539 research outputs found
Property valuation model for rural Victoria
Licensed valuers in the State of Victoria, Australia currently appraise rural land using manual techniques. Manual techniques typically involve site visits to the property, liaison with property owners through interview, and require a valuer experienced in agricultural properties to determine a value. The use of manual techniques typically takes longer to determine a property value than for valuations performed using automated techniques, providing appropriate data are available. Manual methods of valuation can be subjective and lead to bias in valuation estimates, especially where valuers have varying levels of experience within a specific regional area. Automation may lend itself to more accurate valuation estimates by providing greater consistency between valuations. Automated techniques presently in use for valuation include artificial neural networks, expert systems, case based reasoning and multiple regression analysis. The latter technique appears most widely used for valuation. The research aimed to develop a conceptual rural property valuation model, and to develop and evaluate quantitative models for rural property valuation based on the variables identified in the conceptual model. The conceptual model was developed by examining peer research, Valuation Best Practice Standards, a standard in use throughout Victoria for rating valuations, and rural property valuation texts. Using data that are only available digitally and publicly, the research assessed this conceptualisation using properties from four LGAs in the Wellington and Wimmera Catchment Management Authority (CMAs) areas in Victoria. Cluster analysis was undertaken to assess if the use of sub-markets, that are determined statistically, can lead to models that are more accurate than sub-markets that have been determined using geographically defined areas. The research is divided into two phases; the 'available data phase' and the 'restricted data phase'. The 'available data phase' used publicly available digital data to build quantitative models to estimate the value of rural properties. The 'restricted data phase' used data that became available near the completion of the research. The research examined the effect of using statistically derived sub-markets as opposed to geographically derived ones for property valuation. Cluster analysis was used during both phases of model development and showed that one of the clusters developed in the available data phase was superior in its model prediction compared to the models produced using geographically derived regions. A number of limitations with the digital property data available for Victoria were found. Although GIS analysis can enable more property characteristics to be derived and measured from existing data, it is reliant on having access to suitable digital data. The research also identified limitations with the metadata elements in use in Victoria (ANZMETA DTD version 1). It is hypothesised that to further refine the models and achieve greater levels of price estimation, additional properties would need to be sourced and added to the current property database. It is suggested that additional research needs to address issues associated with sub-market identification. If results of additional modelling indicated significantly different levels of price estimation, then these models could be used with manual techniques to evaluate manually derived valuation estimates
The efficacy of self-management strategies for females with endometriosis : a systematic review
Self-management is critical for the care of endometriosis. Females with endometriosis frequently use self-management strategies to manage associated symptoms; however, the efficacy of such strategies is unknown. The aim of this review was to systematically appraise the evidence concerning efficacy of self-management strategies for endometriosis symptoms. Electronic databases, including Medline, Embase, Emcare, Web of Science Core Collection, Scopus, and the Cochrane Central Register of Controlled Trials, were searched from inception to March 2021. We included peer-reviewed experimental studies published in English evaluating the efficacy of self-management strategies in human females laparoscopically diagnosed with endometriosis. Studies underwent screening, data extraction, and risk of bias appraisal (randomised studies: Risk of Bias 2 tool; non-randomised studies: Risk Of Bias In Non-randomized Studies – of Interventions tool). Of the fifteen studies included, 10 evaluated dietary supplements, three evaluated dietary modifications, one evaluated over-the-counter medication, and one evaluated exercise. Most studies had a high-critical risk of bias. Many self-management strategies were not more effective at reducing endometriosis symptoms compared to placebo or hormonal therapies. Where studies suggest efficacy for self-management strategies, no recommendations can be made due to the poor quality and heterogeneity of evidence. High-quality empirical evidence is required to investigate the efficacy of self-management strategies for females with endometriosis
She: gothic reverberations in Star Trek: first contact
This essay discusses how the film Star Trek: First Contact uses the gothic tropes of the femme fatale as expressed in Rider Haggard's iconic text She. This is a collection of essays edited by Ben Brabon and Stephanie Genz
PomBase 2018: user-driven reimplementation of the fission yeast database provides rapid and intuitive access to diverse, interconnected information
PomBase (www.pombase.org), the model organism database for the fission yeast Schizosaccharomyces pombe, has undergone a complete redevelopment, resulting in a more fully integrated, better-performing service. The new infrastructure supports daily data updates as well as fast, efficient querying and smoother navigation within and between pages. New pages for publications and genotypes provide routes to all data curated from a single source and to all phenotypes associated with a specific genotype, respectively. For ontology-based annotations, improved displays balance comprehensive data coverage with ease of use. The default view now uses ontology structure to provide a concise, non-redundant summary that can be expanded to reveal underlying details and metadata. The phenotype annotation display also offers filtering options to allow users to focus on specific areas of interest. An instance of the JBrowse genome browser has been integrated, facilitating loading of and intuitive access to, genome-scale datasets. Taken together, the new data and pages, along with improvements in annotation display and querying, allow users to probe connections among different types of data to form a comprehensive view of fission yeast biology. The new PomBase implementation also provides a rich set of modular, reusable tools that can be deployed to create new, or enhance existing, organism-specific databases
The biosocial subject: sensor technologies and worldly sensibility
Sensor technologies are increasingly part of everyday life, embedded in buildings (movement, sound, temperature) and worn on persons (heart rate, electro-dermal activity, eye tracking). This paper presents a theoretical framework for research on computational sensor data. My approach moves away from theories of agent-centered perceptual synthesis (on behalf of a perceiving organism) and towards a more expansive understanding of the biosocial learning environment. The focus is on sensor technologies that track sensation below the bandwidth of human consciousness. I argue that there is an urgent need to reclaim this kind of biodata as part of an unequally distributed worldly sensibility, and to thereby undermine more narrow reductive readings of such data. The paper explores the biopolitical implications of recasting biodata in terms of trans-individual inhuman forces, while continuing to track the distinctive power of humans
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