). Finally, LMS (least mean squares) and RLS (recursive least squares) iterative channel equalization techniques which are wildly employed in traditional electrical wireless communications are tested at the receiver of the VLC system. Their convergence rates as well as impacts on the BER performances are investigated by determining the optimal control parameters of these algorithms. It is concluded that for the equalizer operating with its optimal parameters, the BER performances of the VLC systems are very sensitivie to the field of view (FOV) values.

24th Signal Processing and Communication Application Conference (SIU) (2016 : Zonguldak, TURKEY), Critical Infrastructure Security had always been an issue. With the technological advancements, there has been a continuous inflow of novel methods for critical infrastructure security. In this paper, design, implementation, and field tests of a novel critical infrastructure security system based on wireless sensor networks is presented.

24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY, WOS: 000391250900110, 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., IEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engn

In this paper, a new optical orthogonal frequency division multiplexing (OFDM) method is proposed for multiple-input multiple-output (MIMO) visible light communications (VLC) systems. In the new scheme, non-DC biased optical OFDM (NDC-OFDM) and optical spatial modulation (OSM) methods are combined to obtain a novel optical OFDM scheme which has a better error performance. The new scheme is named as non-DC biased optical spatial modulation OFDM (NDC-OSM-OFDM). It is shown via computer simulations that the proposed scheme achieves better bit error rate (BER) performance than DC-biased optical spatial modulation OFDM (OSM-OFDM-DC), asymmetrically clipped optical spatial modulation OFDM (OSM-OFDM-AC) and NDC-OFDM.

Compressed sensing theory shows that any signal which is defined as sparse in a given domain can be reconstructed using fewer linear projections instead of using all Nyquist-rate samples. In this paper, we investigate basis pursuit, matching pursuit, orthogonal matching pursuit and compressive sampling matching pursuit algorithms, which are basic compressed sensing based algorithms, and present performance curves in terms of mean squared error for various parameters including signal-to-noise ratio, sparsity and number of measurements with regard to mean squared error. In addition, accuracy of estimation performances has been supported with theoretical lower bounds (Cramer-Rao lower bound and deterministic lower mean squared error). Considering estimation performances, compressive sampling matching pursuit yields the best results unless the signal has a non-sparse structure.

23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEY WOS: 000380500900192 Superpixels recently gained in importance in image segmentation and classification problems. In scene labeling the image is initially segmented into visually consistent small regions using a superpixel algorithm; then, superpixels are parsed into different classes. Classification performance heavily depends on the properties and parametric settings of the superpixel algorithm in use. In this paper, a method is proposed to improve scene labeling accuracy by fusing at classifier level the results of multiple superpixel segmentations. First, likelihood ratios are determined for superpixel labels using simple, nonparametric SuperParsing algorithm, which requires no training. Then, final scene segmentation and labeling is performed by pixel-level fusion of the likelihood ratios that are computed for alternative superpixel segmentation scenarios. The proposed method is tested on the SIFT Flow dataset consisting of 2,688 images and 33 labels, and is shown to outperform SuperParsing in terms of classification accuracy. Dept Comp Engn & Elect & Elect Engn, Elect & Elect Engn, Bilkent Univ

In this paper a new grounded capacitance multiplier using two Voltage Differencing Current Conveyors (VDCCs), two resistors, and one grounded capacitor is presented. The proposed capacitance multiplier can be tuned electronically by changing the biasing current of the VDCC. Moreover, the circuit does not require any conditions of component matching. The performance of the proposed capacitance multiplier is verified, and simulated by using PSPICE with TSMC CMOS 0.18 μm process parameters. © 2015 IEEE.

19th National Biomedical Engineering Meeting (BIYOMUT) -- NOV 05-06, 2015 -- -- Istanbul, TURKEY, WOS: 000380507300012, Electroencephalogram (EEG)-based emotion recognition is a rapidly growing field. This paper presents a research study on identifying the changes caused by human emotions in brain signals through EEG records and further examines the availability of chaotic analysis for emotion prediction applications. We designed an efficient presentation including 30 pictures from International Affective Picture System (IAPS) which could stimulate the emotions of happiness, sadness and fear. A group of 20 persons consisting of 12 males and 8 females took place in our research study as subjects voluntarily. In order to acquire the EEG signals under picture induction environment, a total of 30 pictures that might reveal the feelings of happiness, sadness and fear were shown to the volunteer subjects that participated in the study voluntarily. Data acquired from EEG records were analyzed by using chaotic analysis through MATLAB program and two different attributes consisting of "Largest Lyapunov Exponent (LLE)" and "Correlation Dimension" were obtained. The mean values of each attribute that obtained through chaotic analysis were compared by using independent t-test and dependent t-test in SPSS program with 95% confidence interval and a P value of p

22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY B. Akar, Gozde/0000-0002-4227-5606 WOS: 000356351400423 In the last two decades the Internet technology has boosted and the connection speeds have been incrased from kilobits to hundred megabits scale. With the rising coverage of the Internet and the usage of mobile devices such as tablets and smart phones, the usage of social media and especially multimedia elements has been increased rapidly. This increment in streaming multimedia created a need for the assessment of the user experience on multimedia and especially video. Even though there are different Video Quality Assessment (VQA) methods for that purpose, most of them are Full-Reference (FR) or Reduced-Reference (RR). In today's world with many mobile devices, the application of these methods are not possible since they need the reference data. The No-Reference (NR) video metrics are much more suitable for the case. In this paper, the main objective is to evaluate a previously proposed NR VQA metric with a new dataset and to compare the results to other high-performance NR metrics such as G.1070 and G.1070E which do not utilize spatial and temporal characteristics of a given video sequence. Evaluation and comparison results show the accuracy and robustness of the proposed metric. IEEE, Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Engn

22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY WOS: 000356351400252 In this paper, an prediction speed method of hand open-close by using the Artificial Neural Network (ANN) surface electromyography (sEMG) signal is presented. The first step of this method is to analyze sEMG signal detected from the subject's right upper forearm and extract features using the mean absolute value (MAV), the root mean square (RMS), the variance (VAR), the standart deviation (STD), the median frekans of power spectrum (MDF), the mean frekans of PS (MNF), the maximum frekans of PS (MAXF). The second step is to import the feature values into an ANN to identify the speed of hand open-close (SHOC). Based on the results of experiments, it is concluded that this method is effective in prediction of SHOC. IEEE, Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Engn

In this paper, we present a cooperative communication system employing maximum ratio transmission technique and its outage probability performance over Rayleigh fading channels. Since maximum ratio transmission can achieve full diversity when used at tranmitters having multiple antennas while requiring no complexity increase at the receiver, the proposed system can be a preferable structure to be used both at the source and amplify-forward type relays of wireless networks to provide high speed and reliable transmission in practice. For this system, average end-to-end signal to noise ratio is analyzed mathematically, moreover, our computer simulation results show the error performance for several scenarios.

22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY Akleylek, Sedat/0000-0001-7005-6489 WOS: 000356351400193 The demand to lattice-based cryptographic schemes has been inreasing. Due to processing unit having multiple processors, there is a need to implements such protocols on these platforms. Graphical processing units (GPU) have attracted so much attention. In this paper, polynomial multiplication algorithms, having a very important role in lattice-based cryptographic schemes, are implemented on a GPU (NVIDIA Quadro 600) using the CUDA platform. FFT-based and schoolbook multiplication methods are implemented in serial and parallel way and a timing comparison for these techniques is given. It's concluded that for the polynomials whose degrees are up to 2000 the fastest polynomial multiplication method is iterative NTT. IEEE, Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Engn

22nd IEEE Signal Processing and Communications Applications Conference (SIU) (2014 : Trabzon), In fading channels to get diversity gain, transmitted data can be repeated in time or frequency. Constellation reaarangement can be used instead of using the same signal constellation for each repeated transmission. In this method, symbols and the points in the signal space can be chosen differently for each one of the diversity branches. On the other hand, power allocation is another method that improves the performance. In this paper, repetition coding that uses signal constellations of 4-pulse amplitude modulation and signal constellation reaarangement are compared for both fixed and optimal power allocation. It is observed that most of the gain is due to constellation rearrangement and advantages of power allocation are limited.

In this paper, we developed an interactive global illumination application for mobile devices and we show that interactive filtered importance sampling is possible even with a low-power mobile graphics processing unit (GPU). Taking the limited power and the screen size of mobile devices into account, we designed a user interface that allows selecting different predefined objects, environments and textures. With our implementation, desired materials can be visualized interactively by changing the parameters of Bidirectional Reflectance Distribution Function (BRDF).

22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY WOS: 000356351400039 Currently, chaotic signal generators is of importance in cryptographic applications and chaotic communication systems. One of the significant field of the chaotic signal oscillators are random number generators. In this paper, an FPGA-based new true random number generator system using discrete-time chaotic signal generator is presented. The system designed incorporates the Sprott 94 G chaotic system based on an FPGA deployed with IEEE 754 standard. In order to produce random bits a quantification process has been performed on the results produced by the chaotic oscillator unit. Furthermore, the XOR method has been determined as restoring function to obtain a true random bit generator. The maximum operating frequency of FPGA-based true random number generator has been able to reach up to 399,383 MHz. The 20,000-bit sequence has been generated by the designed system and they have been saved to the test result file. They have been tested using NIST test suite and FIPS-140-1 standards and successful results have been obtained. It is concluded that the FPGA-based system is able to be used in cryptologic applications. IEEE, Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Engn

21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS WOS: 000325005300016 In literature video coding efficiency of H. 264 standard has been improved using decoder-side super-resolution (SR). In this paper SR estimation is used during encoding in place of skip/direct mode prediction of H. 264 standard and coding performance is optimized. First P-and B-frames are downsampled and H. 264 encoded at lower resolution (LR). Then reconstructed LR frames are super-resolved using decoder-side motion estimation. Also bicubic interpolation of the LR frame is used as an alternative to SR reconstruction. A rate-distortion optimal mode selection algorithm determines for each macroblock which of the two reconstructions to use as skip/direct mode prediction. Simulations indicate an average of 1.36 dB PSNR improvement or 30.3% bitrate reduction at low bitrates when compared to H. 264 standard. Average PSNR gains reach as high as 3.63 dB depending on the video content.

This paper examines the performance of Hidden Markov Tree model based weights in reconstruction quality for an existing task-aware compressive video coding system which aims object detection specifically. The existing system utilizes weights in reconstruction which are computed by tracking of the foreground object. The proposed system acquires similar average PSNR with the existing one which reported some improvement compared to the conventional unweighted reconstruction at low sampling rates. Furthermore, it is a little bit better than the existing system at higher sampling rates. It can be inferred from this study that Bayesian approaches that take account structural dependencies between transformation coefficients has the potential of improving reconstruction quality for such a compressive video coding system with object detection task.

21st Signal Processing and Communications Applications Conference (SIU) --APR 24-26, 2013 -- CYPRUS, Çolak, M. Alper (Arel Author), Bölükbaş, Deniz (Arel Author) --- WOS: 000325005300275, As one of the renewable energy sources, wind energy has received great attention in Turkey as in the rest of the world in the last decade. Despite of this trend, there is an increasing number of assessment reports stating the impact of wind farms on the performance degradation of electromagnetic propagation systems. In this paper, wind turbines' effects on radar detection performance are investigated using radar data which we constructed using a real terrain scenario and two-dimensional propagation analysis employing different numerical electromagnetic techniques.

Ultra wideband impulse radio (UWB-IR) technology has been defined in the IEEE 802.15.4a standard for location and ranging applications. In this paper, UWB-IR sensors are considered in wireless sensor networks (WSNs) with two different IEEE 802.15.4a based signalling; (i) binary pulse position modulation (BPPM) and (ii) combined BPPM/binary phase shift keying (BPPM/BPSK) modulation, for the detection of primary users. In addition to the modulation effects, the effects of each sensor's false alarm and misdetection performances and the effect of signal-to-noise ratio (SNR) of the sensor-fusion center link have been investigated. For practical implementation of the WSN, some suggestions have been provided.

Date of Conference: 24-26 April 2013 In this paper, variability of trend over Turkey is investigated statistically by Sliding Window Statistical Analysis (SWSA) method. First and second moment of the variability of ionospheric trend is calculated by SWSA method in a period of several years. Variance bounds are also obtained. This method is applied to Total Electron Content (TEC) estimates which are obtained from Turkish National Permanent GPS Network (TNPGNActive) between 2009 and 2012. The Wide Sense Stationarity (WSS) period of ionospheric trend over Turkey is determined for the first time. © 2013 IEEE.

Date of Conference: 18-20 April 2012 In this paper, performances of low complexity time based range estimators that are employed for ultra wide-band (UWB) systems are compared using experimental data. These estimators are widely used in practical applications due to their low complexity. However, performances of these estimators vary depending on the choice of certain parameters such as the threshold value and window size. The optimal values for these parameters are investigated for several situations using the data acquired in the experiments. © 2012 IEEE.

Date of Conference: 20-22 April 2011 Conference Name: 19th Signal Processing and Communications Applications Conference, SIU 2011 In this paper, a new histogram based auto-focusing method for thermal cameras is proposed. This proposed method is realized by FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) working together and simultaneously. HF (High Frequency) component, obtained from real-time image flow by FPGA and DSP is used for auto-focusing process. Proposed method is able to determine the focus direction from the HF component produced in the process of histogram equalization by FPGA, unlike Fourier transform and pixel differenve based methods in the literature. With this superiority, proposed method requires no extra calculation for thermal cameras for which histogram equalization is necessary. Analysis show that proposed method is successful on the simulations and scanning thermal cameras.

IEEE 17th Signal Processing and Communications Applications Conference -- APR 09-11, 2009 -- Antalya, TURKEY WOS: 000273935600007 In 1979, Blakley and Shamir proposed a new concept called secret sharing based on dividing the secret among n participants. This method, also called the (t, n) threshold scheme, requires at least I of the n participants for revealing the secret. Chen used the Blakley's geometry based secret sharing scheme for secret image sharing in 2008. Share image sizes are the same with the original secret image. Geometry based secret shoring scheme that uses the hyperspherical functions, proposed by Wu and He in 1995 is adopted to secret image sharing in this paper. Share sizes are 1/t smaller than that of the Chen's scheme as stated in results. Smaller shares are an important criterion for evaluation of Secret Image sharing schemes. Using geometry based SS scheme different from Blakley's scheme resulted in smaller shadow images. IEEE

IEEE 17th Signal Processing and Communications Applications Conference -- APR 09-11, 2009 -- Antalya, TURKEY, WOS: 000273935600032, In this paper, a novel Mycielski based approach for wind speed data generation is developed and presented. The efficincy of the proposed approach is tested using hourly wind speed data obtained from Izmir region. To test the efficiecy of the approach, the four year-long measured data are seperarted into two parts: data belonging to first three years are used for training whereas the remaining one-year data are used for testing and accuracy comparison purposes. In order to compare the efficiency of the proposed generation method, the same data are used in artificial wind speed generation with the classical method of first order Markov chains. Results indicate that the proposed Mycielski based algorithm produces better quality artificial data as compared to previous methods., IEEE

A powerful method in analysis of large data sets where there are many natural clusters with varying statistics such as different sizes, shapes, density distribution, is the use of sel-forganizing maps (SOMs) [1]. However, further processing tools, such as visualization, interactive clustering, are often necessary to capture the clusters from the learned SOM knowledge. A recent visualization scheme, CONNvis [2], and interactive clustering from CONNvis, utilizes the data topology for SOM knowledge representation by using a weighted Delaunay graph, CONN. In this paper, an automated clustering scheme for SOMs, SOMcluster, which is a two-level clustering of CONN by the skills obtained in the interactive process, is proposed. It is shown that SOMcluster, which does not require the number of clusters a priori, is used successfully for automated segmentation of a remote sensing spectral image which has many clusters some of which were unidentified in previous works.

IEEE 17th Signal Processing and Communications Applications Conference -- APR 09-11, 2009 -- Antalya, TURKEY, WOS: 000273935600074, This paper proposes the use of single sideband modulation technique with Gaussian and band pass fillers for the analysis of the thermal lens fringe to obtain the map of the refractive index change. Maps of the refractive index and phase change are achieved by using single side band modulation technique with Gaussian and band pass filters. Consequently it is seen that single side band modulation technique with Gaussian filter shows more accurate results., IEEE

The low data rate, accurate location-ranging Wireless Personal Area Network (WPAN) standard IEEE 802.15.4a, which is based on ultra-wideband (UWB) impulse radios, suggests using linear combination of pulses to reduce interference to coexisting primary systems. In this paper, we consider possible implementations of linear combination of pulses as suggested in the standard, and study the generated notches in the resulting code spectrum. Using the z-transform approach, we show that the number of these notches is limited and the notch locations are not flexible due to the limited number of pulses allowed by the standard. We also make some suggestions for increasing the number of notches at desired frequencies.

In stereoscopic 3D video, it is well-known that humans can perceive high quality 3D video provided that one of the views is in high quality. Hence, in stereo video encoding, the best overall rate vs. perceived-distortion performance may be achieved by reduction of the spatial, temporal and/or quantization resolution of the second view, while keeping the first view in full resolution. Objective stereo video quality metric is a crucial point for the success of unequal rate allocation. Since the perceived 3D video quality does not correlate well with the average PSNR of the two views, we proposed a new quantitative measure using a weighted combination of two PSNR values and a jerkiness measure [1]. In this paper, we investigate whether the PSNR weights should be related with spatial activity in different scaling options and video contents. Spatial activity is examined in terms of blockiness and blur. The optimal weights for some specific experiments are determined by matching, i.e. searching the best correlation between, subjective quality test results and the objective measure scores on a set of test videos.

Date of Conference: 9-11 April 2009 Conference Name: IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 In the last few years, there is great increase in capture and representation of real 3-Dimensonal scenes using 3D animation models. The 3D signals are then compressed, transmitted to the client side and reconstructed for the user view. Each step mentioned here opened a new subject in the field of signal processing. While processing these models, using the model as a whole is not the best approach. Therefore clustering the model vertices became a very common method. For example, it is very common to use motion based clustering in animation compression. In this paper a new dynamic model clustering algorithm is proposed. Animation vertices are first put through PCA and partitioned into their eigenvalues and eigenvectors. The eigenvectors found using the proposed method can be called eigentrajectories. Then the dot product of the these eigentrajectories with the trajectories of the animation vertice are found. These coefficients are used to cluster the animation model. The results and the comparisons with a similar approach show that the proposed algorithm is successful.

IEEE 16th Signal Processing and Communications Applications Conference -- APR 20-22, 2008 -- Aydin, TURKEY WOS: 000261359200081 The analysis of antibiotics towards a microorganism responsible of an illness is evaluated using the antibiogtam test. In the diffusion method which is the most popular implementation of this test, several paper disks, each one impregnated with a different antibiotic, are spread all over a agar plate which is diffused standard cultivation prepared from test microorganism. After some time, the reaction produced by the antibiotics against the microorganism appear as circular areas of different texture that have grown around the antibiotic disks. Currently, the evaluation and measurement of these areas, called Inhibition Zones, is carried out by human visual inspection via caliper in the laboratories. In this study, a new segmentation and analysis strategy to automatically measure the inhibition zone and disk diameters in antibiograms is presented. It is based on the application of Circular Hough Transform surrounded appropriate pre- and post-processing stages. IEEE

In this paper, electronically tunable square root domain low pass and band pass filter is designed by using state space synthesis procedure. A dummy DC input is added to state space equations in order to realize the filter. Natural frequency of the proposed filter could be tuned by varying the currents of the current sources. The designed filter is simulated in PSpice using TSMC 0.35 ?m CMOS technology parameters. By varying the values of the current sources, the natural frequencies is swept for 2.95 MHz-8.31 MHz and 3.67 MHz-8.46 MHz, for band pass and low pass filters respectively. Also THD and noise analysis are simulated. The obtained simulation results are given.