A Feminist Exploration of Violence: How Language and Identity Shape Perceptions

Using research from across disciplines such as Criminology, Feminist Theory, and Social Psychology, the following paper presents a case for the restructuring of the present understanding of violence, victims, survivors, and perpetrators. The current definitions and understandings of each of these topics are narrow caricatures which results in the exclusion of many instances of violence. I complicate our understandings of victims and of perpetrators, to allow people thought of as unable to perpetrate violence, to be held accountable and those thought as unable to be victimized to be believed

Teaching social work in times of change

Social Work, a profession with explicit academic and practice links to social policy, is undergoing profound change and transformation. ( DOH 2009) As part of this ongoing critique, the teaching of social work is being increasingly questioned by the general public, employers and government. Over the last two years innovative research at the University of Lincoln, jointly undertaken by a team of academic researchers and former social work students, has been analysing the efficacy of teaching methods and university support systems. In particular, the effectiveness of the social work undergraduate degree programme in equipping graduates for the demands of front line practice is being evaluated. The paper draws on key themes identified by the research and shares findings relating to; • Good practice in teaching and learning; including what students value most from lecturers and how academics can best support students • The use of students in research; opportunities and pitfall

Some Lambda Calculus and Type Theory Formalized

"This paper is about our hobby." That is the first sentence of [MP93], the first report on our formal development of lambda calculus and type theory, written in autumn 1992. We have continued to pursue this hobby on and off ever since, and have developed a substantial body of formal knowledge, including Church-Rosser and standardizationtheorems for beta reduction, and the basic theory ofPure Type Systems (PTS) leading to the strengthening theorem and type checking algorithms for PTS. Some of this work is reported in [MP93, vBJMP94, Pol94b, Pol95]. In the present paper we survey this work, including some new proofs, and point out what we feel has been learned about the general issues of formalizing mathematics. On the technical side, we describe an abstract, and simplified, proof of standardization for beta reduction, not previously published, that doesnot mention redex positions or residuals. On the general issues, we emphasize the search for formal definitions that are convenient for formal proof and convincingly represent the intended informal concepts. The LEGO Proof Development System [LP92] was used to check the work in an implementation of the Extended Calculus of Constructions(ECC) with inductive types [Luo94]. LEGO is a refinement styleproof checker, publicly available by ftp and WWW, with a User's Manual [LP92] and a large collection of examples. Section 1.3 contains information on accessing the formal development described in this paper. Other interesting examples formalized in LEGO include program specification and data refinement [Luo91], strong normalization of System F [Alt93], synthetic domain theory [Reu95, Reu96], and operational semantics for imperative programs [Sch97]

Proviola: A Tool for Proof Re-animation

To improve on existing models of interaction with a proof assistant (PA), in particular for storage and replay of proofs, we in- troduce three related concepts, those of: a proof movie, consisting of frames which record both user input and the corresponding PA response; a camera, which films a user's interactive session with a PA as a movie; and a proviola, which replays a movie frame-by-frame to a third party. In this paper we describe the movie data structure and we discuss a proto- type implementation of the camera and proviola based on the ProofWeb system. ProofWeb uncouples the interaction with a PA via a web- interface (the client) from the actual PA that resides on the server. Our camera films a movie by "listening" to the ProofWeb communication. The first reason for developing movies is to uncouple the reviewing of a formal proof from the PA used to develop it: the movie concept enables users to discuss small code fragments without the need to install the PA or to load a whole library into it. Other advantages include the possibility to develop a separate com- mentary track to discuss or explain the PA interaction. We assert that a combined camera+proviola provides a generic layer between a client (user) and a server (PA). Finally we claim that movies are the right type of data to be stored in an encyclopedia of formalized mathematics, based on our experience in filming the Coq standard library.Comment: Accepted for the 9th International Conference on Mathematical Knowledge Management (MKM 2010), 15 page

Seasonal Climate Prediction for the Australian Sugar Industry Using Data Mining Techniques

The ability to predict rainfall with adequate certainty and lead time is beneficial to both industry and public. Periods of high or low seasonal rainfall can have many follow on effects to agriculture, industry, public health and, water supply and management. In order to implement decisions, planning and management strategies to contend with these issues, the ability to predict seasonal rainfall quantities is of great importance (Klopper et al., 2006).\ud Climate conditions are known to influence the cultivation of Sugarcane influencing planting, harvesting and milling (Muchow and Wood, 1996; Everingham et al., 2002; Jones and\ud Everingham, 2005). Unforeseen climate events such as excessive rainfall, can adversely effect the agricultural practices related to Sugarcane cultivation. The Australian Sugarcane harvest period commences in May/June and aims to finish by November/December before the start of the rainy season (Everingham et al., 2002). The risk of excessive rainfall disrupting harvest operations is greatest towards the end of the sugarcane harvest period (Muchow and Wood, 1996; Everingham et al., 2002). Therefore, improved seasonal rainfall prediction during the October-December period is beneficial

Detecting trend and seasonal changes in bathymetry derived from HICO imagery: A case study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallow water inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used. Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than ± 20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as low as 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed

Improving the optimization solution for a semi-analytical shallow water inversion model in the presence of spectrally correlated noise

In coastal regions, shallow water semi-analytical inversion algorithms may be used to derive geophysical parameters such as inherent optical properties (IOPs), water column depth, and bottom albedo coefficients by inverting sensor-derived sub-surface remote sensing reflectance, rrs. The uncertainties of these derived geophysical parameters due to instrumental and environmental noise can be estimated numerically via the addition of spectral noise to the sensor-derived rrs before inversion. Repeating this process multiple times allows the calculation of the standard error and average for each derived parameter. Apart from spectral non-uniqueness, the optimization algorithm employed in the inversion must converge onto a single minimum to obtain a true representation of the uncertainty for a given set of noise-perturbed rrs. Failure to do so inflates the uncertainty and affects the average retrieved value (accuracy). We show that the standard approach of seeding the optimization with an arbitrary, fixed initial guess, can lead to the convergence to multiple minima, each having substantially different centroids in multi-parameter solution space. We present the Update-Repeat Levenberg-Marquardt (UR-LM) and Latin Hypercube Sampling (LHS) routines that dynamically search the solution space for an optimal initial guess, that when applied to the optimization allows convergence to the best local minimum. We apply the UR-LM and LHS methods on HICO-derived and simulated rrs and demonstrate the improved computational efficiency, precision, and accuracy afforded from these methods compared with the standard approach. Conceptually, these methods are applicable to remote sensing based, shallow water or oceanic semi-analytical inversion algorithms requiring nonlinear least squares optimization