OpenRaiser/Intern-Atlas huggingface dataset:
Identifying critical features for network forensics investigation perspectives
Venue: arXiv cs.CR 2012
Year: 2012

Research in the field of network forensics is gradually expanding with the propensity to fully accommodate the tenacity to help in adjudicating, curbing and apprehending the exponential growth of cyber crimes. However, investigating cyber crime differs, depending on the perspective of investigation. There is therefore the need for a comprehensive model, containing relevant critical features required for a thorough investigation for each perspective, which can be adopted by investigators. This paper therefore presents the findings on the critical features for each perspective, as well as their characteristics. The paper also presents a review of existing frameworks on network forensics. Furthermore, the paper discussed an illustrative methodological process for each perspective encompassing the relevant critical features. These illustrations present a procedure for the thorough investigation in network forensics.
An Improved Proof-Theoretic Compilation of Logic Programs
Venue: arXiv cs.LO 2012
Year: 2012

In prior work, we showed that logic programming compilation can be given a proof-theoretic justification for generic abstract logic programming languages, and demonstrated this technique in the case of hereditary Harrop formulas and their linear variant. Compiled clauses were themselves logic formulas except for the presence of a second-order abstraction over the atomic goals matching their head. In this paper, we revisit our previous results into a more detailed and fully logical justification that does away with this spurious abstraction. We then refine the resulting technique to support well-moded programs efficiently.
Annotation of Logic Programs for Independent AND-Parallelism by Partial Evaluation
Venue: arXiv cs.PL 2012
Year: 2012

Traditional approaches to automatic AND-parallelization of logic programs rely on some static analysis to identify independent goals that can be safely and efficiently run in parallel in any possible execution. In this paper, we present a novel technique for generating annotations for independent AND-parallelism that is based on partial evaluation. Basically, we augment a simple partial evaluation procedure with (run-time) groundness and variable sharing information so that parallel conjunctions are added to the residual clauses when the conditions for independence are met. In contrast to previous approaches, our partial evaluator is able to transform the source program in order to expose more opportunities for parallelism. To the best of our knowledge, we present the first approach to a parallelizing partial evaluator.
Relative Expressiveness of Defeasible Logics
Venue: arXiv cs.AI 2012
Year: 2012

We address the relative expressiveness of defeasible logics in the framework DL. Relative expressiveness is formulated as the ability to simulate the reasoning of one logic within another logic. We show that such simulations must be modular, in the sense that they also work if applied only to part of a theory, in order to achieve a useful notion of relative expressiveness. We present simulations showing that logics in DL with and without the capability of team defeat are equally expressive. We also show that logics that handle ambiguity differently -- ambiguity blocking versus ambiguity propagating -- have distinct expressiveness, with neither able to simulate the other under a different formulation of expressiveness.
A Class of Non Invertible Matrices in GF (2) for Practical One Way Hash Algorithm
Venue: arXiv cs.CR 2012
Year: 2012

In this paper, we describe non invertible matrix in GF(2)which can be used as multiplication matrix in Hill Cipher technique for one way hash algorithm. The matrices proposed are permutation matrices with exactly one entry 1 in each row and each column and 0 elsewhere. Such matrices represent a permutation of m elements. Since the invention, Hill cipher algorithm was used for symmetric encryption, where the multiplication matrix is the key. The Hill cipher requires the inverse of the matrix to recover the plaintext from cipher text. We propose a class of matrices in GF(2) which are non invertible and easy to generate.
Synthesis of Reactive Protocols for Vehicle-to-Vehicle Communication
Venue: arXiv cs.SY 2012
Year: 2012

We present a synthesis method for communication protocols for active safety applications that satisfy certain formal specifications on quality of service requirements. The protocols are developed to provide reliable communication services for automobile active safety applications. The synthesis method transforms a specification into a distributed implementation of senders and receivers that together satisfy the quality of service requirements by transmitting messages over an unreliable medium. We develop a specification language and an execution model for the implementations, and demonstrate the viability of our method by developing a protocol for a traffic scenario in which a car runs a red light at a busy intersection.
A Declarative Recommender System for Cloud Infrastructure Services Selection
Venue: arXiv cs.DC 2012
Year: 2012

The cloud infrastructure services landscape advances steadily leaving users in the agony of choice...
VCS: Value Chains Simulator, a Tool for Value Analysis of Manufacturing Enterprise Processes (A Value-Based Decision Support Tool)
Venue: arXiv cs.OH 2012
Year: 2012

Manufacturing enterprises are facing a competitive challenge. This paper proposes the use of a value chain based approach to support the modelling and simulation of manufacturing enterprise processes. The aim is to help experts to make relevant decisions on product design and/or product manufacturing process planning. This decision tool is based on the value chain modelling, by considering the product requirements. In order to evaluate several performance indicators, a simulation of various potential value chains adapted to market demand was conducted through a Value Chains Simulator (VCS). A discrete event simulator is used to perform the simulation of these scenarios and to evaluate the value as a global performance criterion (balancing cost, quality, delivery time, services, etc.). An Analytical Hierarchy Process module supports the analysis process. The value chain model is based on activities and uses the concepts of resource consumption, while integrating the benefiting entities view point. A case study in the microelectronic field is carried out to corroborate the validity of the proposed VCS.
Approximate Ergodic Capacity of a Class of Fading 2-user 2-hop Networks
Venue: arXiv cs.IT 2012
Year: 2012

We consider a fading AWGN 2-user 2-hop network where the channel coefficients are independent and identically distributed (i.i.d.) drawn from a continuous distribution and vary over time. For a broad class of channel distributions, we characterize the ergodic sum capacity to within a constant number of bits/sec/Hz, independent of signal-to-noise ratio. The achievability follows from the analysis of an interference neutralization scheme where the relays are partitioned into $M$ pairs, and interference is neutralized separately by each pair of relays. When $M=1$, the proposed ergodic interference neutralization characterizes the ergodic sum capacity to within $4$ bits/sec/Hz for i.i.d. uniform phase fading and approximately $4.7$ bits/sec/Hz for i.i.d. Rayleigh fading. We further show that this gap can be tightened to $4\log π-4$ bits/sec/Hz (approximately $2.6$) for i.i.d. uniform phase fading and $4-4\log( \frac{3π}{8})$ bits/sec/Hz (approximately $3.1$) for i.i.d. Rayleigh fading in the limit of large $M$.
A Fast Distributed Proximal-Gradient Method
Venue: arXiv cs.DC 2012
Year: 2012

We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private local objective of an agent in a network with time-varying topology. The local objectives have distinct differentiable components, but they share a common nondifferentiable component, which has a favorable structure suitable for effective computation of the proximal operator. In our method, each agent iteratively updates its estimate of the global minimum by optimizing its local objective function, and exchanging estimates with others via communication in the network. Using Nesterov-type acceleration techniques and multiple communication steps per iteration, we show that this method converges at the rate 1/k (where k is the number of communication rounds between the agents), which is faster than the convergence rate of the existing distributed methods for solving this problem. The superior convergence rate of our method is also verified by numerical experiments.
Disjunctive Datalog with Existential Quantifiers: Semantics, Decidability, and Complexity Issues
Venue: arXiv cs.AI 2012
Year: 2012

Datalog is one of the best-known rule-based languages, and extensions of it are used in a wide context of applications. An important Datalog extension is Disjunctive Datalog, which significantly increases the expressivity of the basic language. Disjunctive Datalog is useful in a wide range of applications, ranging from Databases (e.g., Data Integration) to Artificial Intelligence (e.g., diagnosis and planning under incomplete knowledge). However, in recent years an important shortcoming of Datalog-based languages became evident, e.g. in the context of data-integration (consistent query-answering, ontology-based data access) and Semantic Web applications: The language does not permit any generation of and reasoning with unnamed individuals in an obvious way. In general, it is weak in supporting many cases of existential quantification. To overcome this problem, Datalogex has recently been proposed, which extends traditional Datalog by existential quantification in rule heads. In this work, we propose a natural extension of Disjunctive Datalog and Datalogex, called Datalogexor, which allows both disjunctions and existential quantification in rule heads and is therefore an attractive language for knowledge representation and reasoning, especially in domains where ontology-based reasoning is needed. We formally define syntax and semantics of the language Datalogexor, and provide a notion of instantiation, which we prove to be adequate for Datalogexor. A main issue of Datalogex and hence also of Datalogexor is that decidability is no longer guaranteed for typical reasoning tasks. In order to address this issue, we identify many decidable fragments of the language, which extend, in a natural way, analog classes defined in the non-disjunctive case. Moreover, we carry out an in-depth complexity analysis, deriving interesting results which range from Logarithmic Space to Exponential Time.
Ostrowski Numeration and the Local Period of Sturmian Words
Venue: arXiv cs.FL 2012
Year: 2012

We show that the local period at position n in a characteristic Sturmian word can be given in terms of the Ostrowski representation for n + 1.
Quick Search for Rare Events
Venue: arXiv cs.IT 2012
Year: 2012

Rare events can potentially occur in many applications. When manifested as opportunities to be exploited, risks to be ameliorated, or certain features to be extracted, such events become of paramount significance. Due to their sporadic nature, the information-bearing signals associated with rare events often lie in a large set of irrelevant signals and are not easily accessible. This paper provides a statistical framework for detecting such events so that an optimal balance between detection reliability and agility, as two opposing performance measures, is established. The core component of this framework is a sampling procedure that adaptively and quickly focuses the information-gathering resources on the segments of the dataset that bear the information pertinent to the rare events. Particular focus is placed on Gaussian signals with the aim of detecting signals with rare mean and variance values.
Rapid Recovery for Systems with Scarce Faults
Venue: arXiv cs.SY 2012
Year: 2012

Our goal is to achieve a high degree of fault tolerance through the control of a safety critical systems. This reduces to solving a game between a malicious environment that injects failures and a controller who tries to establish a correct behavior. We suggest a new control objective for such systems that offers a better balance between complexity and precision: we seek systems that are k-resilient. In order to be k-resilient, a system needs to be able to rapidly recover from a small number, up to k, of local faults infinitely many times, provided that blocks of up to k faults are separated by short recovery periods in which no fault occurs. k-resilience is a simple but powerful abstraction from the precise distribution of local faults, but much more refined than the traditional objective to maximize the number of local faults. We argue why we believe this to be the right level of abstraction for safety critical systems when local faults are few and far between. We show that the computational complexity of constructing optimal control with respect to resilience is low and demonstrate the feasibility through an implementation and experimental results.
Deciding KAT and Hoare Logic with Derivatives
Venue: arXiv cs.FL 2012
Year: 2012

Kleene algebra with tests (KAT) is an equational system for program verification, which is the combination of Boolean algebra (BA) and Kleene algebra (KA), the algebra of regular expressions. In particular, KAT subsumes the propositional fragment of Hoare logic (PHL) which is a formal system for the specification and verification of programs, and that is currently the base of most tools for checking program correctness. Both the equational theory of KAT and the encoding of PHL in KAT are known to be decidable. In this paper we present a new decision procedure for the equivalence of two KAT expressions based on the notion of partial derivatives. We also introduce the notion of derivative modulo particular sets of equations. With this we extend the previous procedure for deciding PHL. Some experimental results are also presented.
Down the Borel Hierarchy: Solving Muller Games via Safety Games
Venue: arXiv cs.LO 2012
Year: 2012

We transform a Muller game with n vertices into a safety game with (n!)^3 vertices whose solution allows to determine the winning regions of the Muller game and to compute a finite-state winning strategy for one player. This yields a novel antichain-based memory structure and a natural notion of permissive strategies for Muller games. Moreover, we generalize our construction by presenting a new type of game reduction from infinite games to safety games and show its applicability to several other winning conditions.
Interval Temporal Logics over Strongly Discrete Linear Orders: the Complete Picture
Venue: arXiv cs.LO 2012
Year: 2012

Interval temporal logics provide a general framework for temporal reasoning about interval structures over linearly ordered domains, where intervals are taken as the primitive ontological entities. In this paper, we identify all fragments of Halpern and Shoham's interval temporal logic HS with a decidable satisfiability problem over the class of strongly discrete linear orders. We classify them in terms of both their relative expressive power and their complexity. We show that there are exactly 44 expressively different decidable fragments, whose complexity ranges from NP to EXPSPACE. In addition, we identify some new undecidable fragments (all the remaining HS fragments were already known to be undecidable over strongly discrete linear orders). We conclude the paper by an analysis of the specific case of natural numbers, whose behavior slightly differs from that of the whole class of strongly discrete linear orders. The number of decidable fragments over natural numbers raises up to 47: three undecidable fragments become decidable with a non-primitive recursive complexity.
Minimum Grounded Component Based Voltage-Mode Quadrature Oscillator using DVCC
Venue: arXiv cs.OH 2012
Year: 2012

In this paper, a new voltage-mode quadrature oscillator using minimum number of active and passive component is proposed. The proposed circuit employs single modified DVCC, two grounded capacitor and two grounded resistors, which is ideal for IC implementation. The active and passive sensitivity are no more than unity. The proposed circuit is verified through PSPICE simulation results.
Scheduling tree-shaped task graphs to minimize memory and makespan
Venue: arXiv cs.DC 2012
Year: 2012

This paper investigates the execution of tree-shaped task graphs using multiple processors. Each edge of such a tree represents a large IO file. A task can only be executed if all input and output files fit into memory, and a file can only be removed from memory after it has been consumed. Such trees arise, for instance, in the multifrontal method of sparse matrix factorization. The maximum amount of memory needed depends on the execution order of the tasks. With one processor the objective of the tree traversal is to minimize the required memory. This problem was well studied and optimal polynomial algorithms were proposed. Here, we extend the problem by considering multiple processors, which is of obvious interest in the application area of matrix factorization. With the multiple processors comes the additional objective to minimize the time needed to traverse the tree, i.e., to minimize the makespan. Not surprisingly, this problem proves to be much harder than the sequential one. We study the computational complexity of this problem and provide an inapproximability result even for unit weight trees. Several heuristics are proposed, each with a different optimization focus, and they are analyzed in an extensive experimental evaluation using realistic trees.
Multi-view constrained clustering with an incomplete mapping between views
Venue: arXiv cs.LG 2012
Year: 2012

Multi-view learning algorithms typically assume a complete bipartite mapping between the different views in order to exchange information during the learning process. However, many applications provide only a partial mapping between the views, creating a challenge for current methods. To address this problem, we propose a multi-view algorithm based on constrained clustering that can operate with an incomplete mapping. Given a set of pairwise constraints in each view, our approach propagates these constraints using a local similarity measure to those instances that can be mapped to the other views, allowing the propagated constraints to be transferred across views via the partial mapping. It uses co-EM to iteratively estimate the propagation within each view based on the current clustering model, transfer the constraints across views, and then update the clustering model. By alternating the learning process between views, this approach produces a unified clustering model that is consistent with all views. We show that this approach significantly improves clustering performance over several other methods for transferring constraints and allows multi-view clustering to be reliably applied when given a limited mapping between the views. Our evaluation reveals that the propagated constraints have high precision with respect to the true clusters in the data, explaining their benefit to clustering performance in both single- and multi-view learning scenarios.
Improved Approximation Lower Bounds for Vertex Cover on Power Law Graphs and Some Generalizations
Venue: arXiv cs.CC 2012
Year: 2012

We prove new explicit inapproximability results for the Vertex Cover Problem on the Power Law Graphs and some functional generalizations of that class of graphs. Our results depend on special bounded degree amplifier constructions for those classes of graphs and could be also of independent interest.
Data Mining and Its Applications for Knowledge Management: A Literature Review from 2007 to 2012
Venue: arXiv cs.DB 2012
Year: 2012

Data mining is one of the most important steps of the knowledge discovery in databases process and is considered as significant subfield in knowledge management. Research in data mining continues growing in business and in learning organization over coming decades. This review paper explores the applications of data mining techniques which have been developed to support knowledge management process. The journal articles indexed in ScienceDirect Database from 2007 to 2012 are analyzed and classified. The discussion on the findings is divided into 4 topics: (i) knowledge resource; (ii) knowledge types and/or knowledge datasets; (iii) data mining tasks; and (iv) data mining techniques and applications used in knowledge management. The article first briefly describes the definition of data mining and data mining functionality. Then the knowledge management rationale and major knowledge management tools integrated in knowledge management cycle are described. Finally, the applications of data mining techniques in the process of knowledge management are summarized and discussed.
Vibrotactile Stimulus Frequency Optimization for the Haptic BCI Prototype
Venue: arXiv cs.HC 2012
Year: 2012

The paper presents results from a psychophysical study conducted to optimize vibrotactile stimuli delivered to subject finger tips in order to evoke the somatosensory responses to be utilized next in a haptic brain computer interface (hBCI) paradigm. We also present the preliminary EEG evoked responses for the chosen stimulating frequency. The obtained results confirm our hypothesis that the hBCI paradigm concept is valid and it will allow for rapid stimuli presentation in order to improve information-transfer-rate (ITR) of the BCI.
Robust Analog Function Computation via Wireless Multiple-Access Channels
Venue: arXiv cs.IT 2012
Year: 2012

Various wireless sensor network applications involve the computation of a pre-defined function of the measurements without the need for reconstructing each individual sensor reading. Widely-considered examples of such functions include the arithmetic mean and the maximum value. Standard approaches to the computation problem separate computation from communication: quantized sensor readings are transmitted interference-free to a fusion center that reconstructs each sensor reading and subsequently computes the sought function value. Such separation-based computation schemes are generally highly inefficient as a complete reconstruction of individual sensor readings is not necessary for the fusion center to compute a function of them. In particular, if the mathematical structure of the wireless channel is suitably matched (in some sense) to the function, then channel collisions induced by concurrent transmissions of different nodes can be beneficially exploited for computation purposes. Therefore, in this paper a practically relevant analog computation scheme is proposed that allows for an efficient estimate of linear and nonlinear functions over the wireless multiple-access channel. After analyzing the asymptotic properties of the estimation error, numerical simulations are presented to show the potential for huge performance gains when compared with time-division multiple-access based computation schemes.