On model compatibility with referees and contexts

A model-based engineering discipline presupposes that models are organised by creating relationships between them. While there has been considerable work on understanding what it means to instantiate one model from another, little is known about when a model should be considered to be a specialisation of another one. This article motivates and discusses ways of defining specialisation relationships between models, languages, and transformations respectively. Consideration is given to both structural and behavioural compatibility concerns. Several alternatives of defining a specialisation relationship are considered and discussed. The article furthermore discusses the notions of referee and context in order to validate and define specialisation relationships. The ideas and discussions presented in this article are meant to provide a further stepping stone towards a systematic basis for organising models.     

Integrated SMD pressure/flow/temperature multisensor for compressed air in LTCC technology: Thermal flow and temperature sensing

In this work, we present and analyse the flow-sensing part of a recently-developed multisensor in LTCC (low-temperature co-fired ceramic) technology; this device integrates flow/pressure/temperature sensing and is designed for diagnostics monitoring of standard industrial compressed air circuits and devices such as valves and actuators. In this prototype, flow is sensed using the constant-temperature anemometric principle, with temperature-sensing active and reference thermistors placed in the fluidic channel integrated within the LTCC structure. The LTCC bridge structuration technology and electronics are analysed, and possible improvements in fabrication yield and efficiency outlined.     

Thermally Stable, Latent Olefin Metathesis Catalysts

Highly thermally stable N-aryl,N-alkyl N-heterocyclic carbene (NHC) ruthenium catalysts were designed and synthesized for latent olefin metathesis. These catalysts showed excellent latent behavior toward metathesis reactions, whereby the complexes were inactive at ambient temperature and initiated at elevated temperatures, a challenging property to achieve with second generation catalysts. A sterically hindered N-tert-butyl substituent on the NHC ligand of the ruthenium complex was found to induce latent behavior toward cross-metathesis reactions, and exchange of the chloride ligands for iodide ligands was necessary to attain latent behavior during ring-opening metathesis polymerization (ROMP). Iodide-based catalysts showed no reactivity toward ROMP of norbornene-derived monomers at 25 °C, and upon heating to 85 °C gave complete conversion of monomer to polymer in less than 2 hours. All of the complexes were very stable to air, moisture, and elevated temperatures up to at least 90 °C, and exhibited a long catalyst lifetime in solution at elevated temperatures.     

功率模块的封装和“一体化”封装——一针对可再生能源和电动交通工具

风力发电和电动汽车需要具有高功率密度的功率模块。文章介绍了满足这些领域要求的功率模块的封装技术。     

Discerning nonstationarity from nonlinearity in seizure-free and preseizure EEG recordings from epilepsy patients

A number of recent studies indicate that nonlinear electroencephalogram (EEG) analyses allow to define a state predictive of an impending epileptic seizure. In this paper, we combine a method for detecting nonlinear determinism with a novel test for stationarity to characterize EEG recordings from both the seizure-free interval and the preseizure phase. We discuss differences between these periods, particularly an increased occurrence of stationary, nonlinear segments prior to seizures. These differences seem most prominent for recording sites within the seizure-generating area and for EEG segments less than one minute's length.     

Image classification using correlation tensor analysis

Images, as high-dimensional data, usually embody large variabilities. To classify images for versatile applications, an effective algorithm is necessarily designed by systematically considering the data structure, similarity metric, discriminant subspace, and classifier. In this paper, we provide evidence that, besides the Fisher criterion, graph embedding, and tensorization used in many existing methods, the correlation-based similarity metric embodied in supervised multilinear discriminant subspace learning can additionally improve the classification performance. In particular, a novel discriminant subspace learning algorithm, called correlation tensor analysis (CTA), is designed to incorporate both graph-embedded correlational mapping and discriminant analysis in a Fisher type of learning manner. The correlation metric can estimate intrinsic angles and distances for the locally isometric embedding, which can deal with the case when Euclidean metric is incapable of capturing the intrinsic similarities between data points. CTA learns multiple interrelated subspaces to obtain a low-dimensional data representation reflecting both class label information and intrinsic geometric structure of the data distribution. Extensive comparisons with most popular subspace learning methods on face recognition evaluation demonstrate the effectiveness and superiority of CTA. Parameter analysis also reveals its robustness.     

B-spline explicit active surfaces: an efficient framework for real-time 3-D region-based segmentation

A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also show that this framework allows evolving the active contour using local region-based terms, thereby overcoming the limitations of the original method while preserving computational speed. The feasibility of real-time 3-D segmentation is demonstrated using simulated and medical data such as liver computer tomography and cardiac ultrasound images.