Abstract
Background. To analyze the relationship of objective and subjective evaluation tools of breast aesthetics, we compare the results of the BCCT.core (breast cancer conservative treatment.cosmetic results) software, a semiautomated objective symmetry evaluation tool, with those of the Aesthetic Status of the BCTOS (Breast Cancer Treatment Outcome Scale) patient questionnaire. Materials and Methods. We included 128 patients with one-sided, primary breast cancer, treated conservatively in a prospective, exploratory study in order to assess the inter-rater reliability of the BCCT.core and the agreement between the BCCT.core and the BCTOS preoperatively, shortly and 1 year after surgery. Therefore, we use agreement rates, multiple (mk), and weighted (wk) kappa coefficients as statistical methods. Furthermore, we analyzed patient-, tumor-, and therapy-related variables as possible covariates to explain agreement. Results. The inter-rater reliability for the semiautomated BCCT.core is very good with agreement rates up to 84% (mk = 0.80). The agreement rates of the BCCT.core and the BCTOS Aesthetic Status range between 35 and 44% subject to the different times of assessment (wk = 0.34 at best). Moreover, the patients judge their aesthetic outcome more positively than the software. None of the considered patient-, tumor-, and therapy-related covariates turned out to explain agreement. Conclusion. The BCCT.core is a reliable instrument that shows fair agreement with patient's perspective.

Abstract
We propose a technical solution that enables 3D video-based in-bore movement quantification to be acquired synchronously with the BOLD function magnetic resonance imaging (fMRI) sequences. Our solution relies on in-bore video setup with 2 cameras mounted in a 90 degrees angle that allows tracking movments while acquiring fMRI sequences. In this study we show that using 3D motion quantification of a simple finger opposition paradigm we were able to map two different finger positions to two different BOLD response patterns in a typical block design protocol. The motion information was also used to adjust the block design to the actual motion start and stop improving the time accuracy of the analysis. These results reinforce the role of video based motion quantification in fMRI analysis as an independent regressor that allows new findings not discernable when using traditional block designs.

Abstract

Abstract
Computer networks are highly dynamic environments in which the meaning of normal and anomalous behaviours can drift considerably throughout time. Behaviour-based Network Intrusion Detection System (NIDS) have thus to cope with the temporal normality drift intrinsic on computer networks, by tuning adaptively its level of response, in order to be able to distinguish harmful from harmless network traffic flows. In this paper we put forward the intrinsic Tunable Activation Threshold (TAT) theory ability to adaptively tolerate normal drifting network traffic flows. This is embodied on the TAT-NIDS, a TAT-based Artificial Immune System (AIS) we have developed for network intrusion detection. We describe the generic AIS framework we have developed to assemble TAT-NIDS and present the results obtained thus far on processing real network traffic data sets. We also compare the performance obtained by TAT-NIDS with the well known and widely deployed signature-based snort network intrusion detection system. © 2011 Springer-Verlag.

Abstract
This paper proposes technical solutions that can be implemented in variable speed permanent magnet synchronous generators driven wind turbine systems aiming to mitigate high voltage problems in low voltage MicroGrids by controlling the active power output. Due to the limited control capability of these systems, controlling the output power to prevent voltage rise will require the local accommodation of the generation surplus. For this purpose, additional control functionalities are developed to be integrated in the control systems of the power electronic based interfaces. Their performance is evaluated through numerical simulations performed in Matlab (R)/Simulink (R) environment and considering the detailed models of the power electronic converters. The results obtained demonstrate the effectiveness of the proposed control functionalities.

Abstract
Accurate localization techniques have long been of major importance for safety systems and a lot of research has been conducted in the distributed computing field regarding its functionality and reliability. In the specific scenario of long yet narrow tunnels existing at CERN, localization methods will enable a number of applications and processes to substantially reduce human intervention. In this paper we evaluate the use of Fingerprinting techniques with GSM signal available throughout the LHC tunnel via a radiating cable and compare some methods to estimate the location. The existing GSM infrastructure and tunnel conditions seem to be favorable to the adoption of these Fingerprinting methods. Nevertheless significant variations in the signal have been observed which might be traced back to different operational states of accelerator equipment. These effects and their sources will be analyzed in more detail in order to improve the applied techniques and their accuracy under such challenging conditions.