Improved career decision-making through the use of labor market information /

Mode of access: Internet.

Making money in the stock market,

Mode of access: Internet.

Manual for dairy manufacturing short courses. Course I.-Testing dairy products and the manufacture of butter and cheese. Course II.-Ice cream making. Course III.-Market milk and milk control.

Mode of access: Internet.

Manures : how to make and how to use them : a new practical treatise on the chemistry of manures and manure-making, written specially for the use of farmers, horticulturists and market gardeners /

Mode of access: Internet.

Competition and price making in food retailing: the anatomy of super market operations.

Mode of access: Internet.

Does reviewing lead to better learning and decision making? Answers from a randomized stock market experiment

Background - The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives - The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods - We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results - The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

The Role of Non-Market Valuation in Forest Management and Recreation Policy

Forests, and particularly those where native and mixed species are gown, provide a variety of non-wood values, important among which are recreation and environmental services. Substantial progress has been made in recent years in estimating economic values on these services. A considerable amount of research on forest values has been carried out recently in tropical and sub-tropical eastern Australia, some of which is reported in the following papers. The need for estimates of non-wood forest benefits is apparent, and it is clear that further development of techniques and a greater understanding of the way these values can be integrated into public-sector decision making is required.

Segmenting the market of West Australian senior tourists using an artificial neural network

Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.

Risk Aversion in a Mixed-Integer Nonlinear Approach to Support Decision-Making for a Hydro Power Producer

In this paper, a mixed-integer nonlinear approach is proposed to support decision-making for a hydro power producer, considering a head-dependent hydro chain. The aim is to maximize the profit of the hydro power producer from selling energy into the electric market. As a new contribution to earlier studies, a risk aversion criterion is taken into account, as well as head-dependency. The volatility of the expected profit is limited through the conditional value-at-risk (CVaR). The proposed approach has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems.

Portugal making a difference with children and families: the GADIF model

Portugal is a culture grounded in strong traditions and family. Yet, social changes like women returning to the workforce and a decreas ed national birth rate are impacting the traditional family structure and care giving environments of children. Female employment has been increasing steadily in P ortugal over the last three decades (Galego & Pereira, 2006) and the total fert ility rate decreasing from 4.1 to 2.8 (INE, 2006). Furthermore, extended family me mbers, like grandparents, no longer reside close by to their children and grandc hildren as in the past, because of a changing labor market. Many of the younger gen eration are leaving their rural communities to flock to urban areas because o f job opportunities, leaving behind older relatives who would have otherwise par ticipated in the daily care of children. Given these social and economic changes, children are spending more time in out-of-home care with non-familial caregive rs. Yet, government regulations and guidelines in early care and educat ion (ECCE) and early intervention (EI) are only just emerging; it contin ues to be a work in progress.