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Yayın Cryptanalysis of a multi-chaotic systems based image cryptosystem(Elsevier Science BV, 2010-01-15) Solak, Ercan; Rhouma, Rhouma; Belghith, Safya MdimeghThis paper is a cryptanalysis of a recently proposed multi-chaotic systems based image cryptosystem. The cryptosystem is composed of two shuffling stages parameterized by chaotically generated sequences. We propose and implement two different attacks which completely break this encryption scheme.Yayın An automatic calibration procedure of driving behaviour parameters in the presence of high bus volume(Faculty of Transport and Traffic Engineering, 2019-11) Dadashzadeh, Nima; Ergün, Murat; Kesten, Ali Sercan; Zura, MarijanMost of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the 0-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.Yayın A robust localization framework to handle noisy measurements in wireless sensor networks(IEEE, 2009-09-14) Erten, Cesim; Karataş, ÖmerWe construct a robust localization framework to handle noisy measurements in wireless sensor networks. Traditionally many approaches employ the distance information gathered from ranging devices of the sensor nodes to achieve localization. However the measurements of these devices may contain noise both as hardware noise and as environmental noise due to the employment conditions of the network. It Is necessary to provide a general framework that handles such a noise in data and yet still be applicable within several localization algorithms. In order to handle noise in distance measurements, our framework utilizes convex constraints and confidence intervals of a random variable. At the end of the localization process nodes are assigned to a set of feasible regions with corresponding probabilities. The accuracy of the localization can be adjusted and the framework can easily be embedded to work within previously suggested localization algorithms.Yayın Cryptanalysis of a new substitution-diffusion based image cipher(Elsevier Science BV, 2010-07) Rhouma, Rhouma; Solak, Ercan; Belghith, Safya MdimeghThis paper introduces two different types of attacks on a recently proposed cryptosystem based on chaotic standard and logistic maps. In the two attacks, only a pair of (plaintext/ciphertext) was needed to totally break the cryptosystem.Yayın Adaptive Volterra channel equalisation with lattice orthogonalisation(Institution of Engineering and Technology, 1998-04) Özden, Mehmet Tahir; Kayran, Ahmet Hamdi; Panayırcı, ErdalThe authors present a new recursive least-squares adaptive nonlinear equaliser based on Volterra series expansion. The main approach is to transform the nonlinear equalisation problem into an equivalent multichannel, but linear, equalisation problem. Then the multichannel input signal is completely orthogonalised using sequential processing multichannel lattice stages. With the complete orthogonalisation of the input signal, only scalar operations are required, instability problems owing to matrix inversion are avoided, and good numerical properties are achieved. Avoidance of matrix inversion and vector operations reduce the complexity considerably, and make the filter highly modular and suitable for VLSI implementation. Several experiments demonstrating the performance under different channel distortion and channel noise conditions are also included in the paper.Yayın Compression of ECG signals using variable-length classified vector sets and wavelet transforms(Springer International Publishing AG, 2012) Gürkan, HakanIn this article, an improved and more efficient algorithm for the compression of the electrocardiogram (ECG) signals is presented, which combines the processes of modeling ECG signal by variable-length classified signature and envelope vector sets (VL-CSEVS), and residual error coding via wavelet transform. In particular, we form the VL-CSEVS derived from the ECG signals, which exploits the relationship between energy variation and clinical information. The VL-CSEVS are unique patterns generated from many of thousands of ECG segments of two different lengths obtained by the energy based segmentation method, then they are presented to both the transmitter and the receiver used in our proposed compression system. The proposed algorithm is tested on the MIT-BIH Arrhythmia Database and MIT-BIH Compression Test Database and its performance is evaluated by using some evaluation metrics such as the percentage root-mean-square difference (PRD), modified PRD (MPRD), maximum error, and clinical evaluation. Our experimental results imply that our proposed algorithm achieves high compression ratios with low level reconstruction error while preserving the diagnostic information in the reconstructed ECG signal, which has been supported by the clinical tests that we have carried out.Yayın Modeling of electrocardiogram signals using predefined signature and envelope vector sets(Hindawi Publishing Corporation, 2007) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaA novel method is proposed to model ECG signals by means of "predefined signature and envelope vector sets (PSEVS)." On a frame basis, an ECG signal is reconstructed by multiplying three model parameters, namely, predefined signature vector (PSV)(R)," "predefined envelope vector (PEV)(K)," and frame-scaling coefficient (FSC). All the PSVs and PEVs are labeled and stored in their respective sets to describe the signal in the reconstruction process. In this case, an ECG signal frame is modeled by means of the members of these sets labeled with indices R and K and the frame-scaling coefficient, in the least mean square sense. The proposed method is assessed through the use of percentage root-mean-square difference (PRD) and visual inspection measures. Assessment results reveal that the proposed method provides significant data compression ratio (CR) with low-level PRD values while preserving diagnostic information. This fact significantly reduces the bandwidth of communication in telediagnosis operations. Copyright (c) 2007 Hakan Gurkan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Yayın Imaging of rough surfaces by RTM method(IEEE, 2024) Sefer, Ahmet; Yapar, Ali; Yelkenci, TanjuAn electromagnetic imaging framework is implemented utilizing a single frequency reverse time migration (RTM) technique to accurately reconstruct inaccessible two-dimensional (2D) rough surface profiles from the knowledge of scattered field data. The unknown surface profile, which is expressed as a 1D height function, is either perfectly electric conducting (PEC) or an interface between two penetrable media. For both cases, it is assumed that the surface is illuminated by a number of line sources located in the upper medium. The scattered fields, which should be collected by real measurements in practical applications, are obtained synthetically by solving the associated direct scattering problem through the surface integral equations. RTM is subsequently applied to generate a cross-correlation imaging functional which is evaluated numerically and provides a 2D image of the region of interest. A high correlation is observed by the functional in the regions where the transitions between two media occur. Hence, it results in the acquisition of the unknown surface profile at the sites where the functional attains its highest values. The efficiency of the proposed method is comprehensively tested by numerical examples covering various types of scattering scenarios.Yayın EM-Based sequence estimation for wireless systems with orthogonal transmit diversity(IEEE, 2003) Panayırcı, Erdal; Aygölü, Hasan Ümit; Pusane, Ali EmreIn this paper, an optimum sequence estimation algorithm for wireless systems with Alamouti's two transmitter diversity in the presence of multipath fading is proposed. The algorithm is based on a jointly iterative channel and sequence estimation according to the maximum likelihood (ML) criterion, using the Expectation-Maximization (EM) algorithm employing M-PSK modulation scheme with additive Gaussian noise. The discrete multipath channel is represented in terms of the channel gains from each transmit antenna to the receive antenna. EM algorithm derived estimates jointly the complex channel parameters of each channel And the data sequence transmitted, iteratively, which converges to the true ML solution. The channel estimation is achieved in a simple way through the iterative equations by decoupling of the signals transmitted from different antennas. The algorithm is applied to the trellis coded modulation systems and efficiency of the algorithm proposed has been shown by the computer simulations. Simulation results show that the EM algorithm converges quickly for fast fading channels. The performance of the EM-based decoder approaches that of the ML receiver which has perfect knowledge of the channel.Yayın Hierarchical quantization indexing for wavelet and wavelet packet image coding(Elsevier Science BV, 2010-02) Ateş, Hasan Fehmi; Tamer, EnginIn this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger Subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature.
