Product design: Formulation of a screen-printable sintering-type conductive paste

Due to the complexity of the screen-printing operation and the rheological behaviors of the screen-printable paste, such a paste is usually formulated by trial-and-error. In this report, a systematic procedure, based on heuristics and mechanistic models, for the design of a screen-printable paste is developed. The procedure is demonstrated by a case study of the formulation of a conductive paste of copper particles.     

Transmission-line modelling of the class E amplifier with an analytical method

The Transmission line modelling (TLM) technique was used to simulate the class E power amplifier. An analytical method is also used to fix the required component values to ensure the desired output performance of the amplifier. An experiment was carried out to verify the simulation result of the combined method.     

Fucoxanthin content and antioxidant properties of Undaria pinnatifida

This study investigated the fucoxanthin content of New Zealand (NZ) Undaria pinnatifida harvested from two locations in the Marlborough Sounds, New Zealand across its growing season. Fucoxanthin content and antioxidant properties of processed New Zealand U. pinnatifida and commercial wakame from Japan and Korea were further compared. Results showed that U. pinnatifida harvested from Port Underwood had higher fucoxanthin content in the blade compared to Pelorus Sound. The sporophyll also contained a significant amount of fucoxanthin throughout the harvest season, although lower than in the blade. Two antioxidant measurement methods, DPPH and CUPRAC, were utilised to measure antioxidant activities. Processed NZ U. pinnatifida had a lower fucoxanthin content and antioxidant activity than freeze-dried Undaria. Fucoxanthin content and antioxidant activities of NZ processed U. pinnatifida were not significantly different from other commercial samples from Japan and Korea. In conclusion, U. pinnatifida in New Zealand has a great potential to be a food and nutraceutical resource.     

Microscopic Contour Changes of Tribological Surfaces by Chemical and Mechanical Action

An electronic optical laser interferometer capable of resolving depth differences of as low as 30 Å and planar displacements of 6000 Å was constructed for the examination of surface profiles of bearing surfaces without physical contact. This instrument was used to determine topological chemical reactivity by applying a drop of dilute alcoholic hydrochloric acid and measuring the profile of the solid surface before and after application of this probe. It was found that scuffed bearing surfaces exposed to lubricants containing an organic chloride reacted much more slowly. In a separate series of experiments, a number of stainless steel plates were heated in a nitrogen atmosphere to different temperatures and their reactivity examined later at ambient temperature. The change of surface contour as a result of the probe reaction was found to follow an Arrhenius-type relation with respect to heat treatment temperature. This result could have implications on the scuffing mechanism.     

Adaptive filtering of evoked potentials with radial-basis-function neural network prefilter

Evoked potentials (EPs) are time-varying signals typically buried in relatively large background noise. To extract the EP more effectively from noise, we had previously developed an approach using an adaptive signal enhancer (ASE) (Chen et al., 1995). ASE requires a proper reference input signal for its optimal performance. Ensemble- and moving window-averages were formerly used with good results. In this paper, we present a new method to provide even more effective reference inputs for the ASE. Specifically, a Gaussian radial basis function neural network (RBFNN) was used to preprocess raw EP signals before serving as the reference input. Since the RBFNN has built-in nonlinear activation functions that enable it to closely fit any function mapping, the output of RBFNN can effectively track the signal variations of EP. Results confirmed the superior performance of ASE with RBFNN over the previous method.     

Improvement of borrowing channel assignment for patterned traffic load by online cellular probabilistic self-organizing map

This paper describes an improvement of borrowing channel assignment (BCA) for patterned traffic load by using the short-term traffic prediction ability of cellular probabilistic self-organizing map (CPSOM). The fast growing cellular mobile systems demand more efficient and faster channel allocation techniques today. In case of patterned traffic load, the traditional BCA methods are not efficient to further enhance the performance because heavy-traffic cells cannot borrow channels from their neighboring cells with light or medium traffic that may have unused nominal channels. The performance can be increased if the short-term traffic load can be predicted. The predicted results can then be used for channel re-assignment. Therefore, the unused nominal channels of the light-or-medium-traffic cells can be transferred to the heavy-traffic cells that need more nominal channels. In this paper, CPSOM is used online for traffic prediction. In this sense, the proposed CPSOM-based BCA method is able to enhance the performance for patterned traffic load compared with the traditional BCA methods. Simulation results corroborate that the proposed method enables the system to work with better performance for patterned traffic load than the traditional BCA methods.     

Text classification without negative examples revisit

Traditionally, building a classifier requires two sets of examples: positive examples and negative examples. This paper studies the problem of building a text classifier using positive examples (P) and unlabeled examples (U). The unlabeled examples are mixed with both positive and negative examples. Since no negative example is given explicitly, the task of building a reliable text classifier becomes far more challenging. Simply treating all of the unlabeled examples as negative examples and building a classifier thereafter is undoubtedly a poor approach to tackling this problem. Generally speaking, most of the studies solved this problem by a two-step heuristic: first, extract negative examples (N) from U. Second, build a classifier based on P and N. Surprisingly, most studies did not try to extract positive examples from U. Intuitively, enlarging P by P' (positive examples extracted from U) and building a classifier thereafter should enhance the effectiveness of the classifier. Throughout our study, we find that extracting P' is very difficult. A document in U that possesses the features exhibited in P does not necessarily mean that it is a positive example, and vice versa. The very large size of and very high diversity in U also contribute to the difficulties of extracting P'. In this paper, we propose a labeling heuristic called PNLH to tackle this problem. PNLH aims at extracting high quality positive examples and negative examples from U and can be used on top of any existing classifiers. Extensive experiments based on several benchmarks are conducted. The results indicated that PNLH is highly feasible, especially in the situation where |P| is extremely small.     

Dynamic and contact analysis of a bimodal ultrasonic motor

A bimodal ultrasonic motor, which operates with only one power amplifier, uses two simultaneously excited modes to drive the rotor; a longitudinal mode and a flexural mode. The equations of motion describing the vibrations and contact behavior are derived by Hamilton's principle and the geometry constraint. The Lagrange multiplier method is used to treat the frictional contact problem. The finite element method and numerical integration scheme are used to simulate the dynamic responses of this system with and without contact. Some important factors are studied for the bimodal ultrasonic motor design. The factors include structure design, amplitude of input voltage, phase displacement, exciting frequency, and contact behavior.