ppxscal/embedding_network huggingface dataset:
Holonic Models for Traffic Control Systems
Authors: Calin Ciufudean, Constantin Filote
Venue: Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2009)

This paper proposes a new time-placed net model for traffic control systems, respectively railway control traffic systems. This model can be interpreted as a holonic one, and contains three modules: Transport Planning Module, Transport Control Module and Priority Control Module. For railway traffic systems we introduce a strategy in a timed-place Petri net model to solve collision and traffic jam problems.
Wrap Your Objects Safely
Authors: Olaf Owe, Gerardo Schneider
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Despite the effort of researchers on distributed systems, programming languages, and security, there is still no good solution offering basic constructs for guaranteeing minimal security at the programming language level. In particular, the notion of a wrapper around an object or component controlling its interaction with the environment has not properly been addressed. This kind of ''local firewall'' may play two different roles: (1) The untrusted part is what is inside the wrapper; (2) The untrusted part is the environment. In this paper we propose the addition of a language primitive for creating wrapped objects and components, and sketch a formalization based on a minimal object-oriented language for distributed systems using asynchronous communication.
Adding dynamic visual manipulations to declarative multimedia documents
Authors: Fons Kuijk, Rodrigo Laiola Guimarães, Pablo Cesar, Dick C.A. Bulterman
Venue: Proceedings of the 9th ACM symposium on Document engineering (2009)

The objective of this work is to define a document model extension that enables complex spatial and temporal interactions within multimedia documents. As an example we describe an authoring interface of a photo sharing system that can be used to capture stories in an open, declarative format. The document model extension defines visual transformations for synchronized navigation driven by dynamic associated content. Due to the open declarative format, the presentation content can be targeted to individuals, while maintaining the underlying data model. The impact of this work is reflected in its recent standardization in the W3C SMIL language. Multimedia players, as Ambulant and the RealPlayer, support the extension described in this paper.
ILP with noise and fixed example size: a Bayesian approach
Authors: Eric McCreath, Arun Sharma
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Current inductive logic programming systems are limited in their handling of noise, as they employ a greedy covering approach to constructing the hypothesis one clause at a time. This approach also causes difficulty in learning recursive predicates. Additionally, many current systems have an implicit expectation that the cardinality of the positive and negative examples reflect the "proportion" of the concept to the instance space. A framework for learning from noisy data and fixed example size is presented. A Bayesian heuristic for finding the most probable hypothesis in this general framework is derived. This approach evaluates a hypothesis as a whole rather than one clause at a time. The heuristic, which has nice theoretical properties, is incorporated in an ILP system, LIME. Experimental results show that LIME handles noise better than FOIL and PROGOL. It is able to learn recursive definitions from noisy data on which other systems do not perform well. LIME is also capable of learning from only positive data and also from only negative data.
Consistent parameterization and statistical analysis of human head scans
Authors: Pengcheng Xi, Chang Shu
Venue: The Visual Computer: International Journal of Computer Graphics (2009)

Statistical shape analysis of 3-D scanned human heads provides important information for many applications. Nevertheless, special geometry processing techniques have to be developed for consistently parameterizing scans due to the fact that different scanning projects vary in landmark definition, noise control and other factors. For consistent parameterization, fitting a generic model to each scan has proved to be an effective method. In this paper, improved techniques are presented to solve problems in parameterizing different data sets. Principal Component Analysis (PCA) is thus conducted on the consistently parameterized data sets, and shape variances along principal components are demonstrated. In addition, shape variations analyzed by Independent Component Analysis (ICA) are also presented.
Use of a Bayesian network for Red Listing under uncertainty
Authors: Adrian C. Newton
Venue: Environmental Modelling Software (2010)

The IUCN (International Union for Conservation of Nature) Red List is widely recognised as an authoritative assessment of the conservation status of species. However, the data available for Red Listing are often lacking or uncertain. This paper presents a Bayesian network that may be used to perform a Red List assessment of a taxon using uncertain data. In such cases, input variables can be entered as likelihoods, and the appropriate Red List category is identified by the network using Bayesian inference. Relative performance of the Bayesian network was evaluated by comparison with an alternative method (RAMAS^(R) Red List), based on the use of fuzzy numbers. While results were generally comparable, some differences were noted for species with uncertain input data. Contrasting results may be attributed to differences in how uncertain data are analysed by the two approaches. The Bayesian network has the advantage of being more transparent, facilitating sensitivity analysis. The method consequently has potential for facilitating Red List assessments, particularly for poorly known taxa.
Improved Fairing Algorithm with Optimized Modification Amount of Cloud Data in Reverse Engineering
Authors: N. Meng, Y. Q. Zhou, H. J. Yang, J. Qu, X. L. Chen
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

In reverse engineering, noise needs to be processed, which is in existence among measured data. The result data processed directly influences the reconstructed curve and surface precision. In order to acquire point cloud data which can truly reflect the original design view, an improved fairing algorithm with optimized modification amount is proposed. The fairing process includes two blocks: rough fairing and fine fairing. Bad data is identified according to the sign of curvature and its one-order difference respectively. The proposed direction of each modified point is along the positive or negative way of G which points to the triangle’s center, and it is located according to the energy function equation directly. The modified distance is first set an initial value, then it searches the optimized modification amount by a certain step according to the equation. The search is terminated until the energy function equation satisfies the minimum value within a certain value. The modified algorithm can meet the faired requirement of curve and surface reconstruction, which is proved by some examples, and it is good for preserving the original shape.
Face Recognition Using Two-Dimensional Discriminant Locality Preserving Projections
Authors: Yu Weiwei
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

One of the key issues of face recognition is to extract the features of face images, and a new method of feature extraction, two-dimensional discriminate locality preserving projections (2D-DLPP), is proposed. 2D-DLPP benefits from three techniques, i.e., locality preserving projections (LPP), image based projection and discriminant analysis. Firstly, LPP is an effective feature extraction method that optimally preserves the local structure of the samples. Secondly, compared to vector based projection, image based projection can reduce the complexity of algorithm, avoid the small sample size problem and give more spatial structural information of image. Finally, discriminant analysis applied in 2D-DLPP can improve recognition performance by maximizing the interpersonal distance and minimizing the intrapersonal distance. Experiments are performed to test and evaluate the algorithm using the ORL and the Yale face databases. The Experimental results show that 2D-DLPP has better face recognition performance than other methods.
Exploring variant definitions of pointer length in MDL
Authors: Aris Xanthos, Yu Hu, John Goldsmith
Venue: Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology and Morphology (2006)

Within the information-theoretical framework described by (Rissanen, 1989; de Marcken, 1996; Goldsmith, 2001), pointers are used to avoid repetition of phonological material. Work with which we are familiar has assumed that there is only one way in which items could be pointed to. The purpose of this paper is to describe and compare several different methods, each of which satisfies MDL's basic requirements, but which have different consequences for the treatment of linguistic phenomena. In particular, we assess the conditions under which these different ways of pointing yield more compact descriptions of the data, both from a theoretical and an empirical perspective.
DL-Lite: tractable description logics for ontologies
Authors: Diego Calvanese, Giuseppe De Giacomo, Domenico Lemho, Maurizio Lenzerini, Riccardo Rosati
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

We propose a new Description Logic, called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts, and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, conjunctive queries) over the set of instances maintained in secondary storage. We show that in DL-Lite the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is polynomial in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial data complexity for query answering over DL knowledge bases. A notable feature of our logic is to allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current DBMSs.
On the energy-efficiency of software transactional memory
Authors: F. Klein, A. Baldassin, G. Araujo, P. Centoducatte, R. Azevedo
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

Traditional software transactional memory designs are targeted towards performance and therefore little is known about their impact on energy consumption. We provide, in this paper, a comprehensive energy analysis of a standard STM design and propose novel scratchpad-based energy-aware STM design strategies. Experimental results collected through a state-of-the-art MPSoC simulation infrastructure show that our approach can achieve an energy improvement of up to ~36% with regard to the base STM for applications characterized by short-lived transactions and relatively high abort rate.
A New Fuzzy Inertia Weight Particle Swarm Optimization
Authors: Peyman Yadmellat, S. Mohammad Amin Salehizadeh, Mohammad Bagher Menhaj
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

This paper proposes a new Fuzzy tuned Inertia weight Particle Swarm Optimization (FIPSO) which remarkably outperforms the standard PSO, previous fuzzy as well as adaptive based PSO methods. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with those of the other tuned parameter PSO algorithms. Numerical results indicate that FIPSO is competitive due to its ability to increase search space diversity as well as finding the functions’ global optima and a better convergence performance.
A Three-Property-Secure Hash Function
Authors: Elena Andreeva, Bart Preneel
Venue: Selected Areas in Cryptography: 15th International Workshop, SAC 2008, Sackville, New Brunswick, Canada, August 14-15, Revised Selected Papers (2009)

This paper proposes a new hash construction based on the widely used Merkle-Damgård (MD) iteration [13,9]. It achieves the three basic properties required from a cryptographic hash function: collision (Coll), second preimage (Sec) and preimage (Pre) security. We show property preservation for the first two properties in the standard security model and the third Pre security property is proved in the random oracle model. Similar to earlier known hash constructions that achieve a form of Sec (eSec [16]) property preservation [4,17], we make use of fixed key material in the iteration. But while these hashes employ keys of size at least logarithmic in the message length (in blocks), we only need a small constant key size. Another advantage of our construction is that the underlying compression function is instantiated as a keyless primitive.The Sec security of our hash scheme, however, relies heavily on the standard definitional assumption that the target messages are sufficiently random. An example of a practical application that requires Sec security and satisfies this definitional premise on the message inputs is the popular Cramer-Shoup encryption scheme [8]. Still, in practice we have other hashing applications where the target messages are not sampled from spaces with uniform distribution. And while our scheme is Sec preserving for uniform message distributions, we show that this is not always the case for other distributions.
Logics with Rank Operators
Authors: Anuj Dawar, Martin Grohe, Bjarki Holm, Bastian Laubner
Venue: Proceedings of the 2009 24th Annual IEEE Symposium on Logic In Computer Science (2009)

We introduce extensions of first-order logic (FO) and fixed-point logic (FP) with operators that compute the rank of a definable matrix. These operators are generalizations of the counting operations in FP+C (i.e. fixed-point logic with counting) that allow us to count the dimension of a definable vector space, rather than just count the cardinality of a definable set. The logics we define have data complexity contained in polynomial time and all known examples of polynomial time queries that are not definable in FP+C are definable in FP+rk, the extension of FP with rank operators. For each prime number p and each positive integer n, we have rank operators rk_p for determining the rank of a matrix over the finite field GF_p defined by a formula over n-tuples. We compare the expressive power of the logics obtained by varying the values p and n can take. In particular, we show that increasing the arity of the operators yields an infinite hierarchy of expressive power. The rank operators are surprisingly expressive, even in the absence of fixed-point operators. We show that FO+rk_p can define deterministic and symmetric transitive closure. This allows us to show that, on ordered structures, FO+rk_p captures the complexity class MOD_pL, for all prime values of p.
Experiences Running a Parallel Answer Set Solver on Blue Gene
Authors: Lars Schneidenbach, Bettina Schnor, Martin Gebser, Roland Kaminski, Benjamin Kaufmann, Torsten Schaub
Venue: Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2009)

This paper presents the concept of parallelisation of a solver for Answer Set Programming (ASP). While there already exist some approaches to parallel ASP solving, there was a lack of a parallel version of the powerful clasp solver. We implemented a parallel version of clasp based on message-passing. Experimental results on Blue Gene P/L indicate the potential of such an approach.
Predicting response to political blog posts with topic models
Authors: Tae Yano, William W. Cohen, Noah A. Smith
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

In this paper we model discussions in online political blogs. To do this, we extend Latent Dirichlet Allocation (Blei et al., 2003), in various ways to capture different characteristics of the data. Our models jointly describe the generation of the primary documents (posts) as well as the authorship and, optionally, the contents of the blog community's verbal reactions to each post (comments). We evaluate our model on a novel comment prediction task where the models are used to predict which blog users will leave comments on a given post. We also provide a qualitative discussion about what the models discover.
Learning phrasal categories
Authors: William P. Headden,  III, Eugene Charniak, Mark Johnson
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

In this work we learn clusters of contextual annotations for non-terminals in the Penn Treebank. Perhaps the best way to think about this problem is to contrast our work with that of Klein and Manning (2003). That research used tree-transformations to create various grammars with different contextual annotations on the non-terminals. These grammars were then used in conjunction with a CKY parser. The authors explored the space of different annotation combinations by hand. Here we try to automate the process -- to learn the "right" combination automatically. Our results are not quite as good as those carefully created by hand, but they are close (84.8 vs 85.7).
COPE - Automating Coupled Evolution of Metamodels and Models
Authors: Markus Herrmannsdoerfer, Sebastian Benz, Elmar Juergens
Venue: Proceedings of the 23rd European Conference on ECOOP 2009 --- Object-Oriented Programming (2009)

Model-based development promises to increase productivity by offering modeling languages tailored to a specific domain. Such modeling languages are typically defined by a metamodel. In response to changing requirements and technological progress, the domains and thus the metamodels are subject to change. Manually migrating existing models to a new version of their metamodel is tedious and error-prone. Hence, adequate tool support is required to support the maintenance of modeling languages. This paper introduces COPE, an integrated approach to specify the coupled evolution of metamodels and models to reduce migration effort. With COPE, a language is evolved by incrementally composing modular coupled transformations that adapt the metamodel and specify the corresponding model migrations. This modular approach allows to combine the reuse of recurring transformations with the expressiveness to cater for complex transformations. We demonstrate the applicability of COPE in practice by modeling the coupled evolution of two existing modeling languages.
A conversational in-car dialog system
Authors: Baoshi Yan, Fuliang Weng, Zhe Feng, Florin Ratiu, Madhuri Raya, Yao Meng, Sebastian Varges, Matthew Purver, Annie Lien, Tobias Scheideck, Badri Raghunathan, Feng Lin, Rohit Mishra, Brian Lathrop, Zhaoxia Zhang, Harry Bratt, Stanley Peters
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

In this demonstration we present a conversational dialog system for automobile drivers. The system provides a voice-based interface to playing music, finding restaurants, and navigating while driving. The design of the system as well as the new technologies developed will be presented. Our evaluation showed that the system is promising, achieving high task completion rate and good user satisfation.
Blockcipher-Based Hashing Revisited
Authors: Martijn Stam
Venue: Fast Software Encryption: 16th International Workshop, FSE 2009 Leuven, Belgium, February 22-25, 2009 Revised Selected Papers (2009)

We revisit the rate-1 blockcipher based hash functions as first studied by Preneel, Govaerts and Vandewalle (Crypto'93) and later extensively analysed by Black, Rogaway and Shrimpton (Crypto'02). We analyse a further generalization where any pre- and postprocessing is considered. This leads to a clearer understanding of the current classification of rate-1 blockcipher based schemes as introduced by Preneel et al. and refined by Black et al. In addition, we also gain insight in chopped, overloaded and supercharged compression functions. In the latter category we propose two compression functions based on a single call to a blockcipher whose collision resistance exceeds the birthday bound on the cipher's blocklength. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Optimizing Interval Training Protocols Using Data Mining Decision Trees
Authors: Myung-kyung Suh, Mahsan Rofouei, Ani Nahapetian, William J. Kaiser, Majid Sarrafzadeh
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

Interval training consists of interleaving high intensity exercises with rest periods. This training method is a well known exercise protocol which helps strengthen and improve one’s cardiovascular fitness. However, there is no known methodfor formulating and tailoring an optimized interval training protocol for a specific individual which maximizes the amount of work done while limiting fatigue. But by using data mining schemes with various attributes, conditions, and data gathered from an individual’s exercise session, we are able to efficiently formulate an optimized interval training method for an individual. Recent advances in wireless wearable sensors and smart phones have made available a new generation of fitness monitoring systems. With accelerometers embedded in an iPhone, a Bluetooth pulse oximeter, and the Weka data mining tool, we are able to formulate the optimized interval training protocols, which can increase the amount of calorie burned up to 29.54%, compared with the modified Tabata interval training protocol.
Digital Image Watermarking for Malicious Attack
Authors: Wei-Hung Lin, Yuh-Rau Wang, Shi-Jinn Horng, Tzong-Wann Kao
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

In this paper, a copyright protection method for digital image with 1/T rate forward error correction (FEC) is proposed. In the proposed method, the original image is lossless and the watermark is robust to malicious attacks. The watermark logo is fused with noise bits to improve the security, and later XORed with the feature value of the image by 1/T rate FEC. During extraction, the watermark bits are determined by majority voting, and the extraction procedure needs neither the original image nor the watermark logo. Experimental results show that not only the image is lossless but also the proposed method can effectively resist the common geometric and nongeometric attacks. Since the proposed method is based on spatial domain and transferring to frequency domain is not needed, the embedding and extraction performances are improved.