Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan

Knowledge Sharing in Emerging Economies

One of the new factors in Eastern European countries (and there is an acknowledgement that this aspect is inherent in other countries too) is this concept of freely sharing information i.e. the concept of what is known in KM literature of “Knowledge Sharing”. Sharing only takes place where there is trust and where there is a shared feeling of ownership of goals. The reasons behind the tendency to share are based on the kind of interpersonal relations between co- workers inherent within the organization and the effects of social relationships within organizational teams. Strengthening the social relationships between individuals in the team is crucial in motivating team members to share knowledge. New research is currently investigating the concept of “sharing social relationships” and one of the aims of the project is to investigate the barriers to sharing information in a particular type of business - that of the small to medium sized enterprises (the SME) in order to form a comparative study. The results of the study will be used to from a model of “information sharing best practice” for SME who are setting up or using KM systems. The work will examine the barriers to sharing in two newly emerging economies (Poland and Hungary) and one relatively established economy (the UK). At the time of writing the work with Poland and Hungary has been completed and this paper gives the initial results from the Hungarian study

Benchmarking High Performance Architectures With Natural Language Processing Algorithms

Natural Language Processing algorithms are resource demanding, especially when tuning toinflective language like Polish is needed. The paper presents time and memory requirementsof part of speech tagging and clustering algorithms applied to two corpora of the Polishlanguage. The algorithms are benchmarked on three high performance platforms of differentarchitectures. Additionally sequential versions and OpenMP implementations of clusteringalgorithms were compared

Highly Sensitive and Selective VOC Sensor Systems Based on Semiconductor Gas Sensors: How to?

Monitoring of volatile organic compounds (VOCs) is of increasing importance in many application fields such as environmental monitoring, indoor air quality, industrial safety, fire detection, and health applications. The challenges in all of these applications are the wide variety and low concentrations of target molecules combined with the complex matrix containing many inorganic and organic interferents. This paper will give an overview over the application fields and address the requirements, pitfalls, and possible solutions for using low-cost sensor systems for VOC monitoring. The focus lies on highly sensitive metal oxide semiconductor gas sensors, which show very high sensitivity, but normally lack selectivity required for targeting relevant VOC monitoring applications. In addition to providing an overview of methods to increase the selectivity, especially virtual multisensors achieved with dynamic operation, and boost the sensitivity further via novel pro-concentrator concepts, we will also address the requirement for high-performance gas test systems, advanced solutions for operating and read-out electronic, and, finally, a cost-efficient factory and on-site calibration. The various methods will be primarily discussed in the context of requirements for monitoring of indoor air quality, but can equally be applied for environmental monitoring and other fields

Robust and cost-effective approach for discovering action rules

The main goal of Knowledge Discovery in Databases is to find interesting and usable patterns, meaningful in their domain. Actionable Knowledge Discovery came to existence as a direct respond to the need of finding more usable patterns called actionable patterns. Traditional data mining and algorithms are often confined to deliver frequent patterns and come short for suggesting how to make these patterns actionable. In this scenario the users are expected to act. However, the users are not advised about what to do with delivered patterns in order to make them usable. In this paper, we present an automated approach to focus on not only creating rules but also making the discovered rules actionable. Up to now few works have been reported in this field which lacking incomprehensibility to the user, overlooking the cost and not providing rule generality. Here we attempt to present a method to resolving these issues. In this paper CEARDM method is proposed to discover cost-effective action rules from data. These rules offer some cost-effective changes to transferring low profitable instances to higher profitable ones. We also propose an idea for improving in CEARDM method