ppxscal/embedding_network huggingface dataset:
Behavioral control through evolutionary neurocontrollers for autonomous mobile robot navigation
Authors: Jose A. Fernandez-Leon, Gerardo G. Acosta, Miguel A. Mayosky
Venue: Robotics and Autonomous Systems (2009)

This paper deals with the study of scaling up behaviors in evolutive robotics (ER). Complex behaviors were obtained from simple ones. Each behavior is supported by an artificial neural network (ANN)-based controller or neurocontroller. Hence, a method for the generation of a hierarchy of neurocontrollers, resorting to the paradigm of Layered Evolution (LE), is developed and verified experimentally through computer simulations and tests in a Khepera^^^(R) micro-robot. Several behavioral modules are initially evolved using specialized neurocontrollers based on different ANN paradigms. The results show that simple behaviors coordination through LE is a feasible strategy that gives rise to emergent complex behaviors. These complex behaviors can then solve real-world problems efficiently. From a pure evolutionary perspective, however, the methodology presented is too much dependent on user's prior knowledge about the problem to solve and also that evolution take place in a rigid, prescribed framework. Mobile robot's navigation in an unknown environment is used as a test bed for the proposed scaling strategies.
A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks
Authors: Juan R. Castro, Oscar Castillo, Patricia Melin, Antonio Rodríguez-Díaz
Venue: Information Sciences: an International Journal (2009)

In real life, information about the world is uncertain and imprecise. The cause of this uncertainty is due to: deficiencies on given information, the fuzzy nature of our perception of events and objects, and on the limitations of the models we use to explain the world. The development of new methods for dealing with information with uncertainty is crucial for solving real life problems. In this paper three interval type-2 fuzzy neural network (IT2FNN) architectures are proposed, with hybrid learning algorithm techniques (gradient descent backpropagation and gradient descent with adaptive learning rate backpropagation). At the antecedents layer, a interval type-2 fuzzy neuron (IT2FN) model is used, and in case of the consequents layer an interval type-1 fuzzy neuron model (IT1FN), in order to fuzzify the rule's antecedents and consequents of an interval type-2 Takagi-Sugeno-Kang fuzzy inference system (IT2-TSK-FIS). IT2-TSK-FIS is integrated in an adaptive neural network, in order to take advantage the best of both models. This provides a high order intuitive mechanism for representing imperfect information by means of use of fuzzy If-Then rules, in addition to handling uncertainty and imprecision. On the other hand, neural networks are highly adaptable, with learning and generalization capabilities. Experimental results are divided in two kinds: in the first one a non-linear identification problem for control systems is simulated, here a comparative analysis of learning architectures IT2FNN and ANFIS is done. For the second kind, a non-linear Mackey-Glass chaotic time series prediction problem with uncertainty sources is studied. Finally, IT2FNN proved to be more efficient mechanism for modeling real-world problems.
Towards many-core implementation of LU decomposition using Peano Curves
Authors: Alexander Heinecke, Michael Bader
Venue: Proceedings of the combined workshops on UnConventional high performance computing workshop plus memory access workshop (2009)

We present our recent research on cache-oblivious algorithms and implementations of parallel LU decomposition on shared-memory multi- and manycore platforms. Our approach uses a block-recursive matrix storage scheme based on space filling curves, and thus extends our work presented at CF'08. The data structure is based on Peano curves, and is separated into a coarse-grain recursive block-matrix scheme, and a fine-grain iterative order for the elementary matrix blocks. The block element order is derived from the recursive construction of a Peano space-filling curve. The block matrices are stored in ordinary row-major order, and form elementary data types for the block operations. The block size is chosen to perfectly fit the lowest-level data cache in the CPU's cache hierarchy. All matrix operations on this two-level data structure are implemented via routines working on block matrices as operands, and are optimised assembler to exploit the SIMD capacities of the CPUs. For parallelisation on shared memory platforms, we compare two different OpenMP implementations -- one based on OpenMP 2.0, which requires explicit scheduling of the block operations to processor cores, and an implementation that exploits the new task concept in OpenMP 3.0. Performance tests on various platforms ranging from desktop systems to an SGI Altix supercomputer, showed that our implementation 'TifaMMy' optimises the use of the available memory hardware by reducing the bandwidth requirements. Hence, the cache-oblivious approach of TifaMMy is also efficient in the context of multi- and manycore environments. We also demonstrated that the OpenMP 3.0 task concept can lead to both well-structured implementations and competitive parallel efficiency for block-recursive, cache-oblivious algorithms.
A constrained edit distance algorithm between semi-ordered trees
Authors: Aïda Ouangraoua, Pascal Ferraro
Venue: Theoretical Computer Science (2009)

In this paper, we propose a formal definition of a new class of trees called semi-ordered trees and a polynomial dynamic programming algorithm to compute a constrained edit distance between such trees. The core of the method relies on a similar approach to compare unordered [Kaizhong Zhang, A constrained edit distance between unordered labeled trees, Algorithmica 15 (1996) 205-222] and ordered trees [Kaizhong Zhang, Algorithms for the constrained editing distance between ordered labeled trees and related problems, Pattern Recognition 28 (3) (1995) 463-474]. The method is currently applied to evaluate the similarity between architectures of apple trees [Vincent Segura, Aida Ouangraoua, Pascal Ferraro, Evelyne Costes, Comparison of tree architecture using tree edit distances: Application to two-year-old apple tree, Euphytica 161 (2007) 155-164].
Enabling new mobile applications with location proofs
Authors: Stefan Saroiu, Alec Wolman
Venue: Proceedings of the 10th workshop on Mobile Computing Systems and Applications (2009)

Location is rapidly becoming the next "killer application" as location-enabled mobile handheld devices proliferate. One class of applications that has yet-to-emerge are those in which users have an incentive to lie about their location. These applications cannot rely solely on the users' devices to discover and transmit location information because users have an incentive to cheat. Instead, such applications require their users to prove their locations. Unfortunately, today's mobile users lack a mechanism to prove their current or past locations. Consequently, these applications have yet to take off despite their potential. This paper presents location proofs - a simple mechanism that enables the emergence of mobile applications that require "proof" of a user's location. A location proof is a piece of data that certifies a receiver to a geographical location. Location proofs are handed out by the wireless infrastructure (e.g., a Wi-Fi access point or a cell tower) to mobile devices. The relatively short range of the wireless radios ensures that these devices are in physical proximity to the wireless transmitter. As a result, these devices are capable of proving their current or past locations to mobile applications. In this paper, we start by describing a mechanism to implement location proofs. We then present a set of six future applications that require location proofs to enable their core functionality.
New examples of Euclidean tight 4-designs
Authors: Etsuko Bannai
Venue: European Journal of Combinatorics (2009)

In this paper we give some new examples of Euclidean tight 4-designs having good combinatorial structures including combinatorial tight 4-(23,7,1) design and tight 4-design in the Hamming scheme H(11,3).
Phantom-BTB: a virtualized branch target buffer design
Authors: Ioana Burcea, Andreas Moshovos
Venue: Proceeding of the 14th international conference on Architectural support for programming languages and operating systems (2009)

Modern processors use branch target buffers (BTBs) to predict the target address of branches such that they can fetch ahead in the instruction stream increasing concurrency and performance. Ideally, BTBs would be sufficiently large to capture the entire working set of the application and sufficiently small for fast access and practical on-chip dedicated storage. Depending on the application, these requirements are at odds. This work introduces a BTB design that accommodates large instruction footprints without dedicating expensive onchip resources. In the proposed Phantom-BTB (PBTB) design, a conventional BTB is augmented with a virtual table that collects branch target information as the application runs. The virtual table does not have fixed dedicated storage. Instead, it is transparently allocated, on demand, in the on-chip caches, at cache line granularity. The entries in the virtual table are proactively prefetched and installed in the dedicated conventional BTB, thus, increasing its perceived capacity. Experimental results with commercial workloads under full-system simulation demonstrate that PBTB improves IPC performance over a 1K-entry BTB by 6.9% on average and up to 12.7%, with a storage overhead of only 8%. Overall, the virtualized design performs within 1% of a conventional 4K-entry, single-cycle access BTB, while the dedicated storage is 3.6 times smaller.
An ohmic RF MEMS switch for reconfigurable microstrip array antennas built on PCB
Authors: M. Spasos, N. Charalampidis, N. Mallios, D. Kampitaki, K. Tsiakmakis, P. Tsivos Soel, R. Nilavalan
Venue: Proceedings of the 7th conference on Circuits, systems, electronics, control and signal processing (2008)

This paper presents the analysis, design and simulation of an ohmic RF MEMS switch specified for reconfigurable microstrip array antennas built on PCB via an integrated monolithic technology. The proposed switch will be used to allow antenna beamforming in the operating frequency range between 2.4GHz and 4GHz. This application requires a great number of these switches to be integrated with an array of microstrip patch elements. The proposed switch exhibits outstanding switching characteristics, following a relatively simple design, which ensures reliability, robustness and high fabrication yield.
Nonparametric Discriminant Analysis for Face Recognition
Authors: Zhifeng Li, Dahua Lin, Xiaoou Tang
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

In this paper, we develop a new framework for face recognition based on nonparametric discriminant analysis (NDA) and multi-classifier integration. Traditional LDA-based methods suffer a fundamental limitation originating from the parametric nature of scatter matrices, which are based on the Gaussian distribution assumption. The performance of these methods notably degrades when the actual distribution is Non-Gaussian. To address this problem, we propose a new formulation of scatter matrices to extend the two-class nonparametric discriminant analysis to multi-class cases. Then, we develop two more improved multi-class NDA-based algorithms (NSA and NFA) with each one having two complementary methods based on the principal space and the null space of the intra-class scatter matrix respectively. Comparing to the NSA, the NFA is more effective in the utilization of the classification boundary information. In order to exploit the complementary nature of the two kinds of NFA (PNFA and NNFA), we finally develop a dual NFA-based multi-classifier fusion framework by employing the over complete Gabor representation to boost the recognition performance. We show the improvements of the developed new algorithms over the traditional subspace methods through comparative experiments on two challenging face databases, Purdue AR database and XM2VTS database.
Triangulation of Bayesian networks with recursive estimation of distribution algorithms
Authors: Txomin Romero, Pedro Larraòaga
Venue: International Journal of Approximate Reasoning (2009)

Bayesian networks can be used as a model to make inferences in domains with intrinsic uncertainty, that is, to determine the probability distribution of a set of variables given the instantiation of another set. The inference is an NP-hard problem. There are several algorithms to make exact and approximate inference. One of the most popular, and that is also an exact method, is the evidence propagation algorithm of Lauritzen and Spiegelhalter [S.L. Lauritzen, D.J. Spiegelhalter, Local computations with probabilities on graphical structures and their application on expert systems, Journal of the Royal Statistical Society B 50 (2) (1988) 157-224], improved later by Jensen et al. [F.V. Jensen, S.L. Lauritzen, K.G. Olesen, Bayesian updating in causal probalistic networks by local computations, In Computational Statistics Quaterly 4 (1990) 269-282]. This algorithm needs an ordering of the variables in order to make the triangulation of the moral graph associated with the original Bayesian network structure. The effectiveness of the inference depends on the variable ordering. In this paper, we will use a new paradigm for evolutionary computation, the estimation of distribution algorithms (EDAs), to get the optimal ordering of the variables to obtain the most efficient triangulation. We will also present a new type of evolutionary algorithm, the recursive EDAs (REDAs). We will prove that REDAs improve the behaviour of EDAs in this particular problem, and that their results are competitive with other triangulation techniques.
A Modular Equational Generalization Algorithm
Authors: María Alpuente, Santiago Escobar, José Meseguer, Pedro Ojeda
Venue: Logic-Based Program Synthesis and Transformation: 18th International Symposium, LOPSTR 2008, Valencia, Spain, July 17-18, 2008, Revised Selected Papers (2009)

This paper presents a modular equational generalization algorithm, where function symbols can have any combination of associativity, commutativity, and identity axioms (including the empty set). This is suitable for dealing with functions that obey algebraic laws, and are typically mechanized by means of equational atributes in rule-based languages such as ASF+SDF, Elan, OBJ, Cafe-OBJ, and Maude. The algorithm computes a complete set of least general generalizations modulo the given equational axioms, and is specified by a set of inference rules that we prove correct. This work provides a missing connection between least general generalization and computing modulo equational theories, and opens up new applications of generalization to rule-based languages, theorem provers and program manipulation tools such as partial evaluators, test case generators, and machine learning techniques, where function symbols obey algebraic axioms. A Web tool which implements the algorithm has been developed which is publicly available.
Expressive Speech Synthesis Using Emotion-Specific Speech Inventories
Authors: Csaba Zainkó, Márk Fék, Géza Németh
Venue: Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction: COST Action 2102 International Conference, Patras, Greece, October 29-31, 2007. Revised Papers (2008)

In this paper we explore the use of emotion-specific speech inventories for expressive speech synthesis. We recorded a semantically neutral sentence and 26 logatoms containing all the diphones and CVC triphones necessary to synthesize the same sentence. The speech material was produced by a professional actress expressing all logatoms and the sentence with the six basic emotions and in neutral tone. 7 emotion-dependent inventories were constructed from the logatoms. The 7 inventories paired with the prosody extracted from the 7 natural sentences were used to synthesize 49 sentences. 194 listeners evaluated the emotions expressed in the logatoms and in the natural and synthetic sentences. The intended emotion was recognized above chance level for 99% of the logatoms and for all natural sentences. Recognition rates significantly above chance level were obtained for each emotion. The recognition rate for some synthetic sentences exceeded that of natural ones.
A Formal Model of Business Application Integration from Web Services (Position Paper)
Authors: Kaiyu Wan, Mubarak Muhammad, Vasu Alagar
Venue: Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science (2009)

Currently there are many service providers on the Web. Industry recognizes that from Web services many different business applications can be quickly created. A Web services composition tool can automate this process. The challenge lies in the creation of an automatic service composition facility which will tap into the potential of Web services, interact with the consumer in getting their business policies, and ensure that the behavior of Web services do not violate business policies while achieving the stated goals of the consumer. In this paper we discuss the architecture specific to this issue, as an add-on to a trustworthy service-oriented architecture. We provide an abstract view of the service creation facility and its environment, and propose suitable formal notations and formal analysis in the construction of this automated facility.
A New Family of Regular Operators Fitting with the Position Automaton Computation
Authors: Pascal Caron, Jean-Marc Champarnaud, Ludovic Mignot
Venue: Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science (2009)

The aim of this paper is to define a new family of regular operators fitting with the construction of the position automaton. These new operators support the computation of the four Glushkov functions (Null, First, Last and Follow), which allows the conversion of an extended expression with n symbol occurrences into a position automaton with n + 1 states.
Facial Expression Recognition with Multi-channel Deconvolution
Authors: Gerald Krell, Robert Niese, Bernd Michaelis
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

Facial expression recognition is an important task in human computer interaction systems to include emotion processing. In this work we present a Multi-Channel Deconvolution method for post processing of face expression data derived from video sequences. Photogrammetric techniques are applied to determine real world geometric measures and to build the feature vector. SVM classification is used to classify a limited number of emotions from the feature vector. A Multi-Channel Deconvolution removes ambiguities at the transitions between different classified emotions. This way, typical temporal behavior of facial expression change is considered.
Phonological Overgeneration in Paninian System
Authors: Malhar Kulkarni
Venue: Sanskrit Computational Linguistics: First and Second International Symposia Rocquencourt, France, October 29-31, 2007 Providence, RI, USA, May 15-17, 2008 Revised Selected and Invited Papers (2009)

In this paper an attempt is made to study the problem of overgeneration that is caused by the application of the system of P¿¿ini The system of P¿¿ini is made up of certain rules stated by him and his commentators namely, K¿ty¿yana and Patañjali. These rules are supposed to produce the forms that are used in the language, i.e. Sanskrit. However, sometimes the technical application of these rules produces such forms which are not actually used in the language. In fact, sometimes it is beyond human capacities to use such forms. In the present paper two such cases dealing with the phonological overgeneration are studied and possible solutions are proposed to avoid the problem.
Local Construction and Coloring of Spanners of Location Aware Unit Disk Graphs
Authors: Andreas Wiese, Evangelos Kranakis
Venue: Graph-Theoretic Concepts in Computer Science: 34th International Workshop, WG 2008, Durham, UK, June 30 --- July 2, 2008. Revised Papers (2008)

We investigate the problem of locally coloring and constructing special spanners of location aware Unit Disk Graphs (UDGs). First we present a local approximation algorithm for the vertex coloring problem in UDGs which uses at most four times as many colors as required by an optimal solution. Then we look at the colorability of spanners of UDGs. In particular we present a local algorithm for constructing a 4-colorable spanner of a unit disk graph. The output consists of the spanner and the 4-coloring. The computed spanner also has the properties that it is planar, the degree of a vertex in the spanner is at most 5 and the angles between two edges are at least ¿/3. By enlarging the locality distance (i.e. the size of the neighborhood which a vertex has to explore in order to compute its color) we can ensure the total weight of the spanner to be arbitrarily close to the weight of a minimum spanning tree.We prove that a local algorithm cannot compute a bipartite spanner of a unit disk graph and therefore our algorithm needs at most one color more than any local algorithm for the task requires. Moreover, we prove that there is no local algorithm for 3-coloring UDGs or spanners of UDGs, even if the 3-colorability of the graph (or the spanner respectively) is guaranteed in advance.
Efficient Collision Algorithm for the 3D Haptic Interaction with Solid Organs in Medical Environments
Authors: F. J. Badesa, M. L.Pinto, J. M. Sabater, J. M. Azorin, J. Sofrony, P. Cardenas
Venue: Proceedings of the 2009 Second International Conferences on Advances in Computer-Human Interactions (2009)

Using haptic (the sensing of touch) technology as an interface in medical and surgical procedures is a large interesting goal because of the benefits involved. This work presents a developed tool for evaluating the performance of a classic 2D-3D processing of a stack of medical preoperative images, and a new version of an efficient and simple algorithm for the integration of the haptic sense in a medical 3D environment generated from the 3D reconstruction. First of all, the developed tool for the 2D segmentation and 3D reconstruction is presented. The classical pipeline for surface 3D reconstruction is reviewed under a parametrical point of view. These parameters will play an important role in the analysis of the haptic behavior. Besides, all the parameters of the reconstruction are accessible and can be modified on-line during the reconstruction procedure. Later, the software architecture used for the integration of the haptic devices is described. The haptic rendering algorithm is detailed, including the collision detection algorithm (a simple ray-tracing scheme programmed using VTK capacities) that is used with the medical images. Finally, some results of the evaluation of the behavior of this algorithm are resumed.