Results of a User Study on 2D Hurricane Visualization

We present the results from a user study looking at the ability of observers to mentally integrate wind direction and magnitude over a vector field. The data set chosen for the study is an MM5 (PSU/NCAR Mesoscale Model) simulation of Hurricane Lili over the Gulf of Mexico as it approaches the southeastern United States. Nine observers participated in the study. This study investigates the effect of layering on the observer's ability to determine the magnitude and direction of a vector field. We found a tendency for observers to underestimate the magnitude of the vectors and a counter‐clockwise bias when determining the average direction of a vector field. We completed an additional study with two observers to try to uncover the source of the counter‐clockwise bias. These results have direct implications to atmospheric scientists, but may also be able to be applied to other fields that use 2D vector fields.     

A Survey of Inverse Surface Design From Light Transport Behavior Specification

Inverse surface design problems from light transport behavior specification usually represent extremely complex and costly processes, but their importance is well known. In particular, they are very interesting for lighting and luminaire design, in which it is usually difficult to test design decisions on a physical model in order to avoid costly mistakes. In this survey, we present the main ideas behind these kinds of problems, characterize them, and summarize existing work in the area, revealing problems that remain open and possible areas of further research.     

A study into the effects of personality type and methodology on cohesion in software engineering teams

The aim of the research described in this paper is to gain a qualitative understanding of how cohesiveness relates to personality type, performance and adherence to a particular software engineering methodology (XP). A variety of research methods were employed including ethnographic methods, questionnaires and interviews. An online personality test based on the Myers-Briggs Type Indicator (MBTI) was used to ascertain the personality types, and questionnaires were used throughout the project to measure levels of cohesiveness. Examples of how the teams worked together throughout the project are described, and whether and how this relates to the personality types of the individual members. The results indicate that certain teams were found to work consistently well over the project due to homogeneity in personality type and others were found to be very cohesive due to a mixture of types.     

A farm level approach to define successful mitigation strategies for GHG emissions from ruminant livestock systems

Ruminant livestock systems are a significant source of greenhouse gases (GHGs). Thus far, mitigation options for GHG emissions mainly focused on a single gas, and are treated as isolated activities. The present paper proposes a framework for a farm level approach for the full accounting of GHG emissions. The methodology accounts for the relevant direct and indirect emissions of methane, nitrous oxide and carbon dioxide, including carbon sequestration. Furthermore, the potential trade-off with ammonia volatilisation and nitrate leaching are taken into account. A ruminant livestock farm is represented with a conceptual model consisting of five pools: animal, manure, soil, crop and feed. The carbon and nitrogen inputs, throughputs and outputs are described, and the direct emissions are related to the carbon and nitrogen flows. The indirect emissions included in the methodology are mainly carbon dioxide emissions from energy use and nitrous oxide emissions related to imported resources and nitrogen losses. The whole farm approach is illustrated with a case of two dairy farms with contrasting livestock density and grassland management. It is shown that the inclusion of carbon sequestration and all indirect emissions have a major impact on the GHG budget of the farm. For one farm, the effect of four mitigation options on the GHG emissions was quantified. It was concluded that a whole farm approach of full accounting contributes to a better insight in the interactions between the carbon and nitrogen flows and the resulting emissions, within and outside the farm boundaries. Consequently, the methodology can be used to develop efficient and effective mitigation strategies.     

Inverse Procedural Modelling of Trees

Procedural tree models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such models and their parameters is a difficult task. We propose an inverse modelling approach for stochastic trees that takes polygonal tree models as input and estimates the parameters of a procedural model so that it produces trees similar to the input. Our framework is based on a novel parametric model for tree generation and uses Monte Carlo Markov Chains to find the optimal set of parameters. We demonstrate our approach on a variety of input models obtained from different sources, such as interactive modelling systems, reconstructed scans of real trees and developmental models.     

Variational Tree Synthesis

Modelling trees according to desired shapes is important for many applications. Despite numerous methods having been proposed in tree modelling, it is still a non‐trivial task and challenging. In this paper, we present a new variational computing approach for generating realistic trees in specific shapes. Instead of directly modelling trees from symbolic rules, we formulate the tree modelling as an optimization process, in which a variational cost function is iteratively minimized. This cost function measures the difference between the guidance shape and the target tree crown. In addition, to faithfully capture the branch structure of trees, several botanical factors, including the minimum total branches volume and spatial branches patterns, are considered in the optimization to guide the tree modelling process. We demonstrate that our approach is applicable to generate trees with different shapes, from interactive design and complex polygonal meshes.     

Characterization of the Oum El Khacheb phosphorites(South Tunisia)and enrichment of big rejections by grinding

In the last decade, the phosphate reserves have started to decrease. In this study, both phosphate of Oum El Khacheb's(O.E.K) region(South of Tunisia) and its big rejections were characterized mineralogically and chemically by several analysis methods such as the binocular magnifying glass, X-rays diffraction technique, Technicon auto-analyzer, atomic absorption spectroscopy, and carbon sulfur analyzer. Then,this work focuses on the coarse rejections of O.E.K's phosphorites which can be valorized by the wet grinding method. Therefore, we have used the methodology of experimental research to determine the optimal grinding conditions. Results found by Doelhert matrix are: a duration at about 4 min, a pulp on solid concentration of 45.00%, a number of cycles equals to 60 rpm and 3.87 as the jar's loading.The enhancement of the weight yields of phosphate recuperation increased significantly by 46.39% from big rejections with 24.60% of P_2O_5 concentration.