Rights management technologies: A good choice for securing electronic healthrecords?

Advances in healthcare IT bring new concerns with respect to privacy and security. Security critical patient data no longer resides on mainframes physically isolated within an organization, where physical security measures can be taken to defend the data and the system. Modern solutions are heading towards open, interconnected environments where storage outsourcing and operations on untrusted servers happen frequently. In order to allow secure sharing of health records between different healthcare providers, Rights Management Techniques facilitating a datacentric protection model can be employed: data is cryptographically protected and allowed to be outsourced or even freely float on the network. Rather than relying on different networks to provide confidentiality, integrity and authenticity, data is protected at the end points of the communication. In this paper we compare Enterprise/Digital Rights Management with traditional security techniques and discuss how Rights Management can be applied to secure Electronic Health Records

Experimental verification of mathematical model of the heat transfer in exhaust system

A catalyst convertor has maximal efficiency when it reaches working tempera-ture. In a cold start phase efficiency of the catalyst is low and exhaust emissions have high level of air pollutants. The exhaust system optimization, in order to de-crease time of achievement of the catalyst working temperature, caused reduction of the total vehicle emission. Implementation of mathematical models in devel-opment of exhaust systems decrease total costs and reduce time. Mathematical model has to be experimentally verified and calibrated, in order to be useful in the optimization process. Measurement installations have been developed and used for verification of the mathematical model of unsteady heat transfer in ex-haust systems. Comparisons between experimental results and the mathematical model are presented in this paper. Based on obtained results, it can be concluded that there is a good agreement between the model and the experimental results

An automatic visual analysis system for tennis

This article presents a novel video analysis system for coaching tennis players of all levels, which uses computer vision algorithms to automatically edit and index tennis videos into meaningful annotations. Existing tennis coaching software lacks the ability to automatically index a tennis match into key events, and therefore, a coach who uses existing software is burdened with time-consuming manual video editing. This work aims to explore the effectiveness of a system to automatically detect tennis events. A secondary aim of this work is to explore the bene- fits coaches experience in using an event retrieval system to retrieve the automatically indexed events. It was found that automatic event detection can significantly improve the experience of using video feedback as part of an instructional coaching session. In addition to the automatic detection of key tennis events, player and ball movements are automati- cally tracked throughout an entire match and this wealth of data allows users to find interesting patterns in play. Player and ball movement information are integrated with the automatically detected tennis events, and coaches can query the data to retrieve relevant key points during a match or analyse player patterns that need attention. This coaching software system allows coaches to build advanced queries, which cannot be facilitated with existing video coaching solutions, without tedious manual indexing. This article proves that the event detection algorithms in this work can detect the main events in tennis with an average precision and recall of 0.84 and 0.86, respectively, and can typically eliminate man- ual indexing of key tennis events