ppxscal/embedding_network huggingface dataset:
Abstract λ-Calculus Machines
Authors: Werner E. Kluge
Venue: Central European Functional Programming School: Second Summer School, CEFP 2007, Cluj-Napoca, Romania, June 23-30, 2007, Revised Selected Lectures (2008)

This paper is about fully normalizing &lambda;-calculus machines that permit symbolic computations involving free variables. They employ full-fledged &beta;-reductions to preserve static binding scopes when substituting and reducing under abstractions. Abstractions and variables thus become truly first class objects: both may be freely substituted for &lambda;-bound variables and returned as abstraction values. This contrasts with implementations of conventional functional languages which realize a weakly normalizing &lambda;-calculus that is capable of computing closed terms (or basic values) only. The two machines described in this paper are descendants of a weakly normalizing secd-machine that supports a nameless &lambda;-calculus which has bound variable occurrences replaced by binding indices. Full normalization is achieved by a few more state transition rules that &eta;-extend unapplied abstractions to full applications, inserting in ascending order binding indices for missing arguments. Updating these indices in the course of performing &beta;-reductions is accomplished by means of a simple counting mechanism that inflicts very little overhead. Both machines realize a head-order strategy that emphasizes normalization along the leftmost spine of a &lambda;-expression. The simpler fn_secd-machine abides by the concept of saving (and unsaving) on a dump structure machine contexts upon each individual &beta;-reduction. The more sophisticated fn_se(m)cd-machine performs what are called &beta;-reductions-in-the-large that head-normalize entire spines in the same contexts. It also employs an additional trace stack M that facilitates traversing spines in search for and contracting redices. The paper also gives an outline of how the fn_se(m)cd-machine can be implemented as a graph reducer.
MIRAI: Multi-hierarchical, FS-Tree Based Music Information Retrieval System
Authors: Zbigniew W. Raś, Xin Zhang, Rory Lewis
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

With the fast booming of online music repositories, there is a need for content-based automatic indexing which will help users to find their favorite music objects in real time. Recently, numerous successful approaches on musical data feature extraction and selection have been proposed for instrument recognition in monophonic sounds. Unfortunately, none of these methods can be successfully applied to polyphonic sounds. Identification of music instruments in polyphonic sounds is still difficult and challenging, especially when harmonic partials are overlapping with each other. This has stimulated the research on music sound separation and new features development for content-based automatic music information retrieval. Our goal is to build a cooperative query answering system (QAS), for a musical database, retrieving from it all objects satisfying queries like "find all musical pieces in pentatonic scale with a viola and piano where viola is playing for minimum 20 seconds and piano for minimum 10 seconds". We use the database of musical sounds, containing almost 4000 sounds taken from the MUMs (McGill University Master Samples), as a vehicle to construct several classifiers for automatic instrument recognition. Classifiers showing the best performance are adopted for automatic indexing of musical pieces by instruments. Our musical database has an FS-tree (Frame Segment Tree) structure representation. The cooperativeness of QAS is driven by several hierarchical structures used for classifying musical instruments.
A Proposal to Hybridize Multi-Objective Evolutionary Algorithms with Non-gradient Mathematical Programming Techniques
Authors: Saúl Zapotecas Martínez, Carlos A. Coello Coello
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

The hybridization of multi-objective evolutionary algorithms (MOEAs) with mathematical programming techniques has gained increasing popularity in the specialized literature in the last few years. However, such hybrids normally rely on the use of gradients and, therefore, normally consume a high number of extra objective function evaluations in order to estimate the gradient information required. The use of direct (nonlinear) optimization techniques has been, however, less common in the specialized literature, although several hybrids of this sort have been proposed for single-objective evolutionary algorithms. This paper proposes a hybridization between a well-known MOEA (the NSGA-II) and two direct search methods (Nelder and Mead's method and the golden section algorithm). The aim of the proposed approach is to combine the global search mechanisms of the evolutionary algorithm with the local search mechanisms provided by the aforementioned mathematical programming techniques, such that a more efficient (i.e., with a lower number of objective function evaluations) approach can be produced.
Multi-robot Cooperation Based on Hierarchical Reinforcement Learning
Authors: Xiaobei Cheng, Jing Shen, Haibo Liu, Guochang Gu
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Multi-agent reinforcement learning for multi-robot systems is a challenging issue in both robotics and artificial intelligence. But multi-agent reinforcement learning is bedeviled by the curse of dimensionality. In this paper, a novel hierarchical reinforcement learning approach named MOMQ is presented for multi-robot cooperation. The performance of MOMQ is demonstrated in three-robot trash collection task.
A network and QoE aware P2P video streaming solution
Authors: Bertrand Mathieu
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

This paper presents a solution for video streaming in a Peer-to-Peer (P2P) fashion, which takes into account the users' context, including information related to the physical underlying networks (type of access network, topology, Internet Service Provider.), in order to optimize the content delivery. Coupled with this network-aware tree structure, the capability to dynamically adapt video data, by the peers themselves, enable to provide the video in the best possible quality according to the context of the users. Components, launched on the peers, analyse the quality perceived by the end user, namely the QoE (Quality of experience), in real-time in order to reorganize the P2P network in case of insufficient perceived quality. A demonstrator of the solution has been implemented and tests have been done on the PlanetLab network in order to validate the feasibility of such a solution.
Efficient Algorithms for k-Disjoint Paths Problems on DAGs
Authors: Rudolf Fleischer, Qi Ge, Jian Li, Hong Zhu
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

Given an acyclic directed graph and two distinct nodes s and t, we consider the problem of finding k disjoint paths from s to t satisfying some objective. We consider four objectives, MinMax, Balanced, MinSum-MinMin and MinSum-MinMax. We use the algorithm by Perl-Shiloach and labelling and scaling techniques to devise an FPTAS for the first three objectives. For the forth one, we propose a general and efficient polynomial-time algorithm.
Commutation-augmented pregroup grammars and push-down automata with cancellation
Authors: Nissim Francez, Michael Kaminski
Venue: Information and Computation (2008)

The paper proves a pumping lemma for a certain subclass of mildly context-sensitive languages, the one defined by commutation-augmented pregroup grammars; in addition, an automaton equivalent to such grammars is introduced, augmenting push-down automata by cancellation in the bottom of its stack.
Reliability of Wireless Sensor Network with Sleeping Nodes
Authors: Vladimir V. Shakhov, Hyunseung Choo
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Energy efficiency is an important technology of sensor networks development. In this paper we offer a method of sensors lifetime maximizing under required level of network reliability. The optimizing statement is offered. As example, we consider homogeneous sensor networks with topology like tree. Other example concerns ZigBee technology. It shown that heterogeneous network can be improved by power elements reassignments. If a sensor network topology is fixed then the most critical nodes can be detected and improved.
A Robot Collision Avoidance Scheme Based on the Moving Obstacle Motion Prediction
Authors: Rongxin Jiang, Xiang Tian, Li Xie, Yaowu Chen
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

This paper proposes an integrated scheme for the robot to avoid collision based on obstacle’s motion prediction. The robot obtains the target bearing by using object detection technique and fuses the bearing information with the external sensors data to locate the current position of the moving target. The motion state of the moving obstacle is described using the Constant Velocity (CV) model, the Constant Accelerate (CA) model and the Current Statistical (CS) model. Then, a Kalman-based Interacting Multiple Model (IMM) filter is adopted to estimate the obstacle motion trend. This scheme mainly focuses on the obstacle detection and the motion prediction. Based on the motion prediction of the obstacle, an abbreviated strategy is proposed for collision avoidance. To validate the proposed scheme, we have implemented an obstacle avoidance experiment with a Pioneer 3-AT robot and a moving obstacle. The results verify that the proposed scheme is valid and viable.
Gradient scheduling algorithm for fair delay guarantee in logarithmic pricing scenario
Authors: Pete Räsänen, Simo Lintunen, Riku Kuismanen, Jyrki Joutsensalo, Timo Hämäläinen
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

In this paper we propose a packet scheduling scheme for ensuring delay as a Quality of Service (QoS) requirement. For customers, fair service is given while optimizing revenue of the network service provider. Gradient type algorithm for updating the weights of a packet scheduler is derived from a revenue-based optimization problem in the logarithmic pricing scenario. Algorithm is simple to implement. We compared algorithm with optimal brute-force method. The weight updating procedure is independent on the assumption of the connection's statistical behavior, and therefore it is robust against erroneous estimates of statistics.
Improved Schemes for Node Clustering in Decentralized Peer-to-Peer Networks
Authors: Yanxiang He, Haowen Liu, Fubao Zhu
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Node Clustering has wide ranging applications in decentralized Peer-to-Peer (P2P) networks such as P2P file sharing systems, mobile ad-hoc networks, P2P sensor networks and so forth. In this work, We propose two distributed approaches for node clustering that based on the Scaled Coverage Measure (SCM), a measure of the accuracy of the partition of the network into clusters. The novelty of our approaches is to process nodes in local vicinity in special orders. Simulation study shows that our approach derives a more accurate partition with less orphan nodes, and converges faster than previously proposed methods, for both random topologies and power law topologies.
Extending the Overlap Graph for Gene Assembly in Ciliates
Authors: Robert Brijder, Hendrik Jan Hoogeboom
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

Gene assembly is an intricate biological process that has been studied formally and modeled through string and graph rewriting systems. Recently, a restriction of the general (intramolecular) model, called simple gene assembly, has been introduced. This restriction has subsequently been defined as a string rewriting system. We show that by extending the notion of overlap graph it is possible to define a graph rewriting system for two of the three types of rules that make up simple gene assembly. It turns out that this graph rewriting system is less involved than its corresponding string rewriting system. Finally, we give characterizations of the `power' of both types of graph rewriting rules. Because of the equivalence of these string and graph rewriting systems, the given characterizations can be carried over to the string rewriting system.
User Identification Based on Handwritten Signatures with Haptic Information
Authors: Fawaz A. Alsulaiman, Jongeun Cha, Abdulmotaleb Saddik
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

In this paper we focus our research on user identification rather than user verification by analyzing handwritten signature and haptic information such as pressure. For analysis, a multilayer perception (MLP) neural network is adopted. In order to verify the proposed method, 16 users' signatures were measured with haptic information. We successfully identified users at an average success rate of 81%.
Traffic Routing Through Off-Line LSP Creation
Authors: Srecko Krile, Djuro Kuzumilovic
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

In the context of dynamic bandwidth allocation the QoS path provisioning for coexisted and aggregated traffic could be very important element of resource management. As we know all traffic in DiffServ/MPLS network is distributed among LSPs (Label Switching Path). Packets are classified in FEC (Forwarding Equivalence Class) and can be routed in relation to CoS (Class of Service). In the process of resource management we are looking for optimal LSP, taking care of concurrent flows traversing the network simultaneously. For better load-balancing purposes and congestion avoidance the LSP creation can be done off-line, possible during negotiation process. The main difference from well known routing techniques is that optimal LSP need not to be necessarily the shortest path solution as it is in the case of typical on-line routing (e.g. with OSPF protocol).
Read My Day? Communication, campaigning and councillors' blogs
Authors: Scott Wright
Venue: Information Polity (2008)

This article analyses how and why councillors blog on the government-funded civic-blogging platform, Read My Day. Through a mixture of content analysis and interviews, the article assesses the kinds of communication being facilitated and how the blogs were used during the 2007 local elections. The analysis and interpretations are framed by a critique of the normalisation hypothesis. The article concludes that blogs were largely used as tools of representation rather than for campaigning. The extent to which they strengthen representative practices is mixed. Many bloggers fail to exploit the networking potential of the medium such as creating blog rolls and engaging with the broader blogosphere; this leads to a danger that the politically-interested are talking to each other in isolation. Furthermore, the number of comments is limited, and councillors often do not reply to these: it is typically broadcast, one-way communication. However, there are potentially important positive changes that must be fully considered alongside this. If it is true to say that political communication is increasingly negative, attack-orientated, dominated by political leaders and lacking in substance, then the blogs on Read My Day do go some way to redress this: while it is an example of how technologies are being normalised, it is not quite politics as usual.
Using Characteristics of Computational Science Schemas for Workflow Metadata Management
Authors: Scott Jensen, Beth Plale
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Computational science workflows are generating an ever-increasing volume of data products. Metadata for these workflows is communicated using one or more discipline-specific schemas and is not static but instead is subject to frequent updates and additions. In contrast to general XML data, the unique uses for scientific metadata allow further optimization.We propose a general metadata catalog for storing scientific metadata that is optimized for community science use and communicates metadata as XML using the schemas of scientific domains. In this paper we show that our hybrid approach outperforms the well-known inlining approach to storing XML when applied to scientific metadata.
A Logical Framework to Reinforcement Learning Using Hybrid Probabilistic Logic Programs
Authors: Emad Saad
Venue: Proceedings of the 2nd international conference on Scalable Uncertainty Management (2008)

Knowledge representation is an important issue in reinforcement learning. Although logic programming with answer set semantics is a standard in knowledge representation, it has not been exploited in reinforcement learning to resolve its knowledge representation issues. In this paper, we present a logic programming framework to reinforcement learning, by integrating reinforcement learning, in MDP environments, with normal hybrid probabilistic logic programs with probabilistic answer set semantics [29], that is capable of representing domain-specific knowledge. We show that any reinforcement learning problem, MT, can be translated into a normal hybrid probabilistic logic program whose probabilistic answer sets correspond to trajectories in MT. We formally prove the correctness of our approach. Moreover, we show that the complexity of finding a policy for a reinforcement learning problem in our approach is NP-complete. In addition, we show that any reinforcement learning problem, MT, can be encoded as a classical logic program with answer set semantics, whose answer sets corresponds to valid trajectories in MT. We also show that a reinforcement learning problem can be encoded as a SAT problem. In addition, we present a new high level action description language that allows the factored representation of MDP.
Neural Network Based Multiple Model Adaptive Predictive Control for Teleoperation System
Authors: Qihong Chen, Jin Quan, Jianjun Xia
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Environment model and communication time delays of a teleoperation system are variant usually, which will induce bad performance, even instability of the system. In this paper, neural network based multiple model adaptive predictive control method is proposed to solve this problem. The whole control system is composed of predictive controller and decision controller. First of all, neural network model set of any possible environment is built up, and time forward state observer based predictive controllers are designed for all models. In succession, decision controller is designed to adaptive switch among all predictive controllers according to performance target. This method can ensure stability and performance of the system. Finally, simulation results show effectiveness of the proposed method.
Extrinsic Summarization Evaluation: A Decision Audit Task
Authors: Gabriel Murray, Thomas Kleinbauer, Peter Poller, Steve Renals, Jonathan Kilgour, Tilman Becker
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

In this work we describe a large-scale extrinsic evaluation of automatic speech summarization technologies for meeting speech. The particular task is a decision audit, wherein a user must satisfy a complex information need, navigating several meetings in order to gain an understanding of how and why a given decision was made. We compare the usefulness of extractive and abstractive technologies in satisfying this information need, and assess the impact of automatic speech recognition (ASR) errors on user performance. We employ several evaluation methods for participant performance, including post-questionnaire data, human subjective and objective judgments, and an analysis of participant browsing behaviour.
Lagrange interpolation for continuous piecewise smooth functions
Authors: Sergio Amat, Sonia Busquier, Antonio Escudero, J. Carlos Trillo
Venue: Journal of Computational and Applied Mathematics (2008)

This note is devoted to Lagrange interpolation for continuous piecewise smooth functions. A new family of interpolatory functions with explicit approximation error bounds is obtained. We apply the theory to the classical Lagrange interpolation.
Light Weight SOA Governance A Case Study
Authors: Deepti Parachuri, Nagarani Badveeti, Sudeep Mallick
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Here, we present a case study of an ABC company which has recently embarked on a SOA exercise and has adopted a light weight SOA governance process. In SOA Governance world, Service registry and repository play a pivotal role. Service registry can have policies that are needed to govern and enforce the lifecycle management of service. In this case study, we also address versioning and categorization of services using registry.
Experience-Based Design of Behaviors in Videogames
Authors: Gonzalo Flórez Puga, Belén Díaz-Agudo, Pedro González-Calero
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Artificial intelligence in games is usually used for creating player's opponents. Manual edition of intelligent behaviors for Non-Player Characters (NPC) of games is a cumbersome task that needs experienced designers. Amongst other activities, they design new behaviors in terms of perception and actuation over the environment. Behaviors typically use recurring patterns, so that experience and reuse are crucial aspects for behavior design. In this paper we present a behavior editor (eCo) using Case Based Reasoning to retrieve and reuse stored behaviors represented as hierarchical state machines. In this paper we focus on the application of different types of similarity assessment to retrieve the best behavior to reuse. eCo is configurable for different domains. We present our experience within a soccer simulation environment (SoccerBots) to design the behaviors of the automatic soccer players.
Advanced algorithms for coupled and inverse problems in electrical engineering
Authors: Ion Cârstea
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

This paper presents some theoretical and numerical problems that arise in the analysis of coupled electromagnetic-thermal problems, and inverse problems in electromagnetic devices. The principal objective of the paper is to describe some computational aspects for coupled electromagnetic and thermal fields in the context of the finite element method, with emphasis on the reduction of the computing resources. We present coupled models for magnetic field and thermal field. The mathematical model for magnetic field is based on time-harmonic Maxwell equations in vector magnetic potential formulation for axisymmetric fields. The model for the heat transfer is the heat conduction equation. We propose simplified numerical models for coupled fields in electromagnetic devices with target examples on the induction heating devices and high-voltage and large power cables. Domain decomposition is presented in the context of the coupled fields. The analysis domain is divided into two overlapping subdomains for the two coupled-fields considering physical significance of the pseudo-boundary of the two subdomains.