Sharif Digital Repository

Embedding a secret message into a cover media without attracting any attention, known as steganography, is one of the methods used for hidden communication purposes. One of the cover media that can be used for steganography is speech. In this study, the authors propose a new steganography method in speech signals. In this method, the silence intervals of speech are found and the length (number of samples) of these intervals is changed to hide information. The main feature of our method is robustness to MPEG-1 layer III (MP3) compression. This method can hide information in a speech stream with very low processing time which makes it a real-time steganography method. The hiding capacity of... 

With the widespread access of people to the Internet and the increasing usage of social networks in all nations, social networks have become a new source to study cultural similarities and differences. We identified major issues in traditional methods of data collection in cross-cultural studies: Difficulty in access to people from many nations, limited number of samples, negative effects of translation, positive self-enhancement illusion, and a few unreported problems. These issues are either causing difficulty to perform a cross-cultural study or have negative impacts on the validity of the final results. In this paper, we propose a framework that aims to calculate cultural distance among... 

In contrast to the vast amount of literature in random matrices in the field of compressed sensing, the subject of deterministic matrix design is at its early stages. Since these deterministic matrices are usually constructed using the polynomials in finite Galois fields, the number of rows (number of samples) is restricted to some specific integers such as prime powers. In this paper, besides extending a previous matrix design based on the binary BCH codes to the p-ary codes, we introduce matrices with wide variety of options for the number of rows. Simulation results demonstrate that these matrices perform almost as well as random matrices  

Digital music is now widely used and a great number of digital music files are available on the Internet. Designing systems that can automatically index, search and retrieve the digital music is one of the active research fields. One of the requirements for design and evaluation of such systems is corpuses of digital music samples. A good corpus is expected to have a number of features such as including a great number of samples, have samples of different artists and also samples with different quality. Additionally, the regional music of different parts of the world uses local musical instruments which results in music that are acoustically different. So, corpuses of regional music are... 

In this paper, the problem of the waveform design for colocated multiple-input multiple-output (MIMO) radars is considered in two parts. In the first part, we design transmit waveform in order to approximate the desired beampattern with low number of samples in the transmitter. Unlike the traditional waveform design methods, in our solution, waveforms are designed for a specific number of samples. Also, the constant envelope constraint that is an important practical constraint is considered. In the second part, we jointly design the transmit waveform and receive filter by a sequential algorithm, considering a priori information of target and interference angle locations. We have evaluated... 

The lack of knowledge about API correct usage rules is one of the main reasons that APIs are employed incorrectly by programmers, which in some cases lead to serious security vulnerabilities. However, finding a correct usage rule for an API is a time-consuming and error-prone task, particularly in the absence of an API documentation. Existing approaches to extract correct usage rules are mostly based on majority API usages, assuming the correct usage is prevalent. Although statistically extracting API correct usage rules achieves reasonable accuracy, it cannot work correctly in the absence of a fair amount of sample usages. We propose inferring API correct usage rules independent of the... 

The problem of finding the optimal node density for reconstructing a stochastic signal from its noisy samples in sensor networks is considered. The signal could be nonstationary and nonbandlimited. A weight is assigned to each location that indicates the relative importance of the signal at that location. It is shown that when the number of samples is very large, the optimal density of the samples at each location is proportional to the square root of the weight associated to that location  

This paper intends to introduce a simple fast space-efficient linear method for a general pattern recognition problem. The presented algorithm can find the closest match for a given sample within a number of samples which has already been introduced to the system. The fact of using averaging and fuzzy numbers in this method encourages that it may be a noise resistant recognition process. As a test bed, a problem of recognition of spoken words has been set forth to this algorithm. Test data contain clean and noisy samples and results have been compared to that of a widely used speech recognition method, HMM  

This paper studies an iterative stochastic algorithm for solving the stochastic shortest path problem. This algorithm, which uses a distributed learning automata, tries to find the shortest path by taking a sufficient number of samples from the edges of the graph. In this algorithm, which edges to be sampled are determined dynamically as the algorithm proceeds. At each iteration of this algorithm, a distributed learning automata used to determine which edges to be sampled. This sampling method, which uses distributed learning automata, reduces the number of samplings from those edges, which may not be along the shortest path, and resulting in a reduction in the number of the edges to be... 

This study presents a method based on minimum description length criterion to enumerate the incident waves impinging on a large array using a relatively small number of samples. The proposed scheme exploits the statistical properties of eigenvalues of the sample covariance matrix (SCM) of Gaussian processes. The authors use a number of moments of noise eigenvalues of the SCM in order to separate noise and signal subspaces more accurately. In particular, the authors assume a Marcenko-Pastur probability density function (pdf) for the eigenvalues of SCM associated with the noise subspace. We also use an enhanced noise variance estimator to reduce the bias leakage between the subspaces.... 

There has been an increasing interest in telemonitoring thanks to the availability of new technologies for data transmission and processing with better performances and lower costs. In this paper, we try to develop and implement the HRV signal processing into a Field Programmable Gate Array (FPGA). The hardware implementing algorithm was developed in Verilog Hardware Description Language (HDL). In designed hardware, after defining the number of samples in the input, we extract and analyses the Triangular Phase Space Mapping (TPSM), a novel method for representation of heart rate. The performance of the system was tested using MATLAB and validated based on the input signals  

The first-order reliability method (FORM) is a well-known procedure for reliability analysis in the engineering community. It provides an efficient way to calculate the failure probability of a structure. However, it introduces an unknown error in the estimations for non-linear limit states. This paper seeks a correction for the FORM by employing Monte Carlo simulation. The proposed method combines the efficiency of FORM with the robustness of the Monte Carlo method. The merits of the proposed method are illustrated through benchmark examples. The results show the high accuracy of the proposed method and a substantial reduction in the number of samples compared with crude Monte Carlo. ©... 

The authors propose invariant tests for the detection of a complex signal with unknown constant amplitude and unknown phase variation in additive white Gaussian noise (AWGN). The authors show that in this problem, the uniformly most powerful invariant (UMPI) detector does exist only if the number of samples N is two. For more than two samples N≥3, the authors derive the most powerful invariant (MPI) detector in known signal-to-noise ratio (SNR) and use its performance as the upper bound benchmark for any invariant test. In addition, the authors derive the generalised likelihood ratio (GLR) detector and evaluate its performance against the MPI performance bound. This detector is very simple... 

Sensors are among essential building blocks of any Cyber-Physical Systems (CPSs). Acquisition and processing of their sensory data contribute to the power consumption and computation load of the overall CPSs. For data acquisition, the conventional fixed frequency sampling in many such systems is sub-optimal since a sizable number of samples do not contain important information. In this work, we propose a Signal-Dependent Sampling (SDS) method and present its associated circuit implementation. Using the proposed SDS method, the number of retained samples is significantly reduced with little or negligible compromise in the quality of the (reconstructed) signal. The associated error and added...