55 resultados para Visualization Using Computer Algebra Tools

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Radiation induced bystander effects are secondary effects caused by the production of chemical signals by cells in response to radiation. We present a Bio-PEPA model which builds on previous modelling work in this field to predict: the surviving fraction of cells in response to radiation, the relative proportion of cell death caused by bystander signalling, the risk of non-lethal damage and the probability of observing bystander signalling for a given dose. This work provides the foundation for modelling bystander effects caused by biologically realistic dose distributions, with implications for cancer therapies.

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The monitoring of oral disease is important, not alone for oral health, but for the detection and prevention of
systemic disease. The link between oral health and systemic disease is the focus of many studies, with
indications emerging of a causal link [1]. For disease diagnostics, blood has typically been the fluid of choice
for analysis, the retrieval of which is invasive and therefore unsuitable for wearable technology. Analysis of
saliva, however, is less invasive than that of blood, requires little or no pre-treatment and is abundantly
available. A strong correlation has been found between the analytes of blood and saliva [2] with saliva
containing biomarkers for diseases such as diabetes, oral cancer and cardiovascular disease. The development of
an implantable multi-parametric wireless sensor, to monitor both salivary analytes and changes in gingival
temperature, is the aim of this research project.
The aim of our current study is to detect changes in salivary pH, using a gold electrode with a pHsensitive
iridium oxide layer, and an Ion Sensitive Field Effect Transistor probe. Characterisation studies were
carried out in artificial saliva (AS). A salivary pH of between 4.5pH-7.5pH [3], and gingival temperature
between 35°C-38°C [4], were identified as the target range of interest for the human oral environment. Sensor
measurements were recorded in solutions of varying pH and temperature. An ISFET probe was then implanted
into a prototype denture and characterised in AS. This study demonstrates the suitability of ISFET and gold
electrode pH sensors for incorporation into implantable oral sensors.
[1] G. Taylor and W. Borgnakke, “Periodontal disease: associations with diabetes, glycemic control and
complications,” Oral Dis., vol. 14, no. 3, pp. 191–203, Apr. 2008.
[2] E. Tékus, M. Kaj, E. Szabó, N. L. Szénási, I. Kerepesi, M. Figler, R. Gábriel, and M. Wilhelm,
“Comparison of blood and saliva lactate level after maximum intensity exercise,” Acta Biol. Hung., vol. 63
Suppl 1, pp. 89–98, 2012.
[3] S. Naveen, M. L. Asha, G. Shubha, A. Bajoria, and A. Jose, “Salivary Flow Rate, pH and Buffering
Capacity in Pregnant and Non Pregnant Women - A Comparative Study,” JMED Res., pp. 1–8, Feb. 2014.
[4] A. F. Holthuis and F. S. Chebib, “Observations on temperature and temperature patterns of the gingiva. I.
The effect of arch, region and health,” J. Periodontol., vol. 54, no. 10, pp. 624–628, Oct. 1983

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This paper is an overview of the development and application of Computer Vision for the Structural Health
Monitoring (SHM) of Bridges. A brief explanation of SHM is provided, followed by a breakdown of the stages of computer
vision techniques separated into laboratory and field trials. Qualitative evaluations and comparison of these methods have been
provided along with the proposal of guidelines for new vision-based SHM systems.

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Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950s and 1960s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and bridge type. This paper investigates the use of computer vision systems for SHM. A series of field tests have been carried out to test the accuracy of displacement measurements using contactless methods. A video image of each test was processed using a modified version of the optical flow tracking method to track displacement. These results have been validated with an established measurement method using linear variable differential transformers (LVDTs). The results obtained from the algorithm provided an accurate comparison with the validation measurements. The calculated displacements agree within 2% of the verified LVDT measurements, a number of post processing methods were then applied to attempt to reduce this error.

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Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950’s and 1960’s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and system cost. This paper investigates the development of a low cost portable SHM system using commercially available cameras and computer vision techniques. A series of laboratory tests have been carried out to test the accuracy of displacement measurements using contactless methods. The results from each of the tests have been validated with established measurement methods, such as linear variable differential transformers (LVDTs). A video image of each test was processed using two different digital image correlation programs. The results obtained from the digital image correlation methods provided an accurate comparison with the validation measurements. The calculated displacements agree within 4% of the verified measurements LVDT measurements in most cases confirming the suitability full camera based SHM systems

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Background: Digital pathology provides a digital environment for the management and interpretation of pathological images and associated data. It is becoming increasing popular to use modern computer based tools and applications in pathological education, tissue based research and clinical diagnosis. Uptake of this new technology is stymied by its single user orientation and its prerequisite and cumbersome combination of mouse and keyboard for navigation and annotation.

Methodology: In this study we developed SurfaceSlide, a dedicated viewing platform which enables the navigation and annotation of gigapixel digitised pathological images using fingertip touch. SurfaceSlide was developed using the Microsoft Surface, a 30 inch multitouch tabletop computing platform. SurfaceSlide users can perform direct panning and zooming operations on digitised slide images. These images are downloaded onto the Microsoft Surface platform from a remote server on-demand. Users can also draw annotations and key in texts using an on-screen virtual keyboard. We also developed a smart caching protocol which caches the surrounding regions of a field of view in multi-resolutions thus providing a smooth and vivid user experience and reducing the delay for image downloading from the internet. We compared the usability of SurfaceSlide against Aperio ImageScope and PathXL online viewer.

Conclusion: SurfaceSlide is intuitive, fast and easy to use. SurfaceSlide represents the most direct, effective and intimate human–digital slide interaction experience. It is expected that SurfaceSlide will significantly enhance digital pathology tools and applications in education and clinical practice.

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This paper provides an overview of research on modelling of the structure–property interactions of polymer nanocomposites in manufacturing processes (stretch blow moulding and thermoforming) involving large-strain biaxial stretching of relatively thin sheets, aimed at developing computer modelling tools to help producers of materials, product designers and manufacturers exploit these materials to the full, much more quickly than could be done by experimental methods alone. The exemplar systems studied are polypropylene and polyester terephalate, with nanoclays. These were compounded and extruded into 2mm thick sheet which was then biaxially stretched at 155°C for the PP and 90 to 100°C for the PET. Mechanical properties were determined for the unstretched and stretched materials, together with TEM and XRD studies of structure. Multi-scale modelling, using representative volume elements is used to model the properties of these products.

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This work investigates limit cycle oscillations in the transonic regime. A novel approach to predict Limit Cycle Oscillations using high fidelity analysis is exploited to accelerate calculations. The method used is an Aeroeasltic Harmonic Balance approach, which has been proven to be efficient and able to predict periodic phenomena. The behaviour of limit cycle oscillations is analysed using uncertainty quantification tools based on polynomial chaos expansions. To improve the efficiency of the sampling process for the polynomial-chaos expansions an adaptive sampling procedure is used. These methods are exercised using two problems: a pitch/plunge aerofoil and a delta-wing. Results indicate that Mach n. variability is determinant to the amplitude of the LCO for the 2D test case, whereas for the wing case analysed here, variability in the Mach n. has an almost negligible influence in amplitude variation and the LCO frequency variability has an almost linear relation with Mach number. Further test cases are required to understand the generality of these results.

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There is a dearth of evidence focusing on student preferences for computer-based testing versus
testing via student response systems for summative assessment in undergraduate education.
This quantitative study compared the preference and acceptability of computer-based testing
and a student response system for completing multiple choice questions in undergraduate
nursing education. After using both computer-based testing and a student response system to
complete multiple choice questions, 192 first year undergraduate nursing students rated their
preferences and attitudes towards using computer-based testing and a student response system.
Results indicated that seventy four percent felt the student response system was easy to use.
Fifty six percent felt the student response system took more time than the computer-based testing
to become familiar with. Sixty Percent felt computer-based testing was more users friendly.
Seventy Percent of students would prefer to take a multiple choice question summative exam
via computer-based testing, although Fifty percent would be happy to take using student response
system. Results are useful for undergraduate educators in relation to student’s preference
for using computer-based testing or student response system to undertake a summative
multiple choice question exam

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Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.