Abstract
The integrated planning of several activities implicated in paper production can lead to remarkable gains in terms of raw materials and resource usage. However, activities such as order assignment, production sequencing and cutting planning are usually addressed separately while ignoring the interactions among these processes. But the quality of the solution resulting from the juxtaposition of the partial solutions is not guaranteed, and may have a significant impact in terms of inefficiency of global performance. This article considers production planning in a pulp and paper industry in order to meet a set of orders of diverse types of products, admitting the possibility of producing simultaneously in two or more paper machines with their own features. The developed approach, ASC-3Steps, considers not only cutting optimisation but also extends itself to the processes of assigning orders to paper machines and production sequencing at each machine. Minimisation of wasted paper is assumed to be the overall goal. A set of computational results based on real data is presented.

Abstract

Abstract
The proposed sensing device relies on the self-imaging effect that occurs in a pure silica multimode fiber (coreless MMF) section of a single-mode-multimode-single-mode (SMS)-based fiber structure. The influence of the coreless-MMF diameter on the external refractive index (RI) variation permitted the sensing head with the lowest MMF diameter (i.e., 55 mu m) to exhibit the maximum sensitivity (2800 nm/RIU). This approach also implied an ultrahigh sensitivity of this fiber device to temperature variations in the liquid RI of 1.43: a maximum sensitivity of -1880 pm/degrees C was indeed attained. Therefore, the results produced were over 100-fold those of the typical value of approximately 13 pm/degrees C achieved in air using a similar device. Numerical analysis of an evanescent wave absorption sensor was performed, in order to extend the range of liquids with a detectable RI to above 1.43. The suggested model is an SMS fiber device where a polymer coating, with an RI as low as 1.3, is deposited over the coreless MMF; numerical results are presented pertaining to several polymer thicknesses in terms of external RI variation. (C) 2012 Optical Society of America

Abstract

Abstract
This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). MDS is a computational and statistical technique that produces a spatial representation of similarity between objects through factors of relatedness. MDS represents in a low dimensional map data points whose similarities are defined in a higher dimensional space. Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

Abstract
Precision-recall (PR) curves and the areas under them are widely used to summarize machine learning results, especially for data sets exhibiting class skew. They are often used analogously to ROC curves and the area under ROC curves. It is known that PR curves vary as class skew changes. What was not recognized before this paper is that there is a region of PR space that is completely unachievable, and the size of this region depends only on the skew. This paper precisely characterizes the size of that region and discusses its implications for empirical evaluation methodology in machine learning. Copyright 2012 by the author(s)/owner(s).