ppxscal/embedding_network huggingface dataset:
Detecting Commuting Patterns by Clustering Subtrajectories
Authors: Kevin Buchin, Maike Buchin, Joachim Gudmundsson, Maarten Löffler, Jun Luo
Venue: Proceedings of the 19th International Symposium on Algorithms and Computation (2008)

In this paper we consider the problem of detecting commuting patterns in a trajectory. For this we search for similar subtrajectories. To measure spatial similarity we choose the Fréchet distance and the discrete Fréchet distance between subtrajectories, which are invariant under differences in speed. We give several approximation algorithms, and also show that the problem of finding the `longest' subtrajectory cluster is as hard as MaxClique to compute and approximate.
Modeling and Simulation of Container Terminal Logistics System
Authors: Li Li, Xiaodong Wang
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

The modeling and simulation of container terminal logistics system is rapidly developed and widely applied. This paper describes three parts of the modeling and simulation of container terminal logistics system, which includes Logistics system modeling technology, Verification Validation and Accreditation and screening test, and then the research approach and target, the primary coverage and the key problem is given after summarized and selected. This study is devoted to determine the key problems and the best solutions in the process of modeling and simulation, which contributes to reduce the difference between the simulation and reality system and increase the capacity and efficiency of container terminal logistics system.
A Fuzzy-Based Traffic Controller for High-Speed ATM Networks Using Realistic Traffic Models
Authors: Anastasios Kasiolas, Dimitrios Makrakis
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

In modern ATM networks, usage parameter control (UPC) is necessary in order to ensure conformity of the incoming data streams to its negotiated parameters. This protects the quality of conforming applications from degradations that are due to additional network loading produced by non-conforming applications. The present paper focuses on the congestion problem created in an ATM switch by the statistical multiplexing of various traffic sources. The objective is to achieve the maximum possible statistical multiplexing gain without violating the quality of service requirements of the individual streams. A fuzzy traffic controller is being proposed, which performs policing and shaping of the input streams so that the above mentioned goals are satisfied. The controller is a fuzzy implementation of the two-threshold leaky bucket mechanism, which is used in commercial ATM switches
MetaPlab: A Computational Framework for Metabolic P Systems
Authors: Alberto Castellini, Vincenzo Manca
Venue: Membrane Computing: 9th International Workshop, WMC 2008, Edinburgh, UK, July 28-31, 2008, Revised Selected and Invited Papers (2009)

In this work the formalism of metabolic P systems is employed as a basis of a new computational framework for modeling biological networks. The proposed software is a virtual laboratory, called MetaPlab, which supports the synthesis of metabolic P systems by means of an extensible plugin-based architecture. The Java implementation of the software is outlined and a specific plugin at work is described to highlight the internal functioning of the whole architecture.
Solving the Shortest Path Routing Problem Using Noisy Hopfield Neural Networks
Authors: Wen Liu, Lipo Wang
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 02 (2009)

To improve neural network algorithms for the shortest path routing problem (SPRP), we propose a solution using a noisy Hopfield neural network (NHNN), i.e., by adding decaying stochastic noise to the continuous Hopfield neural network (HNN). We also modify the energy function for the SPRP. Simulation results show that our approach achieves better route optimality compared to other algorithms that employ the HNN.
Noise cross PSD estimation using phase information in diffuse noise field
Authors: M. Rahmani, A. Akbari, B. Ayad, B. Lithgow
Venue: Signal Processing (2009)

Among various speech enhancement methods, two-microphone noise reduction systems are utilized for their low cost implementation and acceptable performance. Coherence-based methods are well known as efficient two-microphone noise reduction techniques. These techniques, however, do not work well when the received noise signals are correlated. Coherence-based methods can be improved when the cross power spectral density (CPSD) of input noises is available. In this paper, we propose a new method for estimating noise CPSD based on the assumption of a diffuse noise field. With this assumption, we estimate the noise CPSD using phase information. Then, the estimated noise CPSD is used to calculate a coherence-based gain filter which is then employed to enhance noisy signals. We compare the proposed phase-based noise CPSD estimation with a noise CPSD estimation technique based on a voice activity detector (VAD), both of which are herein separately employed in a two-microphone speech enhancement configuration. The comparison shows that the two-microphone speech enhancement scheme utilizing the proposed noise CPSD estimation technique outperforms the enhancement system using the VAD-based noise CPSD estimation.
Application of genetic algorithms and visual simulation in a real-case production optimization
Authors: Davorin Kofjač, Miroljub Kljajic
Venue: WSEAS Transactions on Systems and Control (2008)

This paper presents a real case customized flexible furniture production optimization. Such a make-to-order production must be flexible to meet the customer's needs, which are changing frequently. Hence, a frequent review of the production process is needed to ensure near-optimal production schedule to meet the minimal makespan constraint. In such a case we are confronted with a tradeoff between makespan and optimization runtime to ensure efficient real-time scheduling. The genetic algorithm production scheduling optimization is presented to solve a job shop scheduling problem with recirculation. Several initial population generators, selection methods, and crossover and mutation methods are discussed and tested. The visual model of the furniture production process was developed during the research. Such a model is closer to end-user perception and is used to clarify the results of numerical optimization. It also enables the implementation of end-user's expert knowledge into the optimizer to reduce the GA search space with a goal of reducing the runtime to a minimum.
Minimum-phase parts of zero-phase sequences
Authors: Corneliu Rusu, Jaakko Astola
Venue: Signal Processing (2009)

For more than a decade it has been empirically known that the causal portion of the inverse Fourier transform of the magnitude spectrum of the speech signal behaves like a minimum-phase signal. Later on, this statement has been shown for an all-pole model. In this paper, we consider related results for both discrete-time Fourier and discrete Fourier transforms of arbitrary sequences. We indicate how the presence of aliasing in circular autocorrelation might be detected. The energy concentration property of zero-phase sequences is discussed.
An Algorithm for image removals and decompositions without inverse matrices
Authors: Dokkyun Yi
Venue: Journal of Computational and Applied Mathematics (2009)

Partial Differential Equation (PDE) based methods in image processing have been actively studied in the past few years. One of the effective methods is the method based on a total variation introduced by Rudin, Oshera and Fatemi (ROF) [L.I. Rudin, S. Osher, E. Fatemi, Nonlinear total variation based noise removal algorithms, Physica D 60 (1992) 259-268]. This method is a well known edge preserving model and an useful tool for image removals and decompositions. Unfortunately, this method has a nonlinear term in the equation which may yield an inaccurate numerical solution. To overcome the nonlinearity, a fixed point iteration method has been widely used. The nonlinear system based on the total variation is induced from the ROF model and the fixed point iteration method to solve the ROF model is introduced by Dobson and Vogel [D.C. Dobson, C.R. Vogel, Convergence of an iterative method for total variation denoising, SIAM J. Numer. Anal. 34 (5) (1997) 1779-1791]. However, some methods had to compute inverse matrices which led to roundoff error. To address this problem, we developed an efficient method for solving the ROF model. We make a sequence like Richardson's method by using a fixed point iteration to evade the nonlinear equation. This approach does not require the computation of inverse matrices. The main idea is to make a direction vector for reducing the error at each iteration step. In other words, we make the next iteration to reduce the error from the computed error and the direction vector. We describe that our method works well in theory. In numerical experiments, we show the results of the proposed method and compare them with the results by D. Dobson and C. Vogel and then we confirm the superiority of our method.
An Efficient ID-Based Proxy Ring Signature Scheme
Authors: Wu Lei, Li Daxing
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 03 (2009)

In a proxy signature scheme, a potential signer delegates his signing power to a proxy, who signs a message on behalf of the original signer. The ring signature allows a user from a set of possible signers to convince the verifier that the author of the signature belongs to the set but identity of the author is not disclosed. In some real situations, we must apply them both concurrently. In this paper, we present an efficient ID-based proxy ring signature scheme and discuss its security and efficiency. It plays an important role in some applications.
Study on error concealment technology for mobile spatial digital audio
Authors: Cong Zhang, Rui-min Hu
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

In the transmission or retrieval of mobile audio signals in compressed digital packet formats, the concealment of errors maybe occur and result from missing or corrupted data. This paper first briefly reviews error-concealment schemes developed for streaming realtime audio over mobile network communications and in digital audio broadcasts. Then a study on the application of the MDCT domain for audio error concealment is described based on theoretical analysis. Finally, some future research directions are identified.
A hybrid hierarchical decision support system for cardiac surgical intensive care patients. Part I: Physiological modelling and decision support system design
Authors: Mouloud A. Denaï, Mahdi Mahfouf, Jonathan J. Ross
Venue: Artificial Intelligence in Medicine (2009)

Objective: To develop a clinical decision support system (CDSS) that models the different levels of the clinician's decision-making strategies when controlling post cardiac surgery patients weaned from cardio pulmonary bypass. Methods: A clinical trial was conducted to define and elucidate an expert anesthetists' decision pathway utilised in controlling this patient population. This data and derived knowledge were used to elicit a decision-making model. The structural framework of the decision-making model is hierarchical, clearly defined, and dynamic. The decision levels are linked to five important components of the cardiovascular physiology in turn, i.e. the systolic blood pressure (SBP), central venous pressure (CVP), systemic vascular resistance (SVR), cardiac output (CO), and heart rate (HR). Progress down the hierarchy is dependent upon the normalisation of each physiological parameter to a value pre-selected by the clinician via fluid, chronotropes or inotropes. Since interventions at each and every level cause changes and disturbances in the other components, the proposed decision support model continuously refers back decision outcomes back to the SBP which is considered to be the overriding supervisory safety component in this hierarchical decision structure. The decision model was then translated into a computerised decision support system prototype and comprehensively tested on a physiological model of the human cardiovascular system. This model was able to reproduce conditions experienced by post-operative cardiac surgery patients including hypertension, hypovolemia, vasodilation and the systemic inflammatory response syndrome (SIRS). Results: In all the simulated patients scenarios considered the CDSS was able to initiate similar therapeutic interventions to that of the expert, and as a result, was also able to control the hemodynamic parameters to the prescribed target values.
HVAC Fault Diagnosis System Using Rough Set Theory and Support Vector Machine
Authors: Xuemei Li, Ming Shao, Lixing Ding
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Preventive maintenance plays a very important role in the modern Heating, Ventilation and Air Conditioning (HVAC) systems for guaranteeing the thermal comfort, energy saving and reliability. The fault diagnosis on HVAC system is a difficult problem due to the complex structure of the HVAC and the presence of multi-excite sources. As the HVAC system fault information has inaccurate and uncertainty characteristic, A new kind of fault diagnosis system based on Rough Set Theory (RST) and Support Vector Machine (SVM) is presented in this paper. The hybrid model is integrated the advantages of RST effectively dealing with the uncertainty information and SVM’s greater generalization performance. The HVAC diagnosis experiment demonstrated that the solution can reduce the cost and raise the efficiency of diagnosis, and verified the feasibility of engineering application. As a result, the presented hybrid fault diagnosis method can help to maintain the health of the HVAC systems, reduce energy consumption and maintenance cost.
Analysis of nonstationary stochastic simulations using classical time-series models
Authors: Rita Marques Brandão, Acácio M. O. Porta Nova
Venue: ACM Transactions on Modeling and Computer Simulation (TOMACS) (2009)

This article extends the use of classical autoregressive and moving average time-series models to the analysis of a variety of nonstationary discrete-event simulations. A thorough experimental evaluation shows that integrated and seasonal time-series models constitute very promising metamodels, especially for analyzing queueing system simulations under congested or cyclical traffic conditions. In some situations, stationarity-inducing transformations may be required before this methodology can be used. Our approach for efficient estimation of meaningful performance measures of selected responses in the target system is illustrated using a set of case studies taken from the simulation literature.
Improvement of the Decision-Directed Frequency Tracking Algorithm for OFDM Systems
Authors: Laibo Zheng, Yewen Cao
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

In this paper, we first analyze a kind of decision-directed frequency tracking algorithm for OFDM systems, and the approximation in derivation of the estimation result, and then we propose an iterative algorithm. In most cases, the frequency offset can be estimated and compensated within one OFDM symbol by using the iterative algorithm. This results in a shortened convergence time. The Cramer-Rao Low Band for the algorithm is derived too, and the simulation results show that the estimation results are close to the Cramer-Rao Low Band.
Inference on a regression model with noised variables and serially correlated errors
Authors: Jinhong You, Xian Zhou, Li-Xing Zhu
Venue: Journal of Multivariate Analysis (2009)

Motivated by a practical problem, [Z.W. Cai, P.A. Naik, C.L. Tsai, De-noised least squares estimators: An application to estimating advertising effectiveness, Statist. Sinica 10 (2000) 1231-1243] proposed a new regression model with noised variables due to measurement errors. In this model, the means of some covariates are nonparametric functions of an auxiliary variable. They also proposed a de-noised estimator for the parameters of interest, and showed that it is root-n consistent and asymptotically normal when undersmoothing is applied. The undersmoothing, however, causes difficulty in selecting the bandwidth. In this paper, we propose an alternative corrected de-noised estimator, which is asymptotically normal without the need for undersmoothing. The asymptotic normality holds over a fairly wide range of bandwidth. A consistent estimator of the asymptotic covariance matrix under a general stationary error process is also proposed. In addition, we discuss the fitting of the error structure, which is important for modeling diagnostics and statistical inference, and extend the existing error structure fitting method to this new regression model. A simulation study is made to evaluate the proposed estimators, and an application to a set of advertising data is also illustrated.
InfoMax Bayesian learning of the Furuta pendulum
Authors: László A. Jeni, György Flórea, András Lörincz
Venue: Acta Cybernetica (2008)

We have studied the InfoMax (D-optimality) learning for the two-link Furuta pendulum. We compared InfoMax and random learning methods. The InfoMax learning method won by a large margin, it visited a larger domain and provided better approximation during the same time interval. The advantages and the limitations of the InfoMax solution are treated.
Developing Web literacy in collaborative inquiry activities
Authors: Els Kuiper, Monique Volman, Jan Terwel
Venue: Computers Education (2009)

Although many children are technically skilled in using the Web, their competences to use it in a critical and meaningful way are usually less well developed. In this article, we report on a multiple case study focusing on the possibilities and limitations of collaborative inquiry activities as an appropriate context to acquire Web literacy skills in primary education. Four 5th grade school teachers and their students worked with collaborative inquiry activities on the subject of 'healthy food'. The project was aimed at both the development of Web literacy skills and content knowledge building. Data from a variety of sources were collected: videotaped and written lesson observations, interviews with teachers and students, teacher diaries, student questionnaires, and student assignments. The teachers appeared to be able to carry out the program to varying degrees. Contextual factors that influenced the realization of the project's goals and results were the adequacy of the research questions formulated by students, students' inquiry skills, and the teachers' teaching styles. Students' learning results show that it is possible to teach Web literacy skills in the context of collaborative inquiry activities. All classes show knowledge gain with regard to the subject healthy food and all classes but one show knowledge gain with regard to Web literacy skills. Although many students show adequate use of particular Web searching, reading and evaluating skills after the project, inconsistency, impulsiveness and impatience are also typical of their Web behaviour. In the context of collaborative inquiry activities teachers are challenged to deal with the paradox that they want their students to be active knowledge builders with help of the Web, whereas the Web seems to invite students to be more or less passive searchers.
Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks
Authors: Mustafa Sarıdemir
Venue: Advances in Engineering Software (2009)

Neural networks have recently been widely used to model some of the human activities in many areas of civil engineering applications. In the present paper, the models in artificial neural networks (ANN) for predicting compressive strength of concretes containing metakaolin and silica fume have been developed at the age of 1, 3, 7, 28, 56, 90 and 180days. For purpose of building these models, training and testing using the available experimental results for 195 specimens produced with 33 different mixture proportions were gathered from the technical literature. The data used in the multilayer feed forward neural networks models are arranged in a format of eight input parameters that cover the age of specimen, cement, metakaolin (MK), silica fume (SF), water, sand, aggregate and superplasticizer. According to these input parameters, in the multilayer feed forward neural networks models are predicted the compressive strength values of concretes containing metakaolin and silica fume. The training and testing results in the neural network models have shown that neural networks have strong potential for predicting 1, 3, 7, 28, 56, 90 and 180days compressive strength values of concretes containing metakaolin and silica fume.
Parts representation in CAD/CAM
Authors: Ikuo Oyake
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

During this decade, numerical models of mechanical parts have been exploited along with the activities related to computer aided design and manufacturing. Indeed, various types of engineering analysis in design have involved the representation problem of the object. N/C machining has required mathematical expressions of the surfaces to be machined for preparing the control information. Also systematical approaches to production require complete numerical representation of parts to provide efficient and smooth interface between design and manufacturing. This paper will describe one approach to parts representation and its applications.
Making sense of agentic objects and teleoperation: in-the-moment and reflective perspectives
Authors: Leila Takayama
Venue: Proceedings of the 4th ACM/IEEE international conference on Human robot interaction (2009)

Agentic objects are those entities that are perceived and responded to in-the-moment as if they were agentic despite the likely reflective perception that they are not agentic at all. They include autonomous robots, but also simpler systems like automatic doors, trashcans, and staplers--anything that seems to possess agency. It is well known that low-level spatiotemporal information elicits in-the-moment responses that are interpreted as perceiving mentalism [8, 17], but people reflectively believe that there is a distinction between human and non-human agents. How are we to make sense of these agentic objects?