A refined algorithm for multisensor image registration based on pixel migration.

Multimodality image registration via pixel migration is a powerful approach. However, it suffers from a serious problem--the global maximum on the sum of squared gradient magnitude (SSG) surface does not correspond to the correct solution of registration. To solve the problem, we partition the search space into feasible and infeasible regions. The genetic algorithm (global optimizer) is used to obtain a good initial estimate of registration parameters and followed by a fast refining with Powell's approach (local optimizer). The experimental results demonstrate that the use of this modified pixel migration algorithm on multisensor image registration is very effective.     

Itemset trees for targeted association querying

Association mining techniques search for groups of frequently co-occurring items in a market-basket type of data and turn these groups into business-oriented rules. Previous research has focused predominantly on how to obtain exhaustive lists of such associations. However, users often prefer a quick response to targeted queries. For instance, they may want to learn about the buying habits of customers that frequently purchase cereals and fruits. To expedite the processing of such queries, we propose an approach that converts the market-basket database into an itemset tree. Experiments indicate that the targeted queries are answered in a time that is roughly linear in the number of market baskets, N. Also, the construction of the itemset tree has O(N) space and time requirements. Some useful theoretical properties are proven.     

Development of a web-based insulin decision aid for the elderly: usability barriers and guidelines

Universal Access in the Information Society - In recent years, researchers have attempted to shift patient decision aids (PDAs) from paper-based to web-based to increase its accessibility. Insulin...     

Urethane‐forming reaction kinetics and catalysis of model palm olein polyols: Quantified impact of primary and secondary hydroxyls

Model palm olein natural oil polyols (NOPs) with varying ratios of primary to secondary hydroxyls were synthesized, characterized, and evaluated in reaction kinetics study with isocyanate in formation of polyurethanes. Reaction rate constants and activation energies associated with primary and secondary hydroxyls of NOPs were quantified. The kinetic study in toluene shows that the NOP containing primary hydroxyls have three times higher reaction rate constants in noncatalyzed reaction with 4,4′‐diphenylmethane diisocyanate (4,4′‐MDI) compared to the model NOP containing only secondary hydroxyls, which is associated with higher activation energy of secondary hydroxyls. However, the difference in reaction rate constants of primary and secondary hydroxyls in NOPs diminished in the reactions catalyzed with dibutyltin dilaurate. Bulk polymerization reaction confirms the kinetics results in toluene, showing that the model NOP containing primary hydroxyls reached gel time at a faster rate. Evaluation of elastomers from bulk polymerization shows low degree of phase separation of hard and soft segments for elastomers based on the model NOPs. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 42955.     

Pt/Y0.16Zr0.84O1.92/Pt thin film solid oxide fuel cells: Electrode microstructure and stability considerations

Symmetric, free standing thin film micro-solid oxide fuel cells of Pt/Y_0.16Zr_0.84O_1.92/Pt structure are studied in this report. The role of parameters such as electrolyte thickness and electrode porosity on fuel cell power output was investigated. A peak power density of 1037 mW cm⁻² was exhibited with an optimized structure consisting of nano-porous Pt electrodes and 100 nm thick Y_0.16Zr_0.84O_1.92 with an open circuit voltage of 0.968 V at 500 °C using H₂ as fuel and standing air as the oxidant. A twelve hour test of these devices indicates that overall performance shows extreme sensitivity to microstructural changes in the pure metallic electrodes. Results presented herein enable mechanistic routes to performance optimization, provide device stability data and are relevant to advancing micro-fuel cells for portable energy.     

Highly Flexible Graphene Oxide Nanosuspension Liquid‐Based Microfluidic Tactile Sensor

A novel graphene oxide (GO) nanosuspension liquid‐based microfluidic tactile sensor is developed. It comprises a UV ozone‐bonded Ecoflex–polydimethylsiloxane microfluidic assembly filled with GO nanosuspension, which serves as the working fluid of the tactile sensor. This device is highly flexible and able to withstand numerous modes of deformation as well as distinguish various user‐applied mechanical forces it is subjected to, including pressing, stretching, and bending. This tactile sensor is also highly deformable and wearable, and capable of recognizing and differentiating distinct hand muscle‐induced motions, such as finger flexing and fist clenching. Moreover, subtle differences in the handgrip strength derived from the first clenching gesture can be identified based on the electrical response of our device. This work highlights the potential application of the GO nanosuspension liquid‐based flexible microfluidic tactile sensing platform as a wearable diagnostic and prognostic device for real‐time health monitoring. Also importantly, this work can further facilitate the exploration and potential realization of a functional liquid‐state device technology with superior mechanical flexibility and conformability.