Modular Digital Watermarking for Image Verification and Secure Data Storage in Web Applications

Our modular approach to data hiding is an innovative concept in the data hiding research field. It enables the creation of modular digital watermarking methods that have extendable features and are designed for use in web applications. The methods consist of two types of modules – a basic module and an application-specific module. The basic module mainly provides features which are connected with the specific image format. As JPEG is a preferred image format on the Internet, we have put a focus on the achievement of a robust and error-free embedding and retrieval of the embedded data in JPEG images. The application-specific modules are adaptable to user requirements in the concrete web application. The experimental results of the modular data watermarking are very promising. They indicate excellent image quality, satisfactory size of the embedded data and perfect robustness against JPEG transformations with prespecified compression ratios. ACM Computing Classification System (1998): C.2.0.

Data Independence in the Multi-dimensional Numbered Information Spaces

The concept of data independence designates the techniques that allow data to be changed without affecting the applications that process it. The different structures of the information bases require corresponded tools for supporting data independence. A kind of information bases (the Multi-dimensional Numbered Information Spaces) are pointed in the paper. The data independence in such information bases is discussed.

File Format for Storage of Multimedia Information

AMS Subj. Classification: 68U05, 68P30

OpenAIREplus

Directions the outcomes of the OpenAIRE project, which implements the EC Open Access (OA) pilot. Capitalizing on the OpenAIRE infrastructure, built for managing FP7 and ERC funded articles, and the associated supporting mechanism of the European Helpdesk System, OpenAIREplus will “develop an open access, participatory infrastructure for scientific information”. It will significantly expand its base of harvested publications to also include all OA publications indexed by the DRIVER infrastructure (more than 270 validated institutional repositories) and any other repository containing “peer-reviewed literature” that complies with certain standards. It will also generically harvest and index the metadata of scientific datasets in selected diverse OA thematic data repositories. It will support the concept of linked publications by deploying novel services for “linking peer- reviewed literature and associated data sets and collections”, from link discovery based on diverse forms of mining (textual, usage, etc.), to storage, visual representation, and on-line exploration. It will offer both user-level services to experts and “non-scientists” alike as well as programming interfaces for “providers of value-added services” to build applications on its content. Deposited articles and data will be openly accessible through an enhanced version of the OpenAIRE portal, together with any available relevant information on associated project funding and usage statistics. OpenAIREplus will retain its European footprint, engaging people and scientific repositories in almost all 27 EU member states and beyond. The technical work will be complemented by a suite of studies and associated research efforts that will partly proceed in collaboration with “different European initiatives” and investigate issues of “intellectual property rights, efficient financing models, and standards”.

Establishing Correspondences between Attribute Spaces and Complex Concept Spaces Using Meta-PGN Classifier

In this paper, we present one approach for extending the learning set of a classification algorithm with additional metadata. It is used as a base for giving appropriate names to found regularities. The analysis of correspondence between connections established in the attribute space and existing links between concepts can be used as a test for creation of an adequate model of the observed world. Meta-PGN classifier is suggested as a possible tool for establishing these connections. Applying this approach in the field of content-based image retrieval of art paintings provides a tool for extracting specific feature combinations, which represent different sides of artists' styles, periods and movements.

Teaching Statistics to Engineers: Learning from Experiential Data

The purpose of the work is to claim that engineers can be motivated to study statistical concepts by using the applications in their experience connected with Statistical ideas. The main idea is to choose a data from the manufacturing factility (for example, output from CMM machine) and explain that even if the parts used do not meet exact specifications they are used in production. By graphing the data one can show that the error is random but follows a distribution, that is, there is regularily in the data in statistical sense. As the error distribution is continuous, we advocate that the concept of randomness be introducted starting with continuous random variables with probabilities connected with areas under the density. The discrete random variables are then introduced in terms of decision connected with size of the errors before generalizing to abstract concept of probability. Using software, they can then be motivated to study statistical analysis of the data they encounter and the use of this analysis to make engineering and management decisions.