Multidimensional Systems Research Papers - Academia.edu (original) (raw)

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- Engineering, Computational Complexity, Mesh generation, Optimization
- by Emanuele Viterbo
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- Lattice Theory, Fading Channel, Entropy, Frequency
- by Aurelio Uncini
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- Convergence, Artificial Neural Networks, Adaptive Systems, Spline
- by Dieter Merkl
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- Functional Analysis, Data Mining, Data Analysis, Pattern Recognition
- by Shogo Muramatsu
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- Mathematics, Computer Science, Signal Processing, Multidisciplinary
- by Ephraim Feig
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- Parallel Algorithms, Inverse Problems, Multidisciplinary, Quantization

The growing demand for link bandwidth and node capacity is a frequent phenomenon in IP network backbones. Within this context, traffic prediction is essential for the network operator. Traffic prediction can be undertaken based on link traffic or on origin-destination (OD) traffic which presents better results. This work investigates a methodology for traffic prediction based on multidimensional OD traffic, focusing on the stage of short-term traffic prediction using Principal Components Analysis as a technique for dimensionality reduction and a Local Linear Model based on K-means as a technique for prediction and trend analysis. The results validated with data on a real network present a satisfactory margin of error for use in practical situations.

- by José Everardo Bessa Maia
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- Spine, Principal Component Analysis, Linear Model, Predictive models
- by Aurelio Uncini
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- Computer Architecture, Digital Signal Processing, Neural Networks, Convergence
- by Salvatore Morgera
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- Independent Component Analysis, TV, Computational Efficiency, Convolution
- by Patrick Groenen
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- Econometrics, Visualization, Audio Signal Processing, Multidimensional Scaling
- by Matthias Renz
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- Computer Science, Informatics, Graph Theory, Computer Networks

Summarizability of OLAP and Statistical Databases is an a extremely important property because violating this condition can lead to erroneous conclusions and decisions. In this paper we explore the conditions for summarizability. We... more

- by Arie Shoshani
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- Data Analysis, Databases, OLAP, Specification Tests
- by Shozo Mori
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- Computer Science, Information Technology, Linear Programming, Data Fusion
- by Shojiro Sakata
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- Information Science, Automata, Encoding, Galois Fields
- by Steen Parl
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- Entropy, Speech Processing, Autocorrelation, Signal Detection
- by Fernando Ferri
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- Computer Science, Production, Decision Support Systems, Data Structure

There are few studies of the human factors involved in the engagement of presence. The present study aims to investigate the influence of five user characteristics - test anxiety, spatial intelligence, verbal intelligence, personality and computer experience - on the sense of presence in university students when exposed to virtual environments designed to assess their levels of test anxiety. This is the first study to investigate the influence of spatial intelligence on the sense of presence, and the first to use an immersive virtual reality system to investigate the relationship between users' personality characteristics and presence. The results show a greater sense of presence in test anxiety environments than in a neutral environment. Moreover, high test anxiety students feel more presence than their non-test anxiety counterparts, especially in test anxiety environments. Spatial intelligence and introversion also influence the sense of presence experienced by high test anxiety students exposed to emotional virtual environments. Interestingly, each of these user characteristics influences different dimensions of the sense of presence. These results may help to identify new groups of patients likely to benefit from virtual reality therapy.

- by Ivan Jurnet
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- Psychology, Personality, Intelligence, Human Factors
- by Krishna Pattipati
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- Aerospace Engineering, Parallel Algorithms, Modeling, State Estimation
- by Dov Dvir
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- Engineering, Project Management, Statistical Analysis, Taxonomy
- by Jorge Tavares
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- Genetics, Computer Science, Algorithms, Artificial Intelligence

Many scientific applications can benejit from eficient clustering algorithm of massively large high dimensional datasets. However most of the developed ,algorithms are impractical to use when the amount of data is very large. Given N objects each de3ned by an M-dimensional fea- ture vectol; any clustering technique for handling very large datasets in high dimensional space should run in time

- by Arie Shoshani
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- Clustering Algorithms, Dimensionality Reduction, Sampling, Sampling methods

This paper investigates the robust H ∞ filtering problem for uncertain two-dimensional (2D) systems described by the Roesser model. The parameter uncertainties considered in this paper are assumed to be of polytopic type. A new structured polynomially parameter-dependent method is utilized, which is based on homogeneous polynomially parameter-dependent matrices of arbitrary degree. The proposed method includes results in the quadratic framework and the linearly parameter-dependent framework as special cases for zeroth degree and first degree, respectively. A numerical example illustrates the feasibility and advantage of the proposed filter design methods.

- by Xiangyu Meng
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- Robustness, Filtering, Multidimensional Systems
- by James Kennedy
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- Information Systems, Evolutionary Computation, Genetic Algorithms, Convergence
- by Samuel Kaski
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- Data Analysis, Computer Networks, Principal Component Analysis, Pattern Recognition
- by Björn Ottersten
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- Signal Processing, Sensor Arrays, Parameter estimation, Impulse response
- by Michael V Davidovich
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- Photonic Crystals, Integral Equations, Photonic Crystal, Mathematical Model
- by Marina Mondin
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- Algorithms, Biomedical Engineering, Information Theory, Computational Complexity
- by Gonzalo Arce
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- Physics, Median Filter, Feature Extraction, Theoretical Analysis
- by Henrique Madeira
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- Computational Modeling, Data Analysis, Data Warehousing, Robustness
- by Henrique Madeira
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- Computational Modeling, Data Analysis, Data Warehousing, Robustness
- by H. Zwart
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- Mechanical Engineering, Mathematics, Applied Mathematics, Computer Science
- by Dr. Mukesh D . Patil
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- Robust control, Control system, Magnetic Levitation, Reliability
- by Ivo Dinov
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- Engineering, Algorithms, Artificial Intelligence, Medical Imaging
- by George Barbastathis
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- Biomedical Engineering, Microscopy, Light Scattering, Fluorescence
- by Martin Burtscher
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- Parallel Algorithms, Data Compression, Compression Algorithms, Throughput
- by Richard Kouzes
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- Computer Architecture, Distributed Computing, Physics, Computational Modeling
- by Frank Ramsak
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- Data Mining, Data Warehousing, Hierarchical Clustering, Query processing

In this paper we discuss the development of a parallel software for the numerical simulation of Participating Life Insurance Policies on distributed architectures. The use of stochastic pricing models, together with the request of solutions in a "useful" time, which have to be sufficiently accurate for the financial problem as well, make the financial problem a very computationally intensive one; as a consequence, advanced architectures are mandatory for effective decisional processes. The mathematical models, which describe the considered problems, usually require the evaluation of multidimensional integrals and the solution of Stochastic Differential Equations. The involved integrals are solved by means of Monte Carlo method in conjunction with the Antithetic Variates variance reduction technique, while Differential Equations are approximated via a fully implicit Euler scheme. The parallelization strategy we adopt relies on the parallelization of Monte Carlo algorithm. W...

- by P. Angelis
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- Computer Architecture, Integral Equations, Differential Equations, Monte Carlo Methods
- by James Garrett
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- Information Visualization, Data Analysis, Life Cycle Assessment, Data Visualization

Abstmct-This paper describes the multidimensional nature of usabil-ity (including tradeoffs between dimensions) and stresses the linkage of the concept to the effective use of documentation by a particular group of readers in performing a... more

- by Ronald Guillemette
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- Information Systems, Design, Usability, Documentation
- by Mehmet Orgun
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- Information Systems, Distributed Computing, Relational Database, Logic
- by H. Trentelman
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- Mathematics, Control Theory, Decomposition, Control Systems
- by Liang Du
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- Stability, Nonlinear system, Lower Bound, Upper Bound