How Game Development Technology Can Assist in Visualization Challenges

Research has shown that product configuration is becoming an increasingly common aspect of commercial sales, where previously it would have been an advantage that sets your products apart from competitors, it’s now becoming normalised as a baseline service offered to customers. Product configurators are notoriously difficult to develop, often requiring mass amounts of content and data. Larger businesses with resources to spare can afford to take on the risks associated with developing a product configurator, but medium and smaller sized businesses often cannot, and so find themselves at an increasingly larger disadvantage. This study aims to investigate whether game technology can mitigate or remove some of the development risks associated with developing a product configurator. Building on existing work on product configurator development, it asks. Can game technology provide an advantage over traditional development solutions? And if so, how exactly does it improve on them Based on a review of the literature on product configurator development, it’s clear that traditional rendering solutions are fine if the products showcased feature low-levels of customisation. But if products exceed this customisation threshold, it’s evident that these practices cannot scale and so bottleneck production, making the investment and risk involved in continuing development too high. The results indicate that when using game technology, you can automate aspects of production, such as rendering and storage. The speed difference between traditional rendering solutions and game technology methods are considerable if implemented correctly. On this basis, it is recommended that game technology is used in place of traditional rendering solutions such as Blender, 3DS Max and other 3D rendering packages as the difference in production speed is immense and the inclusion of automating certain tasks outright removes certain tasks involved in the production of a product configurator

Enhanced Content-Based Fake News Detection Methods with Context-Labeled News Sources

This work examined the relative effectiveness of multilayer perceptron, random forest, and multinomial naïve Bayes classifiers, trained using bag of words and term frequency-inverse dense frequency transformations of documents in the Fake News Corpus and Fake and Real News Dataset. The goal of this work was to help meet the formidable challenges posed by proliferation of fake news to society, including the erosion of public trust, disruption of social harmony, and endangerment of lives. This training included the use of context-categorized fake news in an effort to enhance the tools’ effectiveness. It was found that term frequency-inverse dense frequency provided more accurate results than bag of words across all evaluation metrics for identifying fake news instances, and that the Fake News Corpus provided much higher result metrics than the Fake and Real News Dataset. In comparison to state-of-the-art methods the models performed as expected

Living with chronic illness. A biographical analysis of a family's account.

It has been estimated that by the year 2014 there will be a 12 per cent increase in the number of adults with at least one chronic illness condition (Carrier, 2009). The turn to caring for those with a chronic illness at home has resulted in carers having an increased risk of developing health problems (Ohman & Soderberg, 2004). As such there is a need to understand how families manage and cope with illness at home. This study has examined the effect chronic illness had on not only the woman with illness, but also the immediate family closely involved with her care. Additionally the study has sought to address the effect chronic illness had on the ¿self¿ and ¿identity¿ of these three women and to determine what extent and impact the illness process had on the relationships within this family. The study used open-ended biographic narrative interviews to elicit data. The research revealed that each woman experienced change and loss to both ¿self¿ and ¿identity¿ albeit in different ways. Interestingly and of significance is the way these women in their narrative accounts revisited their past lives in implicating and accounting for the present and the future (Freeman 2010). It was discovered that the past history and past relationships of these women affected how they each responded to illness and each other in their present circumstances

Six Researchers in Search of A Meaning In Lockdown: A Collective Essay (RN03)

‘Stay at home!’. Biographical researchers are accustomed to, and they are well equipped (methodologically) to reflect on, changing life trajectories in unprecedented circumstances. This collective essay maps our individual experiences of a lockdown (see the list of contributors at the bottom)

Dosimetric verification of the anisotropic analytical algorithm for radiotherapy treatment planning

BACKGROUND AND PURPOSE: To investigate the accuracy of photon dose calculations performed by the Anisotropic Analytical Algorithm, in homogeneous and inhomogeneous media and in simulated treatment plans. MATERIALS AND METHODS: Predicted dose distributions were compared with ionisation chamber and film measurements for a series of increasingly complex situations. Initially, simple and complex fields in a homogeneous medium were studied. The effect of inhomogeneities was investigated using a range of phantoms constructed of water, bone and lung substitute materials. Simulated treatment plans were then produced using a semi-anthropomorphic phantom and the delivered doses compared to the doses predicted by the Anisotropic Analytical Algorithm. RESULTS: In a homogeneous medium, agreement was found to be within 2% dose or 2mm dta in most instances. In the presence of heterogeneities, agreement was generally to within 2.5%. The simulated treatment plan measurements agreed to within 2.5% or 2mm. Conclusions: The accuracy of the algorithm was found to be satisfactory at 6MV and 10MV both in homogeneous and inhomogeneous situations and in the simulated treatment plans. The algorithm was more accurate than the Pencil Beam Convolution model, particularly in the presence of low density heterogeneities

Data Formats: Using Self-Describing Data Formats

No abstract availabl

Collaboration between doctors and nurses in children's cancer care: insights from a European project.

Purpose It has long been recognised that effective cancer care is not possible without multi-professional team working. Collaboration and multi-professional working however are known to be less than straightforward. This project aimed to use a collaborative approach to explore and facilitate professional groups to work together more effectively in the field of children's cancer care. Method Based on an earlier project in Italy, a three-year seminar series was organised involving both a doctor and nurse from 15 paediatric haematology/oncology units across Europe. Participants had to be able to speak English and commit to participate in annual seminars as well as the development and implementation of a local project to enhance doctor–nurse collaboration in their own unit. Appreciative Inquiry was the methodological approach used to address organisational as well as interpersonal change. Results Fifteen doctor–nurse teams were initially selected from a range of different countries, and 10 completed the project. Key outcomes reported include implementation and successful completion of projects, publication of the results achieved, participant satisfaction with improvements in collaboration. Feedback from participants would suggest that change had been implemented and possibly sustained. Conclusions Active involvement and group support were required for success. More formal relationships needed to be activated with participating centres to guarantee support for those involved in implementing lasting change. A web-based resource to allow other programmes and centres to use the resources developed has been made available. The same approach, we believe, could be used to improve multi-professional working in the care of other childhood illnesses

Clinical implications of the anisotropic analytical algorithm for IMRT treatment planning and verification

PURPOSE: To determine the implications of the use of the Anisotropic Analytical Algorithm(AAA) for the production and dosimetric verification of IMRT plans for treatments of the prostate, parotid, nasopharynx and lung. METHODS: 72 IMRT treatment plans produced using the Pencil Beam Convolution (PBC)algorithm were recalculated using the AAA and the dose distributions compared. 24 of the plans were delivered to inhomogeneous phantoms and verification measurements made using a pinpoint ionisation chamber. The agreement between the AAA and measurement was determined. RESULTS: Small differences were seen in the prostate plans, with the AAA predicting slightly lower minimum PTV doses. In the parotid plans, there were small increases in the lens and contralateral parotid doses while the nasopharyngeal plans revealed a reduction in the volume of the PTV covered by the 95% isodose (the V95%) when the AAA was used. Large changes were seen in the lung plans, the AAA predicting reductions in the minimum PTV dose and large reductions in the V95%. The AAA also predicted small increases in the mean dose to the normal lung and the V20. In the verification measurements, all AAA calculations were within 3% or 3.5mm distance to agreement of the measured doses. Conclusions: The AAA should be used in preference to the PBC algorithm for treatments involving low density tissue but this may necessitate re-evaluation of plan acceptability criteria. Improvements to the Multi-Resolution Dose Calculation algorithm used in the inverse planning are required to reduce the convergence error in the presence of lung tissue. There was excellent agreement between the AAA and verification measurements for all sites

Engineering Tool for Temperature, Electric Field and Dose Rate Dependence of High Resistivity Spacecraft Materials

An engineering tool has been developed to predict the equilibrium conductivity of common spacecraft insulating materials as a function of electric field, temperature, and adsorbed dose rate based on parameterized, analytic functions derived from physics-based theories. The USU Resistivity Calculator Engineering Tool calculates the total conductivity as the sum of three independent conductivity mechanisms: a thermally activated hopping conductivity, a variable range hopping conductivity, and a radiation induced conductivity using a total of nine independent fitting parameters determined from fits to an extensive data set taken by the Utah State University Materials Physics Group. It also provides a fit for the temperature dependence of the electrostatic breakdown field strength, in terms of a tenth independent fitting parameter related to an interchain bond strength. The extent of F, T and D& measured in the experiments were designed to cover as much of the ranges typically encountered in space environments as possible. This Mathcad worksheet calculates the total conductivity and the individual contributions from each conductivity mechanism based on user inputs for F, T and D. It also plots 2D and 3D graphs of the conductivities over the appropriate full ranges of F, T and D&