ppxscal/embedding_network huggingface dataset:
A Sliding Singular Spectrum Entropy Method and Its Application to Gear Fault Diagnosis
Authors: Yong Lu, Yourong Li, Han Xiao, Zhigang Wang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Entropy changes with the variation of the system status. It has been widely used as a standard for the determination of system status, quantity of system complexity and system classification. Based on the singular spectrum entropy of traditional calculation method, a sliding singular spectrum entropy method is proposed to use for singularity detection and extraction of impaction signal. Each original signal point is intercepted a neighborhood points of the signal with a given length and the singular spectrum entropy for the intercepted signal is calculated. A surrogate signal with the same length as the original signal is acquired by point-to-point calculation. Numerical simulation and gear fault diagnosis experiment are studied to verify the proposed method, the results show that the method is valid for the reflection on the changing of system status, singularity detection and the extraction of the weak fault feature signal mixed in the strong background signal.
On the Proxy-Protected Property of Chen et al.'s Proxy Multisignature Schemes
Authors: Pei-Hui Huang, Hsiang-An Wen, Chih-Hung Wang, Tzonelih Hwang
Venue: Informatica (2007)

Recently, Chen, Chung, and Huang proposed a traceable proxy multisignature scheme based on the elliptic curve cryptosystem. However, this paper shows that the original signers can produce a valid signature as the proxy signer does in the proxy protected scheme. Therefore, Chen et al.'s proxy-protected scheme cannot protect the proxy signer from being forged by the original signers. We further find that the early work of Chen et al. in 2003 suffers the same attack. To overcome this problem, an improved scheme will be presented.
An Indexing Matrix Based Retrieval Model
Authors: Xu Zhao, Zongli Jiang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

The Latent Semantic Indexing based standard retrieval usually computes semantic similarity between the query and every document, which is sensitive to the noise. Furthermore, it will take much more time when the scale of the corpus becomes larger. We propose a retrieval method which is based on an indexing matrix. The noises can be wiped off at a certain extent and it can get a better result than the traditional ways. The time cost of our method is much less than the standard retrieval method.
Numerical Solution of a Two-Class LWR Traffic Flow Model by High-Resolution Central-Upwind Scheme
Authors: Jianzhong Chen, Zhongke Shi, Yanmei Hu
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

A high-resolution semi-discrete central-upwind scheme for solving a two class Lighthill-Whitham-Richards (LWR) traffic flow model is investigated in this paper. This scheme is based on combining a fourth-order central weighted essentially nonoscillatory (CWENO) reconstruction with semi-discrete central-upwind numerical flux. The CWENO re construction is chosen to improve the accuracy and guarantee the non-oscillatory behavior of the present method. The strong stability preserving Runge-Kutta method is used for time integration. The resulting method is applied to simulating several tests such as mixture of the two traffic flows. The simulated results illustrate the effectiveness of the present method.
The heat element status assignment algorithms for the selective inhibition of sintering process array-based heating system
Authors: Bahram Asiabanpour, Chandrashekar Subbareddy, Sravan Kolichala, Lane VanWagner
Venue: International Journal of Computer Applications in Technology (2008)

To minimise polymer and energy waste in the SIS process, a new adjustable heater system is designed. In this heater, many small heat elements are installed in the form of an array. Each heat element, independent of other heat elements, can be in an ON or OFF status. The heat element status assignment enables the heater to sinter polymer powders solely in the necessary areas. In this paper, the array-based mechanism and the algorithms that generate heat elements status by using the CAD file are explained. Results of this research show an effective method to save energy and material.
MasDISPO_xt: heat and sequence optimisation based on simulated trading inside the supply chain of steel production
Authors: Sven Jacobi, David Raber, Klaus Fischer
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track (2008)

The production of steel normally constitutes the inception of most Supply Chains in different areas. Steel manufacturing companies are strongly affected by bull whip effects. Due to nondeterministic incoming orders and changes of customer requirements on accepted orders, making the right decision at a certain stage can be the difference between earning or loosing a great turnover. Improving their operational efficiency is required to keep a competitive position on the market. Therefore, flexible planning and scheduling systems are needed to support these processes which are based on considerable amounts of data which can hardly be processed manually. Existing systems are dominated by centralized decision making processes, mostly data driven and often not modeling the business processes they should. MasDISPO_xt is an agent-based generic online planning and online scheduling system for monitoring of the complete Supply Chain of Saarstahl AG, a globally respected steel manufacturer. This paper concentrates on the creation and optimisation of heats and sequences as a presetting for the production inside the steelwork.
Utilizing Open Travel Alliance-Based Ontology of Golf in an Agent-Based Travel Support System
Authors: Agnieszka Cieślik, Maria Ganzha, Marcin Paprzycki
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Currently, we are developing an agent-based travel support system, in which ontologically demarcated data is used to facilitate personalized information provisioning. Recently we have shown how Open Travel Alliance golf-related messages can be reverse-engineered to create an OTA ontology of golf. The aim of this paper is to illustrate how these ontologies are going to be used in the system. In addition to the general scenario, details concerning implementation of needed translators will be discussed.
Effective Computation for Nonlinear Systems
Authors: Pieter Collins
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

Nonlinear dynamical and control systems are an important source of applications for theories of computation over the the real numbers, since these systems are usually to complicated to study analytically, but may be extremely sensitive to numerical error. Further, computer-assisted proofs and verification problems require a rigorous treatment of numerical errors. In this paper we will describe how to provide a semantics for effective computations on sets and maps and show how these operations have been implemented in the tool Ariadne for the analysis, design and verification of nonlinear and hybrid systems.
Simulated Evolution of the Adaptability of the Genetic Code Using Genetic Algorithms
Authors: Ángel Monteagudo, José Santos
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

In this work we use simulated evolution to corroborate the adaptability of the natural genetic code. An adapted genetic algorithm searches for optimal hypothetical codes. The adaptability is measured as the average variation of the hydrophobicity that experiment the encoded amino acids when errors or mutations are presented in the codons of the hypothetical codes. Different types of mutations and base position mutation probabilities are considered in this study.
Object-Oriented Support for Adaptive Methods on Paranel Machines
Authors: Sandeep Bhatt, Marina Chen, James Cowie, Cheng-Yee Lin, Pangfeng Liu
Venue: Scientific Programming (1993)

This article reports on experiments from our ongoing project whose goal is to develop a C++ library which supports adaptive and irregular data structures on distributed memory supercomputers. We demonstrate the use of our abstractions in implementing "tree codes" for large-scale N-body simulations. These algorithms require dynamically evolving treelike data structures, as well as load-balancing, both of which are widely believed to make the application difficult and cumbersome to program for distributed-memory machines. The ease of writing the application code on top of our C++ library abstractions (which themselves are application independent), and the low overhead of the resulting C++ code (over hand-crafted C code) supports our belief that object-oriented approaches are eminently suited to programming distributed-memory machines in a manner that (to the applications programmer) is architecture-independent. Our contribution in parallel programming methodology is to identify and encapsulate general classes of communication and load-balancing strategies useful across applications and MIMD architectures. This article reports experimental results from simulations of half a million particles using multiple methods.
GraSeq: A Novel Approximate Mining Approach of Sequential Patterns over Data Stream
Authors: Haifeng Li, Hong Chen
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Sequential patterns mining is an important data mining approach with broad applications. Traditional mining algorithms on database were not adapted to data stream. Recently, some approximate sequential pattern mining algorithms over data stream were presented which solved some problems except the one of wasting too many system resources in processing long sequences. According to observation and proof, a novel approximate sequential pattern mining algorithm is proposed named GraSeq. GraSeq uses directed weighted graph structure and stores the synopsis of sequences with only one scan of data stream; furthermore, a subsequences matching method is mentioned to reduce the cost of long sequences' processing and a conception validnode is introduced to improve the accuracy of mining results. Our experimental results demonstrate that this algorithm is effective and efficient.
Vector control for loss minimization of induction motor using GA-PSO
Authors: Dong Hwa Kim, Kaoro Hirota
Venue: Applied Soft Computing (2008)

This paper deals with the GA-PSO (genetic algorithm-particle swarm optimization) based vector control for loss minimization operation of induction motor. It is estimated that more than around 50% of the world electric energy generated is consumed by electric machines such as induction motor, dc motor. So, improving efficiency in electric drives is important and control strategy for minimum energy loss is needed as one of optimal operation strategies. The vector control of induction motor has been widely used to operate in a wide speed range by using flux weakening at rated speed. However, it is still necessary to advance because of coupling is behavior between fluxes in motor. In this paper, vector control approach is suggested for an optimal operation of induction motor using variable acceleration and GA-PSO tuning method through simulation. We can obtain satisfactory results for energy saving control.
Detection of Anomalies in Large Datasets Using an Active Learning Scheme Based on Dirichlet Distributions
Authors: Karim Pichara, Alvaro Soto, Anita Araneda
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

Today, the detection of anomalous records is a highly valuable application in the analysis of current huge datasets. In this paper we propose a new algorithm that, with the help of a human expert, efficiently explores a dataset with the goal of detecting relevant anomalous records. Under this scheme the computer selectively asks the expert for data labeling, looking for relevant semantic feedback in order to improve its knowledge about what characterizes a relevant anomaly. Our rationale is that while computers can process huge amounts of low level data, an expert has high level semantic knowledge to efficiently lead the search. We build upon our previous work based on Bayesian networks that provides an initial set of potential anomalies. In this paper, we augment this approach with an active learning scheme based on the clustering properties of Dirichlet distributions. We test the performance of our algorithm using synthetic and real datasets. Our results indicate that, under noisy data and anomalies presenting regular patterns, our approach significantly reduces the rate of false positives, while decreasing the time to reach the relevant anomalies.
Study on Venture Investment Model Base on Signaling Game
Authors: Xubo Zhang, Zigang Zhang
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

This paper present a new method and model to analysis the venture investment decision based on the signaling game. We analyze and describe the venture investment decision making of two-period using mathematics models under the uncertainty to establish our option value model of venture investment. We analyze the asymmetric information between venture enterprises and venture investment corporations. Boil down the game between venture enterprises and venture investment corporations to signaling game under the incompleteness information. Get a solution of combination perfect Bayesian equilibrium.
A Sociogram Analysis on Group Interaction in an Online Discussion Forum
Authors: Jianhua Zhao
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

Group interaction reveals how group members communicate each other when they are working for a group task. The purposes for analysing group interaction are to know how students engaged in the group learning activities and what kinds of social networks are built. 23 students enrol a course and they are organised into 5 groups in this study. Each group has to complete two tasks in a group discussion forum which is offered by WebCL system (an online learning environment). The messages in the discussion forums posted by students in these 5 groups are analysed through sociogram and the results illustrate the characteristics of group interaction in this course.
Efficient Multiplication Using Type 2 Optimal Normal Bases
Authors: Joachim Zur Gathen, Amin Shokrollahi, Jamshid Shokrollahi
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

In this paper we propose a new structure for multiplication using optimal normal bases of type 2. The multiplier uses an efficient linear transformation to convert the normal basis representations of elements of $\mathbb{F}_{q^{n}}$ to suitable polynomials of degree at most n over $\mathbb{F}_{q}$. These polynomials are multiplied using any method which is suitable for the implementation platform, then the product is converted back to the normal basis using the inverse of the above transformation. The efficiency of the transformation arises from a special factorization of its matrix into sparse matrices. This factorization -- which resembles the FFT factorization of the DFT matrix -- allows to compute the transformation and its inverse using O(n logn) operations in $\mathbb{F}_{q}$, rather than O(n 2) operations needed for a general change of basis. Using this technique we can reduce the asymptotic cost of multiplication in optimal normal bases of type 2 from reported by Gao et al. (2000) to M(n) + O(n logn) operations in $\mathbb{F}_{q}$, where M(n) is the number of $\mathbb{F}_{q}$-operations to multiply two polynomials of degree n ¿ 1 over $\mathbb{F}_{q}$. We show that this cost is also smaller than other proposed multipliers for n > 160, values which are used in elliptic curve cryptography.
The impact of adversarial knowledge on adversarial planning in perimeter patrol
Authors: Noa Agmon, Vladimir Sadov, Gal A. Kaminka, Sarit Kraus
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

This paper considers the problem of multi-robot patrolling around a closed area, in the presence of an adversary trying to penetrate the area. Previous work on planning in similar adversarial environments addressed worst-case settings, in which the adversary has full knowledge of the defending robots. It was shown that non deterministic algorithms may be effectively used to maximize the chances of blocking such a full-knowledge opponent, and such algorithms guarantee a "lower bound" to the performance of the team. However, an open question remains as to the impact of the knowledge of the opponent on the performance of the robots. This paper explores this question in depth and provides theoretical results, supported by extensive experiments with 68 human subjects concerning the compatibility of algorithms to the extent of information possessed by the subjects. First, we analytically examine the case of a zero-knowledge opponent---a different extreme---and show that surprisingly, this seemingly best-case scenario (from the point of view of defending robots) is optimally addressed by a deterministic, non-randomizing patrol. Moreover, we show empirically that an optimal algorithm for the full-knowledge opponent fails miserably in this case. We then address the case in which the adversary gained partial information, propose the Combine algorithm that maximizes the expected probability of penetration detection along with minimizing the deviation between the probabilities of penetration detection along the perimeter, and support the performance of this algorithm in the experiments.
Particle Imaging Velocimetry Measurements in a Heart Simulator
Authors: Y. Knapp, E. Bertrand
Venue: Journal of Visualization (2005)

In vitro experiments are often unable to reproduce all the complexities of biological flows observed in vivo. The in vitro models are often rigid, use Newtonian fluids, and/or some ideal geometry tested under ideal physiological parameters. The study presented in this article describes the in vitro assessment of mitral prosthetic heart valves in a setup able to simulate the pulsatile blood flow in a model of the left heart with moving walls. The specific laboratory mockup built for these experiments consists in a Dual Activation Simulator (DAS) that provides a realistic simulation of the atrial and ventricular flow in anatomically shaped silicone models cavities. This mockup, initially designed for ultrasonic velocity measurements took recently advantage of the use of particle image velocimetry. We present here some aspects of flow visualization and phase averaged two-dimensional PIV measurements which can provide new insight in the interaction between the flow dynamics and the heart valves.
Specification of Timed EFSM Fault Models in SDL
Authors: S. S. Batth, E. R. Vieira, A. Cavalli, M. Ü. Uyar
Venue: Proceedings of the 27th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2007)

In this paper, we apply our timing fault modeling strategy to writing formal specifications for communication protocols. Using the formal language of Specification and Description Language (SDL), we specify the Controller process of rail-road crossing system, a popular benchmark for real-time systems. Our extended finite state machine (EFSM) model has the capability of representing a class of timing faults, which otherwise may not be detected in an IUT. Hit-or-Jump algorithm is applied to the SDL specification based on our EFSM model to generate a test sequence that can detect these timing faults. This application of fault modeling into SDL specification ensures the synchronization among the timing constraints of different processes, and enables generation of portable test sequences since they can be easily represented in other formal notations such as TTCN or MSC.
Tracking a Moving Target Using Chaotic Dynamics in a Recurrent Neural Network Model
Authors: Yongtao Li, Shigetoshi Nara
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Chaotic dynamics introduced in a recurrent neural network model is applied to controlling an tracker to track a moving target in two-dimensional space, which is set as an ill-posed problem. The motion increments of the tracker are determined by a group of motion functions calculated in real time with firing states of the neurons in the network. Several groups of cyclic memory attractors that correspond to several simple motions of the tracker in two-dimensional space are embedded. Chaotic dynamics enables the tracker to perform various motions. Adaptively real-time switching of control parameter causes chaotic itinerancy and enables the tracker to track a moving target successfully. The performance of tracking is evaluated by calculating the success rate over 100 trials. Simulation results show that chaotic dynamics is useful to track a moving target. To understand them further, dynamical structure of chaotic dynamics is investigated from dynamical viewpoint.
Personal Mobile Assistant for Air Passengers with Disabilities (PMA)
Authors: Alireza Darvishy, Hans-Peter Hutter, Peter Früh, Alexander Horvath, Dominik Berner
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

This paper describes the PMA research project in progress, whose aim is to develop a concept for personalized mobile route guidance and information for air passengers with disabilities (PWDs), and to implement this concept step by step. The PMA guides PWDs along their route from home to the desired departure gate (or vice-versa: from landing to destination), and provides them with information - as and when they need it - on their current position and remaining travel route, together with the latest flight information (e.g. delays or gate changes). This project mainly focuses on in-house guidance within the airport for passengers with visual disabilities. The concept is based on normal commercial mobile devices (cell phones or PDAs) with cameras. Within this project, the implementation of the concept is also restricted to the airport area, but is easily extendable to other public transport facilities.
An Interactive Large Graph Visualizer
Authors: Hiroshi Hosobe
Venue: Proceedings of the 9th international symposium on Smart Graphics (2008)

Real-world information can often be expressed as a graph that consists of nodes and edges. Graphs are often effectively represented in a visual manner. To make visual representations of graphs easily available, researchers have proposed numerous techniques for automatic visualization of graphs [1].An important class of graphs is the general undirected graph, which imposes no restrictions on its structure as well as having no directed edges. The forcedirected approach [1] is often adopted to visualize general undirected graphs, and works well for graphs with hundreds of nodes.