Transforming Rehabilitation as ‘policy disaster’: Unbalanced policy-making and probation reform

This paper utilizes the notion of ‘policy disasters’ to examine the policy developments that led to the part-privatization and marketization of probation services in England and Wales – Transforming Rehabilitation. Specifically, it examines the ‘internal’ component of policy disasters, drawing on semi-structured interviews with senior policymakers and other relevant sources. The findings presented demonstrate that the policy dynamics relating to Transforming Rehabilitation specifically, and the departmental budget as an important underlying component, were both distinctly ‘unbalanced’. This is argued to be an important explanatory factor in its damagingly swift implementation and operationalization. In closing, the paper reflects on the policy studies notion of ‘policy equilibrium’ to consider whether the policy landscape relating to probation in England and Wales has reached a ‘steady state’, or whether the ongoing apparent failings of the Transforming Rehabilitation reforms may result in a further round of considerable policy change.

Discrete Particle Swarm Optimization with Scout Particles for Library Materials Acquisition

Materials acquisition is one of the critical challenges faced by academic libraries. This paper presents an integer programming model of the studied problem by considering how to select materials in order to maximize the average preference and the budget execution rate under some practical restrictions including departmental budget, limitation of the number of materials in each category and each language. To tackle the constrained problem, we propose a discrete particle swarm optimization (DPSO) with scout particles, where each particle, represented as a binary matrix, corresponds to a candidate solution to the problem. An initialization algorithm and a penalty function are designed to cope with the constraints, and the scout particles are employed to enhance the exploration within the solution space. To demonstrate the effectiveness and efficiency of the proposed DPSO, a series of computational experiments are designed and conducted. The results are statistically analyzed, and it is evinced that the proposed DPSO is an effective approach for the studied problem.

Putting Artificial Intelligence And Expert Systems To Work for The Hospitality Industry

Artificial intelligence (AI) has existed formally as a field of science and technology for over thirty years. 109634808801200264Nevertheless, it has no precise definition due to it's diversity. Over the years Al has developed into three principal branches: expert systems, natural language communication, and robotics. Expert systems (ES) among the three branches is currently attracting much attention and is of most interest to many professionals as well as organizations. However, the development of expert systems—the computer programs that emulate the thinking processes of human brain in solving problems—is very complex and extremely costly. Although the current applications of ES are mainly is space exploration, it should be noted that some of the greatest opportunities for expert systems in the hospitality industry lie in small, routine, everyday tasks like departmental budget analysis, shift scheduling, credit verification, and room assignment.