Components for Algebra Transformation Systems

In this paper we study the instantiation of the generic notion of component introduced before in terms of algebra transformation systems, where refinements are defined by means of high-level replacement rules. With this work we follow two aims. On one hand we show that our generic component concept is not purely syntactic, but it may take into account the semantics of the specifications involved. On the other hand, with this instantiation we strengthen the role of our component concept in the study of component-based heterogeneous systems.     

A Conceptual and Formal Framework for the Integration of Data Type and Process Modeling Techniques

A conceptual framework for the integration of data type and process modeling techniques, called integration paradigm, has been presented by the authors in previous papers already. The aim of this paper is to give a short review of this conceptual framework and to present a formal model for the integration paradigm. The formal model for the four layers, called data type, data states and transformations, processes and system architecture layers respectively, is based on an integration of abstract data types and structured transition systems. This formal model can be instantiated by all kinds of basic and integrated modeling techniques. Algebraic high-level nets, attributed graph transformation, an integration of Z with statecharts, and some diagram techniques of UML are discussed on the conceptual level. As instantiation of the formal model, a well-known CCS sender specification, place/transition nets, algebraic high-level nets and attributed graph transformation are presented in this paper, while instantiations of other modeling techniques will be discussed elsewhere.     

Automated sleep stage identification system based on time-frequency analysis of a single EEG channel and random forest classifier

In this work, an efficient automated new approach for sleep stage identification based on the new standard of the American academy of sleep medicine (AASM) is presented. The propose approach employs time-frequency analysis and entropy measures for feature extraction from a single electroencephalograph (EEG) channel. Three time-frequency techniques were deployed for the analysis of the EEG signal: Choi-Williams distribution (CWD), continuous wavelet transform (CWT), and Hilbert-Huang Transform (HHT). Polysomnographic recordings from sixteen subjects were used in this study and features were extracted from the time-frequency representation of the EEG signal using Renyi's entropy. The classification of the extracted features was done using random forest classifier. The performance of the new approach was tested by evaluating the accuracy and the kappa coefficient for the three time-frequency distributions: CWD, CWT, and HHT. The CWT time-frequency distribution outperformed the other two distributions and showed excellent performance with an accuracy of 0.83 and a kappa coefficient of 0.76.     

Phase Composition, Oxygen Content, and Thermal Conductivity of AIN(Y2O3) Ceramics

An indirect method to determine the oxygen dissolved in AIN is devised for AIN(Y₂O₃) ceramics and then related to thermal conductivity. Dissolved oxygen is determined by first constructing the AIN-rich corner of the AIN—Y₂O₃—Al₂O₃ phase diagram (isothermal section). This is achieved by (1) measuring the total oxygen content and subtracting from it the oxygen in the Y₂O₃, resulting in a virtual alumina content; (2) placing the sample composition on the diagram; (3) determining the phases present by XRD for each sample; and (4) drawing phase boundaries which best agree with the phases present. The intersection of these tie lines through the sample location with the AIN—Al₂O₃ axis then gives the particular Al₂O₃ oxygen content dissolved in the AIN lattice. For the system AIN—Y₂O₃—Al₂O₃, it is shown that it is indeed this fraction of the total oxygen content that has a decisive limiting influence on thermal conductivity of dense, polyphase AIN ceramics.     

Mullite with Lattice Constants a > b

The mullite phase was synthesized in a sol–gel process using aluminum sec -butylate and silicon chloride in proportions corresponding to an Al/Si ratio of 4:1. Heat treatment at 1000°C yielded a mullite-type phase, γ-alumina, and amorphous fractions. Conventional indexing based on the orthorhombic ( Pbam ) mullite unit cell with b > a showed that X-ray diffraction peaks with high k and l but low h indices are strongly shifted toward higher d -spacings as compared with a "normal" mullite. Furthermore, the relative positions of reflection pairs hkl and khl are interchanged. The Rietveld analysis yielded the following constants: a = 7.760(2) Å, b = 7.595(2) Å, c = 2.9192(4) Å confirming a > b .     

Consistent integration of models based on views of meta models

The complexity of large system models in software engineering nowadays is mastered by using different views. View-based modelling aims at creating small, partial models, each one of them describing some aspect of the system. Existing formal techniques supporting view-based visual modelling are based on typed attributed graphs, where views are related by typed attributed graph morphisms. Such morphisms up to now require a meta model given by a fixed type graph, as well as a fixed data signature and domain. This is in general not adequate for view-oriented modeling where only parts of the complete meta model are known and necessary when modelling a partial view of the system. The aim of this paper is to extend the framework of typed attributed graph morphisms to generalized typed attributed graph morphisms, short GAG-morphisms, which involve changes of the type graph, data signature, and domain. This allows the modeller to formulate type hierarchies and views of visual languages defined by GAG-morphisms between type graphs, short GATG-morphisms. In this paper, we study the interaction and integration of views, and the restriction of views along type hierarchies. In the main result, we present suitable conditions for the integration and decomposition of consistent view models (Theorem 4.1) and extend these conditions to view models defined over meta models with constraints (Theorem 5.1). As a running example, we use a visual domain-specific modelling language to model coarse-grained IT components and their connectors in decentralized IT infrastructures. Using constraints, we formulate connection properties as invariants.     

Fabrication of a surface stress-based PDMS micro-membrane biosensor

With the development of technology and society, biosensors are more and more important in the areas of healthcare. Specially, the design and fabrication of perfect biosensors play a crucial role in the whole process. In the paper, a surface stress-based polydimethylsiloxane (PDMS) micro membrane biosensor array has been fabricated based on the surface and bulk microfabrication technology. The challenges in fabrication, such as integration of PDMS processing with conventional microfabrication processes, were successfully mastered to build the biosensor. In addition, the bonding technique, uncured PDMS as the intermediate layer for bonding the biosensor with microfluidic devices or components, has been developed to later construct the BioMEMS. Bond strength is close to that of bulk PDMS. Through the bio-experiments to Escherichia coli (E. coli), the cells can be detected based on the membrane deflection induced by surface stress.     

Liquid-crystalline polyesters with y-shaped mesogens: Phase structure pecularities

Summary Liquid crystalline (LC) main-chain polyesters with y-shaped mesogenic elements have been investigated by X-ray diffraction. The X-ray pattern of the glassy nematic polyester with the largest branching shows besides the reflections in the wide angle range corresponding to the average distance between the molecules also equatorial reflections in the small angle range. This is suggesting a spontaneous formation of microfibrils. X-ray pattern of the polymer above 150 °C points to the existence of a normal nematic phase. The proposed order-disorder model is supported by results of calorimetric measurements and mixing experiments with a low-molecularweight LC-compound.