ppxscal/embedding_network huggingface dataset:
A Complete Pyramidal Geometrical Scheme for Text Based Image Description and Retrieval
Authors: Guillaume Joutel, Véronique Eglin, Hubert Emptoz
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

This paper presents a general architecture for ancient handwriting documents content description and retrieval. It is based on the Curvelets decomposition of images for indexing linear singularities of handwritten shapes. As it belongs to the Wavelets family, its representation is used at several scales of details. The proposed scheme for handwritten shape characterization targets to detect oriented and curved fragments at different scales: it is used in a first step to extract visual textual interest regions and secondly to compose a cross-scale signature for each handwritten analyzed samples. The images description is studied through different kinds of deformations that show the efficiency of the proposition for even degraded and variable handwriting text. The complete implementation scheme is validated with a content based images retrieval (CBIR) application on the medieval database from the IRHT and on the European 18th century correspondences corpus from the CERPHI.
Parallel Computing of Kernel Density Estimates with MPI
Authors: Szymon Łukasik
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Kernel density estimation is nowadays a very popular tool for nonparametric probabilistic density estimation. One of its most important disadvantages is computational complexity of calculations needed, especially for data-based bandwidth selection and adaptation of bandwidth coefficient. The article presents parallel methods which can significantly improve calculation time. Results of using reference implementation based on Message Passing Interface standard in multicomputer environment are included as well as a discussion on effectiveness of parallelization.
Improving Multi-Agent Architectural Design
Authors: Carla Silva, Jaelson Castro, Patrícia Tedesco, João Araújo, Ana Moreira, John Mylopoulos
Venue: Software Engineering for Multi-Agent Systems V: Research Issues and Practical Applications (2007)

Agents provide developers with a flexible way to structure systems around autonomous, communicating elements. To support the efficient development of such systems, design techniques need to be introduced. In this context, we propose an extension of the UML 2.0 metamodel to support agency features and UML-based diagrams which can be used to capture four views of multi-agent systems architecture (Architectural, Intentional, Environmental and Communication). The approach also provides heuristics to guide the description of multi-agent systems according to the proposed diagrams in the context of the Tropos framework. To illustrate the approach we present an Electronic Newspaper example.
Implementing ReGreT in a Decentralized Multi-agent Environment
Authors: Stefan König, Sven Kaffille, Guido Wirtz
Venue: Proceedings of the 5th German conference on Multiagent System Technologies (2007)

Since the last decade reputation management has been examined as a possible foundation for trust establishment and trust dissemination in distributed artificial intelligence. While the systems are distributed the reputation management systems are in most cases centralized. This paper describes the implementation of the ReGreT approach to trust and reputation management in Multi-Agent Systems in a decentralized environment, where the services which provide reputation management are also distributed.
A Preliminary Neural Model for Movement Direction Recognition Based on Biologically Plausible Plasticity Rules
Authors: Eduardo A. Kinto, Emílio Moral Hernandez, Alexis Marcano, Javier Ropero Peláez
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

In this work we implement a neural architecture for recognizing the direction of movement using neural properties that are consistent with biological findings like intrinsic plasticity and synaptic metaplasticity. The network architecture has two memory layers and two competitive layers. This un-supervised neural network is able to identify the direction of movement of an object, being a promising network for object tracking, hand-written and speech recognition.
An Empirical Study of Lazy Multilabel Classification Algorithms
Authors: E. Spyromitros, G. Tsoumakas, Ioannis Vlahavas
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

Multilabel classification is a rapidly developing field of machine learning. Despite its short life, various methods for solving the task of multilabel classification have been proposed. In this paper we focus on a subset of these methods that adopt a lazy learning approach and are based on the traditional k-nearest neighbor (kNN) algorithm. Two are our main contributions. Firstly, we implement BRkNN, an adaptation of the kNN algorithm for multilabel classification that is conceptually equivalent to using the popular Binary Relevance problem transformation method in conjunction with the kNN algorithm, but much faster. We also identify two useful extensions of BRkNN that improve its overall predictive performance. Secondly, we compare this method against two other lazy multilabel classification methods, in order to determine the overall best performer. Experiments on different real-world multilabel datasets, using a variety of evaluation metrics, expose the advantages and limitations of each method with respect to specific dataset characteristics.
Modular Counting of Rational Points over Finite Fields
Authors: Daqing Wan
Venue: Foundations of Computational Mathematics (2008)

Let Fq be the finite field of q elements, where q = ph. Let f(x) be a polynomial over Fq in n variables with m nonzero terms. Let N(f) denote the number of solutions of f(x) = 0 with coordinates in Fq. In this paper we give a deterministic algorithm which computes the reduction of N(f) modulo pb in O(n(8m)p(h+b)p) bit operations. This is singly exponential in each of the parameters {h, b, p}, answering affirmatively an open problem proposed by Gopalan, Guruswami, and Lipton.
A Comparative Study on Region-Based Moments for Facial Expression Recognition
Authors: Ruicong Zhi, Qiuqi Ruan
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

Automatic facial expression is a challenging task of intelligent human-computer interaction. In this paper, we present a comparative study on moments based feature extraction methods in terms of their capability to recognize facial expression images. The moments include Hu’s moments, Zernike moments, Wavelet moments and Krawtchouk moments. Krawtchouk moments are applied to facial expression analysis for the first time. Experiments are conducted on Cohn-Kanade facial expression database. The test images are original images, localized images and edge detected images. Experimental results show that wavelet moments outperform other moments based methods in facial expression recognition.
Feedback analysis of U-model via small gain theorem
Authors: Syed Saad Azhar Ali, Fouad M. Al-Sunni, Muhammad Shafiq, Jamil M. Bakhashwain
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

In this paper, the stability and convergence issues for the control-oriented U-model are discussed. In order to guarantee stability and faster convergence speeds, bounds are suggested for the learning rate of adaptation algorithm that estimate the parameters of U-model. The adaptation algorithm is first associated with a feedback structure and then its stability is investigated using l2 stability and small gain theorem. The paper also discusses about the robustness of adaptation algorithm in the presence of noise and suggests optimal choices for faster convergence speeds.
Cognitive Surveying: A Framework for Mobile Data Collection, Analysis, and Visualization of Spatial Knowledge and Navigation Practices
Authors: Drew Dara-Abrams
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

Spatial cognition researchers must, at present, choose between the relevance of the real world and the precision of the lab. Here I introduce cognitive surveying as a framework of computational techniques to enable the automated and precise study of spatial knowledge and navigation practices in everyday environments. I draw on surveying engineering to develop the framework's components: a hardware platform, data structures and algorithms for mobile data collection, and routines for data analysis and visualization. The cognitive surveying system tracks users with GPS, allows them to label meaningful points as landmarks, and asks them to point toward or estimate the distance to out-of-sight landmarks. The data from these and other questions is then used to produce specific analyses and comprehensive overviews of the user's spatial knowledge and navigation practices, which will be of great interest to spatial cognition researchers, the developers of location-based services, urban designers, and city planners alike.
DNA Based Evolutionary Approach for Microprocessor Design Automation
Authors: Nagarajan Venkateswaran, Arjun Kumeresh, Harish Chandran
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

In a paper [1] presented to BICS 2006, a basic methodology for microprocessor design automation using DNA sequences was proposed. A refined methodology with new schemes for traversal, encoding, recombination, and processor evaluation are proposed in this paper. Moreover concepts such as mutation, graphical decoding and environment simulation are introduced and a new technique for creating DNA based algorithms used in the mutation process is also presented. The proposed methodology is then generalized to extend its application to other domains. This paper presents a conceptual framework whose implementation aspects are still under investigation.
The Neighbourhood of S0.9 and S1
Authors: Roderic A. Girle
Venue: Proceedings of the 16th international conference on Automated Reasoning with Analytic Tableaux and Related Methods (2007)

Considerable work has been undertaken on the neighbourhood semantics for S1 but little on S0.9. In this paper we use tableaux to represent the model-set / model-system neighbourhood semantics for both S1 and S0.9 and some other nearby systems. S0.9 is often seen as a more "natural" logic in the sequence: S0.5 to S0.9 to S2 to S3 than S1. This perception is discussed in terms of the interpretation of alternate worlds or model-sets.
Semiotics of Sounds Evoking Motions: Categorization and Acoustic Features
Authors: Adrien Merer, Sølvi Ystad, Richard Kronland-Martinet, Mitsuko Aramaki
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

The current study is part of a larger project aiming at offering intuitive mappings of control parameters piloting synthesis models by semantic descriptions of sounds, i.e. simple verbal labels related to various feelings, emotions, gestures or motions. Hence, this work is directly related to the general problem of semiotics of sounds. We here put a special interest in sounds evoking different perceived motions. In this paper, the experimental design of the listening tests is described and the results obtained from behavioural data are discussed. Then a set of signal descriptors is compared to categories using feature selection methods. A special interest is given to applications for sound synthesis.
Service Architecture Design for E-Businesses: A Pattern-Based Approach
Authors: Veronica Gacitua-Decar, Claus Pahl
Venue: Proceedings of the 9th international conference on E-Commerce and Web Technologies (2008)

E-business involves the implementation of business processes over the Web. At a technical level, this imposes an application integration problem. In a wider sense, the integration of software and business levels across organisations becomes a significant challenge. Service architectures are an increasingly adopted architectural approach for solving Enterprise Applications Integration (EAI). The adoption of this new architectural paradigm requires adaptation or creation of novel methodologies and techniques to solve the integration problem. In this paper we present the pattern-based techniques supporting a methodological framework to design service architectures for EAI. The techniques are used for services identification, for transformation from business models to service architectures and for architecture modifications.
Association Rule Mining Based on the Semantic Categories of Tourism Information
Authors: Yipeng Zhou, Junping Du, Guangping Zeng, Xuyan Tu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

It is difficult for traditional data mining algorithms to mine semantic information from text set because of its complexity and high dimension. To solve this problem, the semantic categories of words appearing in tourism emergency reports are studied, and a semantic association rule mining algorithm is presented based on these categories. Association words are also gained from these rules, which can better describe the semantic contents of the texts. Quantum-inspired genetic algorithm is utilized to improve the effectiveness of rule-searching process. Experiments show the better results than traditional methods.
Edutain@Grid: A Business Grid Infrastructure for Real-Time On-Line Interactive Applications
Authors: Justin Ferris, Mike Surridge, E. Rowland Watkins, Thomas Fahringer, Radu Prodan, Frank Glinka, Sergei Gorlatch, Christoph Anthes, Alexis Arragon, Chris Rawlings, Arton Lipaj
Venue: Proceedings of the 5th international workshop on Grid Economics and Business Models (2008)

Grid infrastructures are maturing to a point where they are attracting the interest of businesses in many application domains. While many large-scale on-line gaming platforms exist, they fail to take into consideration the potential business to business relationships when it comes to dynamic on-line game hosting. This work presents an initial implementation of the edutain@grid architecture to support business value chains identified for on-line gaming and e-learning application hosting. An analysis of business actors and value chains is presented briefly before a detailed description of the edutain@grid implementation. We also consider first results concerning how best to construct appropriate value chains using bipartite and bi-directional Service Level Agreements.
Electronic transport properties in copper nanowire
Authors: Saeideh Mohammadzadeh, Davoud Pouladsaz, Reinhard Streiter, Thomas Gessner
Venue: Microelectronic Engineering (2008)

In present work, we study the electronic transport properties of copper nanowire using the non-equilibrium Green's function technique on the density functional tight binding method for modelling the conductance under external bias voltage. We also carried out the calculations for the Au nanowire for comparison.
Linear Transformations in Boolean Complexity Theory
Authors: Joel Friedman
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We attempt to understand a cohomological approach to lower bounds in Boolean circuits (of [Fri05]) by studying a very restricted case; in this case Boolean complexity is described via the kernel (or nullspace) of a fairly simple linear transformation and its transpose. We look at this linear transformation approach for Boolean functions where we only allow AND gates, which is essentially the SET COVER problem. These linear transformations can recover the linear programming bound. More importantly, we learn that the optimal linear transformation to use can depend on the Boolean function whose complexity we wish to bound; we also learn that infinite complexity (that can occur in AND complexity over arbitrary sets and "bases") appears as a limits of the linear transformation bounds.
Data Warehousing Technology for Surgical Workflow Analysis
Authors: Thomas Neumuth, Svetlana Mansmann, Marc H. Scholl, Oliver Burgert
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Analysis of surgical procedures is an emerging domain of medical engineering aimed at advancing surgical assist systems. The term Surgical Workflows is used for describing the methodical framework for acquiring formal descriptions of surgical interventions. A formal model and a uniform recording scheme of a surgical process are crucial for systematic accumulation of relevant data from running surgical instances in a form, appropriate for analysis. This paper describes the process of designing a data warehouse for surgical workflow analysis. Data warehousing technology, originally developed for quantitative business data analysis for the purpose of decision making, is adaptable to the requirements of surgical data and analysis. We describe a conceptual model of a surgical procedure obtained in accordance with the multidimensional data model. We demonstrate how a subject-oriented multidimensional perspective of a surgery and its components enables powerful analysis and exploration by defining the metrics of interests and aggregating those metrics along various dimensions and levels of details. Apart from its primary function, i.e. quantitative analysis, the data of the surgical data warehouse may serve as input for other data-intensive systems, e.g. visualization and data mining tools.
Applying Logic Forms and Statistical Methods to CL-SR Performance
Authors: Rafael M. Terol, Patricio Martinez-Barco, Manuel Palomar
Venue: Evaluation of Multilingual and Multi-modal Information Retrieval: 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers (2007)

This paper describes a CL-SR system that employs two different techniques: the first one is based on NLP rules that consist on applying logic forms to the topic processing while the second one basically consists on applying the IR-n statistical search engine to the spoken document collection. The application of logic forms to the topics allows to increase the weight of topic terms according to a set of syntactic rules. Thus, the weights of the topic terms are used by IR-n system in the information retrieval process.
RoadSpeak: enabling voice chat on roadways using vehicular social networks
Authors: Stephen Smaldone, Lu Han, Pravin Shankar, Liviu Iftode
Venue: Proceedings of the 1st Workshop on Social Network Systems (2008)

A great number of people spend one or more hours each day driving between home and the office. These daily roadway commutes are highly predictable and regular, and provide a great opportunity to form virtual mobile communities. However, even though these commuters are already physically present in the same location, they are limited in their ability to communicate with each other. This paper presents a framework for building such communities, which we call Vehicular Social Networks (VSNs), to facilitate better communication between commuters driving on roadways. As a proof of concept, we present the design of RoadSpeak, a VSN-based system which allows drivers to automatically join VSNs along popular roadways, and communicate with each other by means of voice chat messages.
A Bio-inspired Connectionist Architecture for Visual Classification of Moving Objects
Authors: Pedro L. Sánchez Orellana, Claudio Castellanos Sánchez
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In this paper we propose a bio-inspired connectionist architecture for visual classification of moving objects in articulated and non-articulated ones. It is based on a previous model called CONEPVIM, which uses the behaviour of simples cells in the visual primary cortex (V1) to estimate motion. Besides, on general new ideas on the area of neurophysiology for detecting the articulated moving objects and understanding the processing of the visual information from the earlier vision. We tested our architecture with real images without illumination constraints and any previous knowledge.
Multi-agent System for Dynamic Manufacturing System Optimization
Authors: Tawfeeq Al-Kanhal, Maysam Abbod
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

This paper deals with the application of multi-agent system concept for optimization of dynamic uncertain process. These problems are known to have a computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs bundle of intelligent systems algorithms tied together in a multi-agent system. In order to demonstrate the system, a metal reheat furnace scheduling problem is adopted for highly demanded optimization problem. The proposed multi-agent approach has been evaluated for different settings of the reheat furnace scheduling problem. Particle Swarm Optimization, Genetic Algorithm with different classic and advanced versions: GA with chromosome differentiation, Age GA, and Sexual GA, and finally a Mimetic GA, which is based on combining the GA as a global optimizer and the PSO as a local optimizer. Experimentation has been performed to validate the multi-agent system on the reheat furnace scheduling problem.