Coding Problem Research Articles

Exploiting label consistency in structured sparse representation for classification

Sparse representation with adaptive dictionaries has emerged as a promising tool in computer vision and pattern analysis. While standard sparsity promoted by $$\ell _0$$ or $$\ell _1$$ regularization has been widely used, recent approaches seek for kinds of structured sparsity to improve the discriminability of sparse codes. For classification, label consistency is one useful concept regarding structured sparsity, which relates class labels to dictionary atoms for generating discriminative sparsity patterns. Motivated by the limitations of existing label-consistent regularization methods, in this paper, we investigate the exploitation of label consistency and propose an effective sparse coding approach. The proposed approach enforces the sparse approximation of a label consistency matrix by sparse code during dictionary learning, which encourages the supports of sparse codes to be consistent for intra-class signals and distinct for inter-class signals. Thus, the learned dictionary can induce discriminative sparsity patterns when used in sparse coding. Moreover, the proposed method is computationally efficient, as the label consistency regularization developed in our method brings very little additional computational cost in solving the related sparse coding problem. The effectiveness of the proposed method is demonstrated with several recognition tasks, and the experimental results show that our method is very competitive with some state-of-the-art approaches.

Theoretic constructions in pedagogy: the initial stage or dialogue between methodologists

A possibility of theoretic presentation of modern pedagogic knowledge is discussed in the article, difficulties in this process are observed, among them: problems of object coding, difficulties in correct logic-gnoseologic interpretation of research procedures, negative effect of «explosive» publications of famous authors in previous 10 years and others. One of possible ideas deal with theoretical pedagogical constructions and «primal» sketch of their structure is proposed; a possibility of realization descriptive, interpretive and prognostic functions in pedagogic theoretic constructions is analyzed.

Not what to wear? Employers’ liability for dress codes?

This article argues that in the United Kingdom currently there is a lack of an effective legal basis for challenging the imposition by employers of unfair or discriminatory dress codes in the workplace on employees or workers. Given the breadth of this topic, it will not be possible to also consider appearance or grooming standards such as outlawing beards or banning piercings or tattoos. Also consideration will be restricted to the aspects of discrimination which are contentious or most affected by dress codes or have not been dealt with in detail elsewhere namely sex and transgender discrimination. It is sadly the case that there is often uncertainty on the part of both employers and employees about when dress codes are acceptable or not and this should be addressed. There have been a number of research studies and legal cases highlighted recently which make this article timely. The cases tend to support the employers managerial prerogative to impose dress restrictions. Of recent interest is an incident where a woman was sent home from work on her first day for not wearing high heels which caused a public outcry, of which, more later. Clearly dress codes are often contentious and can lead to the discontent of employees and workers. In the absence of adequate legal protection in the United Kingdom, this article will examine what steps should be taken by management and legislators to deal with the problem of dress codes.

JET: Joint source and channel coding for error resilient virtual reality video wireless transmission

Virtual reality (VR) provides users extraordinary viewing experience and draws more and more attentions from both industry and academia. In this paper, we propose JET: Joint source and channel coding for Error resilient virtual reality video wireless Transmission, where we jointly investigate how to conquer the problem of source video’s huge size, how to efficiently satisfy a user’s view switch request and how to handle packet loss. Specifically, we first divide a VR video into smaller video tiles. Upon a user’s view switch request, the tiles corresponding to the part that the user is requesting, referred to as the field of view (FoV), and the part that the user may switch to before new video can be received, are delivered over a wireless network. We consider unequal error protection (UEP) for FoV and the rest part and formulate the inherent error resilient VR video transmission problem into a joint source and channel coding problem. In particular, we optimize the tile partition, quantization parameter and Forward Error Correction (FEC) packet allocation to maximize a user’s received video quality. We also propose a low-complexity heuristic algorithm to solve this optimization problem. Extensive simulations are conducted and simulation results verify the superior performance.

On the Geometric Ergodicity of Metropolis-Hastings Algorithms for Lattice Gaussian Sampling

Sampling from the lattice Gaussian distribution has emerged as an important problem in coding, decoding, and cryptography. In this paper, the classic Metropolis-Hastings (MH) algorithm in Markov chain Monte Carlo methods is adopted for lattice Gaussian sampling. Two MH-based algorithms are proposed, which overcome the limitation of Klein’s algorithm. The first one, referred to as the independent Metropolis-Hastings-Klein (MHK) algorithm, establishes a Markov chain via an independent proposal distribution. We show that the Markov chain arising from this independent MHK algorithm is uniformly ergodic, namely, it converges to the stationary distribution exponentially fast regardless of the initial state. Moreover, the rate of convergence is analyzed in terms of the theta series, leading to predictable mixing time. A symmetric Metropolis-Klein algorithm is also proposed, which is proven to be geometrically ergodic.

Unequal Error Protection Querying Policies for the Noisy 20 Questions Problem

In this paper, we propose an open-loop unequal-error-protection querying policy based on superposition coding for the noisy 20 questions problem. In this problem, a player wishes to successively refine an estimate of the value of a continuous random variable by posing binary queries and receiving noisy responses. When the queries are designed non-adaptively as a single block and the noisy responses are modeled as the output of a binary symmetric channel the 20 questions problem can be mapped to an equivalent problem of channel coding with unequal error protection (UEP). A new non-adaptive querying strategy based on UEP superposition coding is introduced whose estimation error decreases with an exponential rate of convergence that is significantly better than that of the UEP repetition coding introduced by Variani et al. (2015). With the proposed querying strategy, the rate of exponential decrease in the number of queries matches the rate of a closed-loop adaptive scheme where queries are sequentially designed with the benefit of feedback. Furthermore, the achievable error exponent is significantly better than that of random block codes employing equal error protection.

A New Powerful Scheme Based on Self Invertible Stabilizer Multiplier Permutation to Find the Minimum Distance for large BCH Codes

In this paper, we present the powerful scheme ZSISMP (Zimmermann Self Invertible Stabilizer Multiplier Permutation) to attack the hardness of the minimum distance search problem of BCH codes. This scheme consists in evaluating the minimum distance of the reduced dimension sub code fixed by a Self Invertible Stabilizer Multiplier Permutation by Zimmermann algorithm. The proposed scheme ZSISMP is validated on all BCH codes of known minimum distance. A comparison with several known powerful techniques proves its efficiency in giving more accurate results in short time. The use of this efficient local search had yield to determine the error correcting capability of many BCH codes of length 1023 and 4095.

Chain Code Approach For Shape Based Image Retrieval

Background/Objectives: Shape recognition is the most important issue in image understanding and computer vision. Shape representation is a primary issue in shape recognition. This work aims to image retrieval from image databases based on shape recognition. Methods: The Chain Code Histogram is used to generate a numerical feature vector which is used to describe a given shape; the problems of chain code consist of its sensitivity to rotation, scaling and flipping changes. In this paper, new methods are proposed to solve the problems of image rotation and flipping, by applying the second-moments method to calculating the rotation angle, and analyzing the data of the histogram directions. Findings: The rotation angle of the object and the similarity between the horizontally/ vertically flipping shapes and the original shape. Application: The proposed system works efficiently in recognize both regular and irregular objects for the different categories of the MRI images and results of this research will be useful for the calculate the brain object tilted; research will be extended in near future when we combining this method with color and texture features. Keywords: Chain Code Histogram, Flipping, Image Retrieval, Image Segmentation, Rotation

Secure Polar Coding for the Two-Way Wiretap Channel

We consider the problem of polar coding for secure communications over the two-way wiretap channel, where two legitimate users communicate with each other simultaneously while a passive eavesdropper overhears a combination of their exchanged signals. The legitimate users wish to design a cooperative jamming code such that the interference between their codewords can jam the eavesdropper. In this paper, we design a polar coded cooperative jamming scheme that achieves the whole secrecy rate region of the general two-way wiretap channel under the strong secrecy criterion. The chaining method is used to make proper alignment of polar indices. The randomness required to be shared between two legitimate users is treated as a limited resource and we show that its rate can be made negligible by increasing the blocklength and the number of chained blocks. For the special case when the eavesdropper channel is degraded with respect to the legitimate ones, a simplified scheme is proposed which can simultaneously ensure reliability and weak secrecy within a single transmission block. An example of the binary erasure channel case is given to demonstrate the performance of our scheme.

Delay-Aware Quality Optimization in Cloud-Assisted Video Streaming System

Cloud-assisted video streaming has emerged as a new paradigm to optimize multimedia content distribution over the Internet. This article investigates the problem of streaming cloud-assisted real-time video to multiple destinations (e.g., cloud video conferencing, multi-player cloud gaming, etc.) over lossy communication networks. The user diversity and network dynamics result in the delay differences among multiple destinations. This research proposes <underline>D</underline>ifferentiated cloud-<underline>A</underline>ssisted <underline>VI</underline>deo <underline>S</underline>treaming (DAVIS) framework, which proactively leverages such delay differences in video coding and transmission optimization. First, we analytically formulate the optimization problem of joint coding and transmission to maximize received video quality. Second, we develop a quality optimization framework that integrates the video representation selection and FEC (Forward Error Correction) packet interleaving. The proposed DAVIS is able to effectively perform differentiated quality optimization for multiple destinations by taking advantage of the delay differences in cloud-assisted video streaming system. We conduct the performance evaluation through extensive experiments with the Amazon EC2 instances and Exata emulation platform. Evaluation results show that DAVIS outperforms the reference cloud-assisted streaming solutions in video quality and delay performance.

A Metrics Suite for code annotation assessment

Code annotation is a language feature that enables the introduction of custom metadata on programming elements. In Java, this feature was introduced on version 5, and today it is widely used by main enterprise application frameworks and APIs. Although this language feature potentially simplifies metadata configuration, its abuse and misuse can reduce source code readability and complicate its maintenance. The goal of this paper is to propose software metrics regarding annotations in the source code and analyze their distribution in real-world projects. We have defined a suite of metrics to assess characteristics of the usage of source code annotations in a code base. Our study collected data from 24947 classes extracted from open source projects to analyze the distribution of the proposed metrics. We developed a tool to automatically extract the metrics and provide a full report on annotations usage. Based on the analysis of the distribution, we defined an appropriate approach for the calculation of thresholds to interpret the metric values. The results allow the assessment of annotated code characteristics. Using the thresholds values, we proposed a way to interpret the use of annotations, which can reveal potential problems in the source code.

On the Tradeoff Region of Secure Exact-Repair Regenerating Codes

We consider the $(n,k,d,\ell )$ secure exact-repair regenerating code problem, which generalizes the $(n,k,d)$ exact-repair regenerating code problem with the additional constraint that the stored file needs to be kept information-theoretically secure against an eavesdropper, who can access the data transmitted to regenerate a total of $\ell $ different failed nodes. For all known results on this problem, the achievable tradeoff regions between the normalized storage capacity and repair bandwidth have a single corner point, achieved by a scheme proposed by Shah, Rashmi, and Kumar (the SRK point). Since the achievable tradeoff regions of the exact-repair regenerating code problem without any secrecy constraints are known to have multiple corner points in general, these existing results suggest a phase-change-like behavior, i.e., enforcing a secrecy constraint ( $\ell \geq 1$ ) immediately reduces the tradeoff region to one with a single corner point. In this paper, we first show that when the secrecy parameter $\ell $ is sufficiently large, the SRK point is indeed the only corner point of the tradeoff region. However, when $\ell $ is small, we show that the tradeoff region can in fact have multiple corner points. In particular, we establish a precise characterization of the tradeoff region for the (7, 6, 6, 1) problem, which has exactly two corner points. Thus, a smooth transition, instead of a phase-change-type of transition, should be expected as the secrecy constraint is gradually strengthened.

A linear-time algorithm for the identifying code problem on block graphs

The identifying code problem is a special search problem, challenging both from a theoretical and from a computational point of view, even for several graphs where other usually hard problems are easy to solve, like bipartite graphs or chordal graphs. Hence, a typical line of attack for this problem is to determine minimum identifying codes of special graphs. In this work we study the problem of determining the cardinality of a minimum identifying code in block graphs (that are diamond-free chordal graphs). We present a linear-time algorithm for this problem, as a generalization of a linear-time algorithm proposed by Auger in 2010 for the case of trees. Thereby, we provide a subclass of chordal graphs for which the identifying code problem can be solved in linear time.

On the equivalence of cyclic and quasi-cyclic codes over finite fields

This paper studies the equivalence problem for cyclic codes of length $p^r$ and quasi-cyclic codes of length $p^rl$. In particular, we generalize the results of Huffman, Job, and Pless (J. Combin. Theory. A, 62, 183--215, 1993), who considered the special case $p^2$. This is achieved by explicitly giving the permutations by which two cyclic codes of prime power length are equivalent. This allows us to obtain an algorithm which solves the problem of equivalency for cyclic codes of length $p^r$ in polynomial time. Further, we characterize the set by which two quasi-cyclic codes of length $p^rl$ can be equivalent, and prove that the affine group is one of its subsets.

Context‐based approach to prioritize code smells for prefactoring

Existing techniques for detecting code smells (indicators of source code problems) do not consider the current context, which renders them unsuitable for developers who have a specific context, such as modules within their focus. Consequently, the developers must spend time identifying relevant smells. We propose a technique to prioritize code smells using the developers' context. Explicit data of the context are obtained using a list of issues extracted from an issue tracking system. We applied impact analysis to the list of issues and used the results to specify the context‐relevant smells. Results show that our approach can provide developers with a list of prioritized code smells related to their current context. We conducted several empirical studies to investigate the characteristics of our technique and factors that might affect the ranking quality. Additionally, we conducted a controlled experiment with professional developers to evaluate our technique. The results demonstrate the effectiveness of our technique.

Insuperable problems of the genetic code initially emerging in an RNA world

Differential equations for error-prone information transfer (template replication, transcription or translation) are developed in order to consider, within the theory of autocatalysis, the advent of coded protein synthesis. Variations of these equations furnish a basis for comparing the plausibility of contrasting scenarios for the emergence of specific tRNA aminoacylation, ultimately by enzymes, and the relationship of this process with the origin of the universal system of molecular biological information processing embodied in the Central Dogma. The hypothetical RNA World does not furnish an adequate basis for explaining how this system came into being, but principles of self-organisation that transcend Darwinian natural selection furnish an unexpectedly robust basis for a rapid, concerted transition to genetic coding from a peptide·RNA world.

Hashing with Angular Reconstructive Embeddings.

Large-scale search methods are increasingly critical for many content-based visual analysis applications, among which hashing-based approximate nearest neighbor search techniques have attracted broad interests due to their high efficiency in storage and retrieval. However, existing hashing works are commonly designed for measuring data similarity by the Euclidean distances. In this paper, we focus on the problem of learning compact binary codes using the cosine similarity. Specifically, we proposed novel angular reconstructive embeddings (ARE) method, which aims at learning binary codes by minimizing the reconstruction error between the cosine similarities computed by original features and the resulting binary embeddings. Furthermore, we devise two efficient algorithms for optimizing our ARE in continuous and discrete manners, respectively. We extensively evaluate the proposed ARE on several large-scale image benchmarks. The results demonstrate that ARE outperforms several state-of-the-art methods.

Probability of Partially Decoding Network-Coded Messages

In the literature there exists analytical expressions for the probability of a receiver decoding a transmitted source message that has been encoded using random linear network coding. In this work, we look into the probability that the receiver will decode at least a fraction of the source message, and present an exact solution to this problem for both non-systematic and systematic network coding. Based on the derived expressions, we investigate the potential of these two implementations of network coding for information-theoretic secure communication and progressive recovery of data.

Polynomial-time key recovery attack on the Faure–Loidreau scheme based on Gabidulin codes

Encryption schemes based on the rank metric lead to small public key sizes of order of few thousands bytes which represents a very attractive feature compared to Hamming metric-based encryption schemes where public key sizes are of order of hundreds of thousands bytes even with additional structures like the cyclicity. The main tool for building public key encryption schemes in rank metric is the McEliece encryption setting used with the family of Gabidulin codes. Since the original scheme proposed in 1991 by Gabidulin, Paramonov and Tretjakov, many systems have been proposed based on different masking techniques for Gabidulin codes. Nevertheless, over the years most of these systems were attacked essentially by the use of an attack proposed by Overbeck. In 2005 Faure and Loidreau designed a rank-metric encryption scheme which was not in the McEliece setting. The scheme is very efficient, with small public keys of size a few kiloBytes and with security closely related to the linearized polynomial reconstruction problem which corresponds to the decoding problem of Gabidulin codes. The structure of the scheme differs considerably from the classical McEliece setting and until our work, the scheme had never been attacked. We show in this article that for a range of parameters, this scheme is also vulnerable to a polynomial-time attack that recovers the private key by applying Overbeck’s attack on an appropriate public code. As an example we break in a few seconds parameters with 80-bit security claim. Our work also shows that some parameters are not affected by our attack but at the cost of a lost of efficiency for the underlying schemes.

A boundary integral method for numerical computation of radar cross section of 3D targets using hybrid BEM/FEM with edge elements

This contribution presents the boundary integral formulation for numerical computation of time-harmonic radar cross section for 3D targets. Method relies on hybrid edge element BEM/FEM to compute near field edge element coefficients that are associated with near electric and magnetic fields at the boundary of the computational domain. Special boundary integral formulation is presented that computes radar cross section directly from these edge element coefficients. Consequently, there is no need for near-to-far field transformation (NTFFT) which is common step in RCS computations. By the end of the paper it is demonstrated that the formulation yields accurate results for canonical models such as spheres, cubes, cones and pyramids. Method has demonstrated accuracy even in the case of dielectrically coated PEC sphere at interior resonance frequency which is common problem for computational electromagnetic codes.