Quantification of multiple bioagents with wireless, remote-query magnetoelastic microsensors

This paper presents a micromagnetoelastic sensor array for simultaneously monitoring multiple biological agents. Magnetoelastic sensors, made of low-cost amorphous ferromagnetic ribbons, are analogous and complementary to piezoelectric acoustic wave sensors, which track parameters of interest via changes in resonance behavior. Magnetoelastic sensors are excited with magnetic ac fields, and, in turn, they generate magnetic fluxes that can be detected with a sensing coil from a distance. As a result, these sensors are highly attractive, not only due to their small size and low cost, but also because of their passive and wireless nature. Magnetoelastic sensors have been applied for monitoring pressure, temperature, liquid density, and viscosity, fluid How velocity and direction, and with chemical/biological responsive coatings that change mass or elasticity, various biological and chemical agents. In this paper, we report the fabrication and application of a six-sensor array for simultaneous measurement of Escherichia coli O157:H7, staphylococcal enterotoxin B, and ricin. In addition, the sensor array also monitors temperature and pH so the measurements are independent from these two parameters.     

Feature-based design in a distributed and collaborative environment

In this paper, a client/server framework has been developed to enable a dispersed team to accomplish a feature-based design task collaboratively. A manipulation client+modelling server infrastructure has been proposed to facilitate consistent primary information modelling for multiple users and adaptability of the system. Based on feature-to-feature relationships, a distributed feature manipulation mechanism has been proposed to filter the varied information of a working part during a co-design activity to avoid unnecessary re-transferring of the complete large-size CAD files each time when any interactive operation is imposed on the model by a client. In the distributed environment, a design task and the engaged clients are organised and connected through working sessions generated and maintained dynamically with a collaborative server. The environment is open to downstream manufacturing analysis modules to achieve distributed concurrent engineering.     

Fabricating micromilling tool using wire electrodischarge grinding and focused ion beam sputtering

In the present research, wire electrical discharge machining (WEDM) of γ titanium aluminide is studied. Selection of optimum machining parameter combinations for obtaining higher cutting efficiency and accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complicated stochastic process mechanisms. In general, no perfect combination exists that can simultaneously result in both the best cutting speed and the best surface finish quality. This paper presents an attempt to develop an appropriate machining strategy for a maximum process criteria yield. A feed-forward back-propagation neural network is developed to model the machining process. The three most important parameters – cutting speed, surface roughness and wire offset – have been considered as measures of the process performance. The model is capable of predicting the response parameters as a function of six different control parameters, i.e. pulse on time, pulse off time, peak current, wire tension, dielectric flow rate and servo reference voltage. Experimental results demonstrate that the machining model is suitable and the optimisation strategy satisfies practical requirements.     

Activity-based cost-modelling procedures for PCB assembly

Accurate product cost estimation is important in decisions which involved the selection of the least-cost design among alternative designs and the economic feasibility of a product. An accurate cost-estimating procedure would include the cost of materials and all activities that incur cost.This paper presents the development of cost models for printed circuit board (PCB) assembly which will take into consideration activities that incur cost owing to complexity, volume and batch size of PCB manufactured. All activities are allocated into three level bases and they are unit-level cost, batch-level cost and product-level cost. The cost of assembling one PCB is the summation of all these three costs. A case example is presented to illustrate the application of the models developed.     

An experimental investigation on the effects of exponential window and impact force level on harmonic reduction in impact-synchronous modal analysis

A novel method called Impact-synchronous modal analysis (ISMA) was proposed previously which allows modal testing to be performed during operation. This technique focuses on signal processing of the upstream data to provide cleaner Frequency response function (FRF) estimation prior to modal extraction. Two important parameters, i.e., windowing function and impact force level were identified and their effect on the effectiveness of this technique were experimentally investigated. When performing modal testing during running condition, the cyclic loads signals are dominant in the measured response for the entire time history. Exponential window is effectively in minimizing leakage and attenuating signals of non-synchronous running speed, its harmonics and noises to zero at the end of each time record window block. Besides, with the information of the calculated cyclic force, suitable amount of impact force to be applied on the system could be decided prior to performing ISMA. Maximum allowable impact force could be determined from nonlinearity test using coherence function. By applying higher impact forces than the cyclic loads along with an ideal decay rate in ISMA, harmonic reduction is significantly achieved in FRF estimation. Subsequently, the dynamic characteristics of the system are successfully extracted from a cleaner FRF and the results obtained are comparable with Experimental modal analysis (EMA).     

Motion analytics of zebrafish using fine motor kinematics and multi-view trajectory

Zebrafish is a useful animal model for studying human diseases such as muscle disorders. However, manual monitoring of fish motion is time-consuming and prone to subjective variations. In this paper, an automatic fish motion analytics framework is proposed. The proposed framework could be exploited to help validate zebrafish models of transgenic zebrafish that express human genes carrying mutations which lead to muscle disorders, thus affecting their ability to swim normally. To differentiate between wild-type (normal) and transgenic zebrafish, the proposed framework consists of two approaches to exploit discriminative spatial–temporal kinematic features which are extracted to represent zebrafish movements. First, the proposed approach studies precise quantitative measurements of motor movement abnormalities using a camera with the capability to record videos with high frames rates (up to 1,000 frames per second). This differs from previous works, which only tracked each fish as a single point over time. Second, the proposed approach studies multi-view spatial–temporal swimming trajectories. This differs from previous works which typically only considered single-view analysis of fish swimming trajectories. The proposed motion features are then incorporated into a supervised classification approach to identify abnormal fish movements. Experimental results have shown that the proposed approach is capable of differentiating between wild-type and transgenic zebrafish, thus helping to validate the zebrafish models.