ppxscal/embedding_network huggingface dataset:
Toward Systemic MAS Development: Enforcing Decentralized Self---organization by Composition and Refinement of Archetype Dynamics
Authors: Jan Sudeikat, Wolfgang Renz
Venue: Engineering Environment-Mediated Multi-Agent Systems: International Workshop, EEMMAS 2007, Dresden, Germany, October 5, 2007. Selected Revised and Invited Papers (2008)

The utilization of self-organizing processes promises scalability, robustness and adaptivity in Multi-Agent Systems (MAS), solely based on decentralized coordination of individual actors. Bionic development approaches have been established, which reuse decentralized coordination mechanisms that are derived from natural self---organizing systems. In this paper, we address analysis activities in incremental MAS development, concerning with the derivation of system architectures that enable applications to meet system requirements. As the functional requirements to self---organizing MAS comprise recurring types of system wide dynamics, we propose a systemic approach to analysis and architectural design activities by the iterative refinement of macroscopic dynamics. Based on a catalog of dynamic models of currently applied environment---mediated design metaphors, we discuss how intended MAS dynamics can be modeled and refined to decentralized MAS designs. A systemic design procedure is proposed and exemplified in a case study that demands the combination of two established design metaphors to enable an projected level of MAS adaptivity.
Rotating Fault Diagnosis Based on Wavelet Kernel Principal Component
Authors: L. Guo, G. M. Dong, J. Chen, Y. Zhu, Y. N. Pan
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

In this paper, the application of nonlinear feature extraction based on wavelet kernel KPCA for faults diagnosis is presented. Mexican hat wavelet kernel is intruded to enhance Kernel-PCA nonlinear mapping capability. The experimental data sets of rotor working under four conditions: normal, oil whirling, rub and unbalance are used to test the WKPCA method. The feature reduction results of WKPCA are compared with that of PCA method and KPCA method. The results indicate that WKPCA can classify the rotor fault type efficiently. The WKPCA is more suitable for nonlinear feature reduction in fault diagnosis area.
k-Ordered Hamilton cycles in digraphs
Authors: Daniela Kühn, Deryk Osthus, Andrew Young
Venue: Journal of Combinatorial Theory Series B (2008)

Given a digraph D, let @d^0(D):=min{@d^+(D),@d^-(D)} be the minimum semi-degree of D. D is k-ordered Hamiltonian if for every sequence s"1,...,s"k of distinct vertices of D there is a directed Hamilton cycle which encounters s"1,...,s"k in this order. Our main result is that every digraph D of sufficiently large order n with @d^0(D)>=@?(n+k)/2@?-1 is k-ordered Hamiltonian. The bound on the minimum semi-degree is best possible. An undirected version of this result was proved earlier by Kierstead, Sarkozy and Selkow [H. Kierstead, G. Sarkozy, S. Selkow, On k-ordered Hamiltonian graphs, J. Graph Theory 32 (1999) 17-25].
Adapting Bayes network structures to non-stationary domains
Authors: Søren Holbech Nielsen, Thomas D. Nielsen
Venue: International Journal of Approximate Reasoning (2008)

When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit a sequential stream of observations, we call the process structural adaptation. Structural adaptation is useful when the learner is set to work in an unknown environment, where a BN is gradually being constructed as observations of the environment are made. Existing algorithms for incremental learning assume that the samples in the database have been drawn from a single underlying distribution. In this paper we relax this assumption, so that the underlying distribution can change during the sampling of the database. The proposed method can thus be used in unknown environments, where it is not even known whether the dynamics of the environment are stable. We state formal correctness results for our method, and demonstrate its feasibility experimentally.
An Application of Causality for Representing and Providing Formal Explanations about the Behavior of the Threshold Accepting Algorithm
Authors: Joaquín Pérez, Laura Cruz, Rodolfo Pazos, Vanesa Landero, Gerardo Reyes, Héctor Fraire, Juan Frausto
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The problem of algorithm selection for solving NP problems arises with the appearance of a variety of heuristic algorithms. The first works claimed the supremacy of some algorithm for a given problem. Subsequent works revealed the supremacy of algorithms only applied to a subset of instances. However, it was not explained why an algorithm solved better a subset of instances. In this respect, this work approaches the problem of explaining through causal model the interrelations between instances characteristics and the inner workings of algorithms. For validating the results of the proposed approach, a set of experiments was carried out in a study case of the Threshold Accepting algorithm to solve the Bin Packing problem. Finally, the proposed approach can be useful for redesigning the logic of heuristic algorithms and for justifying the use of an algorithm to solve an instance subset. This information could contribute to algorithm selection for NP problems.
Multiple-instance content-based image retrieval employing isometric embedded similarity measure
Authors: John Y. Chiang, Shuenn-Ren Cheng
Venue: Pattern Recognition (2009)

In image-based retrieval, global or local features sufficiently discriminative to summarize the image content are commonly extracted first. Traditional features, such as color, texture, shape or corner, characterizing image content are not reliable in terms of similarity measure. A good match in the feature domain does not necessarily map to image pairs with similar relationship. Applying these features as search keys may retrieve dissimilar false-positive images, or leave similar false-negative ones behind. Moreover, images are inherently ambiguous since they contain a great amount of information that justifies many different facets of interpretation. Using a single image to query a database might employ features that do not match user's expectation and retrieve results with low precision/recall ratios. How to automatically extract reliable image features as a query key that matches user's expectation in a content-based image retrieval (CBIR) system is an important topic. The objective of the present work is to propose a multiple-instance learning image retrieval system by incorporating an isometric embedded similarity measure. Multiple-instance learning is a way of modeling ambiguity in supervised learning given multiple examples. From a small collection of positive and negative example images, semantically relevant concepts can be derived automatically and employed to retrieve images from an image database. Each positive and negative example images are represented by a linear combination of fractal orthonormal basis vectors. The mapping coefficients of an image projected onto each orthonormal basis constitute a feature vector. The Euclidean-distance similarity measure is proved to remain consistent, i.e., isometric embedded, between any image pairs before and after the projection onto orthonormal axes. Not only similar images generate points close to each other in the feature space, but also dissimilar ones produce feature points far apart. The utilization of an isometric-embedded fractal-based technique to extract reliable image features, combined with a multiple-instance learning paradigm to derive relevant concepts, can produce desirable retrieval results that better match user's expectation. In order to demonstrate the feasibility of the proposed approach, two sets of test for querying an image database are performed, namely, the fractal-based feature extraction algorithm vs. three other feature extractors, and single-instance vs. multiple-instance learning. Both the retrieval results, execution time and precision/recall curves show favorably for the proposed multiple-instance fractal-based approach.
Predictable performance optimization for wireless networks
Authors: Yi Li, Lili Qiu, Yin Zhang, Ratul Mahajan, Eric Rozner
Venue: Proceedings of the ACM SIGCOMM 2008 conference on Data communication (2008)

We present a novel approach to optimize the performance of IEEE 802.11-based multi-hop wireless networks. A unique feature of our approach is that it enables an accurate prediction of the resulting throughput of individual flows. At its heart lies a simple yet model of the network that captures interference, traffic, and MAC-induced dependencies. Unless properly accounted for, these dependencies lead to unpredictable behaviors. For instance, we show that even a simple network of two links with one flow is vulnerable to severe performance degradation. We design algorithms that build on this model to optimize the network for fairness and throughput. Given traffic demands as input, these algorithms compute rates at which individual flows must send to meet the objective. Evaluation using a multi-hop wireless testbed as well as simulations show that our approach is very effective. When optimizing for fairness, our methods result in close to perfect fairness. When optimizing for throughput, they lead to 100-200% improvement for UDP traffic and 10-50% for TCP traffic.
Power and EM Attacks on Passive $13.56\,\textrm{MHz}$ RFID Devices
Authors: Michael Hutter, Stefan Mangard, Martin Feldhofer
Venue: Proceedings of the 9th international workshop on Cryptographic Hardware and Embedded Systems (2007)

During the last years, more and more security applications have been developed that are based on passive 13.56 MHz RFID devices. Among the most prominent applications are electronic passports and contactless payment systems. This article discusses the effectiveness of power and EM attacks on this kind of devices. It provides an overview of different measurement setups and it presents concrete results of power and EM attacks on two RFID prototype devices. The first device performs AES encryptions in software, while the second one performs AES encryptions in hardware. Both devices have been successfully attacked with less than 1 000 EM traces. These results emphasize the need to include countermeasures into RFID devices.
Fuzzy inference-based control approach for thermal-visual comfort and air quality in indoor environments
Authors: Jean J. Saade, Ali H. Ramadan
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

This paper presents a fuzzy inference-based control approach for the adjustment and maintenance, according to users' preferences, of air quality, thermal and visual comfort for buildings' occupants while minimizing energy consumption. First, the control objectives and criteria are described and their models are provided. Then, the designed fuzzy controller along with the criteria models are simulated using MatLab/Simulink. The simulation results are depicted for each control criterion and the efficiency of the presented approach is verified. It is shown that this approach is capable of responding to fixed and variable users' preferences and eliminating overshoots and oscillations without the need for any adaptive procedure.
Development of a Generic XML Personality Metadata Handler for Distributed Entertainment Services
Authors: Simon Reymann, Jakub Rachwalski, Stefan Kemper, Artur Lugmayr
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

Especially in the case of entertainment services, the provision of a general valid personality profile is gaining in importance. The personality profile shall include information about the usage-context of media services. These media services can be arbitrary and range from simple playlist compilations of audio-visual content to complex feedback profiles in interactive television. This research paper provides an overview of a metadata based solution for merging personalized content. Multiple applications, such as audio or video players contribute with user-context information enabling future personalization scenarios. An XML metadata specification is presented providing a generic container format for representing a personality user profile. To enable generality, the personality profile simply extends existing XML standards by adding attributes and thus keeping the existing structure intact. This also allows the creation of slim and resource efficient personality schemas which are especially beneficial when deployed on resource-sensitive client devices like mobile phones.
A wavelet-based method for overcoming the Gibbs phenomenon
Authors: Nataniel Greene
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

The Gibbs phenomenon refers to the lack of uniform convergence which occurs in many orthogonal basis approximations to piecewise smooth functions. This lack of uniform convergence manifests itself in spurious oscillations near the points of discontinuity and a low order of convergence away from the discontinuities. Here we describe a numerical procedure for overcoming the Gibbs phenomenon called the inverse wavelet reconstruction method. The method takes the Fourier coefficients of an oscillatory partial sum and uses them to construct the wavelet coefficients of a non-oscillatory wavelet series.
Relative Convex Hulls in Semi-dynamic Subdivisions
Authors: Mashhood Ishaque, Csaba D. Tóth
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

We present data structures for maintaining the relative convex hull of a set of points (sites) in the presence of pairwise non-crossing line segments (barriers) that subdivide a bounding box into simply connected faces. Our data structures have O((n + m)logn) size for n sites and m barriers. They support O(m) barrier insertions and O(n) site deletions in O((m + n) polylog (mn)) total time, and can answer analogues of standard convex hull queries in O(polylog(mn)) time.Our data structures support a generalization of the sweep line technique, in which the sweep wavefront may have arbitrary polygonal shape, possibly bending around obstacles. We reduce the total time of m online updates of a polygonal sweep wavefront from $O(m\sqrt{n}\,{\rm polylog} n)$ to O((m + n) polylog (mn)).
Edge Coloring and Decompositions of Weighted Graphs
Authors: Uriel Feige, Mohit Singh
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

We consider two generalizations of the edge coloring problem in bipartite graphs. The first problem we consider is the weighted bipartite edge coloring problem where we are given an edge-weighted bipartite graph G = (V,E) with weights w:E¿[0,1]. The task is to find a proper weighted coloring of the edges with as few colors as possible. An edge coloring of the weighted graph is called a proper weighted coloring if the sum of the weights of the edges incident to a vertex of any color is at most one. We give a polynomial time algorithm for the weighted bipartite edge coloring problem which returns a proper weighted coloring using at most ¿2.25 n¿ colors where n is the maximum total weight incident at any vertex. This improves on the previous best bound of Correa and Goemans [5] which returned a coloring using 2.557n + o(n) colors. The second problem we consider is the Balanced Decomposition of Bipartite graphs problem where we are given a bipartite graph G = (V,E) and ¿ 1,...,¿ k ¿ (0,1) summing to one. The task is to find a partition E 1,..., E k of E such that $deg_{E_i}(v)$ is close to ¿ i deg E (v) for each 1 ≤ i ≤ k and v ¿ V. We give an alternate proof of the result of Correa and Goemans [5] that there is a decomposition such that $\lfloor\alpha_i deg_E(v) \rfloor -2 \leq deg_{E_i}(v) \leq \lceil \alpha_i deg_E(v) \rceil +2$ for each v ¿ V and 1 ≤ i ≤ k. Moreover, we show that the additive error can be improved from two to one if only upper bounds or only lower bounds on the degree are present. All our results hold also for bipartite multigraphs, and the decomposition results hold also for general graphs.
Performance Characterization of Shape Descriptors for Symbol Representation
Authors: Ernest Valveny, Salvatore Tabbone, Oriol Ramos, Emilie Philippot
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

In this paper we propose a general framework for the characterization of shape descriptors and show its application to graphic symbols. The framework is based on the combination of several performance measures independent of the application. We have applied this framework using a standard set of descriptors and databases. We show how it can be used to characterize the properties of each descriptor for a given database.
Extension and use of KMRCRelat algorithm for biological problems
Authors: Nahla El Zant El Kadhi, Nabil El Kadhi, Pierre-Antoine Gourraud
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

The main goal of this paper is to present a new extension of KMRCRelat algorithm allowing Word Train searches. First, we recall the fundamental lemma of our KMRCRelat algorithm and we focus on the concept of flexible relational repeated words. Then, we introduce the concept of Word Trains and we show, in deep, the needed modification and extension to include such features in this algorithm. To illustrate Word Train searches, we present all details about KMRCRelat extension computation steps. We also show how this new extension is applicable to the characterization of short tandem repeat in DNA sequence providing an alternative way to solve originally this known problem in sequence analysis. Before concluding by introducing other possible KMRCRelat applications, the paper expands a set of experimental results obtained when applied to locus identification problem.
A Watermarking Approach for MIDI File Based on Velocity and Duration Modulation
Authors: Alexander Adli, Hanane Mirza, Zensho Nakao
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

The feasibility of inserting a signature into a musical file is proven to be one of widely used technique for copyright and security purposes. In this paper we present a brief overview of the watermarking approaches and implementation in simple MIDI files (SMF). The authors suggest a method based on velocity and duration modulation to embed a digital logo representing watermark data. The watermark robustness is shown via experiments with simulated attacks. Potential problems are discussed in further studies.
Addressing Cross-Tool Semantic Ambiguities in Behavior Modeling for Vehicle Motion Control
Authors: Sandeep Neema, Sushil Birla, Shige Wang, Tripti Saxena
Venue: Model-Driven Development of Reliable Automotive Services: Second Automotive Software Workshop, ASWSD 2006, San Diego, CA, USA, March 15-17, 2006, Revised Selected Papers (2006)

Emerging model-based development methods in the Automotive Vehicle Motion Control (VMC) domain are using different tools at various stages of the engineering process. Behavioral models created in various forms of finite state machines have to be exchanged across these tools, but semantic unknowns in modeling environments and semantic variations across tools preclude automated correct interpretation. This research presents an approach to address this issue through an unambiguous, math-based, tool-neutral extended finite state machine metamodel (eFSM) for behavior specifications in the automotive VMC domain. The semantics of the metamodel are anchored to formal specifications in a mathematical framework. Our approach requires modeling with commercial tool environments conforming to the eFSM. The conformance is enforced by exporting the tool native models into eFSM-conformant models and checking them against the well-formed rules encoded as OCL constraints in the eFSM. We have performed "proof of concept" exercises with two commercial tools in transforming their native models into eFSM-conformant forms, and have been able to show that certain ambiguities in both tools can be prevented through the eFSM, promising higher confidence software engineering for the VMC domain.
Combining Classifiers for Web Violent Content Detection and Filtering
Authors: Radhouane Guermazi, Mohamed Hammami, Abdelmajid Hamadou
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Keeping people away from litigious information becomes one of the most important research area in network information security. Indeed, Web filtering is used to prevent access to undesirable Web pages. In this paper we review some existing solutions, then we propose a violent Web content detection and filtering system called "WebAngels filter" which uses textual and structural analysis. "WebAngels filter" has the advantage of combining several data-mining algorithms for Web site classification. We discuss how the combination learning based methods can improve filtering performances. Our preliminary results show that it can detect and filter violent content effectively.
Electric properties of diatomic molecules: A comparison of finite basis set and finite difference Hartree-Fock calculations
Authors: J. Kobus, D. Moncrieff, S. Wilson
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

Recent work comparing the accuracy with which the electric properties of diatomic molecules can be obtained in the Hartree-Fock model from finite basis set (the algebraic approximation) and finite difference techniques is reviewed. The electric moments &mu;, &Theta;, &Omega; and &Phi; are considered together with the electric dipole polarizability &alpha;$_{zz}$ and hyperpolarizability &beta;$_{zzz}$. By comparing results obtained within the finite basis set approximation with those given by using finite difference techniques, accurate estimates of the basis set truncation errors corresponding to different electric properties of diatomic molecules can be gained. Accurate Hartree-Fock calculations of these electric properties are an essential prerequisite of precision correlation studies.
Presence Technology: More than Just Instant Messaging
Authors: Steven J. Vaughan-Nichols
Venue: Computer (2003)

In many popular visions of ubiquitous computing, the environment proactively responds to individuals who inhabit the space. For example, a display magically presents a personalized advertisement, the most relevant video feed, or the desired page from a secret government document. Such capability requires more than an abundance of networked displays, devices, and sensors; it relies implicitly on recommendation systems that either directly serve the end user or provide critical services to some other application.