31 Slices
Medium 9781601323231

Structural and Percolation Models of Intelligence

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

109

Structural and Percolation Models of Intelligence

Dmitry Zhukov1, Irina Samoylo 2, James William Brooks 3 and Victoria Hodges4

Professor, Head of the Department of Regional Systems of Education Quality Management, Institute of

Higher Education Quality, National University of Sciences and Technology (NUST "MISiS"), Moscow,

Russia

2

Professor, Department of Medical and Biological Physics, I.M. Sechenov First Moscow State Medical

University, Moscow, Russia

3

Consultant, Salem International University, Salem, West Virginia, USA

4

Consultant , Department of Medical and Biological Physics, I.M. Sechenov First Moscow State Medical

University, Moscow, Russia

1

Abstract - This paper discusses the questions of the application of Percolation Theory with the purpose of estimating the number of neuronal synaptic connections sufficient for a productive intellectual activity. The use of the percolation approach in the description of human intellectual activity can be practically useful for solving problems of the creation of effective models of artificial neural networks, as well as for the development of sensitive methods for diagnostics of neural networks of the brain in autism and hyperactivity, and for the development of information security systems.

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Medium 9781601323231

Faces Recognition with Image Feature Weights and Least Mean Square Learning Approach

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

21

Faces Recognition with Image Feature Weights and Least Mean Square

Learning Approach

Wei-Li Fang, Ying-Kuei Yang and Jung-Kuei Pan

Dept. of Electrical Engineering, National Taiwan Uni. of Sci. & Technology, Taipei, Taiwan

Email: yingkyang@yahoo.com

Abstract - Most of 2DPCA-enhanced approaches improve face recognition rate while at the expense of computation load.

In this paper, an approach is proposed to greatly improve face recognition rate with slightly increased computation load.

In this approach, the 2DPCA is applied against a face image to extract important image features for selection. A weight is then assigned to each of selected image features according to the feature’s importance to face recognition. The least mean square (LMS) algorithm is further applied to optimize the feature weights based on the recognition error rate during learning process in order to improve face recognition performance. The experiments have been conducted against

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Medium 9781601323231

Session - Knowledge and Information Visualization + Imaging Science and Applications

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF
Medium 9781601323231

Session - Information and Knowledge Engineering and Management + Feature Extraction and AI

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF
Medium 9781601323231

Bookmarking and Tagging Patterns in Social Bookmarking Systems

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

55

Bookmarking and Tagging Patterns in Social

Bookmarking Systems

Alawya Alawami1

School of information Science, University Of Pittsburgh, Pittsburgh, PA,USA

Abstract - Social bookmarking systems are a promising tool for classifying web resources. To be able to use such systems intelligently, it is important to understand how they work.

This study takes a look at one such system to examine tagging and bookmarking patterns. The existing literature tends to view these patterns somewhat simplistically. We specifically examine three questions: (1) at what rate do bookmarks accumulate? (2) To what extent do early tags influence later tagging behavior? (3) How do the top 10 tags evolve? Given the influence of the literature on the direction of future research on social bookmarking systems, a more careful analysis may be of use.

Keywords: Tagging patterns, Social Bookmarking Systems,

Tagging behavior.

1

Introduction

With the development of the social web, many interesting tools that focus on the social interaction and collaboration between users have appeared including

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