OpenRaiser/Intern-Atlas huggingface dataset:
A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation
Venue: arXiv cs.LG 2014
Year: 2014

In big data image/video analytics, we encounter the problem of learning an overcomplete dictionary for sparse representation from a large training dataset, which can not be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm for parallel dictionary learning. The fundamental idea behind the algorithm is to learn a sparse representation in two phases. In the first phase, the whole training dataset is partitioned into small non-overlapping subsets, and a dictionary is trained independently on each small database. In the second phase, the dictionaries are merged to form a global dictionary. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy operating on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques, that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.
Chaos Based Mixed Keystream Generation for Voice Data Encryption
Venue: arXiv cs.CR 2014
Year: 2014

In this paper, a high dimensional chaotic systems based mixed keystream generator is proposed to secure the voice data. As the voice-based communication becomes extensively vital in the application areas of military, voice over IP, voice-conferencing, phone banking, news telecasting etc. It greatly demands to preserve sensitive voice signals from the unauthorized listening and illegal usage over shared/open networks. To address the need, the designed keystream generator employed to work as a symmetric encryption technique to protect voice bitstreams over insecure transmission channel. The generator utilizes the features of high dimensional chaos like Lorenz and Chen systems to generate highly unpredictable and random-like sequences. The encryption keystream is dynamically extracted from the pre-treated chaotic mixed sequences, which are then applied to mask the voice bitstream for integrity protection of voice data. The experimental analyses like auto-correlation, signal distribution, parameter residual deviation, key space and key-sensitivity demonstrate the effectiveness of the proposed technique for secure voice communication.
Structure-preserving model reduction of physical network systems by clustering
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, we establish a method for model order reduction of a certain class of physical network systems. The proposed method is based on clustering of the vertices of the underlying graph, and yields a reduced order model within the same class. To capture the physical properties of the network, we allow for weights associated to both the edges as well as the vertices of the graph. We extend the notion of almost equitable partitions to this class of graphs. Consequently, an explicit model reduction error expression in the sense of H2-norm is provided for clustering arising from almost equitable partitions. Finally the method is extended to second-order systems.
Task & Resource Self-adaptive Embedded Real-time Operating System Microkernel for Wireless Sensor Nodes
Venue: arXiv cs.OS 2014
Year: 2014

Wireless Sensor Networks (WSNs) are used in many application fields, such as military, healthcare, environment surveillance, etc. The WSN OS based on event-driven model doesn't support real-time and multi-task application types and the OSs based on thread-driven model consume much energy because of frequent context switch. Due to the high-dense and large-scale deployment of sensor nodes, it is very difficult to collect sensor nodes to update their software. Furthermore, the sensor nodes are vulnerable to security attacks because of the characteristics of broadcast communication and unattended application. This paper presents a task and resource self-adaptive embedded real-time microkernel, which proposes hybrid programming model and offers a two-level scheduling strategy to support real-time multi-task correspondingly. A communication scheme, which takes the "tuple" space and "IN/OUT" primitives from "LINDA", is proposed to support some collaborative and distributed tasks. In addition, this kernel implements a run-time over-the-air updating mechanism and provides a security policy to avoid the attacks and ensure the reliable operation of nodes. The performance evaluation is proposed and the experiential results show this kernel is task-oriented and resource-aware and can be used for the applications of event-driven and real-time multi-task.
Organised crime infiltration in the legitimate private economy - An empirical network analysis approach
Venue: arXiv cs.CY 2014
Year: 2014

It is estimated that Italian Mafias registered 135 billion euros in profits only in 2010. Part of this huge amount of money, coming mostly from the drugs, prostitution and arms illicit markets, is often used to invest into legitimate private economies. As a consequence, the affected economies destabilise, become entrenched with violent forms of competition and are bound to stagnation. Nonetheless, few are the attempts to uncover the patterns followed by criminal organisations in their business ventures. The reason lays mostly in the poor availability of data on criminal activity, or in the highly risky task of gather it. This paper partially fills this gap thanks to access to information about the Sicilian Mafia in a city. More specifically, it tries to analyse the nature and extent of criminal infiltration into the legitimate private economy of the case-study using network techniques. The research demonstrates that sectors with a high degree of centrality and comprising fewer firms are the most vulnerable to this kind of security threat. It also shows that centrality is also the key criterion that makes a firm sensitive to infiltration, provided it belongs to a susceptible economic sector.
Enforcing Operational Properties including Blockfreeness for Deterministic Pushdown Automata
Venue: arXiv cs.FL 2014
Year: 2014

We present an algorithm which modifies a deterministic pushdown automaton (DPDA) such that (i) the marked language is preserved, (ii) lifelocks are removed, (iii) deadlocks are removed, (iv) all states and edges are accessible, and (v) operational blockfreeness is established (i.e., coaccessibility in the sense that every initial derivation can be continued to a marking configuration). This problem can be trivially solved for deterministic finite automata (DFA) but is not solvable for standard petri net classes. The algorithm is required for an operational extension of the supervisory control problem (SCP) to the situation where the specification in modeled by a DPDA.
On Solving the Maximum $k$-club Problem
Venue: arXiv cs.DS 2014
Year: 2014

Given a simple undirected graph $G$, the maximum $k$-club problem is to find a maximum-cardinality subset of nodes inducing a subgraph of diameter at most $k$ in $G$. This NP-hard generalization of clique, originally introduced to model low diameter clusters in social networks, is of interest in network-based data mining and clustering applications. We give two MAX-SAT formulations of the problem and show that two exact methods resulting from our encodings outperform significantly the state-of-the-art exact methods when evaluated both on sparse and dense random graphs as well as on diverse real-life graphs from the literature.
A Novel Quorum Protocol
Venue: arXiv cs.DC 2014
Year: 2014

One of the traditional mechanisms used in distributed systems for maintaining the consistency of replicated data is voting. A problem involved in voting mechanisms is the size of the Quorums needed on each access to the data. In this paper, we present a novel and efficient distributed algorithm for managing replicated data. We impose a logical wheel structure on the set of copies of an object. The protocol ensures minimum read quorum size of one, by reading one copy of an object while guaranteeing fault-tolerance of write operations.Wheel structure has a wider application area as it can be imposed in a network with any number of nodes.
What is Tumblr: A Statistical Overview and Comparison
Venue: arXiv cs.SI 2014
Year: 2014

Tumblr, as one of the most popular microblogging platforms, has gained momentum recently. It is reported to have 166.4 millions of users and 73.4 billions of posts by January 2014. While many articles about Tumblr have been published in major press, there is not much scholar work so far. In this paper, we provide some pioneer analysis on Tumblr from a variety of aspects. We study the social network structure among Tumblr users, analyze its user generated content, and describe reblogging patterns to analyze its user behavior. We aim to provide a comprehensive statistical overview of Tumblr and compare it with other popular social services, including blogosphere, Twitter and Facebook, in answering a couple of key questions: What is Tumblr? How is Tumblr different from other social media networks? In short, we find Tumblr has more rich content than other microblogging platforms, and it contains hybrid characteristics of social networking, traditional blogosphere, and social media. This work serves as an early snapshot of Tumblr that later work can leverage.
A Deterministic Annealing Optimization Approach for Witsenhausen's and Related Decentralized Control Settings
Venue: arXiv cs.SY 2014
Year: 2014

This paper studies the problem of mapping optimization in decentralized control problems. A global optimization algorithm is proposed based on the ideas of ``deterministic annealing" - a powerful non-convex optimization framework derived from information theoretic principles with analogies to statistical physics. The key idea is to randomize the mappings and control the Shannon entropy of the system during optimization. The entropy constraint is gradually relaxed in a deterministic annealing process while tracking the minimum, to obtain the ultimate deterministic mappings. Deterministic annealing has been successfully employed in several problems including clustering, vector quantization, regression, as well as the Witsenhausen's counterexample in our recent work[1]. We extend our method to a more involved setting, a variation of Witsenhausen's counterexample, where there is a side channel between the two controllers. The problem can be viewed as a two stage cancellation problem. We demonstrate that there exist complex strategies that can exploit the side channel efficiently, obtaining significant gains over the best affine and known non-linear strategies.
Differential Dual-Hop Relaying over Time-Varying Rayleigh-Fading Channels
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies dual-hop amplify-and-forward relaying over time-varying Rayleigh fading channels with differential M-PSK modulation and non-coherent detection. For the case of "two-symbol" detection, a first order time-series model is utilized to characterize the time-varying nature of the cascaded channel. Based on this model, an exact bit error rate (BER) expression is derived and confirmed with simulation results. The obtained expression shows that the BER is related to the auto-correlation of the cascaded channel and an irreducible error floor exists at high transmit power. To overcome the error floor experienced with fast-fading, a nearly optimal multiple-symbol differential sphere detection (MSDSD) is also developed. The error performance of MSDSD is illustrated with simulation results under different fading scenarios.
A Non-Local Structure Tensor Based Approach for Multicomponent Image Recovery Problems
Venue: arXiv cs.CV 2014
Year: 2014

Non-Local Total Variation (NLTV) has emerged as a useful tool in variational methods for image recovery problems. In this paper, we extend the NLTV-based regularization to multicomponent images by taking advantage of the Structure Tensor (ST) resulting from the gradient of a multicomponent image. The proposed approach allows us to penalize the non-local variations, jointly for the different components, through various $\ell_{1,p}$ matrix norms with $p \ge 1$. To facilitate the choice of the hyper-parameters, we adopt a constrained convex optimization approach in which we minimize the data fidelity term subject to a constraint involving the ST-NLTV regularization. The resulting convex optimization problem is solved with a novel epigraphical projection method. This formulation can be efficiently implemented thanks to the flexibility offered by recent primal-dual proximal algorithms. Experiments are carried out for multispectral and hyperspectral images. The results demonstrate the interest of introducing a non-local structure tensor regularization and show that the proposed approach leads to significant improvements in terms of convergence speed over current state-of-the-art methods.
Comprehensive Landscapes for Software-related Quality Models
Venue: arXiv cs.SE 2014
Year: 2014

Managing quality (such as service availability or process adherence) during the development, operation, and maintenance of software(-intensive) systems and services is a challenging task. Although many organizations need to define, control, measure, and improve various quality aspects of their devel- opment artifacts and processes, nearly no guidance is available on how to select, adapt, define, combine, use, and evolve quality models. Catalogs of quality models as well as selection and tailoring processes are widely missing. One essential reason for this tremendous lack of support is that software development is a highly context-dependent process. Therefore, quality models always need to be adaptable to the respective project goals and contexts. A first step towards better support for selecting and adapting quality models can be seen in a classification of existing quality models, especially with respect to their suitability for different purposes and contexts. Such a classification of quality models can be applied to provide an integrated overview of the variety of quality models. This article presents the idea of so called comprehensive quality model landscapes (CQMLs), which provide a classification scheme for quality models and help to get an overview of existing quality models and their relationships. The article describes the usage goals for such landscapes, presents a classification scheme, presents the initial concept of such landscapes, illustrates the concept with selected examples, and sketches open questions and future work.
Saliency Based Control in Random Feature Networks
Venue: arXiv cs.SY 2014
Year: 2014

The ability to rapidly focus attention and react to salient environmental features enables animals to move agiley through their habitats. To replicate this kind of high-performance control of movement in synthetic systems, we propose a new approach to feedback control that bases control actions on randomly perceived features. Connections will be made with recent work incorporating communication protocols into networked control systems. The concepts of {\em random channel controllability} and {\em random channel observability} for LTI control systems are introduced and studied.
Beyond Parrondo's paradox
Venue: arXiv cs.GT 2014
Year: 2014

The Parrondo's paradox is a counterintuitive phenomenon where individually-losing strategies can be combined in producing a winning expectation. In this paper, the issues surrounding the Parrondo's paradox are investigated. The focus is lying on testifying whether the same paradoxical effect can be reproduced by using a simple capital dependent game. The paradoxical effect generated by the Parrondo's paradox can be explained by placing all the parameters in one probability space. Based on this framework, it is able to generate other possible paradoxical effects by manipulating the parameters in the probability space.
Scenario optimization with certificates and applications to anti-windup design
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, we introduce a significant extension, called scenario with certificates (SwC), of the so-called scenario approach for uncertain optimization problems. This extension is motivated by the observation that in many control problems only some of the optimization variables are used in the design phase, while the other variables play the role of certificates. Examples are all those control problems that can be reformulated in terms of linear matrix inequalities involving parameter-dependent Lyapunov functions. These control problems include static anti-windup compensator design for uncertain linear systems with input saturation, where the goal is the minimization of the nonlinear gain from an exogenous input to a performance output. The main contribution of this paper is to show that randomization is a useful tool, specifically for anti-windup design, to make the overall approach less conservative compared to its robust counterpart. In particular, we demonstrate that the scenario with certificates reformulation is appealing because it provides a way to implicitly design the parameter-dependent Lyapunov functions. Finally, to further reduce the computational cost of this one-shot approach, we present a sequential randomized algorithm for iteratively solving this problem.
Quantum-noise limited communication with low probability of detection
Venue: arXiv cs.IT 2014
Year: 2014

We demonstrate the achievability of a square root limit on the amount of information transmitted reliably and with low probability of detection (LPD) over the single-mode lossy bosonic channel if either the eavesdropper's measurements or the channel itself is subject to the slightest amount of excess noise. Specifically, Alice can transmit $\mathcal{O}(\sqrt{n})$ bits to Bob over $n$ channel uses such that Bob's average codeword error probability is upper-bounded by an arbitrarily small $δ>0$ while a passive eavesdropper, Warden Willie, who is assumed to be able to collect all the transmitted photons that do not reach Bob, has an average probability of detection error that is lower-bounded by $1/2-ε$ for an arbitrarily small $ε>0$. We analyze the thermal noise and pure loss channels. The square root law holds for the thermal noise channel even if Willie employs a quantum-optimal measurement, while Bob is equipped with a standard coherent detection receiver. We also show that LPD communication is not possible on the pure loss channel. However, this result assumes Willie to possess an ideal receiver that is not subject to excess noise. If Willie is restricted to a practical receiver with a non-zero dark current, the square root law is achievable on the pure loss channel.
Vulnerabilities and Attacks Targeting Social Networks and Industrial Control Systems
Venue: arXiv cs.SI 2014
Year: 2014

Vulnerability is a weakness, shortcoming or flaw in the system or network infrastructure which can be used by an attacker to harm the system, disrupt its normal operation and use it for his financial, competitive or other motives or just for cyber escapades. In this paper, we re-examined the various types of attacks on industrial control systems as well as on social networking users. We have listed which all vulnerabilities were exploited for executing these attacks and their effects on these systems and social networks. The focus will be mainly on the vulnerabilities that are used in OSNs as the convertors which convert the social network into antisocial network and these networks can be further used for the network attacks on the users associated with the victim user whereby creating a consecutive chain of attacks on increasing number of social networking users. Another type of attack, Stuxnet Attack which was originally designed to attack Iran's nuclear facilities is also discussed here which harms the system it controls by changing the code in that target system. The Stuxnet worm is a very treacherous and hazardous means of attack and is the first of its kind as it allows the attacker to manipulate real time equipment.
Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations
Venue: arXiv cs.IT 2014
Year: 2014

Large-scale (or massive) multiple-input multiple-output (MIMO) is expected to be one of the key technologies in next-generation multi-user cellular systems, based on the upcoming 3GPP LTE Release 12 standard, for example. In this work, we propose - to the best of our knowledge - the first VLSI design enabling high-throughput data detection in single-carrier frequency-division multiple access (SC-FDMA)-based large-scale MIMO systems. We propose a new approximate matrix inversion algorithm relying on a Neumann series expansion, which substantially reduces the complexity of linear data detection. We analyze the associated error, and we compare its performance and complexity to those of an exact linear detector. We present corresponding VLSI architectures, which perform exact and approximate soft-output detection for large-scale MIMO systems with various antenna/user configurations. Reference implementation results for a Xilinx Virtex-7 XC7VX980T FPGA show that our designs are able to achieve more than 600 Mb/s for a 128 antenna, 8 user 3GPP LTE-based large-scale MIMO system. We finally provide a performance/complexity trade-off comparison using the presented FPGA designs, which reveals that the detector circuit of choice is determined by the ratio between BS antennas and users, as well as the desired error-rate performance.
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Venue: arXiv cs.NI 2014
Year: 2014

Device-to-device (D2D) communication underlaying cellular networks allows mobile devices such as smartphones and tablets to use the licensed spectrum allocated to cellular services for direct peer-to-peer transmission. D2D communication can use either one-hop transmission (i.e., in D2D direct communication) or multi-hop cluster-based transmission (i.e., in D2D local area networks). The D2D devices can compete or cooperate with each other to reuse the radio resources in D2D networks. Therefore, resource allocation and access for D2D communication can be treated as games. The theories behind these games provide a variety of mathematical tools to effectively model and analyze the individual or group behaviors of D2D users. In addition, game models can provide distributed solutions to the resource allocation problems for D2D communication. The aim of this article is to demonstrate the applications of game-theoretic models to study the radio resource allocation issues in D2D communication. The article also outlines several key open research directions.