Piri Reis University is a private university founded by the Turkish Maritime Education Foundation in 2008 in Istanbul, Turkey. Named after the Turkish admiral and cartographer Piri Reis , it is devoted to the education of maritime studies. Wikipedia.
Mert A.,Piri Reis University
Physiological Measurement | Year: 2016
It is a difficult process to detect abnormal heart beats, known as arrhythmia, in long-term ECG recording. Thus, computer-aided diagnosis systems have become a supportive tool for helping physicians improve the diagnostic accuracy of heartbeat detection. This paper explores the bandwidth properties of the modes obtained using variational mode decomposition (VMD) to classify arrhythmia electrocardiogram (ECG) beats. VMD is an enhanced version of the empirical mode decomposition (EMD) algorithm for analyzing non-linear and non-stationary signals. It decomposes the signal into a set of band-limited oscillations called modes. ECG signals from the MIT-BIH arrhythmia database are decomposed using VMD, and the amplitude modulation bandwidth B AM, the frequency modulation bandwidth B FM and the total bandwidth B of the modes are used as feature vectors to detect heartbeats such as normal (N), premature ventricular contraction (V), left bundle branch block (L), right bundle branch block (R), paced beat (P) and atrial premature beat (A). Bandwidth estimations based on the instantaneous frequency (IF) and amplitude (IA) spectra of the modes indicate that the proposed VMD-based features have sufficient class discrimination capability regarding ECG beats. Moreover, the extracted features using the bandwidths (B AM, B FM and B) of four modes are used to evaluate the diagnostic accuracy rates of several classifiers such as the k-nearest neighbor classifier (k-NN), the decision tree (DT), the artificial neural network (ANN), the bagged decision tree (BDT), the AdaBoost decision tree (ABDT) and random sub-spaced k-NN (RSNN) for N, R, L, V, P, and A beats. The performance of the proposed VMD-based feature extraction with a BDT classifier has accuracy rates of 99.06%, 99.00%, 99.40%, 99.51%, 98.72%, 98.71%, and 99.02% for overall, N-, R-, L-, V-, P-, and A-type ECG beats, respectively. © 2016 Institute of Physics and Engineering in Medicine.
Li Y.,National Renewable Energy Laboratory |
Calisal S.M.,University of British Columbia |
Calisal S.M.,Piri Reis University
Renewable Energy | Year: 2010
Three-dimensional effects in studying a vertical axis tidal current turbine are modeled using a newly developed vortex method. The effects on predicting power output and wake trajectory are analyzed in particular. The numerical results suggest that three-dimensional effects are not significant when the height of the turbine is more than seven times the turbine radius. Further discussions are presented focusing on the relationship between the turbine height and the angle of attack and the induced velocity on a blade of the turbine without arms. Besides the three-dimensional effects, arms effects are quantified with an analytical derivation of the polynomial formula of the relationship between arm effects and the tip speed ratio of the turbine. Such a formula provides a correction for existing numerical models to predict the power output of a turbine. Moreover, a series towing tank tests are conducted to study the three-dimensional effects as well as the arm effects. Good agreements are achieved between the results obtained with numerical calculations with the arm effects correction and the towing tank tests. Finally, three-dimensional effects are examined experimentally together with the arm effects by using an end-plate test, which suggests that the combinational effect is rather minimal. For turbine designers at the early design stage, we recommend that a two-dimensional model is acceptable considering the high cost of the three-dimensional model. © 2010 Elsevier Ltd.
Ozden M.T.,Piri Reis University
Eurasip Journal on Advances in Signal Processing | Year: 2013
A multichannel characterization for autoregressive moving average (ARMA) spectrum estimation in subbands is considered in this article. The fullband ARMA spectrum estimation can be realized in two-channels as a special form of this characterization. A complete orthogonalization of input multichannel data is accomplished using a modified form of sequential processing multichannel lattice stages. Matrix operations are avoided, only scalar operations are used, and a multichannel ARMA prediction filter with a highly modular and suitable structure for VLSI implementations is achieved. Lattice reflection coefficients for autoregressive (AR) and moving average (MA) parts are simultaneously computed. These coefficients are then converted to process parameters using a newly developed Levinson-Durbin type multichannel conversion algorithm. Hence, a novel method for spectrum estimation in subbands as well as in fullband is developed. The computational complexity is given in terms of model order parameters, and comparisons with the complexities of nonparametric methods are provided. In addition, the performance is visually and statistically compared against those of the nonparametric methods under both stationary and nonstationary conditions. © 2013 Ozden; licensee Springer.
Mert A.,Piri Reis University
Biomedical Engineering Letters | Year: 2014
Methods: A hybrid method is proposed using the independent component analysis (ICA) and the discrete wavelet transform (DWT) to reduce feature vectors of Wisconsin diagnostic breast cancer (WDBC) data set. Two independent components (ICs), and one approximation coefficient of the DWT are used as a reduced feature vector to classify breast cancer using PNN. Performance measures such as accuracy, sensitivity, specificity, Youden’s index and the receiver operating characteristics (ROC) curve are computed to indicate the advantages of the hybrid feature reduction.Results: The proposed feature reduction approach using ICA and DWT improves the diagnostic capability of the PNN classifier. The hybrid feature reduction has a higher diagnostic capability than the original thirty features using PNN as a classifier. Accuracy and sensitivity are 96.31% and 98.88%, while the results of the classification using the original thirty features are 92.09% and 95.52%.Conclusions: Feature reduction approach using ICA and DWT together increases the performance measures of breast cancer classification using PNN, while reducing computational complexity.Purpose: Early and correct diagnosis of a disease is vital for the success of treatment. Medical diagnostic decision support system can be used to improve the accuracy of the traditional diagnosis. As such, various pattern recognition methods are studied and applied to develop medical diagnostic decision support system. In this study, the effects of dimensionality reduction techniques with probabilistic neural network (PNN) on breast cancer classification are examined. © 2014, Korean Society of Medical and Biological Engineering and Springer.
Dedeoglu B.,Bogazici University |
Aviyente V.,Bogazici University |
Ozen A.S.,Piri Reis University
Journal of Physical Chemistry C | Year: 2014
Poly(silafluorene-phenylenedivinylene)s and poly((tetraphenyl)-silole- phenylenedivinylene)s are promising materials for use in explosives detection. Monomers and dimers of silafluorene- and silole-containing polymers for the detection of nitro-containing explosives are modeled with M062X/6-31G(d). The geometric features of silafluorene- and silole-containing dimers optimized with M062X/6-31G(d) agree well with experimental findings. The binding properties of explosive and nonexplosive materials have been differentiated by comparing the relative stabilities of their complexes with silafluorene- and silole-containing dimers. The interactions that promote binding in the complexation of silafluorene- and silole-containing polymers with explosives are studied with a small model to shed light on the origin of the stability of the complexes. The topology of the electron density was analyzed using the quantum theory of atoms in molecules (QTAIM) methodology to understand the nature of the noncovalent interactions that are responsible for analyte-polymer binding. The carbon and germanium analogues of silafluorene-containing dimers are modeled to better understand the role of silicon in these polymeric systems. The calculated HOMO-LUMO energy differences of the complexes of dimers with explosives correlate well with the stability of the complexes; both (HOMO-LUMO and stability) support the selectivities of silafluorene- and silole-containing polymers. The stabilities of the complexes have shown that silafluorene- containing polymer detects the analytes in the order of 2,4,6-trinitrotoluene (TNT) ∼ picric acid (PA) > 2,6-dinitrotoluene (DNT) > cyclotrimethylenetrinitramine (RDX) > nitrobenzene (NB), while the silole-containing polymer is able to detect the aromatic TNT but is not responsive to the nonaromatic RDX. © 2014 American Chemical Society.
Cansoy C.E.,Piri Reis University |
Cengiz U.,Canakkale Onsekiz Mart University
Colloids and Surfaces A: Physicochemical and Engineering Aspects | Year: 2014
In this work, the effect of wt.% of perfluoroalkyl content and also hydrocarbon chain length on oleophobic properties of perfluoroethyl alkyl methacrylate-methyl methacrylate (Zonyl-TM-MMA) copolymers was investigated. The wetting performance of p(Zonyl-TM-ran-MMA) copolymer films by hydrocarbon liquids was found to be strongly depended on perfluoroalkyl chain lengths. Besides, increase in hydrocarbon chain length also caused an increase in contact angle results of p(Zonyl-TM-ran-MMA) copolymer films due to the stronger cohesion interactions of liquid molecules and this resulted in weaker adhesion interactions between copolymer surface and hydrocarbon drop. It was also discovered that contact angle hysteresis, δcos. θ, values of copolymers depend on both wt.% Zonyl-TM content and also hydrocarbon chain length of liquids. © 2013 Elsevier B.V.
Mert A.,Piri Reis University |
Akan A.,Istanbul University
Digital Signal Processing: A Review Journal | Year: 2014
Signal decompositions such as wavelet and Gabor transforms have successfully been applied in denoising problems. Empirical mode decomposition (EMD) is a recently proposed method to analyze non-linear and non-stationary time series and may be used for noise elimination. Similar to other decomposition based denoising approaches, EMD based denoising requires a reliable threshold to determine which oscillations called intrinsic mode functions (IMFs) are noise components or noise free signal components. Here, we propose a metric based on detrended fluctuation analysis (DFA) to define a robust threshold. The scaling exponent of DFA is an indicator of statistical self-affinity. In our study, it is used to determine a threshold region to eliminate the noisy IMFs. The proposed DFA threshold and denoising by DFA-EMD are tested on different synthetic and real signals at various signal to noise ratios (SNR). The results are promising especially at 0 dB when signal is corrupted by white Gaussian noise (WGN). The proposed method outperforms soft and hard wavelet threshold method. © 2014 Elsevier Inc.
Ozden M.T.,Piri Reis University
IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC | Year: 2013
A channel shortening equalizer design for cognitive Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) communication systems is considered in this presentation. The proposed receiver consist of two sections : MIMO decision feedback equalizer (MIMO-DFE) and adaptive Viterbi detection. In MIMO-DFE section, a complete modified Gram-Schmidt orthogonalization of multichannel input data is accomplished using sequential processing multichannel Givens lattice stages, so that a Vertical Bell Laboratories Layered Space Time (V-BLAST) type MIMO-DFE is realized at the frontend section of the equalizer. Matrix operations are accordingly avoided, and only scalar operations are used. A highly modular and regular radio receiver architecture, that has a suitable structure for software defined radio implementations, is achieved. In connection with adaptive Viterbi detection section, a systolic array implementation for each channel is performed so that an receiver architecture with high computational concurrency is attained. The total computational complexity is given in terms of equalizer and desired impulse response filter lengths, and the number of data symbols used. The performance of the proposed equalizer under time-invariant and time-variant channel conditions is presented by means of mean squared error (MSE) and probability of error evaluations. © 2013 IEEE.
Akyuz E.,Piri Reis University |
Celik M.,Technical University of Istanbul
Safety Science | Year: 2015
This is an article that conducts an empirical human reliability analysis for tank cleaning process on-board chemical tanker ship to enhance safety and operational reliability in maritime industry, providing a methodological extension through the integration of the AHP technique into the HEART approach. The paper provides a methodological development on decision making and human factors via extending a new approach to weight the proportion of the effect for calculating error producing conditions through operations. The model demonstration illustrates that cleaning of residues from hazardous cargoes such as acetic acid has required performing various critical tasks supported with recovery solutions. This research also provides practical insights along with reliability monitoring in ship operational level. © 2015 Elsevier Ltd.
Elif Cansoy C.,Piri Reis University
RSC Advances | Year: 2014
In this study, the effect of drop volume on contact angle (CA) values and also on the applicability of the Cassie-Baxter equation is experimentally investigated. To do this, dimethyldichlorosilane (DMDCS) coated different sized square pillar surfaces with varying fCBs(geo) values were used. Varying water drop volumes between 0.5 μl and 19 μl were used to measure CA's on square pillar surfaces with different pattern sizes changing from 8 μm to 40 μm. It was found that experimental CA values remained constant for each drop volume, indicating that increase or decrease in drop volume had no significant effect on experimentally measured CA values of square pillar surfaces with varying pattern sizes and fCBs(geo) values. When the relationship between the applicability of the Cassie-Baxter equation and the drop volume was investigated, it was also found that variation in volume of the drop did not cause a significant change in deviations between the theory and the experiments. ΔθCB values remained almost constant for all samples at varying drop volumes. © 2014 The Royal Society of Chemistry.