OpenRaiser/Intern-Atlas huggingface dataset:
Phenomenological Model for Growth of Volumes Digital Data
Venue: arXiv cs.CY 2011
Year: 2011

Currently, experts from IT industry are closely monitoring the soaring total volume of digital data. Moreover the problem is not purely technical, it directly affects human civilization as a whole. The growth rate of the all increasing and is already very large. Began is actively appear apocalyptic scenarios of development IT technology, and humanity as a whole. In this paper we propose a constructive alternative to these emotional ideas. Invited to consider the digital industry as a complete system that is developing in close connection with human civilization. Moreover, system self-organizing and essentially nonlinear in its behavior. To study this system is applied system-cybernetic approach. The mathematical model is developed, shows that in the future rate of production of digital data is stabilize at 13.2 ZB per year.
Support-Predicted Modified-CS for Recursive Robust Principal Components' Pursuit
Venue: arXiv cs.IT 2011
Year: 2011

This work proposes a causal and recursive algorithm for solving the "robust" principal components' analysis (PCA) problem. We primarily focus on robustness to correlated outliers. In recent work, we proposed a new way to look at this problem and showed how a key part of its solution strategy involves solving a noisy compressive sensing(CS) problem. However, if the support size of the outliers becomes too large, for a given dimension of the current PC space, then the number of "measurements" available for CS may become too small. In this work, we show how to address this issue by utilizing the correlation of the outliers to predict their support at the current time; and using this as "partial support knowledge" for solving Modified-CS instead of CS.
A Spatial-Epistemic Logic for Reasoning about Security Protocols
Venue: arXiv cs.LO 2011
Year: 2011

Reasoning about security properties involves reasoning about where the information of a system is located, and how it evolves over time. While most security analysis techniques need to cope with some notions of information locality and knowledge propagation, usually they do not provide a general language for expressing arbitrary properties involving local knowledge and knowledge transfer. Building on this observation, we introduce a framework for security protocol analysis based on dynamic spatial logic specifications. Our computational model is a variant of existing pi-calculi, while specifications are expressed in a dynamic spatial logic extended with an epistemic operator. We present the syntax and semantics of the model and logic, and discuss the expressiveness of the approach, showing it complete for passive attackers. We also prove that generic Dolev-Yao attackers may be mechanically determined for any deterministic finite protocol, and discuss how this result may be used to reason about security properties of open systems. We also present a model-checking algorithm for our logic, which has been implemented as an extension to the SLMC system.
Consensus of Discrete-Time Linear Multi-Agent Systems with Observer-Type Protocols
Venue: arXiv cs.SY 2011
Year: 2011

This paper concerns the consensus of discrete-time multi-agent systems with linear or linearized dynamics. An observer-type protocol based on the relative outputs of neighboring agents is proposed. The consensus of such a multi-agent system with a directed communication topology can be cast into the stability of a set of matrices with the same low dimension as that of a single agent. The notion of discrete-time consensus region is then introduced and analyzed. For neurally stable agents, it is shown that there exists an observer-type protocol having a bounded consensus region in the form of an open unit disk, provided that each agent is stabilizable and detectable. An algorithm is further presented to construct a protocol to achieve consensus with respect to all the communication topologies containing a spanning tree. Moreover, for the case where the agents have no poles outside the unit circle,an algorithm is proposed to construct a protocol having an origin-centered disk of radius $δ$ ($0<δ<1$) as its consensus region, where $δ$ has to further satisfy a constraint related to the unstable eigenvalues of a single agent for the case where each agent has a least one eigenvalue outside the unit circle. Finally, the consensus algorithms are applied to solve formation control problems of multi-agent systems.
An Autonomous Long Range Monitoring System For Emergency Operators
Venue: arXiv cs.OH 2011
Year: 2011

Miniaturization and portability of new electronics lead up to wearable devices embedded within garments: a European program called ProeTEX developed multi-purpose sensors integrated within emergency operators' garments in order to monitor their health state and the surrounding environment. This work deals with the development of an autonomous Long Range communication System (LRS), suitable to transmit data between operators' equipment and the local command post, where remote monitoring software is set up. The LRS infrastructure is based on Wi-Fi protocol and modular architecture. Field tests carried out on the developed prototype showed a high reliability in terms of correctly exchanged data and recovering capabilities in case of temporary disconnection, due to the operator's movements.
Ontology based approach for video transmission over the network
Venue: arXiv cs.MM 2011
Year: 2011

With the increase in the bandwidth & the transmission speed over the internet, transmission of multimedia objects like video, audio, images has become an easier work. In this paper we provide an approach that can be useful for transmission of video objects over the internet without much fuzz. The approach provides a ontology based framework that is used to establish an automatic deployment of video transmission system. Further the video is compressed using the structural flow mechanism that uses the wavelet principle for compression of video frames. Finally the video transmission algorithm known as RRDBFSF algorithm is provided that makes use of the concept of restrictive flooding to avoid redundancy thereby increasing the efficiency.
Normal Factor Graphs: A Diagrammatic Approach to Linear Algebra
Venue: arXiv cs.IT 2011
Year: 2011

Inspired by some new advances on normal factor graphs (NFGs), we introduce NFGs as a simple and intuitive diagrammatic approach towards encoding some concepts from linear algebra. We illustrate with examples the workings of such an approach and settle a conjecture of Peterson on the Pfaffian.
Search-based software test data generation using evolutionary computation
Venue: arXiv cs.SE 2011
Year: 2011

Search-based Software Engineering has been utilized for a number of software engineering activities. One area where Search-Based Software Engineering has seen much application is test data generation. Evolutionary testing designates the use of metaheuristic search methods for test case generation. The search space is the input domain of the test object, with each individual or potential solution, being an encoded set of inputs to that test object. The fitness function is tailored to find test data for the type of test that is being undertaken. Evolutionary Testing (ET) uses optimizing search techniques such as evolutionary algorithms to generate test data. The effectiveness of GA-based testing system is compared with a Random testing system. For simple programs both testing systems work fine, but as the complexity of the program or the complexity of input domain grows, GA-based testing system significantly outperforms Random testing.
Fuzzy Approach to Critical Bus Ranking under Normal and Line Outage Contingencies
Venue: arXiv cs.AI 2011
Year: 2011

Identification of critical or weak buses for a given operating condition is an important task in the load dispatch centre. It has become more vital in view of the threat of voltage instability leading to voltage collapse. This paper presents a fuzzy approach for ranking critical buses in a power system under normal and network contingencies based on Line Flow index and voltage profiles at load buses. The Line Flow index determines the maximum load that is possible to be connected to a bus in order to maintain stability before the system reaches its bifurcation point. Line Flow index (LF index) along with voltage profiles at the load buses are represented in Fuzzy Set notation. Further they are evaluated using fuzzy rules to compute Criticality Index. Based on this index, critical buses are ranked. The bus with highest rank is the weakest bus as it can withstand a small amount of load before causing voltage collapse. The proposed method is tested on Five Bus Test System.
Capacity results for compound wiretap channels
Venue: arXiv cs.IT 2011
Year: 2011

We derive a lower bound on the secrecy capacity of the compound wiretap channel with channel state information at the transmitter which matches the general upper bound on the secrecy capacity of general compound wiretap channels given by Liang et al. and thus establishing a full coding theorem in this case. We achieve this with a quite strong secrecy criterion and with a decoder that is robust against the effect of randomisation in the encoding. This relieves us from the need of decoding the randomisation parameter which is in general not possible within this model. Moreover we prove a lower bound on the secrecy capacity of the compound wiretap channel without channel state information.
Satisfiability of General Intruder Constraints with and without a Set Constructor
Venue: arXiv cs.CR 2011
Year: 2011

Many decision problems on security protocols can be reduced to solving so-called intruder constraints in Dolev Yao model. Most constraint solving procedures for protocol security rely on two properties of constraint systems called monotonicity and variable origination. In this work we relax these restrictions by giving a decision procedure for solving general intruder constraints (that do not have these properties) that stays in NP. Our result extends a first work by L. Mazaré in several directions: we allow non-atomic keys, and an associative, commutative and idempotent symbol (for modeling sets). We also discuss several new applications of the results.
DB Category: Denotational Semantics for View-based Database Mappings
Venue: arXiv cs.DB 2011
Year: 2011

We present a categorical denotational semantics for a database mapping, based on views, in the most general framework of a database integration/exchange. Developed database category DB, for databases (objects) and view-based mappings (morphisms) between them, is different from Set category: the morphisms (based on a set of complex query computations) are not functions, while the objects are database instances (sets of relations). The logic based schema mappings between databases, usually written in a highly expressive logical language (ex. LAV, GAV, GLAV mappings, or tuple generating dependency) may be functorially translated into this "computation" category DB. A new approach is adopted, based on the behavioral point of view for databases, and behavioral equivalences for databases and their mappings are established. By introduction of view-based observations for databases, which are computations without side-effects, we define a fundamental (Universal algebra) monad with a power-view endofunctor T. The resulting 2-category DB is symmetric, so that any mapping can be represented as an object (database instance) as well, where a higher-level mapping between mappings is a 2-cell morphism. Database category DB has the following properties: it is equal to its dual, complete and cocomplete. Special attention is devoted to practical examples: a query definition, a query rewriting in GAV Database-integration environment, and the fixpoint solution of a canonical data integration model.
On the Order Optimality of Large-scale Underwater Networks
Venue: arXiv cs.IT 2011
Year: 2011

Capacity scaling laws are analyzed in an underwater acoustic network with $n$ regularly located nodes on a square, in which both bandwidth and received signal power can be limited significantly. A narrow-band model is assumed where the carrier frequency is allowed to scale as a function of $n$. In the network, we characterize an attenuation parameter that depends on the frequency scaling as well as the transmission distance. Cut-set upper bounds on the throughput scaling are then derived in both extended and dense networks having unit node density and unit area, respectively. It is first analyzed that under extended networks, the upper bound is inversely proportional to the attenuation parameter, thus resulting in a highly power-limited network. Interestingly, it is seen that the upper bound for extended networks is intrinsically related to the attenuation parameter but not the spreading factor. On the other hand, in dense networks, we show that there exists either a bandwidth or power limitation, or both, according to the path-loss attenuation regimes, thus yielding the upper bound that has three fundamentally different operating regimes. Furthermore, we describe an achievable scheme based on the simple nearest-neighbor multi-hop (MH) transmission. We show that under extended networks, the MH scheme is order-optimal for all the operating regimes. An achievability result is also presented in dense networks, where the operating regimes that guarantee the order optimality are identified. It thus turns out that frequency scaling is instrumental towards achieving the order optimality in the regimes. Finally, these scaling results are extended to a random network realization. As a result, vital information for fundamental limits of a variety of underwater network scenarios is provided by showing capacity scaling laws.
GLRT-Based Spectrum Sensing with Blindly Learned Feature under Rank-1 Assumption
Venue: arXiv cs.IT 2011
Year: 2011

Prior knowledge can improve the performance of spectrum sensing. Instead of using universal features as prior knowledge, we propose to blindly learn the localized feature at the secondary user. Motivated by pattern recognition in machine learning, we define signal feature as the leading eigenvector of the signal's sample covariance matrix. Feature learning algorithm (FLA) for blind feature learning and feature template matching algorithm (FTM) for spectrum sensing are proposed. Furthermore, we implement the FLA and FTM in hardware. Simulations and hardware experiments show that signal feature can be learned blindly. In addition, by using signal feature as prior knowledge, the detection performance can be improved by about 2 dB. Motivated by experimental results, we derive several GLRT based spectrum sensing algorithms under rank-1 assumption, considering signal feature, signal power and noise power as the available parameters. The performance of our proposed algorithms is tested on both synthesized rank-1 signal and captured DTV data, and compared to other state-of-the-art covariance matrix based spectrum sensing algorithms. In general, our GLRT based algorithms have better detection performance. In addition, algorithms with signal feature as prior knowledge are about 2 dB better than algorithms without prior knowledge.
On the Achievable Rate of Stationary Rayleigh Flat-Fading Channels with Gaussian Inputs
Venue: arXiv cs.IT 2011
Year: 2011

In this work, we consider a discrete-time stationary Rayleigh flat-fading channel with unknown channel state information at transmitter and receiver. The law of the channel is presumed to be known to the receiver. In addition, we assume the power spectral density (PSD) of the fading process to be compactly supported. For i.i.d. zero-mean proper Gaussian input distributions, we investigate the achievable rate. One of the main contributions is the derivation of two new upper bounds on the achievable rate with zero-mean proper Gaussian input symbols. The first one holds only for the special case of a rectangular PSD and depends on the SNR and the spread of the PSD. Together with a lower bound on the achievable rate, which is achievable with i.i.d. zero-mean proper Gaussian input symbols, we have found a set of bounds which is tight in the sense that their difference is bounded. Furthermore, we show that the high SNR slope is characterized by a pre-log of 1-2f_d, where f_d is the normalized maximum Doppler frequency. This pre-log is equal to the high SNR pre-log of the peak power constrained capacity. Furthermore, we derive an alternative upper bound on the achievable rate with i.i.d. input symbols which is based on the one-step channel prediction error variance. The novelty lies in the fact that this bound is not restricted to peak power constrained input symbols like known bounds, e.g. in [1]. Therefore, the derived upper bound can also be used to evaluate the achievable rate with i.i.d. proper Gaussian input symbols. We compare the derived bounds on the achievable rate with i.i.d. zero-mean proper Gaussian input symbols with bounds on the peak power constrained capacity given in [1-3]. Finally, we compare the achievable rate with i.i.d. zero-mean proper Gaussian input symbols with the achievable rate using synchronized detection in combination with a solely pilot based channel estimation.
On Network Coding Capacity - Matroidal Networks and Network Capacity Regions
Venue: arXiv cs.IT 2011
Year: 2011

One fundamental problem in the field of network coding is to determine the network coding capacity of networks under various network coding schemes. In this thesis, we address the problem with two approaches: matroidal networks and capacity regions. In our matroidal approach, we prove the converse of the theorem which states that, if a network is scalar-linearly solvable then it is a matroidal network associated with a representable matroid over a finite field. As a consequence, we obtain a correspondence between scalar-linearly solvable networks and representable matroids over finite fields in the framework of matroidal networks. We prove a theorem about the scalar-linear solvability of networks and field characteristics. We provide a method for generating scalar-linearly solvable networks that are potentially different from the networks that we already know are scalar-linearly solvable. In our capacity region approach, we define a multi-dimensional object, called the network capacity region, associated with networks that is analogous to the rate regions in information theory. For the network routing capacity region, we show that the region is a computable rational polytope and provide exact algorithms and approximation heuristics for computing the region. For the network linear coding capacity region, we construct a computable rational polytope, with respect to a given finite field, that inner bounds the linear coding capacity region and provide exact algorithms and approximation heuristics for computing the polytope. The exact algorithms and approximation heuristics we present are not polynomial time schemes and may depend on the output size.
A Note on the Sum of Correlated Gamma Random Variables
Venue: arXiv cs.IT 2011
Year: 2011

The sum of correlated gamma random variables appears in the analysis of many wireless communications systems, e.g. in systems under Nakagami-m fading. In this Letter we obtain exact expressions for the probability density function (PDF) and the cumulative distribution function (CDF) of the sum of arbitrarily correlated gamma variables in terms of certain Lauricella functions.
Logical Step-Indexed Logical Relations
Venue: arXiv cs.PL 2011
Year: 2011

Appel and McAllester's "step-indexed" logical relations have proven to be a simple and effective technique for reasoning about programs in languages with semantically interesting types, such as general recursive types and general reference types. However, proofs using step-indexed models typically involve tedious, error-prone, and proof-obscuring step-index arithmetic, so it is important to develop clean, high-level, equational proof principles that avoid mention of step indices. In this paper, we show how to reason about binary step-indexed logical relations in an abstract and elegant way. Specifically, we define a logic LSLR, which is inspired by Plotkin and Abadi's logic for parametricity, but also supports recursively defined relations by means of the modal "later" operator from Appel, Melliès, Richards, and Vouillon's "very modal model" paper. We encode in LSLR a logical relation for reasoning relationally about programs in call-by-value System F extended with general recursive types. Using this logical relation, we derive a set of useful rules with which we can prove contextual equivalence and approximation results without counting steps.
Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems
Venue: arXiv cs.SY 2011
Year: 2011

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to operate in a hostile cluttered urban environment, and the distributed and dynamic nature of the communication and computation resources. Model-based robust design is difficult because of the complexity of the hybrid dynamic models including continuous vehicle dynamics, the discrete models of computations and communications, and the size of the problem. We will overview recent advances in methodology and tools to model, analyze, and design robust autonomous aerospace systems operating in uncertain environment, with stress on efficient uncertainty quantification and robust design using the case studies of the mission including model-based target tracking and search, and trajectory planning in uncertain urban environment. To show that the methodology is generally applicable to uncertain dynamical systems, we will also show examples of application of the new methods to efficient uncertainty quantification of energy usage in buildings, and stability assessment of interconnected power networks.
The Language Features and Architecture of B-Prolog
Venue: arXiv cs.PL 2011
Year: 2011

B-Prolog is a high-performance implementation of the standard Prolog language with several extensions including matching clauses, action rules for event handling, finite-domain constraint solving, arrays and hash tables, declarative loop constructs, and tabling. The B-Prolog system is based on the TOAM architecture which differs from the WAM mainly in that (1) arguments are passed old-fashionedly through the stack, (2) only one frame is used for each predicate call, and (3) instructions are provided for encoding matching trees. The most recent architecture, called TOAM Jr., departs further from the WAM in that it employs no registers for arguments or temporary variables, and provides variable-size instructions for encoding predicate calls. This paper gives an overview of the language features and a detailed description of the TOAM Jr. architecture, including architectural support for action rules and tabling.