Adaptation to global warming by changing internal loads of buildings

Global warming can have a significant impact on the building thermal environment and energy performance. Because greenhouse gas concentrations are still continuing to increase, this warming process will continue and may accelerate. Adaptation to global warming is therefore emerging as one of the key requirements for buildings. This requires all the existing and new buildings not only to perform and operate satisfactorily in the new environment but also to satisfy the environmental performance criteria of sustainability. Through a parametric study using the building simulation technique, this paper investigates the adaptation potential of changing the building internal load densities to the future global warming. Case studies for office buildings in major Australian capital cities are presented. Based on the results of parametric study, possible adaptation strategies are also proposed and evaluated.

Identification of factors predicting clickthrough in Web searching using neural network analysis

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing

Microassembly fabrication of tissue engineering scaffolds with customized design

Browse > Journals> Automation Science and Enginee ...> Volume: 5 Issue: 3 Microassembly Fabrication of Tissue Engineering Scaffolds With Customized Design 4468741 abstract Han Zhang; Burdet, E.; Poo, A.N.; Hutmacher, D.W.; GE Global Res. Center Ltd., Shanghai This paper appears in: Automation Science and Engineering, IEEE Transactions on Issue Date: July 2008 Volume: 5 Issue:3 On page(s): 446 - 456 ISSN: 1545-5955 Digital Object Identifier: 10.1109/TASE.2008.917011 Date of Current Version: 02 July 2008 Sponsored by: IEEE Robotics and Automation Society Abstract This paper presents a novel technique to fabricate scaffold/cell constructs for tissue engineering by robotic assembly of microscopic building blocks (of volume 0.5$,times,$0.5$,times,$0.2 ${hbox{mm}}^{3}$ and 60 $mu {hbox{m}}$ thickness). In this way, it becomes possible to build scaffolds with freedom in the design of architecture, surface morphology, and chemistry. Biocompatible microparts with complex 3-D shapes were first designed and mass produced using MEMS techniques. Semi-automatic assembly was then realized using a robotic workstation with four degrees of freedom integrating a dedicated microgripper and two optical microscopes. Coarse movement of the gripper is determined by pattern matching in the microscopes images, while the operator controls fine positioning and accurate insertion of the microparts. Successful microassembly was demonstrated using SU-8 and acrylic resin microparts. Taking advantage of parts distortion and adhesion forces, which dominate at micro-level, the parts cleave together after assembly. In contrast to many current scaffold fabrication techniques, no heat, pressure, electrical effect, or toxic chemical reaction is involved, a critical condition for creating scaffolds with biological agents.

Numerical simulation of the Riesz fractional diffusion equation with a nonlinear source term

In this paper, A Riesz fractional diffusion equation with a nonlinear source term (RFDE-NST) is considered. This equation is commonly used to model the growth and spreading of biological species. According to the equivalent of the Riemann-Liouville(R-L) and Gr¨unwald-Letnikov(GL) fractional derivative definitions, an implicit difference approximation (IFDA) for the RFDE-NST is derived. We prove the IFDA is unconditionally stable and convergent. In order to evaluate the efficiency of the IFDA, a comparison with a fractional method of lines (FMOL) is used. Finally, two numerical examples are presented to show that the numerical results are in good agreement with our theoretical analysis.

Best basis-based intelligent machine fault diagnosis

The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.