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The safety-critical Java (SCJ) specification provides a restricted set of the Java language intended for applications that require certification. In order to test the specification, implementations are emerging and the need to evaluate those implementations in a systematic way is becoming important. In this paper we evaluate our SCJ implementation which is based on the Java Optimized Processor JOP and we measure different performance and timeliness criteria relevant to hard real-time systems. Our implementation targets Level 0 and Level1 of the specification and to test it we use a series of micro benchmarks, an application-based benchmark, and a reduced set of a SCJ technology compatibility kit. We evaluate the accuracy of periods, linear-time memory allocation, aperiodicevent handling, dispatch latency for interrupts, context switch preemption latency, and synchronization.

In this paper an experimental X-band radar system, called DTU-VISDAM, developed for the detection and monitoring of human vital signs is described. The DTU-VISDAM radar exploits a low intermediate frequency (IF) heterodyne RF front-end architecture and single-sideband (SSB) transmission for easier and more reliable extraction of the vital signs. The hardware implementation of the proposed low-IF RF front-end architecture and associated IF circuitry is discussed. Furthermore, the signal processing and calibration steps necessary to extract the vital signs information measured on a human subject are described.

In this paper we describe an experimental investigation into the significance of different facial parts in the task of age estimation. For this purpose we use an automatic age estimation algorithm capable of producing an estimate of the age of a subject based on his/her face image. We perform automatic age estimation experiments using different facial parts of varying resolution so that the significance of facial parts in this application can be assessed. According to the results obtained, the internal part of the face and in particular the area around the eyes proved to be the most significant for the task of automatic age estimation.