Engeenering

This article presents the design of a smart pet care system based on the slow intelligence framework for providing pets with suitable living conditions that closely mirror their natural habitat. By integrating heterogeneous information from various sensing data, the smart environment-aware pet care system can adaptively adjust the setting of temperature and humidity that best fits for the pet through iterative slow intelligence computation. Simulations of two case studies were provided to illustrate the application of the proposed system for pets such as snakes and dogs. The simulation results demonstrate the feasibility of the proposed approach to the design of smart pet care systems.

Classical multi-resolution image processing using wavelets provides an efficient analysis of image characteristics represented in terms of pixel-based singularities such as connected edge pixels of objects and texture elements given by the pixel intensity statistics. Curvelet transform is a recently developed approach based on curved singularities that provides a more sparse representation for a variety of directional multi-resolution image processing tasks such as denoising and texture analysis. The objective of this research is to develop a multi-class classifier for the automated classification of Gleason patterns of prostate cancer histological images with the utilization of curvelet-based texture analysis. This problem of computer-aided recognition of four pattern classes between Gleason Score 6 (primary Gleason grade 3 plus secondary Gleason grade 3) and Gleason Score 8 (both primary and secondary grades 4) is of critical importance affecting treatment decision and patients’ q...

The capability of artificial neural networks for pattern recognition of real world problems is well known. In recent years, the support vector machine has been advocated for its structure risk minimization leading to tolerance margins of decision boundaries. Structures and performances of these pattern classifiers depend on the feature dimension and training data size. The objective of this research is to compare these pattern recognition systems based on a case study. The particular case considered is on classification of hypertensive and normotensive right ventricle (RV) shapes obtained from Magnetic Resonance Image (MRI) sequences. In this case, the feature dimension is reasonable, but the available training data set is small, however, the decision surface is highly nonlinear.For diagnosis of congenital heart defects, especially those associated with pressure and volume overload problems, a reliable pattern classifier for determining right ventricle function is needed. RVi¦s glob...

An improved process for the esterification of carboxylic acid and alcohols into carboxylic ester is disclosed. It comprises the steps of: (a) charging the esterification reactants into a fixed bed reactor under a predetermined reaction condition; and (b) reacting the esterification reactants in the fixed bed reactor. The fixed bed reactor contains acidic catalysts that are present in a solid phase, and the reaction condition is controlled such that (i) the reactants and the products co-exist in a gas-liquid two-phase equilibrium in the fixed bed reactor and that (ii) at least one component of the reactants is present in one phase and at least one component of the products is present in another phase. Because a phase change is always taking place concurrently with the esteri fication reaction; the reaction stream is maintained at a relatively uniform temperature. This greatly reduces the chances of catalyst poisoning and minimizes the formation of undesired by-products such as polyme...

ZnO can be regarded as one of the most important metal oxide semiconductors for future applications. Similar to silicon in microelectronics, it is not only important to obtain nanoscale building blocks of ZnO, but also extraordinary purity has to be ensured. A new gas-phase approach to obtain size-selected, nanocrystalline ZnO particles is presented. The tetrameric alkyl-alkoxy zinc compound [CH 3 ZnOCH(CH 3 ) 2 ] 4 is chemically transformed into ZnO, and the mechanism of gas-phase transformation is studied in detail. Furthermore, the morphological genesis of particles via gas-phase sintering is investigated, and for the first time a detailed model of the gas-phase sintering processes of ZnO is presented. Various analytical techniques (powder XRD, TEM/energy-dispersive X-ray spectroscopy, magic-angle spinning NMR spectroscopy, FTIR spectroscopy, etc.) are used to investigate the structure and purity of the samples. In particular, the defect structure of the ZnO was studied by photoluminescence spectroscopy.

A method is presented to prepare nanocrystalline α-Zn2SiO4 with the smallest crystal size reported so far for this system. Our approach combines the advantages of organometallic single-source precursor routes with aerosol processing techniques. The chemical design of the precursor enables the preferential formation of pure zinc silicates. Since gas-phase synthesis reduces intermolecular processes, and keeps the particles small, zinc silicate was synthesized from the volatile organometallic precursor [{MeZnOSiMe3}4], possessing a Zn-methyl- and O-silyl-substituted Zn4O4-heterocubane framework (cubane), under oxidizing conditions, using the chemical vapor synthesis (CVS) method. The products obtained under different process conditions and their structural evolution after sintering were investigated by using various analytical techniques (powder X-ray diffraction, transmission electron microscopy, EDX analysis, solid-state NMR, IR, Raman, and UV/Vis spectroscopy). The deposited aerosol obtained first (processing temperature 750 °C) was amorphous, and contained agglomerates with primary particles of 12 nm in size. These primary particles can be described by a [Zn-O-Si] phase without long-range order. The deposit obtained at 900 °C contained particles with embedded nanocrystallites (3–5 nm) of β-Zn2SiO4, Zn1.7SiO4, and ZnO in an amorphous matrix. On further ageing, the as-deposited particles obtained at 900 °C form α-Zn2SiO4 imbedded in amorphous SiO2. The crystallite sizes and primary particle sizes in the formed α-Zn2SiO4 were found to be below ∼50 nm and mainly spherical in morphology. A gas-phase mechanism for the particle formation is proposed. In addition, the solid-state reactions of the same precursor were studied in detail to investigate the fundamental differences between a gas-phase and a solid-state synthesis route.