Collaborative Learning and Authoring in the Frame of e-Projects

It is presented a research on the application of a collaborative learning and authoring during all delivery phases of e-learning programmes or e-courses offered by educational institutions. The possibilities for modelling of an e-project as a specific management process based on planned, dynamically changing or accidentally arising sequences of learning activities, is discussed. New approaches for project-based and collaborative learning and authoring are presented. Special types of test questions are introduced which allow test generation and authoring based on learners’ answers accumulated in the frame of given e-course. Experiments are carried out in an e-learning environment, named BEST.

Collaborative Learning and Assessment in e-Learning

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

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.

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.

VLSI Watermark Implementations and Applications

This paper presents an up to date review of digital watermarking (WM) from a VLSI designer point of view. The reader is introduced to basic principles and terms in the field of image watermarking. It goes through a brief survey on WM theory, laying out common classification criterions and discussing important design considerations and trade-offs. Elementary WM properties such as robustness, computational complexity and their influence on image quality are discussed. Common attacks and testing benchmarks are also briefly mentioned. It is shown that WM design must take the intended application into account. The difference between software and hardware implementations is explained through the introduction of a general scheme of a WM system and two examples from previous works. A versatile methodology to aid in a reliable and modular design process is suggested. Relating to mixed-signal VLSI design and testing, the proposed methodology allows an efficient development of a CMOS image sensor with WM capabilities.

Hankel Transform in Quantum Calculus and Applications

Mathematics Subject Classification: 44A15, 33D15, 81Q99

Existence Results for Fractional Functional Differential Inclusions with Infinite Delay and Applications to Control Theory

Mathematics Subject Classification: 26A33, 34A60, 34K40, 93B05

Integral Inequalities and Applications to Partial Differential Equations with “Maxima”

Кремена В. Стефанова - В тази статия са разрешени някои нелинейни интегрални неравенства, които включват максимума на неизвестната функция на две променливи. Разгледаните неравенства представляват обобщения на класическото неравенство на Гронуол-Белман. Значението на тези интегрални неравенства се определя от широките им приложения в качествените изследвания на частните диференциални уравнения с “максимуми” и е илюстрирано чрез някои директни приложения.

Intercultural Learning and Entrepreneurship

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Trends in Digital Cultural Heritage Management and Applications

We present some recent trends in the field of digital cultural heritage management and applications including digital cultural data curation, interoperability, open linked data publishing, crowd sourcing, visualization, platforms for digital cultural heritage, and applications. We present some examples from research and development projects of MUSIC/TUC in those areas.

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham’s razor non-plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.

The Positive Effect of Using the Integral Approach for Improving Quality of Learning and Students' motivation

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

An extension of Lorentz's almost convergence and applications in Banach spaces

2000 Mathematics Subject Classification: Primary 40C99, 46B99.

Dispersion Phenomena in Dunkl-Schrödinger Equation and Applications

2000 Mathematics Subject Classification: 35Q55,42B10.

Local Energy Decay in Even Dimensions for the Wave Equation with a Time-Periodic Non-Trapping Metric and Applications to Strichartz Estimates

2000 Mathematics Subject Classification: 35B40, 35L15.