ppxscal/embedding_network huggingface dataset:
Live distributed objects
Authors: Ken Birman
Venue:  (2008)

Distributed multiparty protocols such as multicast, atomic commit, or gossip are currently underutilized, but we envision that they could be used pervasively, and that developers could work with such protocols similarly to how they work with CORBA/COM/.NET/Java objects. We have created a new programming model and a platform in which protocol instances are represented as objects of a new type called live distributed objects: strongly-typed building blocks that can be composed in a type-safe manner through a drag and drop interface. Unlike most prior object-oriented distributed protocol embeddings, our model appears to be flexible enough to accommodate most popular protocols, and to be applied uniformly to any part of a distributed system, to build not only front-end, but also back-end components, such as multicast channels, naming, or membership services. While the platform is not limited to applications based on multicast, it is replication-centric, and reliable multicast protocols are important building blocks that can be used to create a variety of scalable components, from shared documents to fault-tolerant storage or scalable role delegation. We propose a new multicast architecture compatible with the model and designed in accordance with object-oriented principles such as modularity and encapsulation. The architecture represents multicast objects as compositions of smaller objects, glued using a decentralized membership mechanism. The benefits include support for heterogeneous networks by allowing a single multicast protocol instance to simultaneously leverage different mechanisms in different parts of the Internet.Finally, we describe and evaluate a scalable reliable multicast prototype that incorporates a novel approach to scaling with the number of protocol instances by leveraging regular patterns of overlap. The system achieves exceptional performance, scalability, and stability in the presence of perturbations, in part thanks to a novel application of techniques such as priority scheduling or pull-based processing. We describe a previously unnoticed relationship between memory overheads and scheduling and the performance and scalability of a reliable multicast protocol. Our results demonstrate that to build a new global Web operating system that the live objects vision leads to, the distributed protocol and the local system architecture cannot be treated in isolation.
Incremental Diagnosis of DES by Satisfiability
Authors: Alban Grastien, Anbulagan
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We propose a SAT-based algorithm for incremental diagnosis of discrete-event systems. The monotonicity is ensured by a prediction window that uses the future observations to lead the current diagnosis. Experiments stress the impact of parameters tuning on the correctness and the efficiency of the approach.
The Empirical Case Against Analyticity: Two Options for Concept Pragmatists
Authors: Bradley Rives
Venue: Minds and Machines (2009)

It is commonplace in cognitive science that concepts are individuated in terms of the roles they play in the cognitive lives of thinkers, a view that Jerry Fodor has recently been dubbed `Concept Pragmatism'. Quinean critics of Pragmatism have long argued that it founders on its commitment to the analytic/synthetic distinction, since without such a distinction there is plausibly no way to distinguish constitutive from non-constitutive roles in cognition. This paper considers Fodor's empirical arguments against analyticity, and in particular his arguments against lexical decomposition and definitions, and argues that Concept Pragmatists have two viable options with respect to them. First, Concept Pragmatists can confront them head-on, and argue that they do not show that lexical items are semantically primitive or that lexical concepts are internally unstructured. Second, Pragmatists may accept that these arguments show that lexical concepts are atomic, but insist that this need not entail that Pragmatism is false. For there is a viable version of Concept Pragmatism that does not take lexical items to be semantically structured or lexical concepts to be internally structured. Adopting a version of Pragmatism that takes meaning relations to be specified by inference rules, or meaning postulates, allows one to accept the empirical arguments in favor of Concept Atomism, while at the same time deny that such arguments show that there are no analyticities. The paper concludes by responding to Fodor's recent objection that such a version of Concept Pragmatism has unhappy consequences concerning the relation between concept constitution and concept possession.
A Tool for Automatic Code Generation from Schemas
Authors: Antonio Gavilanes, Pedro J. Martín, Roberto Torres
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

Algorithm design is one of the more neglected aspects in programming introduction courses. On the contrary, schemas focus on solution construction, since they gather common characteristics of algorithms, so they can be considered as algorithm cognitive units. In this paper, we go beyond the benefits of teaching schemas and we present a tool that incorporates their use. It automatically generates code from the application of schemas, allowing its integration into the class as a useful educational tool.
Decompounding query keywords from compounding languages
Authors: Enrique Alfonseca, Slaven Bilac, Stefan Pharies
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

Splitting compound words has proved to be useful in areas such as Machine Translation, Speech Recognition or Information Retrieval (IR). Furthermore, real-time IR systems (such as search engines) need to cope with noisy data, as user queries are sometimes written quickly and submitted without review. In this paper we apply a state-of-the-art procedure for German decompounding to other compounding languages, and we show that it is possible to have a single decompounding model that is applicable across languages.
Learning block-preserving graph patterns and its application to data mining
Authors: Hitoshi Yamasaki, Yosuke Sasaki, Takayoshi Shoudai, Tomoyuki Uchida, Yusuke Suzuki
Venue: Machine Learning (2009)

Recently, due to the rapid growth of electronic data having graph structures such as HTML and XML texts and chemical compounds, many researchers have been interested in data mining and machine learning techniques for finding useful patterns from graph-structured data (graph data). Since graph data contain a huge number of substructures and it tends to be computationally expensive to decide whether or not such data have given structural features, graph mining problems face computational difficulties. Let ${\mathcal{C}}$ be a graph class which satisfies a connected hereditary property and contains infinitely many different biconnected graphs, and for which a special kind of the graph isomorphism problem can be computed in polynomial time. In this paper, we consider learning and mining problems for ${\mathcal{C}}$ . Firstly, we define a new graph pattern, which is called a block preserving graph pattern (bp-graph pattern) for ${\mathcal{C}}$ . Secondly, we present a polynomial time algorithm for deciding whether or not a given bp-graph pattern matches a given graph in ${\mathcal{C}}$ . Thirdly, by giving refinement operators over bp-graph patterns, we present a polynomial time algorithm for finding a minimally generalized bp-graph pattern for ${\mathcal{C}}$ . Outerplanar graphs are planar graphs which can be embedded in the plane in such a way that all of vertices lie on the outer boundary. Many pharmacologic chemical compounds are known to be represented by outerplanar graphs. The class of connected outerplanar graphs ${\mathcal{O}}$ satisfies the above conditions for ${\mathcal{C}}$ . Next, we propose two incremental polynomial time algorithms for enumerating all frequent bp-graph patterns with respect to a given finite set of graphs in ${\mathcal{O}}$ . Finally, by reporting experimental results obtained by applying the two graph mining algorithms to a subset of the NCI dataset, we evaluate the performance of the two graph mining algorithms.
A method for automated classification of steel microstructures based on extraction of informative parameters and neural network implementation
Authors: Irina Topalova, Alexander Tzokev, Anton Mihailov
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

During the in-service process the structural composition of the steel is changed bringing different damages which can lead to complete breakdown. It is appropriate to develop methods for automated classification of steel microstructures aiming high recognition accuracy, reliability and lack of any subjective evaluation. The common problem in all of the existing methods for texture classification is the low achieved recognition accuracy rate. That is the reason for searching for new reliable methods giving higher classification accuracy. The goal of the represented research is to propose a new method for automated classification of heat resistant steel structures aiming higher accuracy and computational simplicity in comparison to other existing methods. The proposed method is based on recognition of microscope images for representative steel structures having different aging stage grouped in five classes. In the preprocessing stage the histograms of the images are extracted, stretched and a method for choosing a set of the more informative values of the histogram cover curve is developed. The reduced number of values are given to the input layer neurons of a MLP type neural network. The achieved 100% accuracy and computational simplicity is a good preposition to implement the method for automated calculation of the remaining capacity of the steel avoiding the subjective evaluation factor and implementing it in a real time working systems.
Semantic types of some generic relation arguments: detection and evaluation
Authors: Sophia Katrenko, Pieter Adriaans
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper presents an approach to detection of the semantic types of relation arguments employing the WordNet hierarchy. Using the SemEval-2007 data, we show that the method allows to generalize relation arguments with high precision for such generic relations as Origin-Entity, Content-Container, Instrument-Agency and some other.
Using PVsolve to Analyze and Locate Positions of Parallel Vectors
Authors: Allen Van Gelder, Alex Pang
Venue: IEEE Transactions on Visualization and Computer Graphics (2009)

A new method for finding the locus of parallel vectors is presented, called PVsolve. A parallel-vector operator has been proposed as a visualization primitive, as several features can be expressed as the locus of points where two vector fields are parallel. Several applications of the idea have been reported, so accurate and efficient location of such points is an important problem. Previously published methods derive a tangent direction under the assumption that the two vector fields are parallel at the current point in space, then extend in that direction to a new point. PVsolve includes additional terms to allow for the fact that the two vector fields may not be parallel at the current point, and uses a root-finding approach. Mathematical analysis sheds new light on the feature flow field technique (FFF) as well. The root-finding property allows PVsolve to use larger step sizes for tracing parallel-vector curves, compared to previous methods, and does not rely on sophisticated differential equation techniques for accuracy. Experiments are reported on fluid flow simulations, comparing FFF and PVsolve.
A second-order cone cutting surface method: complexity and application
Authors: Mohammad R. Oskoorouchi, John E. Mitchell
Venue: Computational Optimization and Applications (2009)

We present an analytic center cutting surface algorithm that uses mixed linear and multiple second-order cone cuts. Theoretical issues and applications of this technique are discussed. From the theoretical viewpoint, we derive two complexity results. We show that an approximate analytic center can be recovered after simultaneously adding p second-order cone cuts in O(plog¿(p+1)) Newton steps, and that the overall algorithm is polynomial. From the application viewpoint, we implement our algorithm on mixed linear-quadratic-semidefinite programming problems with bounded feasible region and report some computational results on randomly generated fully dense problems. We compare our CPU time with that of SDPLR, SDPT3, and SeDuMi and show that our algorithm outperforms these software packages on problems with fully dense coefficient matrices. We also show the performance of our algorithm on semidefinite relaxations of the maxcut and Lovasz theta problems.
Connectivity maintenance and task allocation for mobile wireless sensor networks
Authors: Burchan Bayazit
Venue:  (2008)

Autonomous robot coordination has several real-world applications where effective usage of robots can provide significant increase in efficiency, reduction in cost and higher security for people. However, providing coordination and cooperation for mobile robots has several challenges because of the physical limitations and inefficient planning methods. In order to overcome these problems, we are proposing an emergent task allocation system for autonomous mobile robots which have limited communication and sensing capabilities. In this system, each robot uses only local information to find the optimal distribution of tasks among itself and its neighbors. Since robots can have different information about the tasks, environment and available robots, the solution found by each robot can be inconsistent with each other. In order to avoid this, robots exchange information using negotiation strategies and eliminate inconsistencies. We show that as the information exchange among the robots is increased, the solution converges to the global optimal solution. The application we have chosen to test our system is target detection and tracking. This application requires robots to keep detected targets in their sensing ranges, provide communication among each other for cooperation, and explore the environment to detect unknown targets. We show that emergent task allocation is suitable for real-time applications and can perform task allocation efficiently. To support communication among robots, we are proposing a connectivity maintenance system. We are defining a new graph property called k -redundancy and show that this property can be used to identify the importance of each node on the connectivity of the network. Once the importance of each node is determined, router robots can be placed around the more important nodes which improves the robustness of the network, and enables easier repair in case there are disconnections in the network. We show that the placement of router robots using this property can provide significant improvement on the connectivity of the network. We have studied this problem for mobile sensor networks, but this system is promising for all types of mobile ad-hoc networks.
Improving Compressed Iris Recognition Accuracy Using JPEG2000 RoI Coding
Authors: J. Hämmerle-Uhl, C. Prähauser, T. Starzacher, Andreas Uhl
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

The impact of using JPEG2000 region of interest coding on the matching accuracy of iris recognition systems is investigated. In particular, we compare the matching scores as obtained by a concrete recognition system when using JPEG2000 compression of rectilinear iris images with and without region of interest coding enabled. The region of interest is restricted to the iris texture area plus the pupil region. It turns out that average matching scores can be improved and that the number of false negative matches is significantly decreased using region of interest coding as compared to plain JPEG2000 compression.
A new possibility for pattern recognition independently from geometrical measuresetrical measures
Authors: Z. Szakal, I. Zsoldos
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

The base of this paper was a new method for the detection of exact and approximate reflective symmetry shown earlier [1]. The searching algorithm was based on the definition of the so called symmetry-parameter which is a rate of the symmetry, a number between 0 and 1 without a dimension and its value does not depend on geometrical measures. A so called shape-diagram was determined from the symmetry-parameters computed for various lines crossing the gravity centre. Beside the possibility of the symmetry detection, the shape-diagram shows an individual shape property of the 2D figures, independently from geometrical measures. In this paper we show a process in which similar 2D figures are sorted out from a multitude of different figures independently from geometrical measures using the definition of the shape-diagram.
Application of advanced rendering and animation techniques for 3D games to softbody modeling and animation
Authors: Miao Song, Peter Grogono
Venue: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering (2009)

This work focuses on the analysis and review of most prominent advanced rendering and animation techniques in the computer graphics used for 3D games, some of which we then juxtapose with our physically based softbody simulation framework we designed and implemented earlier. We then discuss such implementation results and the future directions. The techniques we touch upon are various algorithms for animation and physical based modeling as well as GPU programming with OpenGL. We break down our contribution into two main parts: the analysis and review of the applicability of the techniques to softbody rendering and animation with the summary of the results to date.
A Real generalization of discrete AdaBoost
Authors: Richard Nock, Frank Nielsen
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

Scaling discrete AdaBoost to handle real-valued weak hypotheses has often been done under the auspices of convex optimization, but little is generally known from the original boosting model standpoint. We introduce a novel generalization of discrete AdaBoost which departs from this mainstream of algorithms. From the theoretical standpoint, it formally displays the original boosting property; furthermore, it brings interesting computational and numerical improvements that make it significantly easier to handle “as is”. Conceptually speaking, it provides a new and appealing scaling to R of some well known facts about discrete (ada)boosting. Perhaps the most popular is an iterative weight modification mechanism, according to which examples have their weights decreased iff they receive the right class by the current discrete weak hypothesis. Our generalization to real values makes that decreasing weights affect only the examples on which the hypothesis' margin exceeds its average margin. Thus, while both properties coincide on the discrete case, examples that receive the right class can still be reweighted higher with real-valued weak hypotheses. From the experimental standpoint, our generalization displays the ability to produce low error formulas with particular cumulative margin distributions, and it provides a nice handling of those noisy domains that represent Achilles' heel for common Adaptive Boosting algorithms.
SigRace: signature-based data race detection
Authors: Abdullah Muzahid, Dario Suárez, Shanxiang Qi, Josep Torrellas
Venue: ACM SIGARCH Computer Architecture News (2009)

Detecting data races in parallel programs is important for both software development and production-run diagnosis. Recently, there have been several proposals for hardware-assisted data race detection. Such proposals typically modify the L1 cache and cache coherence protocol messages, and largely lose their capability when lines get displaced or invalidated from the cache. To eliminate these shortcomings, this paper proposes a novel, different approach to hardware-assisted data race detection. The approach, called SigRace, relies on hardware address signatures. As a processor runs, the addresses of the data that it accesses are automatically encoded in signatures. At certain times, the signatures are automatically passed to a hardware module that intersects them with those of other processors. If the intersection is not null, a data race may have occurred. This paper presents the architecture of SigRace, an implementation, and its software interface. With SigRace, caches and coherence protocol messages are unmodified. Moreover, cache lines can be displaced and invalidated with no effect. Our experiments show that SigRace is significantly more effective than a state-of-the-art conventional hardware-assisted race detector. SigRace finds on average 29% more static races and 107% more dynamic races. Moreover, if we inject data races, SigRace finds 150% more static races than the conventional scheme.
Using the Hamming distance to extend TOPSIS in a fuzzy environment
Authors: Mohammad Izadikhah
Venue: Journal of Computational and Applied Mathematics (2009)

Considering the fact that, in some cases, determining precisely the exact value of attributes is difficult and that their values can be considered as fuzzy data, this paper extends the TOPSIS method for dealing with fuzzy data, and an algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. In this approach, to identify the fuzzy ideal solution and fuzzy negative ideal solution, one of the Yager indices which is used for ordering fuzzy quantities in [0, 1] is applied. Using Yager's index leads to a procedure for choosing fuzzy ideal and negative ideal solutions directly from the data for observed alternatives. Then, the Hamming distance is proposed for calculating the distance between two triangular fuzzy numbers. Finally, an application is given, to clarify the main results developed in the paper.
Why choosing advanced nonlinear scale space filtering for denoising and simplifying images?
Authors: Konstantinos Karantzalos
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

Denoising, edge preserving smoothing and image simplification is of fundamental importance in a variety of image processing and computer vision applications during feature extraction and object detection procedures. The construction of an optimal pre-processing filtering tool for various corner/edge detection and segmentation tasks is still an open matter. Towards this end, here we argue that for the most feature extraction and object detection procedures advanced nonlinear scale space filtering has to be employed in order to elegantly denoise and simplify initial data. In particular, experimental results from the application of advanced scale space representations demonstrate that such a filtering forms an effective low-level image processing tool. The evaluation of the different filtering algorithms was carried out both by qualitative and quantitative assessment.