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The present study describes the development and validation of a German questionnaire assessing motivation to change in individuals with eating disorders (Stages of Change Questionnaire-Eating Disorders, SOCQ-ED). The SOCQ-ED measures stages of change separately for each eating disorder symptom domain. Psychometric properties were assessed in a sample of N=63 women with Anorexia Nervosa or Bulimia Nervosa. Test-retest reliability ranged from rtt=0.42 to 0.78 (Mdn=0.56), correlations with the University of Rhode Island Change Assessment were between r=0.21 and 0.32 and correlations with measurements of eating pathology ranged from r=0.19 to 0.46. The results provide initial support for the reliability and validity of the SOCQ-ED.
We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.
The energy topic has become increasingly important in architecture: since buildings are big consumers of energy and architects and the public are interested in energy as never before. [Scognamiglio 2008] The Energy Performance of Building Directive (EPBD) [EU 2010] establishes that starting from 31st December 2020 all new buildings have to be Nearly Zero Energy. The main architectural implication for this condition is that if up until now the domain of design was the building itself, now it is the building and possibly other spaces, that have to be conceived for placing the energy generation devices. Photovoltaics (PV) is particularly suited for reaching the (Nearly) Net ZEB status, due to its technical features, the existing knowledge on how to use PV in buildings, and since it is the easiest and most reliable way to get the (Nearly) Net Zero Energy objectives. [Torcellini 2006] A relevant international effort on the subject of the Net Zero Energy Buildings (Net ZEBs) - Net ZEB meaning that the buildings are connected to an energy infrastructure - is ongoing in the International Energy Agency (IEA), joint Solar Heating and Cooling (SHC) Task 40 and Energy Conservation in Buildings and Community Systems (ECBCS) Annex 52, titled “Towards Net Zero Energy Solar Buildings” [IEA 2008a]. The authors of this paper, all participating in the IEA research group, investigate how the use of PV for Net ZEBs can influence the building’s design, taking into account different building typologies (e. g. new ones vs. existing ones, listed buildings, etc.). Similarities and differences between PV and Solar Thermal (ST) are discussed, too. The paper results in defining some architectural issues for using PV in NZEBs design, which implie to re-think the way buildings are designed.
The discipline of engineering secure software and services brings together researchers and practitioners from software, services, and security engineering. This interdisciplinary community is fairly new, it is still not well integrated and is therefore confronted with differing perspectives, processes, methods, tools, vocabularies, and standards. We present a Common Body of Knowledge (CBK) to overcome the aforementioned problems. We capture use cases from research and practice to derive requirements for the CBK. Our CBK collects, integrates, and structures knowledge from the different disciplines based on an ontology that allows one to semantically enrich content to be able to query the CBK. The CBK heavily relies on user participation, making use of the Semantic MediaWiki as a platform to support collaborative writing. The ontology is complemented by a conceptual framework, consisting of concepts to structure the knowledge and to provide access to it, and a means to build a common terminology. We also present organizational factors covering dissemination and quality assurance.