OpenRaiser/Intern-Atlas huggingface dataset:
Survey study of the QoS Management in Distributed Interactive Simulation Through Dead Reckoning Algorithms
Venue: arXiv cs.NI 2010
Year: 2010

Dead Reckoning mechanism allows reducing the network utilization considerably when used in Distributed Interactive Simulation Applications. However, this technique often ignores available contextual information that may be influential to the state of an entity, sacrificing remote predictive accuracy in favor of low computational complexity. The remainder of this paper focuses on the analysis of the Dead Reckoning Algorithms. Some contributions are expected and overviews of the major bandwidth reduction techniques currently investigated are discussed. A novel extension of Dead Reckoning based on ANFIS systems is suggested to increase the network availability and fulfilling the required QoS in such applications. The model shows it primary benefits regarding the other research contributions, especially in the decision making of the behavior of simulated entities.
Machine Science in Biomedicine: Practicalities, Pitfalls and Potential
Venue: arXiv cs.IR 2010
Year: 2010

Machine Science, or Data-driven Research, is a new and interesting scientific methodology that uses advanced computational techniques to identify, retrieve, classify and analyse data in order to generate hypotheses and develop models. In this paper we describe three recent biomedical Machine Science studies, and use these to assess the current state of the art with specific emphasis on data mining, data assessment, costs, limitations, skills and tool support.
A Generic Scheme for Qualified Logic Programming
Venue: arXiv cs.LO 2010
Year: 2010

Uncertainty in Logic Programming has been investigated since about 25 years, publishing papers dealing with various approaches to semantics and different applications. This report is intended as a first step towards the investigation of qualified computations in Constraint Functional Logic Programming, including uncertain computations as a particular case. We revise an early proposal, namely van Emden's Quantitative Logic Programming, and we improve it in two ways. Firstly, we generalize van Emden's QLP to a generic scheme QLP(D) parameterized by any given Qualification Domain D, which must be a lattice satisfying certain natural axioms. We present several interesting instances for D, one of which corresponds to van Emden's QLP. Secondly, we generalize van Emden's results by providing stronger ones, concerning both semantics and goal solving. We present Qualified SLD Resolution over D, a sound and strongly complete goal solving procedure for QLP(D), which is applicable to open goals and can be efficiently implemented using CLP technology over any constraint domain CD able to deal with qualification constraints over D. We have developed a prototype implementation of some instances of the QLP(D) scheme (including van Emden's QLP) on top of the CFLP system TOY.
Similarity-based Reasoning in Qualified Logic Programming
Venue: arXiv cs.LO 2010
Year: 2010

Similarity-based Logic Programming (briefly, SLP ) has been proposed to enhance the LP paradigm with a kind of approximate reasoning which supports flexible information retrieval applications. This approach uses a fuzzy similarity relation R between symbols in the program's signature, while keeping the syntax for program clauses as in classical LP. Another recent proposal is the QLP(D) scheme for Qualified Logic Programming, an extension of the LP paradigm which supports approximate reasoning and more. This approach uses annotated program clauses and a parametrically given domain D whose elements qualify logical assertions by measuring their closeness to various users' expectations. In this paper we propose a more expressive scheme SQLP(R,D) which subsumes both SLP and QLP(D) as particular cases. We also show that SQLP(R,D) programs can be transformed into semantically equivalent QLP(D) programs. As a consequence, existing QLP(D) implementations can be used to give efficient support for similarity-based reasoning.
Collaborative Structuring of Knowledge by Experts and the Public
Venue: arXiv cs.DL 2010
Year: 2010

There is much debate on how public participation and expertise can be brought together in collaborative knowledge environments. One of the experiments addressing the issue directly is Citizendium. In seeking to harvest the strengths (and avoiding the major pitfalls) of both user-generated wiki projects and traditional expert-approved reference works, it is a wiki to which anybody can contribute using their real names, while those with specific expertise are given a special role in assessing the quality of content. Upon fulfillment of a set of criteria like factual and linguistic accuracy, lack of bias, and readability by non-specialists, these entries are forked into two versions: a stable (and thus citable) approved "cluster" (an article with subpages providing supplementary information) and a draft version, the latter to allow for further development and updates. We provide an overview of how Citizendium is structured and what it offers to the open knowledge communities, particularly to those engaged in education and research. Special attention will be paid to the structures and processes put in place to provide for transparent governance, to encourage collaboration, to resolve disputes in a civil manner and by taking into account expert opinions, and to facilitate navigation of the site and contextualization of its contents.
A dichotomy theorem for conservative general-valued CSPs
Venue: arXiv cs.CC 2010
Year: 2010

We study the complexity of valued constraint satisfaction problems (VCSP). A problem from VCSP is characterised by a \emph{constraint language}, a fixed set of cost functions over a finite domain. An instance of the problem is specified by a sum of cost functions from the language and the goal is to minimise the sum. We consider the case of so-called \emph{conservative} languages; that is, languages containing all unary cost functions, thus allowing arbitrary restrictions on the domains of the variables. We prove a Schaefer-like dichotomy theorem for this case: if all cost functions in the language satisfy a certain condition (specified by a complementary combination of \emph{STP and MJN multimorphisms}) then any instance can be solved in polynomial time by the algorithm of Kolmogorov and Zivny (arXiv:1008.3104v1), otherwise the language is NP-hard. This generalises recent results of Takhanov (STACS'10) who considered $\{0,\infty\}$-valued languages containing additionally all finite-valued unary cost functions, and Kolmogorov and Zivny (arXiv:1008.1555v1) who considered \emph{finite-valued} conservative languages.
Airborne Radar STAP using Sparse Recovery of Clutter Spectrum
Venue: arXiv cs.IT 2010
Year: 2010

Space-time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Statistical-based STAP methods generally need sufficient statistically independent and identically distributed (IID) training data to estimate the clutter characteristics. However, most actual clutter scenarios appear only locally stationary and lack sufficient IID training data. In this paper, by exploiting the intrinsic sparsity of the clutter distribution in the angle-Doppler domain, a new STAP algorithm called SR-STAP is proposed, which uses the technique of sparse recovery to estimate the clutter space-time spectrum. Joint sparse recovery with several training samples is also used to improve the estimation performance. Finally, an effective clutter covariance matrix (CCM) estimate and the corresponding STAP filter are designed based on the estimated clutter spectrum. Both the Mountaintop data and simulated experiments have illustrated the fast convergence rate of this approach. Moreover, SR-STAP is less dependent on prior knowledge, so it is more robust to the mismatch in the prior knowledge than knowledge-based STAP methods. Due to these advantages, SR-STAP has great potential for application in actual clutter scenarios.
Comparative Study of Statistical Skin Detection Algorithms for Sub-Continental Human Images
Venue: arXiv cs.CV 2010
Year: 2010

Object detection has been a focus of research in human-computer interaction. Skin area detection has been a key to different recognitions like face recognition, human motion detection, pornographic and nude image prediction, etc. Most of the research done in the fields of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins. Although there are several intensity invariant approaches to skin detection, the skin color of Indian sub-continentals have not been focused separately. The approach of this research is to make a comparative study between three image segmentation approaches using Indian sub-continental human images, to optimize the detection criteria, and to find some efficient parameters to detect the skin area from these images. The experiments observed that HSV color model based approach to Indian sub-continental skin detection is more suitable with considerable success rate of 91.1% true positives and 88.1% true negatives.
Machine Learning Approaches for Modeling Spammer Behavior
Venue: arXiv cs.IR 2010
Year: 2010

Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy server storage space and consume network bandwidth. Keyword-based spam email filtering strategies will eventually be less successful to model spammer behavior as the spammer constantly changes their tricks to circumvent these filters. The evasive tactics that the spammer uses are patterns and these patterns can be modeled to combat spam. This paper investigates the possibilities of modeling spammer behavioral patterns by well-known classification algorithms such as Naïve Bayesian classifier (Naïve Bayes), Decision Tree Induction (DTI) and Support Vector Machines (SVMs). Preliminary experimental results demonstrate a promising detection rate of around 92%, which is considerably an enhancement of performance compared to similar spammer behavior modeling research.
Geometric construction of voting methods that protect voters' first choices
Venue: arXiv cs.GT 2010
Year: 2010

We consider the possibility of designing an election method that eliminates the incentives for a voter to rank any other candidate equal to or ahead of his or her sincere favorite. We refer to these methods as satisfying the ``Strong Favorite Betrayal Criterion" (SFBC). Methods satisfying our strategic criteria can be classified into four categories, according to their geometrical properties. We prove that two categories of methods are highly restricted and closely related to positional methods (point systems) that give equal points to a voter's first and second choices. The third category is tightly restricted, but if criteria are relaxed slightly a variety of interesting methods can be identified. Finally, we show that methods in the fourth category are largely irrelevant to public elections. Interestingly, most of these methods for satisfying the SFBC do so only ``weakly," in that these methods make no meaningful distinction between the first and second place on the ballot. However, when we relax our conditions and allow (but do not require) equal rankings for first place, a wider range of voting methods are possible, and these methods do indeed make meaningful distinctions between first and second place.
Spectrum Shaping via Network Coding in Cognitive Radio Networks
Venue: arXiv cs.NI 2010
Year: 2010

We consider a cognitive radio network where primary users (PUs) employ network coding for data transmissions. We view network coding as a spectrum shaper, in the sense that it increases spectrum availability to secondary users (SUs) and offers more structure of spectrum holes that improves the predictability of the primary spectrum. With this spectrum shaping effect of network coding, each SU can carry out adaptive channel sensing by dynamically updating the list of the PU channels predicted to be idle while giving priority to these channels when sensing. This dynamic spectrum access approach with network coding improves how SUs detect and utilize temporal spectrum holes over PU channels. Our results show that compared to the existing approaches based on retransmission, both PUs and SUs can achieve higher stable throughput, thanks to the spectrum shaping effect of network coding.
Wrapper/TAM Co-Optimization and Test Scheduling for SOCs Using Rectangle Bin Packing Considering Diagonal Length of Rectangles
Venue: arXiv cs.OH 2010
Year: 2010

This paper describes an integrated framework for SOC test automation. This framework is based on a new approach for Wrapper/TAM co-optimization based on rectangle packing considering the diagonal length of the rectangles to emphasize on both TAM widths required by a core and its corresponding testing time. In this paper, we propose an efficient algorithm to construct wrappers that reduce testing time for cores. We then use rectangle packing to develop an integrated scheduling algorithm that incorporates power constraints in the test schedule. The test power consumption is important to consider since exceeding the system's power limit might damage the system.
MAC design for WiFi infrastructure networks: a game-theoretic approach
Venue: arXiv cs.GT 2010
Year: 2010

In WiFi networks, mobile nodes compete for accessing a shared channel by means of a random access protocol called Distributed Coordination Function (DCF). Although this protocol is in principle fair, since all the stations have the same probability to transmit on the channel, it has been shown that unfair behaviors may emerge in actual networking scenarios because of non-standard configurations of the nodes. Due to the proliferation of open source drivers and programmable cards, enabling an easy customization of the channel access policies, we propose a game-theoretic analysis of random access schemes. Assuming that each node is rational and implements a best response strategy, we show that efficient equilibria conditions can be reached when stations are interested in both uploading and downloading traffic. More interesting, these equilibria are reached when all the stations play the same strategy, thus guaranteeing a fair resource sharing. When stations are interested in upload traffic only, we also propose a mechanism design, based on an artificial dropping of layer-2 acknowledgments, to force desired equilibria. Finally, we propose and evaluate some simple DCF extensions for practically implementing our theoretical findings.
An Algebraic View to Gradient Descent Decoding
Venue: arXiv cs.IT 2010
Year: 2010

There are two gradient descent decoding procedures for binary codes proposed independently by Liebler and by Ashikhmin and Barg. Liebler in his paper mentions that both algorithms have the same philosophy but in fact they are rather different. The purpose of this communication is to show that both algorithms can be seen as two ways of understanding the reduction process algebraic monoid structure related to the code. The main tool used for showing this is the Gröbner representation of the monoid associated to the linear code.
A high speed unsupervised speaker retrieval using vector quantization and second-order statistics
Venue: arXiv cs.IR 2010
Year: 2010

This paper describes an effective unsupervised method for query-by-example speaker retrieval. We suppose that only one speaker is in each audio file or in audio segment. The audio data are modeled using a common universal codebook. The codebook is based on bag-of-frames (BOF). The features corresponding to the audio frames are extracted from all audio files. These features are grouped into clusters using the K-means algorithm. The individual audio files are modeled by the normalized distribution of the numbers of cluster bins corresponding to this file. In the first level the k-nearest to the query files are retrieved using vector space representation. In the second level the second-order statistical measure is applied to obtained k-nearest files to find the final result of the retrieval. The described method is evaluated on the subset of Ester corpus of French broadcast news.
Fundamental Results on Fluid Approximations of Stochastic Process Algebra Models
Venue: arXiv cs.LO 2010
Year: 2010

In order to avoid the state space explosion problem encountered in the quantitative analysis of large scale PEPA models, a fluid approximation approach has recently been proposed, which results in a set of ordinary differential equations (ODEs) to approximate the underlying continuous time Markov chain (CTMC). This paper presents a mapping semantics from PEPA to ODEs based on a numerical representation scheme, which extends the class of PEPA models that can be subjected to fluid approximation. Furthermore, we have established the fundamental characteristics of the derived ODEs, such as the existence, uniqueness, boundedness and nonnegativeness of the solution. The convergence of the solution as time tends to infinity for several classes of PEPA models, has been proved under some mild conditions. For general PEPA models, the convergence is proved under a particular condition, which has been revealed to relate to some famous constants of Markov chains such as the spectral gap and the Log-Sobolev constant. This thesis has established the consistency between the fluid approximation and the underlying CTMCs for PEPA, i.e. the limit of the solution is consistent with the equilibrium probability distribution corresponding to a family of underlying density dependent CTMCs.
Targeting by Transnational Terrorist Groups
Venue: arXiv cs.GT 2010
Year: 2010

Many successful terrorist groups operate across international borders where different countries host different stages of terrorist operations. Often the recruits for the group come from one country or countries, while the targets of the operations are in another. Stopping such attacks is difficult because intervention in any region or route might merely shift the terrorists elsewhere. Here we propose a model of transnational terrorism based on the theory of activity networks. The model represents attacks on different countries as paths in a network. The group is assumed to prefer paths of lowest cost (or risk) and maximal yield from attacks. The parameters of the model are computed for the Islamist-Salafi terrorist movement based on open source data and then used for estimation of risks of future attacks. The central finding is that the USA has an enduring appeal as a target, due to lack of other nations of matching geopolitical weight or openness. It is also shown that countries in Africa and Asia that have been overlooked as terrorist bases may become highly significant threats in the future. The model quantifies the dilemmas facing countries in the effort to cut such networks, and points to a limitation of deterrence against transnational terrorists.
WiNV: A Framework for Web-based Interactive Scalable Network Visualization
Venue: arXiv cs.NI 2010
Year: 2010

In this paper we introduce WiNV - A framework for web-based interactive scalable network visualization. WiNV enables a new class of rich and scalable interactive cross-platform capabilities for visualizing large-scale networks natively in a user's browser. Extensive experiments show that our system can visualize networks that consist of tens of thousands of nodes while maintaining fast, high-quality interaction.
Sorting Reordered Packets with Interrupt Coalescing
Venue: arXiv cs.NI 2010
Year: 2010

TCP performs poorly in networks with serious packet reordering. Processing reordered packets in the TCP layer is costly and inefficient, involving interaction of the sender and receiver. Motivated by the interrupt coalescing mechanism that delivers packets upward for protocol processing in blocks, we propose a new strategy, Sorting Reordered Packets with Interrupt Coalescing (SRPIC), to reduce packet reordering in the receiver. SRPIC works in the network device driver; it makes use of the interrupt coalescing mechanism to sort the reordered packets belonging to the same TCP stream in a block of packets before delivering them upward; each sorted block is internally ordered. Experiments have proven the effectiveness of SRPIC against forward-path reordering.
Multiple source, single sink maximum flow in a planar graph
Venue: arXiv cs.DM 2010
Year: 2010

We give an $O(n^{1.5}\log n)$ time algorithm for finding the maximum flow in a directed planar graph with multiple sources and a single sink. The techniques generalize to a subquadratic time algorithm for bounded genus graphs.
Efficient Privacy-Preserving Authentication Protocol for Vehicular Communications with Trustworthy
Venue: arXiv cs.CR 2010
Year: 2010

In this paper, we introduce an efficient and trustworthy conditional privacy-preserving communication protocol for VANETs based on proxy re-signature. The proposed protocol is characterized by the Trusted Authority (TA) designating the Roadside Units (RSUs) to translate signatures computed by the On-Board Units (OBUs) into one that are valid with respect to TA's public key. In addition, the proposed protocol offers both a priori and a posteriori countermeasures: it can not only provide fast anonymous authentication and privacy tracking, but guarantees message trustworthiness for vehicle-to-vehicle (V2V) communications. Furthermore, it reduces the communication overhead and offers fast message authentication and, low storage requirements. We use extensive analysis to demonstrate the merits of the proposed protocol and to contrast it with previously proposed solutions.
Symmetry Breaking for Answer Set Programming
Venue: arXiv cs.LO 2010
Year: 2010

In the context of answer set programming, this work investigates symmetry detection and symmetry breaking to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We contribute a reduction of symmetry detection to a graph automorphism problem which allows to extract symmetries of a logic program from the symmetries of the constructed coloured graph. We also propose an encoding of symmetry-breaking constraints in terms of permutation cycles and use only generators in this process which implicitly represent symmetries and always with exponential compression. These ideas are formulated as preprocessing and implemented in a completely automated flow that first detects symmetries from a given answer set program, adds symmetry-breaking constraints, and can be applied to any existing answer set solver. We demonstrate computational impact on benchmarks versus direct application of the solver. Furthermore, we explore symmetry breaking for answer set programming in two domains: first, constraint answer set programming as a novel approach to represent and solve constraint satisfaction problems, and second, distributed nonmonotonic multi-context systems. In particular, we formulate a translation-based approach to constraint answer set solving which allows for the application of our symmetry detection and symmetry breaking methods. To compare their performance with a-priori symmetry breaking techniques, we also contribute a decomposition of the global value precedence constraint that enforces domain consistency on the original constraint via the unit-propagation of an answer set solver. We evaluate both options in an empirical analysis. In the context of distributed nonmonotonic multi-context system, we develop an algorithm for distributed symmetry detection and also carry over symmetry-breaking constraints for distributed answer set programming.