Applications of the Sufficiency Principle in Acceleration of Neural Networks Trainig

One of the problems in AI tasks solving by neurocomputing methods is a considerable training time. This problem especially appears when it is needed to reach high quality in forecast reliability or pattern recognition. Some formalised ways for increasing of networks’ training speed without loosing of precision are proposed here. The offered approaches are based on the Sufficiency Principle, which is formal representation of the aim of a concrete task and conditions (limitations) of their solving [1]. This is development of the concept that includes the formal aims’ description to the context of such AI tasks as classification, pattern recognition, estimation etc.

Models, Techniques and Applications of e-Learning Personalization

In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning implementation, which are used in some contemporary web-interfaced Learning Management Systems (LMSs). The problem is not how to create electronic learning materials, but how to locate and utilize the available information in personalized way. Different attitudes to personalization are briefly described in section 1. The real personalization requires a user profile containing information about preferences, aims, and educational history to be stored and used by the system. These issues are considered in section 2. A method for development and design of adaptive learning content in terms of learning strategy system support is represented in section 3. Section 4 includes a set of innovative personalization services that are suggested by several very important research projects (SeLeNe project, ELENA project, etc.) dated from the last few years. This section also describes a model for role- and competency-based learning customization that uses Web Services approach. The last part presents how personalization techniques are implemented in Learning Grid-driven applications.

Some Applications of Simons’ Inequality

We survey several applications of Simons’ inequality and state related open problems. We show that if a Banach space X has a strongly sub-differentiable norm, then every bounded weakly closed subset of X is an intersection of finite union of balls.

Applications of Radial Basis Neural Networks for Area Forest

This paper proposes a new method using radial basis neural networks in order to find the classification and the recognition of trees species for forest inventories. This method computes the wood volume using a set of data easily obtained. The results that are obtained improve the used classic and statistical models.

Applications of Nonclassical Logic Methods for Purposes of Knowledge Discovery and Data Mining

* The work is partially supported by Grant no. NIP917 of the Ministry of Science and Education – Republic of Bulgaria.

Applications of the Owa-Srivastava Operator to the Class of K-Uniformly Convex Functions

2000 Mathematics Subject Classification: Primary 30C45, 26A33; Secondary 33C15

Some Applications of the Graphic Method

There are discussed three groups of problems which are solved with the help of the graphic method.

Applications of Subordination Principle to Log-Harmonic Mappings

MSC 2010: 30C45, 30C55

Applications of the Fréchet subdifferential

2000 Mathematics Subject Classification: 46A30, 54C60, 90C26.

Access to Digital Cultural Heritage: Innovative Applications of Automated Metadata Generation

Access to Digital Cultural Heritage: Innovative Applications of Automated Metadata Generation Edited by: Krassimira Ivanova, Milena Dobreva, Peter Stanchev, George Totkov Authors (in order of appearance): Krassimira Ivanova, Peter Stanchev, George Totkov, Kalina Sotirova, Juliana Peneva, Stanislav Ivanov, Rositza Doneva, Emil Hadjikolev, George Vragov, Elena Somova, Evgenia Velikova, Iliya Mitov, Koen Vanhoof, Benoit Depaire, Dimitar Blagoev Reviewer: Prof., Dr. Avram Eskenazi Published by: Plovdiv University Publishing House "Paisii Hilendarski" ISBN: 978-954-423-722-6 2012, Plovdiv, Bulgaria First Edition

Business Modeling of the Application Architecture of the Bulgarian Folklore Artery

In an attempt to answer the need of wider accessibility and popularization of the treasury of Bulgarian folklore, a team from the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences has planned to develop the Bulgarian folklore artery within the national project ―Knowledge Technologies for Creation of Digital Presentation and Significant Repositories of Folklore Heritage‖. This paper presents the process of business modeling of the application architecture of the Bulgarian folklore artery, which aids requirements analysis, application design and its software implementation. The folklore domain process model is made in the context of the target social applications—e-learning, virtual expositions of folklore artifacts, research, news, cultural/ethno-tourism, etc. The basic processes are analyzed and modeled and some inferences are made for the use cases and requirements specification of the Bulgarian folklore artery application. As a conclusion the application architecture of the Bulgarian folklore artery is presented.

Social - Oriented Applications of the Folklore Heritage for the Needs of the Non-formal Learning and Cultural Tourisms

The report presents a description of the most popular digital folklore archives in the world. Specifications for designing and developing web-based social-oriented applications in the field of education and cultural tourism are formulated on the basis of comparative analysis. A project for structuring and categorizing the content is presented. A website for accessing the digital folklore archive is designed and implemented.