Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

An Introduction to MultiAgent Systems.

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

This chapter introduces the subject of statistical pattern recognition (SPR). It starts by considering how features are defined and emphasizes that the nearest neighbor algorithm achieves error rates comparable with those of an ideal Bayes’ classifier. The concepts of an optimal number of features, representativeness of the training data, and the need to avoid overfitting to the training data are stressed. The chapter shows that methods such as the support vector machine and artificial neural networks are subject to these same training limitations, although each has its advantages. For neural networks, the multilayer perceptron architecture and back-propagation algorithm are described. The chapter distinguishes between supervised and unsupervised learning, demonstrating the advantages of the latter and showing how methods such as clustering and principal components analysis fit into the SPR framework. The chapter also defines the receiver operating characteristic, which allows an optimum balance between false positives and false negatives to be achieved.

Statistical Pattern Recognition

Contactless biometric recognition performed using three-dimensional fingerprint models has the advantages of reducing problems related to the deformations of the skin, dust on the sensor, and spoofing of latent fingerprints. Moreover, the fingerprint area usable for the recognition is wider than the one captured by traditional contact-based acquisition techniques.

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Virtual environment for 3-D synthetic fingerprints

Recent years have seen a growing interest in mission-centric operation of large-scale distributed systems. However, due to their complexity, these systems are prone to failures and vulnerable to a wide range of cyber-attacks. Current solutions focus either on the infrastructure itself or on mission analysis, but fail to consider information about the complex interdependencies existing between system components and mission tasks. In this paper, we take a different approach, and present a solution for deploying mission tasks in a distributed computing environment in a way that minimizes a mission's exposure to vulnerabilities by taking into account available information about vulnerabilities and dependencies. We model the mission deployment problem as a task allocation problem, subject to various dependability constraints. The proposed solution is based on the A* algorithm for searching the solution space, but we also introduce a heuristic to significantly improve the search performance. We validate our approach, and show that our algorithm scales linearly with the size of both missions and networks.

/pdf/reliable-mission-deployment-in-vulnerable-distributed-e0jh6i19r4.pdf

Reliable mission deployment in vulnerable distributed systems

IPSec is a suite of protocols that adds security to communications at the IP level. Protocols within the IPSec suite make extensive use of cryptographic algorithms. Since these algorithms are computationally very intensive, some hardware acceleration is needed to support high throughput. In this paper we discuss a scheduling algorithm for distributing IPSec packet processing over the CPU with a software implementation of the cryptographic algorithms considered and multiple cryptographic accelerators. This algorithm also provides support for quality of service. High-level simulations and the related results are provided to show the properties of the algorithm. Some architectural improvements suitable to better exploit this scheduling algorithm are also presented

A QoS-enabled packet scheduling algorithm for IPSec multi-accelerator based systems

The detection of latent fingerprints can be a great aid in determining the authenticity of ancient artworks. In fact, a commonly used technique for the authentication of artworks consists in the comparison of fingerprints present on the surface of an artifact with other available latent fingerprints of an artist. This kind of analysis is particularly important for the authentication of clay artifacts. The clay, in fact, is often modeled barehanded, causing a great number of fingerprints left on the surface. In many cases, the artworks are very valuable or fragile and the latent fingerprints cannot be acquired using classical forensic methods. For this reason, contactless acquisition techniques have been proposed. Most of these techniques are based on the use of a single camera. In single-view acquisition systems, however, it can be difficult to properly estimate the size of the captured area, the obtained images can suffer from problems related to perspective distortions, and a calibration task cannot be performed in all the cases. In this paper, we propose a two-view acquisition system able to capture the latent fingerprints left on a clay artwork, and to compute their three-dimensional metric reconstruction. The obtained results show that the proposed approach is feasible and the reconstructed models provide a metric, view-independent, and less-distorted reconstruction of the fingerprint. In particular, we describe the application of the proposed method on a specific clay artwork associated by experts to the famous sculptor Antonio Canova (Italy, 1757–1822).

/pdf/two-view-contactless-fingerprint-acquisition-systems-a-case-2yj4yuslz7.pdf

Two-view contactless fingerprint acquisition systems: A case study for clay artworks

We describe a complex optimization problem related to the COSMO-SkyMed project for the observation of the Earth surface through a constellation of satellites equipped with Synthetic Aperture Radar instruments. We describe the optimization problem and we present some algorithms we have tested.

/pdf/an-optimization-approach-to-the-planning-of-earth-observing-7wlcpyz8ec.pdf

Vincenzo Piuri

Papers

Virtual environment for 3-D synthetic fingerprints

Reliable mission deployment in vulnerable distributed systems

A QoS-enabled packet scheduling algorithm for IPSec multi-accelerator based systems

Two-view contactless fingerprint acquisition systems: A case study for clay artworks

An optimization approach to the planning of Earth observing satellites