Description:
The problem of the estimation of a regression function by continuous piecewise linear functions is formulated as a nonconvex, nonsmooth optimization problem. Estimates are defined by minimization of the empirical L 2 risk over a class of functions, which are defined as maxima of minima of linear functions. An algorithm for finding continuous piecewise linear functions is presented. We observe that the objective function in the optimization problem is semismooth, quasidifferentiable and piecewise partially separable. The use of these properties allow us to design an efficient algorithm for approximation of subgradients of the objective function and to apply the discrete gradient method for its minimization. We present computational results with some simulated data and compare the new estimator with a number of existing ones.
Description:
This paper introduces the notion of piecewise partially separable functions and studies their properties. We also consider some of many applications of these functions. Finally, we consider the problem of minimizing of piecewise partially separable functions and develop an algorithm for its solution. This algorithm exploits the structure of such functions. We present the results of preliminary numerical experiments.
Description:
This paper introduces the notion of piecewise partially separable functions and studies their properties. We also consider some of many applications of these functions. Finally, we consider the problem of minimizing of piecewise partially separable functions and develop an algorithm for its solution. This algorithm exploits the structure of such functions. We present the results of preliminary numerical experiments.
Description:
Teachers' informed acceptance of challenges associated with teaching technology might ensure the successful implementation of a Technology syllabus in primary schools. They must be prepared to analyse their own understandings of technology concepts and processes, teaching and resource needs, and engage in professional development activities designed to meet their needs. This paper investigates the introduction of a new Technology syllabus into a school and draws on a number of data sources, for example, surveys, interviews with individual teachers, classroom observations, and field notes. It was evident that very specific personal and classroom related issues (e.g., content and pedagogy), and broader issues related to the school and wider communities (e.g., resources and networking), impacted on teachers' acceptance of the syllabus. Based on these findings, the influence of 20 years of technology education and associated research on the essentials of classroom syllabus implementation by teachers is evaluated. Ways of making this store of knowledge and expertise more meaningful and accessible for teachers are explored. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Technology & Design Education is the property of Springer Science & Business Media B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Description:
Teachers' informed acceptance of challenges associated with teaching technology might ensure the successful implementation of a Technology syllabus in primary schools. They must be prepared to analyse their own understandings of technology concepts and processes, teaching and resource needs, and engage in professional development activities designed to meet their needs. This paper investigates the introduction of a new Technology syllabus into a school and draws on a number of data sources, for example, surveys, interviews with individual teachers, classroom observations, and field notes. It was evident that very specific personal and classroom related issues (e.g., content and pedagogy), and broader issues related to the school and wider communities (e.g., resources and networking), impacted on teachers' acceptance of the syllabus. Based on these findings, the influence of 20 years of technology education and associated research on the essentials of classroom syllabus implementation by teachers is evaluated. Ways of making this store of knowledge and expertise more meaningful and accessible for teachers are explored. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Technology & Design Education is the property of Springer Science & Business Media B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Description:
In this chapter we study the turnpike property for the nonconvex optimal control problems described by the differential inclusion . We study the infinite horizon problem of maximizing the functional as T grows to infinity. The purpose of this chapter is to avoid the convexity conditions usually assumed in turnpike theory. A turnpike theorem is proved in which the main conditions are imposed on the mapping a and the function u. It is shown that these conditions may hold for mappings a with nonconvex images and for nonconcave functions u.
Description:
This research advances the understanding of the location of perceived landscape values through a statistically based approach to spatial analysis of value densities. Survey data were obtained from a sample of people living in and using the Murray River region, Australia, where declining environmental quality prompted a reevaluation of its conservation status. When densities of 12 perceived landscape values were mapped using geographic information systems (GIS), valued places clustered along the entire river bank and in associated National/State Parks and reserves. While simple density mapping revealed high value densities in various locations, it did not indicate what density of a landscape value could be regarded as a statistically significant hotspot or distinguish whether overlapping areas of high density for different values indicate identical or adjacent locations. A spatial statistic Getis-Ord Gi* was used to indicate statistically significant spatial clusters of high ! value densities or "hotspots". Of 251 hotspots, 40% were for single non-use values, primarily spiritual, therapeutic or intrinsic. Four hotspots had 11 landscape values. Two, lacking economic value, were located in ecologically important river red gum forests and two, lacking wilderness value, were near the major towns of Echuca-Moama and Albury-Wodonga. Hotspots for eight values showed statistically significant associations with another value. There were high associations between learning and heritage values while economic and biological diversity values showed moderate associations with several other direct and indirect use values. This approach may improve confidence in the interpretation of spatial analysis of landscape values by enhancing understanding of value relationships.
Description:
Effective multiple clustering systems, or clusterers, have important applications in information security. The aim of the present article is to introduce a new method of designing multiple clusterers based on the Munn rings and describe a class of optimal clusterers which can be obtained in this construction.
Description:
Effective multiple clustering systems, or clusterers, have important applications in information security. The aim of the present article is to introduce a new method of designing multiple clusterers based on the Munn rings and describe a class of optimal clusterers which can be obtained in this construction.
Description:
We study convergence properties of a modified subgradient algorithm, applied to the dual problem defined by the sharp augmented Lagrangian. The primal problem we consider is nonconvex and nondifferentiable, with equality constraints. We obtain primal and dual convergence results, as well as a condition for existence of a dual solution. Using a practical selection of the step-size parameters, we demonstrate the algorithm and its advantages on test problems, including an integer programming and an optimal control problem
Description:
A 10-month study of surface waters in Canadian Creek (Ballarat, Victoria, Australia) showed the significant influence of historic gold mining waste material. The investigation focussed on the hydrogeochemistry of the surface waters and soils in order to: (1) document the levels and seasonal trends in major, minor and trace elements in the creek, (2) identify the process by which As is released from the soil/waste mining material to surface waters. For most dissolved major and trace elements (Na, Ca, Mg, K, and As) in surface waters, the concentrations decreased with the increasing rainfall and flow conditions except for Al and Fe. Two sites selected along the creek (<1 km apart) allowed evaluation of the possibility that mining waste material is contributing to the elevated As concentrations (up to 145
Description:
Gall induction by arthropods results in a range of morphological and physiological changes in their host plants. We examined changes in gas exchange, nutrients, and energetics related to the presence of stem galls on Parthenium hysterophorus L. (Asteraceae) induced by the moth, Epiblema strenuana Walker (Lepidoptera: Tortricidae). We compared the effects of galls on P. hysterophorus in the rosette (young), pre-flowering (mature), and flowering (old) stages. Gall induction reduced the leaf-water potential, especially in flowering stage plants. In young and mature stage plants, galling reduced photosynthetic rates considerably. Gall induction reduced the transpiration rate mostly in mature plants, and this also diminished stomatal conductance. Energy levels in most galls and in shoot tissue immediately below the galls were significantly higher than the energy levels in stem tissue immediately above the galls, indicating that the gall acts as a mobilizing sink for the moth. Galling had significant effects on concentrations of minerals such as boron, chloride, magnesium, and zinc. In galled plants, reduced leaf-water potential and reduced rates of photosynthesis, transpiration, and stomatal conductance may have altered mineral element levels. These observed effects demonstrate that E. strenuana has the potential to regulate P. hysterophorus.
Description:
Gall induction by arthropods results in a range of morphological and physiological changes in their host plants. We examined changes in gas exchange, nutrients, and energetics related to the presence of stem galls on Parthenium hysterophorus L. (Asteraceae) induced by the moth, Epiblema strenuana Walker (Lepidoptera: Tortricidae). We compared the effects of galls on P. hysterophorus in the rosette (young), pre-flowering (mature), and flowering (old) stages. Gall induction reduced the leaf-water potential, especially in flowering stage plants. In young and mature stage plants, galling reduced photosynthetic rates considerably. Gall induction reduced the transpiration rate mostly in mature plants, and this also diminished stomatal conductance. Energy levels in most galls and in shoot tissue immediately below the galls were significantly higher than the energy levels in stem tissue immediately above the galls, indicating that the gall acts as a mobilizing sink for the moth. Galling had significant effects on concentrations of minerals such as boron, chloride, magnesium, and zinc. In galled plants, reduced leaf-water potential and reduced rates of photosynthesis, transpiration, and stomatal conductance may have altered mineral element levels. These observed effects demonstrate that E. strenuana has the potential to regulate P. hysterophorus.
Description:
The nonsmooth optimization methods can mainly be divided into two groups: subgradient and bundle methods. Usually, when developing new algorithms and testing them, the comparison is made between similar kinds of methods. The goal of this work is to test and compare different bundle and subgradient methods as well as some hybrids of these two and/or some others. The test set included a large amount of different unconstrained nonsmooth minimization problems, e.g., convex and nonconvex problems, piecewise linear and quadratic problems, and problems with different sizes. Rather than foreground some method over the others, our aim is to get some insight on which method is suitable for certain types of problems.
Description:
Existing generative classifiers (e.g., BayesNet and AnDE) make independence assumptions and estimate one-dimensional likelihood. This paper presents a new generative classifier called MassBayes that estimates multi-dimensional likelihood without making any explicit assumptions. It aggregates the multi-dimensional likelihoods estimated from random subsets of the training data using varying size random feature subsets. Our empirical evaluations show that MassBayes yields better classification accuracy than the existing generative classifiers in large data sets. As it works with fixed-size subsets of training data, it has constant training time complexity and constant space complexity, and it can easily scale up to very large data sets.
Description:
This chapter considers the characteristics of employer practices concerning age management, with specific reference to career management and learning among European employers. Using data collected for a recent European study of employer behaviour regarding workforce ageing we conceptualise the policy approach in organizations and how this is manifested in the experiences of employees. The chapter begins by examining recent changes in the way career management and learning are viewed, particularly the shift away from conceptualisations based on the notion that career management and learning are the prerogative of the young towards a perspective based on a more inclusive notion of career management learning taking place at different transition points in the lifecycle.
Description:
Dynamic Bayesian networks (DBN) are widely applied in Systems biology for modeling various biological networks, including gene regulatory networks and metabolic networks. The application of DBN models often requires data discretization. Although various discretization techniques exist, currently there is no consensus on which approach is most suitable. Popular discretization strategies within the bioinformatics community, such as interval and quantile discretization, are likely not optimal. In this paper, we propose a novel approach for data discretization for mutual information based learning of DBN. In this approach, the data are discretized so that the mutual information between parent and child nodes is maximized, subject to a suitable penalty put on the complexity of the discretization. A dynamic programming approach is used to find the optimal discretization threshold for each individual variable. Our approach iteratively learns both the network and the discretization scheme until a locally optimal solution is reached. Tests on real genetic networks confirm the effectiveness of the proposed method.