Analysis of micro-structural changes and measurement of their parameters of a food material

Food microstructure represents the way their elements arrangement and their interaction. Researchers in this field benefit from identifying new methods of examination of the microstructure and analysing the images. Experiments were undertaken to study micro-structural changes of food material during drying. Micro-structural images were obtained for potato samples of cubical shape at different moisture contents during drying using scanning electron microscopy. Physical parameters such as cell wall perimeter, and area were calculated using an image identification algorithm, based on edge detection and morphological operators. The algorithm was developed using Matlab.

Understanding intraaortic balloon pumping

Intraaortic balloon pumping (IABP) is an established treatment for the support of a failing heart (Christenson, Simonet et al. 1997). It is a process undertaken in most level two and three intensive care units. Despite IABP appearing complex, the principles are straightforward. A sausage shaped intraaortic balloon (IAB) about 250 millimetres long and 15 millimetres in diameter, is placed in the descending aorta and attached to an external pump. The external pump then inflates and deflates the IAB in synchrony with cardiac contraction. The primary purpose of this is the support of a compromised heart with a simultaneous increase in myocardial oxygen supply, and decrease in myocardial oxygen demand (Overwalder, 1999). As a nurse it is worthwhile understanding the principles of IABP. As a hospital intervention, it’s exposure to nursing is high.

Evaluating effects of eco-driving at traffic intersections based on traffic micro-simulation

Eco-driving is an initiative driving behavior which aims to reduce fuel consumption and emissions from automobiles. Recently, it has attracted increasing interests and has been adopted by many drivers in Australia. Although many of the studies have revealed considerable benefits in terms of fuel consumption and emissions after utilising eco-driving, most of the literature investigated eco-driving effects on individual driver but not traffic flow. The driving behavior of eco-drivers will potentially affect other drivers and thereby affects the entire traffic flow. To comprehensively assess and understand how effectively eco-driving can perform, therefore, measurement on traffic flow is necessary. In this paper, we proposed and demonstrated an evaluation method based on a microscopic traffic simulator (Aimsun). We focus on one particular eco-driving style which involves moderate and smooth acceleration. We evaluated both traffic performance (travel time) and environmental performance (fuel consumption and CO2 emission) at traffic intersection level in a simple simulation model. The before-and-after comparisons indicated potentially negative impacts when using eco-driving, which highlighted the necessity to carefully evaluate and improve eco-driving before wide promotion and implementation.

Developing support for micro-entrepreneurs in a developing economy in Africa

The purpose of this paper is to explore the means of building the capacity of those who are running an organisation designed to support and resource start-ups and growing micro enterprises among some of the world’s poorest urban poor. The project is based in Beira, Mozambique, one of the poorest countries in the world. The result of this study is the development of a model for providing ongoing, inexpensive, effective, capacity building in developing economies. The model also provides a base for the further development of strategies to provide better support to micro entrepreneurs in poor developing economies.

The role of transport infrastructure in facilitating the survival and growth of micro-enterprises in developing economies

Transport and logistics are essential to effective business. Very little is currently known about the impact of improved transport on micro-enterprises in developing economies and whether improvements in this area would assist the very poor. This paper looks at the obstacles of an inefficient transport facilitation system and the high costs incurred by 22 survival micro-entrepreneurs funded by the same local NGO and operating in diverse industry sectors in a peri-urban context in Mozambique. Six case studies are selected to illustrate the most common constraints they face. The perspectives of the micro-business owners are confronted with those of government officials and community leaders for two reasons: to identify any mismatch and to discuss possible solutions. Significant discrepancies are detected between government agenda and needs of the population, while community-based entrepreneurship (CBE) is discussed as a possible collective strategy in dealing with the problem.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Rapid prototyping framework for visual control of autonomous micro aerial vehicles

Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone's video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW

Tooth fracture risk analysis based on a new finite element dental structure models using micro-CT data

The finite element (FE) analysis is an effective method to study the strength and predict the fracture risk of endodontically-treated teeth. This paper presents a rapid method developed to generate a comprehensive tooth FE model using data retrieved from micro-computed tomography (μCT). With this method, the inhomogeneity of material properties of teeth was included into the model without dividing the tooth model into different regions. The material properties of the tooth were assumed to be related to the mineral density. The fracture risk at different tooth portions was assessed for root canal treatments. The micro-CT images of a tooth were processed by a Matlab software programme and the CT numbers were retrieved. The tooth contours were obtained with thresholding segmentation using Amira. The inner and outer surfaces of the tooth were imported into Solidworks and a three-dimensional (3D) tooth model was constructed. An assembly of the tooth model with the periodontal ligament (PDL) layer and surrounding bone was imported into ABAQUS. The material properties of the tooth were calculated from the retrieved CT numbers via ABAQUS user's subroutines. Three root canal geometries (original and two enlargements) were investigated. The proposed method in this study can generate detailed 3D finite element models of a tooth with different root canal enlargements and filling materials, and would be very useful for the assessment of the fracture risk at different tooth portions after root canal treatments.