Depth estimation of metallic objects using multiwavelets scale-space representation

The problem of dimensional defects in aluminum die-castings 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, it is extremely hard to estimate true dimensionality of these metallic parts, autonomously. Some existing vision systems are capable of estimating depth to high accuracy, however are very much hardware dependent, involving the use of light and laser pattern projectors, integrated into vision systems or laser scanners. However, due to the reflective nature of these metallic parts and variable factory environments, the aforementioned vision systems tend to exhibit unpromising performance. Moreover, hardware dependency makes these systems cumbersome and costly. 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 pair of stereo cameras and a defused fluorescent light. The proposed vision system is capable of estimating surface depths within the accuracy of 0.5mm. In addition, the system is invariant to illuminative variations as well as orientation and location of the objects on the input image space, making 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. The proposed system is a major part of quality inspection system for the automotive manufacturing industry.

Depth estimation using multiwavelet 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 camera 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.

Facial age estimation by nonlinear aging pattern subspace

Human age estimation by face images is an interesting yet challenging research topic emerging in recent years. This paper extends our previous work on facial age estimation (a linear method named AGES). In order to match the nonlinear nature of the human aging progress, a new algorithm named KAGES is proposed based on a nonlinear subspace trained on the aging patterns, which are defined as sequences of individual face images sorted in time order. Both the training and test (age estimation) processes of KAGES rely on a probabilistic model of KPCA. In the experimental results, the performance of KAGES is not only better than all the compared algorithms, but also better than the human observers in age estimation. The results are sensitive to parameter choice however, and future research challenges are identified.

Position estimation and tracking of an autonomous mobile sensor using received signal strength

In this paper, an algorithm for approximating the path of a moving autonomous mobile sensor with an unknown position location using Received Signal Strength (RSS) measurements is proposed. Using a Least Squares (LS) estimation method as an input, a Maximum-Likelihood (ML) approach is used to determine the location of the unknown mobile sensor. For the mobile sensor case, as the sensor changes position the characteristics of the RSS measurements also change; therefore the proposed method adapts the RSS measurement model by dynamically changing the pass loss value alpha to aid in position estimation. Secondly, a Recursive Least-Squares (RLS) algorithm is used to estimate the path of a moving mobile sensor using the Maximum-Likelihood position estimation as an input. The performance of the proposed algorithm is evaluated via simulation and it is shown that this method can accurately determine the position of the mobile sensor, and can efficiently track the position of the mobile sensor during motion.

Object focused simultaneous estimation of optical flow and state dynamics

The framework of differential optical flow has been built upon to enhance the performance of motion estimation from optical flow. By coupling optical flow and object state parameters, an effective procedure for object tracking is implemented with the dasiaSimultaneous Estimation of Optical Flow and Object Statepsila (SEOS) technique. The SEOS method utilizes dynamic object parameter information when calculating optical flow for tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires minimization of an error functional containing object physical parameter data. The convergence of an energy functional to a feasible or optimal solution set is not guaranteed. Convergence criteria is often assumed and not shown explicitly. Convergence of the SEOS method for both the Jacobi and Gauss-Seidel numerical resolution methods is evaluated.

Localization of mobile transmitters by means of linear state estimation using RSS measurements

This paper investigates the problem of estimating the location and velocity of a mobile agent using the received signal strength (RSS) measurements. Typical power measurements are inherently nonlinear and in this approach we derive a linear measurement scheme using an analytical measurement conversion technique which can readily be used with RSS measuring sensors. Power measurements are hence used in our robust version of a linear Kalman filter to estimate the dynamic parameters of the moving transmitter.

Wireless estimation of canine pose for search and rescue

In this paper we discuss the use of accelerometers and Bluetooth to monitor canine pose in the context of common poses observed in urban search and rescue dogs. We discuss the use of the canine pose system in a disaster environment, and propose techniques for determining canine pose. In addition we discuss the challenges with this approach in such environments. The paper presents the experimental results obtained from the heavy urban search and rescue disaster simulation, where experiments were conducted using multiple canines, which show that angles can be derived from acceleration readings. Our experiments show that similar angles were measured for each of the poses, even when measured on multiple USAR canines of varying size. We also found measurable and consistent differences between each of the poses, making them clearly distinguishable from one another, again even when comparing with different USAR canines.

A simple 96-well microplate method for estimation of total polyphenolic content in seaweeds

Seaweed polyphenols are potent antioxidants and have also been shown to have α-glucosidase inhibiting activity. In our continuous efforts to develop new marine-based nutraceuticals and functional food ingredients, we have investigated many algal species collected on the Atlantic coast of Canada. A simple method for estimating the total polyphenol content in seaweeds and their extracts was developed based on the classic Folin-Ciocalteau colorimetric reaction. By using the 96-well microplate and a microplate reader, this new method saves experimental time, significantly reduces the amount of sample required, handles large number of samples in one experiment, and also improves the repeatability of the results.

A number of algal samples collected on the seashore of Nova Scotia, Canada, were analyzed for their levels of polyphenol content using this microplate-based method. The antioxidant activity of these samples was also assessed by using DPPH (2, 2-diphenyl-1-picrylhydrazyl) radical scavenging assay. The results showed that there is a strong correlation between the total polyphenol content and the potency of antioxidant effect.

Estimation of the dietary requirement for vitamin D in healthy adults

Background: Knowledge gaps have contributed to considerable variation among international dietary recommendations for vitamin D.

Objective: We aimed to establish the distribution of dietary vitamin D required to maintain serum 25-hydroxyvitamin D [25(OH)D] concentrations above several proposed cutoffs (ie, 25, 37.5, 50, and 80 nmol/L) during wintertime after adjustment for the effect of summer sunshine exposure and diet.

Design: A randomized, placebo-controlled, double-blind 22-wk intervention study was conducted in men and women aged 20–40 y (n = 238) by using different supplemental doses (0, 5, 10, and 15 µg/d) of vitamin D3 throughout the winter. Serum 25(OH)D concentrations were measured by using enzyme-linked immunoassay at baseline (October 2006) and endpoint (March 2007).

Results: There were clear dose-related increments (P < 0.0001) in serum 25(OH)D with increasing supplemental vitamin D3. The slope of the relation between vitamin D intake and serum 25(OH)D was 1.96 nmol·L–1·µg–1 intake. The vitamin D intake that maintained serum 25(OH)D concentrations of >25 nmol/L in 97.5% of the sample was 8.7 µg/d. This intake ranged from 7.2 µg/d in those who enjoyed sunshine exposure, 8.8 µg/d in those who sometimes had sun exposure, and 12.3 µg/d in those who avoided sunshine. Vitamin D intakes required to maintain serum 25(OH)D concentrations of >37.5, >50, and >80 nmol/L in 97.5% of the sample were 19.9, 28.0, and 41.1 µg/d, respectively.

Conclusion: The range of vitamin D intakes required to ensure maintenance of wintertime vitamin D status [as defined by incremental cutoffs of serum 25(OH)D] in the vast majority (>97.5%) of 20–40-y-old adults, considering a variety of sun exposure preferences, is between 7.2 and 41.1 µg/d.

Estimation of in vitro prebiotic activity of individual and mixed dietary fibres

Background: Epidemiological studies have demonstrated a link between dietary fibre deficiency and prevalence of many “Western diseases” particularly colon related diseases. Many of the health benefits associated with dietary fibre are attributed to their prebiotic effect. However, not all fibres have the same prebiotic potential or the same impact on colon health.

Objective: To examine the in vitro fermentation properties of individual and mixed dietary fibres by measuring fermentation byproducts over time.

Design: Wheat bran and guar gum were selected for this study. Individual and mixed dietary fibres were added to batch fermentation system and were inoculated with fresh faecal inoculum (n= 4). Positive (inulin) and negative (no substrate) fermenters were also used to determine the differences. The pH of the five fermenters was adjusted to a baseline of 5.5 and 6.8 representing the pH of the proximal and distal sections of the colon respectively. Samples were drawn out of the fermenters at 0, 3, 9 and 24 hours for the analysis of pH, ammonia and short chain fatty acids (SCFAs).

Outcomes: There were no significant differences in the pH levels at various time points between fermenters adjusted to pH 5.5 at baseline. However, in fermenters adjusted to pH 6.8 the pH of the fermenter containing wheat bran increased over the time (24h (P = 0.017)) due to production of a high amount of ammonia. The total SCFAs production was greater in fermenters containing combined fibres.

Conclusion: There is a large inter-individual variation in the prebiotic effect of all types of dietary fibres, however, in the present study, dietary fibre combinations showed greater prebiotic potential compared with the individual fibres.

Exposure estimation, uncertainty and variability in occupational hygiene retrospective assessment

This thesis reports on a quantitative exposure assessment and on an analysis of the attributes of the data used in the estimations, in particular distinguishing between its uncertainty and variability. A retrospective assessment of exposure to benzene was carried out for a case control study of leukaemia in the Australian petroleum industry. The study used the mean of personal task-based measurements (Base Estimates) in a deterministic algorithm and applied factors to model back to places, times etc for which no exposure measurements were available. Mean daily exposures were estimated, on an individual subject basis, by summing the task-based exposures. These mean exposures were multiplied by the years spent on each job to provide exposure estimates in ppm-years. These were summed to provide a Cumulative Estimate for each subject. Validation was completed for the model and key inputs. Exposures were low, most jobs were below TWA of 5 ppm benzene. Exposures in terminals were generally higher than at refineries. Cumulative Estimates ranged from 0.005 to 50.9 ppm-years, with 84 percent less than 10 ppm-years. Exposure probability distributions were developed for tanker drivers using Monte Carlo simulation of the exposure estimation algorithm. The outcome was a lognormal distribution of exposure for each driver. These provide the basis for alternative risk assessment metrics e.g. the frequency of short but intense exposures which provided only a minimal contribution to the long-term average exposure but may increase risk of leukaemia. The effect of different inputs to the model were examined and their significance assessed using Monte Carlo simulation. The Base Estimates were the most important determinant of exposure in the model. The sources of variability in the measured data were examined, including the effect of having censored data and the between and within-worker variability. The sources of uncertainty in the exposure estimates were analysed and consequential improvements in exposure assessment identified. Monte Carlo sampling was also used to examine the uncertainties and variability associated with the tanker drivers' exposure assessment, to derive an estimate of the range and to put confidence intervals on the daily mean exposures. The identified uncertainty was less than the variability associated with the estimates. The traditional approach to exposure estimation typically derives only point estimates of mean exposure. The approach developed here allows a range of exposure estimates to be made and provides a more flexible and improved basis for risk assessment.

On the simultaneous estimation of optical flow and object state

This thesis focuses on the enhancement of differential optical flow techniques. The framwork of differential optical flow has been built upon to improve object motion estimation within a video stream or image sequence. This augmentation comes in the form of a combined optical flow and object state estimation method (SEOS)

3D depth estimation using wavelet analysis based stereo vision approach

A complete and highly robust 3D reconstruction algorithm based on stereo vision is presented. The developed system is capable of reconstructing dimensionally accurate 3D models of the objects and is very simple and cost effective due to its prominent software dependency and minimal hardware involvevment unlike existing systems.