This paper presents one implementation of tracking system of GPS devices and describes solution for different issues during the design, such as detection of current position, communication to databases and storing the data. Once the warehouse is created the multidimensional data model cube, is produced and OLAP operations are performed in order to obtain different statistics. Mining of spatial data is possible in order to produce predictable data important for decision support. One of the results is identification of congested areas and support for selecting the fastest route. Key-Words: location based services; tracking system; data cube; data mining

This paper presents a model and implementation of applications used as an interactive guide which aims to filter the specified locations of interest that are located near the current device position. Locations of interest are defined by geographic coordinates according to Google Maps standard, and it is possible to display them graphically on a map and to administrate them via web services. The effects of the ownership of these applications by telecom operators are also explored in the paper.

The paper presents utilization of existing aspects of global navigation and global position system (GPS), and visualization of Earth using satellite images, in order to gather and store particular data. The analyzed GPS data are related to the position and tracking of important person, vehicle or device. The described model of developed monitoring application allows more comprehensive and detailed analysis and insight in the traffic congested areas on the map in the specific amount of time, which is achieved by creation and manipulating of multidimensional data model presented in the paper. The paper also describes practical aspects of implemented monitoring center for GPS devices and possible future improvements.

Price decision support systems (PDSS) are crucial for every big retailer in order to be able to decide about product prices in hundreds of stores and thousands of products. In this paper we identify, describe and formalize several price decision support system features that can be used as an input for machine learning algorithms, after that we select the features that can be exploited by potential attackers and discuss/evaluate the security issues of online learning features in adversarial environment PDSS. At the end we propose a kernel learning defense model for the sensitive features.

This paper describes how application of Six Sigma methodology in the area of Continuous Service Improvements can help service provider organization to improve quality of its services and achieve planed goals and objectives. It is shown how DMAIC methodology can be used in the ITIL framework as its complementary discipline. The five steps of DMAIC are applied in the context of Continuous Service Improvement cycle and for each of stages different techniques are used to identify problem, gather right data, convert to useful information, and propose implementation. The rights Key Performance Indicators are identify, and continuously monitored. Clustering of measured data is performed to simplify data analysis and identify possible areas of improvement. The most effective project for improvement was identified and implemented. Key-Words: Service Management, Continuous Service Improvement, Change Management, Affinity Diagrams, Pareto Diagram

Climate data analysis is an active research area, focused on analysis of change of climate conditions, analysis of climate phenomena, analysis of interconnections of climate conditions. Data mining techniques provide better and faster analysis of large amounts of data in climatology. This paper is focused on development of algorithm for climate data analysis using clustering data mining techniques. Developed solution represents climate data from different points of view in order to provide a complete view of the data for researchers from which they can draw their own conclusions and perform detailed climate change analysis. Climate data is represented graphically as a map of measured climate parameters, map of climate clusters identified in specified moment and map of evolution steps identified between consecutive time slices. Key-Words: data mining, clustering, climate, hierarchical clustering, meteorology, evolving clusters

This paper describes one approach of the classification of the speech signals. The initial signals are vowels collected during the speech therapy. Continuous wavelet transformation has been applied on these incorrectly pronounce vowels using Morlet wavelet. Coefficients have been analyzed in the context of three main formants that characterized each of the vowels. The selected coefficients have been classified into main clusters, and have been compared with the one obtained for correct signals. The further improvements have been proposed in order to use results in the daily speech therapy and to automate process.

This paper presents specific approach of the classification of the incorrect speech sounds. Sampled data are vowels gathered during the speech therapy with children that have difficulties to pronounce them correctly. Continuous wavelet transformation has been applied on these incorrectly pronounce vowels using Morlet wavelet. Coefficients have been analyzed in the context of three main formants that characterized each of the vowels. The selected coefficients have been classified into main clusters, and have been compared with the one obtained for correct signals. At the end some improvements have been proposed in order to use results in the daily speech therapy and to automate process. Data that is used in analysis is gathered during the speech therapy with the children of age between 12 and 14 years. Session is supervised by speech therapist that listens and guides patient to pronounce vowels correctly. The process is very time consuming and will benefit from some elements of automation and provision of feedback to patients by the expert system. Sound features of language can be viewed in several ways. The first way is that the signals are grouped in terms of distribution of acoustic energy in the resonant field, which is caused by speech, which is the acoustic side of the problem, and this approach is given in this paper. Another way is to look at the voice signals from the point of hearing and the ability to receive those signals and to implement parts of the brain, in

This paper describes model driven development of dynamic web application using a few different frameworks. Those are the following open source Java frameworks: Modelibra, ModelibraWicket and Wicket. Modelibra is a domain model framework. ModelibraWicket is an application development framework. This web framework uses Modelibra for domain models and Wicket for application views. The domain models are created by ModelibraModeler, design and code generation tool. ModelibraWicket interprets the application model and creates default web application. Web pages of the default web application are created from ModelibraWicket components. Those web components are based on the domain model.

In this paper we present a Recommendation system that uses the Social Network Services like Facebook Connect, OpenSocial etc. to get useful interest and friend interest data as an input for a Trust Clustering - Friends interest clustering applied on the results of a Collaborative filtering algorithm. We also discuss the advantages and disadvantages of Collaborative filtering and Trust based Clustering and how our solution uses the advantages and solves the disadvantages by combining them.

The paper describes a specific problem - the process of damage claim processing in insurance companies that is reported for earlier underwritten risk. During the analysis of this problem the model has been created that can be used in similar cases for the transfer of knowledge and facts from the real system in the information system model. These processes are normatively regulated to a feasible extent. Analysis of the implementation of the proposed model shows that the model may offer beside the transactional level also a component of intelligent systems, namely a component of monitoring activities. This model is based on domain modeling and it can be used in the context of the software product line - SPL because its characteristics fit into the setting of this approach in the development of the system.

This session will describe concept of normatively regulated activities and their basic concept. Normatively regulated activities are characterized by precise objective or purpose, participation of actors as role-holders, and norms and rules that govern the performance of these activities. They are typically found in insurance companies, banks, courts and many public administrations. In order to perform normatively regulated activities efficiently and effectively, actors need proper information and documents, but also have to act in accordance with relevant norms and rules. The performance of activities in accordance with norms and rules makes them normatively or legally correct and vice versa. Therefore, computerized support for this class of activities should also include, besides information processing and dissemination, support for taking actions in accord with applicable norms and rules. The main goal of the software systems in support of normatively regulated activities is increased efficiency and effectiveness, but also increased consistency in interpretation and application of norms and rules, and thus increased legitimacy of their performance. Aspects of the normatively regulated organizational activities and approach to make model of normatively regulated activities, which are bases for building software systems to support their performance, are also described. Some aspects of object view on normatively regulated activities will be described, with particular case of procurement activity and IT service management.

Most of the service providers today have become increasingly dependent on their technology, being organized in terms of strong linkage between IT and business units in order to maximize units' business value. Many companies are performing re-engineering using IT Infrastructure Library (ITIL) framework. In this paper Incident Management process is analyzed in one telecom service provider company. For this specific case formal model is applied. More optimal resources utilization is possible through this model and improvement in process like pro-active approach and simulation of exceptional cases are optional.

In this paper the concept of the measuring service effectiveness focusing on customer-defined quality, continual improvement, employee empowerment, and measurement-based management and feedback is described. Metrics must be developed based on the priorities of the strategic plan, which provides the key business drivers and criteria for metrics. We will define these metrics and relevant information for their evaluation and establishment of measurement criteria. The most difficult part in implementation of this approach is consolidation. Described framework will captures relationship between business and IT service and will identify quantitative technique for establishing baselines and discovering possible losses during deployment of processes.

This paper studied perspectives of Balanced Scorecard and how they can be used to align Service Operation as the part of IT Service Lifecycle with business strategy in a service provider company. An organization framework based on Balanced Scorecard is presented. Objectives and indicators that are linked to the Service Operation processes and functions are identified and they are mapped to the particular performance key indicators and performance management process. The final result is identification of quantitative approach for identification of possible loss caused by poor performance of service management and understanding of complex interdependency between IT services and business processes.