ppxscal/embedding_network huggingface dataset:
Contextualizing Behavioural Substitutability and Refinement of Role Components in MAS
Authors: Nabil Hameurlain
Venue: Engineering Societies in the Agents World VIII: 8th International Workshop, ESAW 2007, Athens, Greece, October 22-24, 2007, Revised Selected Papers (2008)

In this paper we focus on a new approach for the definition of context-based behavioural substitutability and refinement of roles in MAS. First, we introduce two flexible roles compatibility relations depending on the context of use (environment). Then, our formal framework is enhanced with the definition of two flexible behavioral subtyping relations related to the principle of substitutability. We show the existing link between compatibility and substitutability, and namely the preservation of the proposed compatibility relations by substitutability. Finally, we study the action as well as the state-based refinements of roles and investigate the links between the substitutability and the refinements of roles. We show that the proposed behavioural substitutability relations are preserved under the roles refinement.
Collision-Resilient Multi-state Query Tree Protocol for Fast RFID Tag Identification
Authors: Jae-Min Seol, Seong-Whan Kim
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

RFID (radio frequency identification) is a RF based identification system, where RF reader reads (and writes) data from each entity (RF tag). Upon request from reader, tags in reader's accessible RF range will respond, and if the number of tags is larger than 2, the reader cannot identify tags (collision). To avoid the collision, there are two previous approaches: ALOHA based and binary tree algorithm. However, they are essentially collision avoidance algorithms, and require much overhead in retransmission time. In this paper, we present collision recovery scheme for RFID system. It uses 20 symbols, and each symbol is 16-bit vectors derived from (16, 4, 1)-BIBD (balanced Incomplete Block design) which is resilient to collision. Although our scheme can decrease the total number of support users, it shows good performance even with low SNR region.
Towards an Architecture for Aligned Speech and Gesture Production
Authors: Stefan Kopp, Kirsten Bergmann
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

The automatic production of speech and gesture is one of the most challenging issues in building embodied conversational agents, due to the intricacy of how the two modalities seem to "align" with each other. Based on experiences from computational approaches and inspired by current theoretical modeling attempts, we propose an architecture to simulate how on-the-spot speech and gesture production might run and bring about more natural multimodal behavior.
A Case Study of Some Issues in the Optimization of Fortran 90 Array Notation
Authors: John D. McCalpin
Venue: Scientific Programming (1996)

Some issues in the relationship of coding style and compiler optimization are discussed with regard to Fortran 90 array notation. A review of several important Fortran 90 array constructs and their performance on vector and scalar hardware sets the stage for a more detailed example based on the kernel of a finite difference computational fluid dynamics model, specifically the nonlinear shallow water equations. Special attention is paid to the optimization of memory use and memory traffic. It is shown that the style of coding interacts with the rules of Fortran 90 and the current state of the art of Fortran 90 compilers to produce a fairly wide range of performance levels. Although performance degradations are typically small, a few cases of more serious loss of effciency are identified and discussed.
Computing by Swarm Networks
Authors: Teijiro Isokawa, Ferdinand Peper, Masahiko Mitsui, Jian-Qin Liu, Kenichi Morita, Hiroshi Umeo, Naotake Kamiura, Nobuyuki Matsui
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

Though the regular and fixed structure of cellular automata greatly contributes to their simplicity, it imposes a strict limitation on the applications that can be modeled by them. This paper proposes swarm networks, a model in which cells, unlike in cellular automata, have irregular neighborhoods. Timed asynchronously, a cell in this model acts like an agent that can dynamically interact with a varying set of other cells under the control of transition rules. The configurations in which cells are organized according to their neighborhoods can move around in space, following simple mechanical laws. We prove computational universality of this model by simulating a circuit consisting of asynchronously timed circuit modules. The proposed model may find applications in nanorobotic systems and artifical biological systems.
Towards Optimal Toom-Cook Multiplication for Univariate and Multivariate Polynomials in Characteristic 2 and 0
Authors: Marco Bodrato
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

Toom-Cook strategy is a well-known method for building algorithms to efficiently multiply dense univariate polynomials. Efficiency of the algorithm depends on the choice of interpolation points and on the exact sequence of operations for evaluation and interpolation. If carefully tuned, it gives the fastest algorithm for a wide range of inputs.This work smoothly extends the Toom strategy to polynomial rings, with a focus on . Moreover a method is proposed to find the faster Toom multiplication algorithm for any given splitting order. New results found with it, for polynomials in characteristic 2, are presented.A new extension for multivariate polynomials is also introduced; through a new definition of density leading Toom strategy to be efficient.
Measuring the Perceived Difficulty of a Lecture Using Automatic Facial Expression Recognition
Authors: Jacob Whitehill, Marian Bartlett, Javier Movellan
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

This project explores the idea of facial expression for automated feedback in teaching. We show how automatic real-time facial expression recognition can be effectively used to estimate the difficulty level, as perceived by an individual student, of a delivered lecture. We also show that facial expression is predictive of an individual student's preferred rate of curriculum presentation at each moment in time. On a video lecture viewing task, training on less than two minutes of recorded facial expression data and testing on a separate validation set, our system predicted the subjects' self-reported difficulty scores with mean accuracy of 0.42 (Pearson r) and their preferred viewing speeds with mean accuracy of 0.29. Our techniques are fully automatic and have potential applications for both intelligent tutoring systems (ITS) and standard classroom environments.
DISC 20th Anniversary: Invited Talk My Early Days in Distributed Computing Theory: 1979-1982
Authors: Nancy Lynch
Venue: Proceedings of the 21st international symposium on Distributed Computing (2007)

I first became involved in Distributed Computing Theory around 1978 or 1979, as a new professor at Georgia Tech. Looking back at my first few years in the field, approximately 1979-1982, I see that they were tremendously exciting, productive, and fun. I collaborated with, and learned from, many leaders of the field, including Mike Fischer, Jim Burns, Michael Merritt, Gary Peterson, Danny Dolev, and Leslie Lamport.Results that emerged during that time included space lower bounds for mutual exclusion; definition of the k-exclusion problem, with associated lower bounds and algorithms; the Burns-Lynch lower bound on the number of registers needed for mutual exclusion; fast network-wide resource allocation algorithms; the Lynch-Fischer semantic model for distributed systems (a precursor to I/O automata); early work on proof techniques for distributed algorithms; lower bounds on the number of rounds for Byzantine agreement; definition of the approximate agreement problem and associated algorithms; and finally, the Fischer-Lynch-Paterson impossibility result for consensus.In this talk, I will review this early work, trying to explain how we were thinking at the time, and how the ideas in these projects influenced later work.
Optimization of rational-powered membership functions using extended Kalman filter
Authors: M. Mottaghi-Kashtiban, A. Khoei, Kh. Hadidi
Venue: Fuzzy Sets and Systems (2008)

This paper presents an extension to the application of the extended Kalman filter (EKF) in membership function (MF) optimization. Since the EKF is a derivative-based method, and derivative calculations of various MF shapes are too complicated, so far only triangular type has been optimized via this approach. In this article, the EKF is applied in optimizing the rational-powered MFs which are extended form of triangular/trapezoidal functions, and hence can offer better performance in almost all applications. In addition, because of the efficiency of the singleton MFs, which makes them a common and desirable choice in hardware/software realization of fuzzy systems, these MFs are also optimized using the EKF. The corresponding analytical equations and derivative formulas are given, and finally the efficiency of the EKF in MF optimization is discussed.
Extending the Edit Distance Using Frequencies of Common Characters
Authors: Muhammad Marwan Muhammad Fuad, Pierre-François Marteau
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

Similarity search of time series has attracted many researchers recently. In this scope, reducing the dimensionality of data is required to scale up the similarity search. Symbolic representation is a promising technique of dimensionality reduction, since it allows researchers to benefit from the richness of algorithms used for textual databases. To improve the effectiveness of similarity search we propose in this paper an extension to the edit distance that we call the extended edit distance. This new distance is applied to symbolic sequential data objects, and we test it on time series data bases in classification task experiments. We also prove that our distance is a metric.
A Decidable Class of Planar Linear Hybrid Systems
Authors: Pavithra Prabhakar, Vladimeros Vladimerou, Mahesh Viswanathan, Geir E. Dullerud
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

The paper shows the decidability of the reachability problem for planar, monotonic, linear hybrid automata without resets. These automata are a special class of linear hybrid automata with only two variables, whose flows in all states is monotonic along some direction in the plane, and in which the continuous variables are not reset on a discrete transition.
A generalized multi-period mean-variance portfolio optimization with Markov switching parameters
Authors: Oswaldo L. V. Costa, Michael V. Araujo
Venue: Automatica (Journal of IFAC) (2008)

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period mean-variance problem, based on a set of interconnected Riccati difference equations, and on a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for risk control over bankruptcy in a dynamic portfolio selection problem with Markov jumps selection problem.
Mining Gene Expression Profiles and Gene Regulatory Networks: Identification of Phenotype-Specific Molecular Mechanisms
Authors: Alexandros Kanterakis, Dimitris Kafetzopoulos, Vassilis Moustakis, George Potamias
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

The complex regulatory mechanisms of genes and their transcription are the major gene regulatory steps in the cell. Gene Regulatory Networks (GRNs) and DNA Microarrays (MAs) present two of the most prominent and heavily researched concepts in contemporary molecular biology and bioinformatics. The challenge in contemporary biomedical informatics research lies in systems biology - the linking of various pillars of heterogeneous data so they can be used in synergy for life science research. Faced with this challenge we devised and present an integrated methodology that `amalgamates' knowledge and data from both GRNs and MA gene expression sources. The methodology, is able to identify phenotype-specific GRN functional paths, and aims to uncover potential gene-regulatory `fingerprints' and molecular mechanisms that govern the genomic profiles of diseases. Initial implementation and experimental results on a real-world breast-cancer study demonstrate the suitability and reliability of the approach.
The Design and Evaluation of Unified Cellular and Ad Hoc Networks
Authors: Haiyun Luo, Xiaqiao Meng, Ram Ramjee, Prasun Sinha, Li (Erran) Li
Venue: IEEE Transactions on Mobile Computing (2007)

In third-generation (3G) wireless data networks, providing service to low data-rate users is required for maintaining fairness, but at the cost of reducing the cell's aggregate throughput. In this paper, we propose the Unified Cellular and Ad-Hoc Network (UCAN) architecture for enhancing cell throughput, while maintaining fairness. In UCAN, a mobile client has both 3G interface and IEEE 802.11-based peer-to-peer links. The 3G base station forwards packets for destination clients with poor channel quality to proxy clients with better channel quality. The proxy clients then use an ad-hoc network composed of other mobile clients and IEEE 802.11 wireless links to forward the packets to the appropriate destinations, thereby improving cell throughput. We refine the 3G base station scheduling algorithm so that the throughput gains are distributed proportional to users' average channel rates, thereby maintaining fairness. With the UCAN architecture in place, we propose novel greedy and on-demand protocols for proxy discovery and ad-hoc routing that explicitly leverage the existence of the 3G infrastructure to reduce complexity and improve reliability. We further propose secure crediting mechanisms to motivate users that are not actively receiving to participate in relaying packets for others. Through both analysis and extensive simulations with HDR and IEEE 802.11b, we show that the UCAN architecture can increase individual user's throughput by more than 100% and the aggregate throughput of the HDR downlink by up to 50%.
An Ontology to Support Adaptive Training for Breast Radiologists
Authors: Shanghua Sun, Paul Taylor, Louise Wilkinson, Lisanne Khoo
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Medical education and training increasingly rely on computer-based tools. A number of initiatives incorporate digital libraries in tools to train radiologists. Our research involves the use of an informatics infrastructure to access a database of annotated images. We argue that an intelligent training tool requires a rich annotation of images in the database. In order to allow for the flexible querying of the database and intelligent feedback to trainees, those annotations must be organised using a clear and explicit model of the relevant concepts: an ontology. The paper reviews existing work on ontologies for mammography and outlines a new approach which is (a) derived from a detailed analysis of a large number of cases and (b) rich enough to meet the requirements of a training tool.
Learning Transcriptional Regulatory Networks with Evolutionary Algorithms Enhanced with Niching
Authors: Cédric Auliac, Florence D'Alché---Buc, Vincent Frouin
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Reverse engineering of gene regulatory networks is a key issue for functional genomic. Indeed, unraveling complex interactions among genes is a crucial step in order to understand their role in cellular processes. High-throughput technologies such as DNA microarrays or ChIP on chip have in principle opened the door to network inference from data. However the size of available data is still limited compared to their dimension. Machine learning methods have thus to be worked out in order to respond to this challenge. In this work we focused our attention on modeling gene regulatory networks with Bayesian networks. Bayesian networks offer a probabilistic framework for the reconstruction of biological interactions networks using data, but the structure learning problem is still a bottleneck. In this paper, we use evolutionary algorithms to stochastically evolve a set of candidate Bayesian networks structures and find the model that best explains the small number of available observational data. We propose different kinds of recombination strategies and an appropriate technique of niching that ensure diversity among candidate solutions. Tests are carried out on simulated data drawn from a biorealistic network. The effect of deterministic crowding, a niching method, is compared to mutation for different kinds of recombination strategies and is shown to improve significantly the performances. Enhanced by deterministic crowding, our evolutionary approach outperforms K2, Greedy-search and MCMC, for training sets whose size is small compared to the standard in machine learning.
Evolution of learning folksonomies: social tagging in e-learning repositories
Authors: Daniel Dahl, Gottfried Vossen
Venue: International Journal of Technology Enhanced Learning (2008)

Repositories for learning objects typically offer two different views for the discovery of stored content: search based on keywords and navigation in a context-dependent directory. In the course of the Web 2.0 phenomenon, the social tagging mechanism provides a new way to categorise and organise content. This user-centred approach, generating the so-called folksonomies, is also offering high potential for the context of e-Learning repositories. The paper illustrates how this particular Web 2.0 technique can be exploited within the metadata repository share.loc and the content repository Learnr, both under development at the University of Muenster.
Validated Modeling of Mechanical Systems with SmartMOBILE: Improvement of Performance by ValEncIA-IVP
Authors: Ekaterina Auer, Andreas Rauh, Eberhard P. Hofer, Wolfram Luther
Venue: Reliable Implementation of Real Number Algorithms: Theory and Practice: International Seminar Dagstuhl Castle, Germany, January 8-13, 2006 Revised Papers (2008)

Computer simulations of real life processes can generate erroneous results, in many cases due to the use of finite precision arithmetic. To ensure correctness of the results obtained with the help of a computer, various kinds of validating arithmetic and algorithms were developed. Their purpose is to provide bounds in which the exact result is guaranteed to be contained. Verified modeling of kinematics and dynamics of multibody systems is a challenging application field for such methods, largely because of possible overestimation of the guaranteed bounds, leading to meaningless results.In this paper, we discuss approaches to validated modeling of multibody systems and present a template-based tool SmartMOBILE, which features the possibility to choose an appropriate kind of arithmetic according to the modeling task. We consider different strategies for obtaining tight state enclosures in SmartMOBILE including improvements in the underlying data types (Taylor models), modeling elements (rotation error reduction), and focus on enhancement through the choice of initial value problem solvers (ValEncIA-IVP).
Control, De-politicization and the eState
Authors: Rahul De'
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

Using an extensive case analysis of the Bhoomi system of India, this paper examines the role and nature of the state with regards to the rationale for and deployment of e-government systems. Issues such as the nature of control in governance, the discourse of de-politicization in justifying e-government and the reinvention of the state via electronic means are examined. Analysis of data collected over several years shows that e-government systems are primarily used to centralize control in the hands of the upper echelons of the bureaucracy, a strong discourse of technology and `high modernism' permeates the justification for deploying e-government and this effectively de-politicizes the intent and purpose of the project. The paper concludes that through e-government the state reinvents itself, as the e-State, as a powerful, centralized force that disrupts historical practices and relations.
Optimal Lambda Lifting in Quadratic Time
Authors: Marco T. Morazán, Ulrik P. Schultz
Venue: Implementation and Application of Functional Languages: 19th International Workshop, IFL 2007, Freiburg, Germany, September 27-29, 2007. Revised Selected Papers (2008)

The process of lambda lifting flattens a program by lifting all local function definitions to the global level. Optimal lambda lifting computes the minimal set of extraneous parameters needed by each function as is done by the O(n 3) equation-based algorithm proposed by Johnsson. In contrast, modern lambda lifting algorithms have used a graph-based approach to compute the set of extraneous parameters needed by each function. Danvy and Schultz proposed an algorithm that reduced the complexity of lambda lifting from O(n 3) to O(n 2). Their algorithm, however, is an approximation of optimal lambda lifting. Morazán and Mucha proposed an optimal graph-based algorithm at the expense of raising the complexity to O(n 3). Their algorithm, however, suggested that dominator trees might be used to develop an O(n 2) algorithm. This article explores the relationship between the call graph of a program, its dominator tree, and lambda lifting by developing algorithms for successively richer sets of programs. The result of this exploration is an O(n 2) optimal lambda lifting algorithm.
Finsler optimal control and geometric dynamics
Authors: Constantin Udriste
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

This paper relates the theory of optimal control to the Finsler geometry and to the geometric dynamics. Section 1 shows how we build a Finsler structure starting from an optimal control problem. Section 2 studies a dynamic system evolving over time and controlled through a Finsler control. In order to choose properly the controls, we use a payoff functional and the Pontryagin Maximum Principle. Section 3 transforms a controlled evolution system in a Finsler geometric dynamics. Section 4 introduces the idea of the controlled Finsler gradient flows in optimization problems. Section 5 studies the Finsler optimal control attached to Rosenbrock function. Section 6 formulates a Finsler affine regulator problem. Section 7 describes a Finsler optimal growth model.