Intensive alternatives to custody process evaluation of pilots in five areas

A qualitative process evaluation of five Intensive Alternative to Custody (IAC) pioneer areas was undertaken to assess implementation of IAC, identify approaches to implementation and capture the lessons learnt. The findings indicated that many of the persistent offenders (those with at least 29 prior convictions) targeted by pilots were positive about the IAC order. Although intensive, it provided order and stability, allowing them to move away from a criminal lifestyle. Sentencers welcomed the order as a viable alternative to custody. Probation staff and partners were equally positive about its efficacy. Only one in four IAC orders were revoked because requirements were breached, which suggests that the pilots had managed to engage many of the offenders

"I Ain't No Tea Lady": Identifying and addressing barriers to non-traditional employment, training and education from a female perspective, SOVA

The aim of this research was to examine perceptions and experiences of accessing non-traditional Education Training and Employment (ETE) from the vantage point of disadvantaged women using innovative sampling and research techniques. The research design and strategy sought to access the participant’s views and valuable experience. Many of the women whose opinions the research was trying to elicit had never considered non-traditional ETE, in their own words it simply was 'not on their radar'. We decided to adopt a 'workshop' approach. A workshop format was designed which used fun and thought provoking exercises to promote discussion. These interactive and dynamic workshops proved successful in generating some excellent data. In total 80 women from a range of areas of disadvantage participated in the research

Evaluation of the South Yorkshire Restorative Justice programme (SYRJP)

The SYRJP was developed in partnership between South Yorkshire Police and the Local Criminal Justice Board (LCJB) with the aim of implementing a county wide model of Restorative Justice (RJ) for use in neighbourhood policing and other community applications. It is aimed at tackling low level crime and anti-social behaviour in neighbourhoods and gives police officers the discretion to use Youth and Adult Restorative disposals as an alternative to prosecution for low level offending behaviour where offenders have no previous convictions, make an admission of guilt and where both offender and victim consent to the RJ process

Enhancing the role of the voluntary and community sector - a case study of the Yorkshire and Humber Region

This report was commissioned by the Chief Executive of the National Offender Management Service (NOMS) to evaluate at ground level, using the Yorkshire and Humberside region as a case study, what is currently being achieved by the Prison and Probation Services in working with the Voluntary and Community Sector (VCS); and to identify and provide analysis of perceived barriers and make recommendations to improve the engagement of the sector

Offenders and E-Learning - a literature review on behalf of Becta

This literature review has been prepared by the Hallam Centre of Community Justice at Sheffield Hallam University, on behalf of Becta. The literature review provides a summary of existing research and knowledge relating to e-learning in the offending learning sector with a view to developing a range of e-maturity indicators across the sector. The review also highlights linkages with current Government policy in relation to offender learning and skills

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras. Imaging spectrometers are therefore often referred to as hyperspectral cameras (HSCs). Higher spectral resolution enables material identification via spectroscopic analysis, which facilitates countless applications that require identifying materials in scenarios unsuitable for classical spectroscopic analysis. Due to low spatial resolution of HSCs, microscopic material mixing, and multiple scattering, spectra measured by HSCs are mixtures of spectra of materials in a scene. Thus, accurate estimation requires unmixing. Pixels are assumed to be mixtures of a few materials, called endmembers. Unmixing involves estimating all or some of: the number of endmembers, their spectral signatures, and their abundances at each pixel. Unmixing is a challenging, ill-posed inverse problem because of model inaccuracies, observation noise, environmental conditions, endmember variability, and data set size. Researchers have devised and investigated many models searching for robust, stable, tractable, and accurate unmixing algorithms. This paper presents an overview of unmixing methods from the time of Keshava and Mustard's unmixing tutorial [1] to the present. Mixing models are first discussed. Signal-subspace, geometrical, statistical, sparsity-based, and spatial-contextual unmixing algorithms are described. Mathematical problems and potential solutions are described. Algorithm characteristics are illustrated experimentally.Comment: This work has been accepted for publication in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensin

Fuzzy spectral and spatial feature integration for classification of nonferrous materials in hyperspectral data

Hyperspectral data allows the construction of more elaborate models to sample the properties of the nonferrous materials than the standard RGB color representation. In this paper, the nonferrous waste materials are studied as they cannot be sorted by classical procedures due to their color, weight and shape similarities. The experimental results presented in this paper reveal that factors such as the various levels of oxidization of the waste materials and the slight differences in their chemical composition preclude the use of the spectral features in a simplistic manner for robust material classification. To address these problems, the proposed FUSSER (fuzzy spectral and spatial classifier) algorithm detailed in this paper merges the spectral and spatial features to obtain a combined feature vector that is able to better sample the properties of the nonferrous materials than the single pixel spectral features when applied to the construction of multivariate Gaussian distributions. This approach allows the implementation of statistical region merging techniques in order to increase the performance of the classification process. To achieve an efficient implementation, the dimensionality of the hyperspectral data is reduced by constructing bio-inspired spectral fuzzy sets that minimize the amount of redundant information contained in adjacent hyperspectral bands. The experimental results indicate that the proposed algorithm increased the overall classification rate from 44% using RGB data up to 98% when the spectral-spatial features are used for nonferrous material classification

Process evaluation of five integrated offender management pioneer areas

A qualitative process evaluation of five Integrated Offender Management (IOM) pioneer areas was undertaken to assess implementation of IOM, identify approaches to implementation and capture the lessons learnt. The findings indicated that IOM enabled structural changes, transforming the delivery of offender management. There was considerable commitment and enthusiasm for IOM at the sites, whilst acknowledging barriers to development such as definition, resourcing, governance and clarity of agency roles. Since the evaluation took place, the political and criminal justice landscape has changed somewhat, supporting a more locally driven approach which can draw on the learning directly from the pioneers which were shaped and delivered locally