ppxscal/embedding_network huggingface dataset:
Testing Erlang Refactorings with QuickCheck
Authors: Huiqing Li, Simon Thompson
Venue: Implementation and Application of Functional Languages: 19th International Workshop, IFL 2007, Freiburg, Germany, September 27-29, 2007. Revised Selected Papers (2008)

Refactoring is a technique for improving the design of existing programs without changing their behaviour. Wrangler is a tool built at the University of Kent to support Erlang program refactoring; the Wrangler tool is written in Erlang.In this paper we present the use of a novel testing tool, Quviq QuickCheck, for testing the implementation of Wrangler. QuickCheck is a specification-based testing tool for Erlang. With QuickCheck, programs are tested by writing properties in a restricted logic, and using the tool these properties are tested in randomly generated test cases.This paper first gives overviews of Wrangler and Quviq QuickCheck, then discusses the various ways in which refactorings can be validated, and finally shows how QuickCheck can be used to test the correctness of refactorings in an efficient way.
Working Memory Dynamics in a Flip-Flop Oscillations Network Model with Milnor Attractor
Authors: David Colliaux, Yoko Yamaguchi, Colin Molter, Hiroaki Wagatsuma
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

A phenomenological model is developed where complex dynamics are the correlate of spatio-temporal memories. If resting is not a classical fixed point attractor but a Milnor attractor, multiple oscillations appear in the dynamics of a coupled system. This model can be helpful for describing brain activity in terms of well classified dynamics and for implementing human-like real-time computation.
News Annotations for Navigation by Semantic Similarity
Authors: Walter Kasper, Jörg Steffen, Yajing Zhang
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

We present a system for browsing a news repository that is based on semantic similarity of documents. News documents get automatically annotated semantically using information extraction. Annotations are displayed to a user who can easily retrieve crosslingual semantically related documents by selecting interesting content items.
A Fast CBIR System of Old Ornamental Letter
Authors: Mathieu Delalandre, Jean-Marc Ogier, Josep Lladós
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

This paper deals with the CBIR of old printed graphics (of XVI° and XVII° centuries) like the headpieces, the pictures and the ornamental letters. These graphical parts are previously segmented from digitized old books in order to constitute image databases for the historians. Today, large databases exist and involves to use automatic retrieval tools able to process large amounts of data. For this purpose, we have developed a fast retrieval system based on a Run Length Encoding (RLE) of images. We use the RLE in an image comparison algorithm using two steps: one of image centering and then a distance computation. Our centering step allows to solve the shifting problems usually met between the segmented images. We present experiments and results about our system concerning the processing time and the retrieval precision.
Evolutionary Graph Models with Dynamic Topologies on the Ubichip
Authors: Juan Camilo Peña, Jorge Peña, Andres Upegui
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

The ubichip is a reconfigurable digital circuit with special reconfiguration mechanisms, such as dynamic routing and self-replication, for supporting the implementation of bio-inspired hardware systems. The dynamic routing mechanism allows to create and destroy interconnections between remote units in a distributed fashion, thus proving useful for implementing cellular systems featuring dynamic topologies. Evolutionary graph theory investigates genetic and cultural evolution processes using the mathematical formalism of both evolutionary game and graph theory. Populations are embedded in graphs representing interaction and imitation links. Payoffs are assigned and successful individuals are imitated with high probability. This paper describes the hardware implementation of a general evolutionary graph model in which the imitation network changes over time by exploiting the dynamic routing capabilities of the ubichip. As a particular example, we analyze the case of a coordination game played by agents arranged in a cycle in which imitation links are randomly created so as to simulate dynamic small-world networks.
Effective Emotional Classification Combining Facial Classifiers and User Assessment
Authors: Isabelle Hupont, Sandra Baldassarri, Rafael Hoyo, Eva Cerezo
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

An effective method for the automatic classification of facial expressions into emotional categories is presented. The system is able to classify the user facial expression in terms of the six Ekman's universal emotions (plus the neutral one), giving a membership confidence value to each emotional category. The method is capable of analysing any subject, male or female of any age and ethnicity. The classification strategy is based on a combination (weighted majority voting) of the five most used classifiers. Another significant difference with other works is that human assessment is taken into account in the evaluation of the results. The information obtained from the users classification makes it possible to verify the validity of our results and to increase the performance of our method.
A Matrix-Based Model for Web Page Community Construction and More
Authors: Jingyu Hou
Venue: Informatica (2007)

The rapid development of network technologies has made the web a huge information source with its own characteristics. In most cases, traditional database-based technologies are no longer suitable for web information processing and management. For effectively processing and managing web information, it is necessary to reveal intrinsic relationships/structures among concerned web information objects such as web pages. In this work, a set of web pages that have their intrinsic relationships is called a web page community. This paper proposes a matrix-based model to describe relationships among concerned web pages. Based on this model, intrinsic relationships among pages could be revealed, and in turn a web page community could be constructed. The issues that are related to the application of the model are deeply investigated and studied. The concepts of community and intrinsic relationships, as well as the proposed matrix-based model, are then extended to other application areas such as biological data processing. Some application cases of the model in a broad range of areas are presented, demonstrating the potentials of this matrix-based model.
Segmentation and 3D Reconstruction Approaches for the Design of Laparoscopic Augmented Reality Environments
Authors: Patricia Sánchez-González, Francisco Gayá, Alicia M. Cano, Enrique J. Gómez
Venue: Proceedings of the 4th international symposium on Biomedical Simulation (2008)

A trend in abdominal surgery is the transition from minimally invasive surgery to surgeries where augmented reality is used. Endoscopic video images are proposed to be employed for extracting useful information to help surgeons performing the operating techniques. This work introduces an illumination model into the design of automatic segmentation algorithms and 3D reconstruction methods. Results obtained from the implementation of our methods to real images are supposed to be an initial step useful for designing new methodologies that will help surgeons operating MIS techniques.
Implementing a Multimodal Interface to a DITA User Assistance Repository
Authors: Aidan Kehoe, Ian Pitt
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

User assistance systems can be extended to enable multimodal access to user assistance material. Implementing multimodal user assistance introduces new considerations with respect to authoring and storage of assistance material, transformation of assistance material for effective presentation on a range of devices, and user interaction issues. We describe an implementation of a multimodal interface to enable access to a DITA user assistance repository.
A Context-Aware Service Discovery Framework Based on Human Needs Model
Authors: Nasser Ghadiri, Mohammad Ali Nematbakhsh, Ahmad Baraani-Dastjerdi, Nasser Ghasem-Aghaee
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

In this paper we have proposed an approach to extend the existing service-oriented architecture reference model by taking into consideration the hierarchical human needs model, which can help us in determining the user's goals and enhancing the service discovery process. This is achieved by enriching the user's context model and representing the needs model as a specific ontology. The main benefits of this approach are improved service matching, and ensuring better privacy as required by users in utilizing specific services like profile-matching.
A new mechanism for resource monitoring in Grid computing
Authors: Wu-Chun Chung, Ruay-Shiung Chang
Venue: Future Generation Computer Systems (2009)

Grid computing is a technology for distributed computing. To manage a large scale of Grid resources for dynamic access, resource management is a key component. In this paper, a Grid Resource Information Monitoring (GRIM) prototype is introduced. To support the constantly changing resource states in the GRIM prototype, the push-based data delivery protocol named Grid Resource Information Retrieving (GRIR) is provided. There is a trade-off between information fidelity and updating transmission cost. The more frequent the reporting is, the more precise the information will be. But there will be more overheads. The offset-sensitive mechanism, the time-sensitive mechanism, and the hybrid mechanism in GRIR are used to achieve a high degree of data accuracy while decreasing the cost of updating messages. Experimental results show that the proposal alleviates both the update transmission cost and the loss of data accuracy compared to prior methods.
Inductive Proofs of Computational Secrecy
Authors: Arnab Roy, Anupam Datta, Ante Derek, John C. Mitchell
Venue: Proceedings of the 12th European symposium on Research In Computer Security (2007)

Secrecy properties of network protocols assert that no probabilistic polynomial-time distinguisher can win a suitable game presented by a challenger. Because such properties are not determined by traceby- trace behavior of the protocol, we establish a trace-based protocol condition, suitable for inductive proofs, that guarantees a generic reduction from protocol attacks to attacks on underlying primitives. We use this condition to present a compositional inductive proof system for secrecy, and illustrate the system by giving a modular, formal proof of computational authentication and secrecy properties of Kerberos V5.
Calculation of Latent Semantic Weight Based on Fuzzy Membership
Authors: Jingtao Sun, Qiuyu Zhang, Zhanting Yuan, Wenhan Huang, Xiaowen Yan, Jianshe Dong
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

One important process of Latent semantic analysis (LSA) is the weighting scheme to the term-document matrix by weight function, the weight function has directly affects the quality of LSA. This text leads to apriori information and global weighting of document on the traditional method and the modified weight function base on Fuzzy membership, Calculation of Latent Semantic Weight Based on Fuzzy Membership is proposed in this paper. By the last experiment, the results show that Latent Semantic Analysis based on modified weight function is better than that old one. The experiments show the expected results obtained, and the feasibility and advantage of the new spam filtering method is validated.
Model&Metamodel, Metadata and Document Repository for Software and Data Integration
Authors: Nikola Milanovic, Ralf Kutsche, Timo Baum, Mario Cartsburg, Hatice Elmasgünes, Marco Pohl, Jürgen Widiker
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Model-based software engineering (MBSE) projects require and generate numerous artifacts. While MBSE methodology and design tools have reached certain maturity level, the issue of artifact persistence and management has been somewhat left in the background. We present design and implementation of the repository that supports storing and managing of artifacts such as metamodels, models, constraints, metadata, specifications, transformation rules, code, templates, configuration or documentation, and their metadata.
Evolutionary Optimization with Dynamic Fidelity Computational Models
Authors: Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

In this paper, we propose an evolutionary framework for model fidelity control that decides, at runtime, the appropriate fidelity level of the computational model, which is deemed to be computationally less expensive, to be used in place of the exact analysis code as the search progresses. Empirical study on an aerodynamic airfoil design problem based on a Memetic Algorithm with Dynamic Fidelity Model (MA-DFM) demonstrates that improved quality solution and efficiency are obtained over existing evolutionary schemes.
Content Aware Image Enhancement
Authors: Gianluigi Ciocca, Claudio Cusano, Francesca Gasparini, Raimondo Schettini
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

We present our approach, integrating imaging and vision, for content-aware enhancement and processing of digital photographs. The overall quality of images is improved by a modular procedure automatically driven by the image class and content.
An Implementation of the PCP, SRP, D-PCP, M-PCP, and FMLP Real-Time Synchronization Protocols in LITMUS^RT
Authors: Björn B. Brandenburg, James H. Anderson
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

We extend the FMLP to partitioned static-priority scheduling and derive corresponding worst-case blocking bounds. Further, we present the first implementation of the PCP, SRP, D-PCP, M-PCP, and FMLP synchronization protocolsin a unified framework in a general-purpose OS and discuss design issues that were beyond the scope of prior algorithmic-oriented work on real-time synchronization.
Discrete-Time Recurrent High Order Neural Observer for Induction Motors
Authors: Edgar N. Sanchez, Alma Y. Alanis, Alexander G. Loukianov
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

A nonlinear discrete-time neural observer for the state estimation of a discrete-time induction motor model, in presence of external and internal uncertainties is presented. The observer is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter (EKF)-based algorithm. This observer estimates the state of the unknown discrete-time nonlinear system, using a parallel configuration. The paper also includes the stability proof on the basis of the Lyapunov approach. To illustrate the applicability simulation results are included.
Data mining with vertically computable metrics
Authors: William Perrizo
Venue:  (2007)

We live in a "data rich," "information poor" environment with a greater requirement for computational tools to extract valuable information. Data mining is a multi-disciplinary field with the primary objective of supporting knowledge workers to extract meaningful information from large volumes of data. In most of the practical data-mining applications, domain-specific, large-scale tool customization is required, or the practitioner is restricted to work around the available tools. This work is an attempt to investigate, build, and evaluate a generalized prediction framework that facilitates easy tool migration towards the application domain in an attempt to achieve meaningful data mining. We propose the use of a vertical bit-slice-based data structure that enables the tool framework to be designed in a computationally efficient generalized setting. In this dissertation, we show how bit-wise operations on vertical bit slices can be efficiently and easily manipulated using a generalized application programming interface to achieve computationally efficient, high-quality results. We introduce innovative solutions to traditional data-mining problems and application areas that outperform existing solutions, made possible through the use of the vertical data-mining approach.
Concise Coupled Neural Network Algorithm for Principal Component Analysis
Authors: Lijun Liu, Jun Tie, Tianshuang Qiu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

A concise ordinary differential equations (ODE) for eigen-decomposition problem of a symmetric positive matrix is proposed in this paper. Stability properties of the proposed ODE is obtained by the theory of first order approximation. Novel coupled neural network (CNN) algorithm for principal component analysis (PCA) is obtained based on this concise ODE model. Compared with most non-coupled neural PCA algorithms, the proposed online CNN algorithm works in a recursive manner and simultaneously estimates eigenvalue and eigenvector adaptively. Due to the fact the proposed CNN effectively makes use of online eigenvalue estimate during learning process, it reaches a fast convergence speed, which is further verified by the numerical experiment result. Adaptive algorithm for sequential extraction of subsequent principal components is also obtained by means of deflation techniques.
A Probabilistic Framework for Decentralized Management of Trust and Quality
Authors: Le-Hung Vu, Karl Aberer
Venue: Proceedings of the 11th international workshop on Cooperative Information Agents XI (2007)

In this paper, we propose a probabilistic framework targeting three important issues in the computation of quality and trust in decentralized systems. Specifically, our approach addresses the multi-dimensionality of quality and trust, taking into account credibility of the collected data sources for more reliable estimates, while also enabling the personalization of the computation. We use graphical models to represent peers' qualitative behaviors and exploit appropriate probabilistic learning and inference algorithms to evaluate their quality and trustworthiness based on related reports. Our implementation of the framework introduces the most typical quality models, uses the Expectation-Maximization algorithm to learn their parameters, and applies the Junction Tree algorithm to inference on them for the estimation of quality and trust. The experimental results validate the advantages of our approach: first, using an appropriate personalized quality model, our computational framework can produce good estimates, even with a sparse and incomplete recommendation data set; second, the output of our solution has well-defined semantics and useful meanings for many purposes; third, the framework is scalable in terms of performance, computation, and communication cost. Furthermore, our solution can be shown as a generalization or serve as the theoretical basis of many existing trust computational approaches.
A unified architecture for a public key cryptographic coprocessor
Authors: Yi Wang, Douglas L. Maskell, Jussipekka Leiwo
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

This paper presents a unified architecture for public key cryptosystems that can support the operations of the Rivest-Shamir-Adleman cryptogram (RSA) and the elliptic curve cryptogram (ECC). A hardware solution is proposed for operations over finite fields GF(p) and GF(2^p). The proposed architecture presents a unified arithmetic unit which provides the functions of dual-field modular multiplication, dual-field modular addition/subtraction, and dual-field modular inversion. A new adder based on the signed-digit (SD) number representation is provided for carry-propagated and carry-less operations. The critical path of the proposed design is reduced compared with previous full adder implementation methods. Experimental results show that the proposed design can achieve a clock speed of 1GHz using 776K gates in a 0.09@mm CMOS standard cell technology, or 150MHz using 5227 CLBs in a Xilinx Virtex 4 FPGA. While the different technologies, platforms and standards make a definitive comparison difficult, based on the performance of our proposed design, we achieve a performance improvement of between 30% and 250% when compared with existing designs.
RSS-Based Interoperability for User Adaptive Systems
Authors: Yiwen Wang, Federica Cena, Francesca Carmagnola, Omar Cortassa, Cristina Gena, Natalia Stash, Lora Aroyo
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

This paper presents an approach to exploit widely used tag annotations to address two important issues in user-adaptive systems: the cold-start problem and the integration of distributed user models. The paper provides an example of re-use of user interaction data (tags) generated by one application into another one in similar domains for providing cross-system recommendations.