Qualitative representation of spatial knowledge in two-dimensional space

Various relation-based systems, concerned with the qualitative representation and processing of spatial knowledge, have been developed in numerous application domains. In this article, we identify the common concepts underlying qualitative spatial knowledge representation, we compare the representational properties of the different systems, and we outline the computational tasks involved in relation-based spatial information processing. We also describesymbolic spatial indexes, relation-based structures that combine several ideas in spatial knowledge representation. A symbolic spatial index is an array that preserves only a set of spatial relations among distinct objects in an image, called the modeling space; the index array discards information, such as shape and size of objects, and irrelevant spatial relations. The construction of a symbolic spatial index from an input image can be thought of as a transformation that keeps only a set of representative points needed to define the relations of the modeling space. By keeping the relative arrangements of the representative points in symbolic spatial indexes and discarding all other points, we maintain enough information to answer queries regarding the spatial relations of the modeling space without the need to access the initial image or an object database. Symbolic spatial indexes can be used to solve problems involving route planning, composition of spatial relations, and update operations.     

Management of multidimensional discrete data

Spatial database management involves two main categories of data: vector and raster data. The former has received a lot of in-depth investigation; the latter still lacks a sound framework. Current DBMSs either regard raster data as pure byte sequences where the DBMS has no knowledge about the underlying semantics, or they do not complement array structures with storage mechanisms suitable for huge arrays, or they are designed as specialized systems with sophisticated imaging functionality, but no general database capabilities (e.g., a query language). Many types of array data will require database support in the future, notably 2-D images, audio data and general signal-time series (1-D), animations (3-D), static or time-variant voxel fields (3-D and 4-D), and the ISO/IEC PIKS (Programmer's Imaging Kernel System) BasicImage type (5-D). In this article, we propose a comprehensive support ofmultidimensional discrete data (MDD) in databases, including operations on arrays of arbitrary size over arbitrary data types. A set of requirements is developed, a small set of language constructs is proposed (based on a formal algebraic semantics), and a novel MDD architecture is outlined to provide the basis for efficient MDD query evaluation.     

A semantic modeling approach for image retrieval by content

We introduce a semantic data model to capture the hierarchical, spatial, temporal, and evolutionary semantics of images in pictorial databases. This model mimics the user's conceptual view of the image content, providing the framework and guidelines for preprocessing to extract image features. Based on the model constructs, a spatial evolutionary query language (SEQL), which provides direct image object manipulation capabilities, is presented. With semantic information captured in the model, spatial evolutionary queries are answered efficiently. Using an object-oriented platform, a prototype medical-image management system was implemented at UCLA to demonstrate the feasibility of the proposed approach.     

The aditi deductive database system

Deductive databases generalize relational databases by providing support for recursive views and non-atomic data. Aditi is a deductive system based on the client-server model; it is inherently multi-user and capable of exploiting parallelism on shared-memory multiprocessors. The back-end uses relational technology for efficiency in the management of disk-based data and uses optimization algorithms especially developed for the bottom-up evaluation of logical queries involving recursion. The front-end interacts with the user in a logical language that has more expressive power than relational query languages. We present the structure of Aditi, discuss its components in some detail, and present performance figures.     

TQM implementation in hospitals

This paper discusses the essential elements for successful Total Quality Management (TQM) implementation in hospital, and the challenges that occur with such implementation. Guidelines for this implementation are provided to show how TQM tools can be used effectively in hospitals.     

Investigating the thermal-plasma processing of advanced materials

Due to several inherent advantages, plasma processing technology may become a very useful tool in the production of new materials. An increasing research effort based on experimental as well as theoretical investigations has been invested in this area for the synthesis of advanced materials. In describing the thermal-plasma processing technique, this article employs examples from research at the Plasma Processing Laboratory at the University of Idaho.     

Containerless solidification of highly undercooled mullite melts: Crystal growth behavior and microstructure formation

A mullite (3Al₂O₃·2SiO₂) sample has been levitated and undercooled in an aero-acoustic levitator, so as to investigate the solidification behavior in a containerless condition. Crystal-growth velocities are measured as a function of melt undercoolings, which increase slowly with melt undercoolings up to 380 K and then increase quickly when undercoolings exceed 400 K. In order to elucidate the crystal growth and solidification behavior, the relationship of melt viscosities as a function of melt undercoolings is established on the basis of the fact that molten mullite melts are fragile, from which the atomic diffusivity is calculated via the Einstein-Stokes equation. The interface kinetics is analyzed when considering atomic diffusivities. The crystal-growth velocity vs melt undercooling is calculated based on the classical rate theory. Interestingly, two different microstructures are observed; one exhibits a straight, faceted rod without any branching with melt undercoolings up to 400 K, and the other is a feathery faceted dendrite when undercoolings exceed 400 K. The formation of these morphologies is discussed, taking into account the contributions of constitutional and kinetic undercoolings at different bulk undercoolings.     

Numerical simulation of Zn coating solidification

A numerical model, which simulates nucleation and growth of Zn grains, has been developed in order to describe quantitatively the solidification of Zn coatings during the hot-dipping process. The inputs of the model are the nucleation distribution, which has been measured by electron backscattered diffraction (EBSD), and the dendritic growth kinetics, calculated with an analytical model of a parabolic dendrite tip modified to account for the interactions with the coating interfaces. The model predicts the shapes of the grain envelopes as a function of the grain orientation and the texture induced by growth. Three types of grain envelopes have been evidenced, depending on the angle between the c-axis and the normal to the coating plane. Moreover, it has been shown that growth reinforces the already existing {00.1} nucleation texture, in good agreement with experimental data. The model also predicts the cooling curve, including recalescence, and the grain size. Thus, it is used to describe the effects of Pb additions on solidification. In particular, it has been shown that Pb increases the nucleation undercooling and strongly decreases the density of active nuclei, thus resulting in a much larger grain size.