Online Sorting via Searching and Selection

In this paper, we present a framework based on a simple data structure and parameterized algorithms for the problems of finding items in an unsorted list of linearly ordered items based on their rank (selection) or value (search). As a side-effect of answering these online selection and search queries, we progressively sort the list. Our algorithms are based on Hoare's Quickselect, and are parameterized based on the pivot selection method. For example, if we choose the pivot as the last item in a subinterval, our framework yields algorithms that will answer q<=n unique selection and/or search queries in a total of O(n log q) average time. After q=\Omega(n) queries the list is sorted. Each repeated selection query takes constant time, and each repeated search query takes O(log n) time. The two query types can be interleaved freely. By plugging different pivot selection methods into our framework, these results can, for example, become randomized expected time or deterministic worst-case time. Our methods are easy to implement, and we show they perform well in practice

Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection Scheme in Evolutionary Algorithms

Boltzmann selection is an important selection mechanism in evolutionary algorithms as it has theoretical properties which help in theoretical analysis. However, Boltzmann selection is not used in practice because a good annealing schedule for the `inverse temperature' parameter is lacking. In this paper we propose a Cauchy annealing schedule for Boltzmann selection scheme based on a hypothesis that selection-strength should increase as evolutionary process goes on and distance between two selection strengths should decrease for the process to converge. To formalize these aspects, we develop formalism for selection mechanisms using fitness distributions and give an appropriate measure for selection-strength. In this paper, we prove an important result, by which we derive an annealing schedule called Cauchy annealing schedule. We demonstrate the novelty of proposed annealing schedule using simulations in the framework of genetic algorithms

Justifying the design and selection of literacy and thinking tools

Criteria for the design and selection of literacy and thinking tools that allow educators to justify what they do are described within a wider framework of learning theory and research into best practice. Based on a meta-analysis of best practice, results from a three year project designed to evaluate the effectiveness of a secondary school literacy initiative in New Zealand, together with recent research from cognitive and neuro-psychologists, it is argued that the design and selection of literacy and thinking tools used in elementary schools should be consistent with (i) teaching focused (ii) learner focused, (iii) thought linked (iv) neurologically consistent, (v) subject specific, (vi) text linked, (vii) developmentally appropriate, and (viii) assessment linked criteria. Key words: Literacy, thinking, tools, justifying criteria

Choosing how to choose : Institutional pressures affecting the adoption of personnel selection procedures

The gap between science and practice in personnel selection is an ongoing concern of human resource management. This paper takes Oliver´s framework of organizations´ strategic responses to institutional pressures as a basis for outlining the diverse economic and social demands that facilitate or inhibit the application of scientifically recommended selection procedures. Faced with a complex network of multiple requirements, practitioners make more diverse choices in response to any of these pressures than has previously been acknowledged in the scientific literature. Implications for the science-practitioner gap are discussed

Penalized Likelihood and Bayesian Function Selection in Regression Models

Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonlinear functions in models with additive predictors has been considered only more recently. Several competing suggestions have been developed at about the same time and often do not refer to each other. This article provides a state-of-the-art review on function selection, focusing on penalized likelihood and Bayesian concepts, relating various approaches to each other in a unified framework. In an empirical comparison, also including boosting, we evaluate several methods through applications to simulated and real data, thereby providing some guidance on their performance in practice

Bidirectional branch and bound for controlled variable selection. Part III: local average loss minimization

The selection of controlled variables (CVs) from available measurements through exhaustive search is computationally forbidding for large-scale processes. We have recently proposed novel bidirectional branch and bound (B-3) approaches for CV selection using the minimum singular value (MSV) rule and the local worst- case loss criterion in the framework of self-optimizing control. However, the MSV rule is approximate and worst-case scenario may not occur frequently in practice. Thus, CV selection by minimizing local average loss can be deemed as most reliable. In this work, the B-3 approach is extended to CV selection based on local average loss metric. Lower bounds on local average loss and, fast pruning and branching algorithms are derived for the efficient B-3 algorithm. Random matrices and binary distillation column case study are used to demonstrate the computational efficiency of the proposed method

East Midlands FRESA targets project

Reviewed employment and skills targets in use by organisations in the East Midlands in order to inform the development of targets for the East Midlands Framework for Employment and Skills action (FRESA). Established target development process later adopted by emda for 2006 RES. Developed criteria for applying to future selection of economic performance monitoring metrics - especially for skills, based on extant best practice, such as the Treasury's 'Green Book'