A custom-built insulin resistance gene chip

Objectives/Aim—Microarray (gene chip) technology offers a powerful new tool for analyzing the expression of large numbers of genes in many experimental samples. The aim of this study was to design, construct, and use a gene chip to measure the expression levels of key genes in metabolic pathways related to insulin resistance.
Methods—We selected genes that were implicated in the development of insulin resistance, including genes involved in insulin signaling; glucose uptake, oxidation, and storage; fat uptake, oxidation, and storage; cytoskeletal components; and transcription factors. The key regulatory genes in the pathways were identified, along with other recently identified candidate genes such as calpain-10. A total of 242 selected genes (including 32 internal control elements) were sequence-verified, purified, and arrayed on aldehyde-coated slides.
Results—Where more than 1 clone containing the gene of interest was available, we chose those containing the genes in the 5' orientation and an insert size of around 1.5 kb. Of the 262 clones purchased, 56 (21%) were found to contain sequences other than those expected. In addition, 2 (1%) did not grow under standard conditions and were assumed to be nonviable. In these cases, alternate clones containing the gene of interest were chosen as described above. The current version of the Insulin Resistance Gene Chip contains 210 genes of interest, plus 48 control elements. A full list of the genes is available at http://www.hbs.deakin.edu.au/mru/research/gene_chip_tech/genechip_three.htm/.
Conclusions—The human Insulin Resistance Gene Chip that we have constructed will be a very useful tool for investigating variation in the expression of genes relevant to insulin resistance under various experimental conditions. Initially, the gene chip will be used in studies such as exercise interventions, fasting, euglycemic-hyperinsulinemic clamps, and administration of antidiabetic agents

Machine vision system for automatic inspection of surface defects in aluminum die casting

A camera based machine vision system for the automatic inspection of surface defects in aluminum die casting is presented. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production.

An active stereo vision-based learning approach for robotic tracking, fixating and grasping control

In this paper, an active stereo vision-based learning approach is proposed for a robot to track, fixate and grasp an object in unknown environments. First, the functional mapping relationships between the joint angles of the active stereo vision system and the spatial representations of the object are derived and expressed in a three-dimensional workspace frame. Next, the self-adaptive resonance theory-based neural networks and the feedforward neural networks are used to learn the mapping relationships in a self-organized way. Then, the approach is verified by simulation using the models of an active stereo vision system which is installed in the end-effector of a robot. Finally, the simulation results confirm the effectiveness of the present approach.

Mcommerce - a vision in time

Global mCommerce revenues are expected to grow from $400 million in 2000, to 22.2 billion by 2005 (Raczkowski, 2002) mCommerce is a key driver in developing the global information society, with applications emerging in numerous areas including banking, financial services, security services and shopping (Khalifa and Cheng, 2002). With optimistic projections regarding its growth, many researchers are actively determining the future of mCommerce. In this paper, we have tried to synthesise some predictions and evolving definitions, explored security as a critical impediment and developing solutions; investigated the mPayment scenario; and derived a futuristic research framework. Specifically, we have attempted to capture the moving mCommerce scenario in present time, with a special focus into mPayments.

Machine vision system for automatic inspection of surface defects in aluminium die casting

A machine vision system is presented for the automatic inspection of surface defects in aluminium die casting. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production.

Stereo-vision-based moving object tracking via robust linear filtering

Vision-based tracking sensors typically provide nonlinear measurements
of the targets Cartesian position and velocity state components. In this paper we derive linear measurements using an analytical measurement conversion technique which can be used with two (or more) vision sensors. We derive
linear measurements in the target’s Cartesian position and velocity components and we derive a robust version of a linear Kalman filter. We show that our linear robust filter significantly outperforms the extended Kalman Filter. Moreover, we prove that the state estimation error is bounded.

Vision based target tracking using robust linear filtering

The use of perspective projection in tracking a target from a video stream involves nonlinear observations. The target dynamics, however, are modeled in Cartesian coordinates and result in a linear system. In this paper we provide a robust version of a linear Kalman filter and perform a measurement conversion technique on the nonlinear optical measurements. We show that our linear robust filter significantly outperforms the Extended Kalman Filter. Moreover, we prove that the state estimation error is bounded in a probabilistic sense.

Depth estimation using multi-wavelet analysis based stereo vision approach

The problem of dimensional defects in aluminum die- casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo cameras pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.