Sharif Digital Repository

The lack of proper documentation makes program comprehension a cumbersome process for developers. Source code summarization is one of the existing solutions to this problem. Many approaches have been proposed to summarize source code in recent years. A prevalent weakness of these solutions is that they do not pay much attention to interactions among elements of software. An element is simply a callable code snippet such as a method or even a clickable button. As a result, these approaches cannot be applied to event-driven programs, such as Android applications, because they have specific features such as numerous interactions between their elements. To tackle this problem, we propose a novel... 

We study the problem of remote reconstruction of a continuous signal from its multiple corrupted versions. We are interested in the optimal number of samples and their locations for each corrupted signal to minimize the total reconstruction distortion of the remote signal. The correlation among the corrupted signals can be utilized to reduce the sampling rate. For a class of Gaussian signals, we show that in the low sampling rate region, it is optimal to use a certain nonuniform sampling scheme on all the signals. On the other hand, in the high sampling rate region, it is optimal to uniformly sample all the signals. We also show that both of these sampling strategies are optimal if we are... 

Visual attributes are great means of describing images or scenes, in a way both humans and computers understand. In order to establish a correspondence between images and to be able to compare the strength of each property between images, relative attributes were introduced. However, since their introduction, hand-crafted and engineered features were used to learn increasingly complex models for the problem of relative attributes. This limits the applicability of those methods for more realistic cases. We introduce a deep neural network architecture for the task of relative attribute prediction. A convolutional neural network (ConvNet) is adopted to learn the features by including an... 

A function is said to be additive if, similar to mutual information, expands by a factor of n, when evaluated on n i.i.d. repetitions of a source or channel. On the other hand, a function is said to satisfy the tensorization property if it remains unchanged when evaluated on i.i.d. repetitions. Additive rate regions are of fundamental importance in network information theory, serving as capacity regions or upper bounds thereof. Tensorizing measures of correlation have also found applications in distributed source and channel coding problems as well as the distribution simulation problem. Prior to our work only two measures of correlation, namely the hypercontractivity ribbon and maximal... 

In this paper we study the sum modulo two problem proposed by Körner and Marton. In this source coding problem, two transmitters who observe binary sources X and Y, send messages of limited rate to a receiver whose goal is to compute the sum modulo of X and Y. This problem has been solved for the two special cases of independent and symmetric sources. In both of these cases, the rate pair (H(X|Y), H(Y|X)) is achievable. The best known outer bound for this problem is a conventional cut-set bound, and the best known inner bound is derived by Ahlswede and Han using a combination of Slepian-Wolf and Körner-Marton's coding schemes. In this paper, we propose a new outer bound which is strictly... 

In this paper, we investigate reliable transmission of three correlated discrete memoryless sources over a two-relay network. In our considered model, one of the sources is available at the sender whereas, the other two sources are known to the first and the second relay. We present both joint and separate source-channel coding schemes, and derive the corresponding sets of sufficient conditions for reliable sources transmission. The manner of cooperation in both schemes is Decode-and-Forward strategy. In the joint approach, we generalize the correlation preserving mapping technique to our model using nested backward decoding. Our proposed separate approach is based on Slepian-Wolf source... 

In this work, we study the lossy source coding of a Gaussian source with polar codes. We show through two distributions on discrete alphabet, quantized approach as well as Central Limit Theorem (CLT) approach, when the alphabet size grows to infinity, polar codes can achieve the rate distortion bound for a Gaussian source. By comparing the rate of convergence on two distributions, we show that the quantized approach have a better convergence rate than the CLT approach  

We study the reliable transmission of correlated sources over the relay channel. One of the sources is available at the sender while the other one is known to the relay. The receiver wishes to reconstruct both sources. We find necessary and sufficient conditions for optimal separation of source and channel codes. The coding scheme is based on the combination of the Slepian-Wolf source coding and Partial Decode-and-Forward (PDF) strategy. In this scheme, the relay partially decodes the message transmitted by the sender. We also consider the semi-deterministic relay channel where the output at the relay is a deterministic function of inputs from the sender and the relay. For the transmission... 

New inner and outer bounds on the achievable compression-equivocation rate region for generalised secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and Charlie intend to transmit information to Bob via channels with limited capacity so that he can reliably reconstruct their observations. The eavesdropper, Eve, has access to one of the channels at each instant and is interested in the source of the same channel at the time. Bob and Eve also have their own observations, which are correlated with Alice's and Charlie's observations. In this model, two equivocation and compression rates are defined with respect to the sources... 

Power and bandwidth constraints are two major challenges in wireless sensor networks. Since a considerable amount of energy in sensor networks is consumed for data transmission, compression techniques may prolong the life of such networks. Moreover, with fewer bits to transmit, the network can cope better with the problem of inadequate bandwidth. In this paper, we consider an image sensor network and propose a paradigm based on the principles of Distributed Source Coding (DSC) for efficient compression. Our method relies on high correlation between the sensor nodes. The algorithm consists of two phases: the Training Phase and the Main Phase. In the Training Phase an aggregation node or a... 

Multimedia multicast with two servers based on the mul- titerminal source coding is studied in some previous researches. Due to the possibility of providing an approach for practical code design for more than two correlated sources in IMTSC/CEO setup, in this paper, the framework of Slepian-Wolf coded quantization is extended and a practical code design is presented for IMTSC/CEO with the number of encoders greater than two. Then the multicast system based on the IMTSC/CEO is applied to the cases with three, four and five servers. Since the underlying code design approach for the IMTSC/CEO problem has the capability of applying to an arbitrary number of active encoders, the proposed MMBMSC... 

We study the estimation of a Gaussian source by a Gaussian wireless sensor network (WSN) where L distributed sensors transmit noisy observations of the source through a fading Gaussian multiple access channel to a fusion center. In a recent work Gastpar, [ "Uncoded transmission is exactly optimal for a Simple Gaussian Sensor Network", IEEE Trans. Inf. Theory, vol. 54, no. 11, pp. 52475251, Nov. 2008] showed that for a symmetric Gaussian WSN with no fading, uncoded (analog) transmission achieves the optimal performance theoretically attainable (OPTA). In this correspondence, we consider an asymmetric fading WSN in which the sensors have differing noise and transmission powers. We first... 

The minimum cost subgraph for joint distributed source and network coding has been studied using a linear programming approach. This problem considers some statistically correlated information sources in a network, where sending over each link has a defined cost. The desired solution to this problem is a set of coding rates over the graph links, that minimizes the total communication costs. But in this problem, the placement of the sources is pre-defined, which is not necessarily optimal. In this paper, for the first time, we find a "good" placement for the sources using a genetic programming approach. This problem can be seen as the generalized mirror sites problem, where sources are not... 

Few works has been focused on the problem of joint distributed data compression and network coding. In this paper we give some examples showing the advantage of broadcast nature of wireless environment as a basis for joint codes design. Also we show that joint coding is possible in the case of multiple unicasts. The idea of this paper can be exploited in an opportunistic manner. Actually, the foundation of our idea is nothing but combining opportunistic network coding (COPE) and distributed source coding using syndromes (DISCUS) for wireless applications. © 2009 IEEE  

Watermarking is the process of hiding information in a media and usually used to for copyright protection. In software watermarking, the information is added to the source code of program and can be extracted from compiled executable code. In this paper, a new software watermarking algorithm is proposed by equation reordering. In this method, the order of operands in an equation is changed according to the information we want to hide in a way that the result of the equation is unchanged. One of the main advantages of this method is that no code added to the program, so the size and speed of the program not changed  

A matrix pseudo inversion based method is developed for coding of images in real field in a way that at the receiver, one can restore the lost portions of the images. The proposed solution is similar to channel coding techniques, but it is done before source coding at the transmitter and after decoding of the compressed data at the receiver. Experiments show the effectiveness of the proposed solution in recove ring missed portions of the images and video frames. ©2007 IEEE  

A novel error resilient source coding method is proposed for video codecs such as H.264 standard. The main idea is to develop an error resilient part similar to the channel coders at the source coder. This enables the receiver to recover a damaged slice of a frame, inter or intra coded, up to a certain size determined by the encoder. In contrast to another previously approach presented in the literature, our algorithm has significantly less artifacts on the video frames with a considerable increase in speed  

In this paper applications of an iterative method in some signal recovery problems are introduced. It is proved that the distorting effect of linear operators can be removed completely using the iterative scheme. The inverse of monotonic functions can also be made indirectly by the method. A novel approach for separating the messages of different subscribers in a CDMA network will be proposed as well, relying on the recursive approach. It would be shown that Sigma Delta Modulated signals can be decoded via the iterative procedure. We will prove both analytically and with simulations that a broad class of nonlinear operators including speech and image codecs can be approximately inverted with... 

In this paper, we develop a new error-resistant secure lossless source coding scheme for discrete sources. Recent results indicate that the same turbo principle that provides sub-optimal strategy for channel coding, can be used to obtain efficient source coding schemes. We extend the source turbo-coding idea to include security for transmission of the compressed data and also to ensure the lossless recovery of information at the receiver. Compression and security are achieved by adapting the random puncturing strategy to the statistics of the source. Lossless compression is guaranteed by finely puncturing the encoded data of a parallel-concatenated turbo code while verifying the integrity of...