A rapid and accurate method to determine or predict cattle diet quality is essential to effectively manage free-ranging cattle production. One popular tool currently available for predicting cattle diet quality is fecal Near Infrared Reflectance Spectroscopy (NIRS) profiling, which requires considerable time and financial investment. Two approaches were taken to develop a replacement of NIRS fecal analysis for predicting real-time cattle diet quality. The first approach took advantage of a standing forage quantity monitoring and prediction model, and its animal diet selection sub model to model cattle diet quality. The second approach tested if a direct relationship is present between cattle diet quality and a simple temperature driven variable. The model used in the first approach is Phytomass Growth Model (PHYGROW). Using the Growing Degree Days (GDD) concept, forage crude protein estimation equations were developed. Coupled with PHYGROW diet selection sub model, cattle diet quality values were modeled. The validation study revealed good correlation between predicted diet quality and observed diet quality (r2=0.84). The Grazing Animal Nutrition lab (GAN lab) commercial fecal NIRS analyzing data for Major Land Resource Area 42 (MLRA 42) was used to analyze the relationship between GDD and cattle diet crude protein (CP). Repeatable high quality regressions were found for CP and GDD. A simple temperature based model was then developed to predict cattle diet quality for regional use. Another independent dataset for MLRA 116B from the GAN lab fecal NIRS data and a controlled grazing study were used to validate the relationship. The study showed that using GDD to predict cattle diet quality is a dependable tool, but regional specific relationships need to be developed. The two developed models set the foundation for remotely predicting cattle diet quality for effectively managing cattle production. The approaches also set the framework for developing broader applications for other animal species.

Ma thèse se situe dans le domaine de l'Ingénierie de l'Interaction Homme Machine. Le sujet traite de l'adaptation des systèmes interactifs à un contexte d'usage varié, variable et imprévisible. Par contexte d'usage, on entend le triplet . J'identifie trois gammes d'approches : l'Ingénierie Dirigée par les Modèles (IDM), les approches par boîtes à outils (BàO) d'interacteurs plastiques et enfin les approches agissant au niveau du système d'exploitation (OS). L'IDM et les approches OS se rejoignent autour des BàO. Je contribue par la proposition d'une BàO d'interacteurs plastiques : les COMET. Les COMET sont un style d'architecture logicielle. Ce style permet de considérer un interacteur selon les quatre niveaux d'abstraction couramment admis en IHM : tâche, interfaces abstraite, concrète et finale. Les COMET peuvent être rendues simultanément dans plusieurs technologies : TK, AJAX, B207 (post-WIMP) et S207 (vocal). Elles sont extensibles dynamiquement, mettant à profit un graphe de descriptions (GDD) jouant le rôle d'annuaire d'IHM. Les COMET sont transformables à l'aide d'un langage de style CSS++. Tous ces travaux (COMET, GDD et CSS++) s'assemblent dans la vision d'Ecosystème que je propose.

Personas (typanvändare) är ett populärt verktyg för interaktionsdesigners och gör det möjligt att, bland annat, uppfatta skillnader mellan en ofta stor mängd potentiella användare och därefter anpassa en design efter detta. Men hur användbart är detta verktyg om användarantalet är litet och deras mål i huvudsak styrs av deras identiska arbetsuppgifter? Interaktionsdesigners som vill försäkra sig om att de skapar användarvänliga applikationer bedriver ofta någon from av datainsamling och testning, från och med användare. Det finns flera kända metoder för analys av data som samlats in från kvalitativa studier. Det finns dock färre konkreta riktlinjer för vilka frågor man bör söka svar på under själva datainsamlingen. Detta varierar så klart kraftigt beroende på vilken kontext man befinner sig och någon universell lista med frågeställningar som alltid täcker in det man behöver kommer sannolikt aldrig att existera. Bardram (2000) och hans kollegor har dock sammanställt en checklista med frågeställningar de utvecklat under utvecklingen av ett nytt informationssystem för Danska sjukhus. Ett sådant system är väldigt komplext så det finns anledning att undersöka hur väl deras checklista fungerar för enklare system. I denna studie utvärderades nyttan av personas och Bardrams (2000) checklista som verktyg under ett designprojekt i en miljö med ett fåtal användare, vars uppgifter i huvudsak styrs av deras identiska arbetsuppgifter och komplexiteten i systemet är liten. Resultatet visade att personas är ett lämpligt verktyg trots likheten mellan användarna. Arbetet med att utveckla det som slutligen endast blev en persona gav författaren (tillika studiens interaktionsdesigner) ett sätt att fastställa att deras mål faktiskt var väldigt lika. Personan var grunden i utvecklingsarbetet som slutade med en lyckad design. Även Bardrams (2000) checklista visade sig vara ett bra stöd under studiens gång. Författaren ger dock förslag på två punkter att lägga till i denna checklista.

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Peanut digging timing is difficult to predict due to indeterminate growth and peanut pods maturing underground, resulting in the need to research methods that provide consistent measurements, while reducing time and effort for farmers and researchers. Experiments were conducted to evaluate the accuracy of the Maturity Index 1 and Maturity Index 2 in predicting peanut grade, the accuracy of the North Carolina 2 degree day method in predicting peanut yield, and remote sensing vegetative indices sensitivity equivalence (SEq) to peanut Maturity Index 2 and harvest grade (TSMK) for cultivars IPG-914 and Georgia-06G in Mississippi. Maturity Index 1 and Maturity Index 2 were found to be inaccurate predictions of peanut grade in Mississippi, suggesting a need to examine the contributions of individual color classes in new genotypes to predict grade and yield. The North Carolina 2 degree day method was found to have a moderate to strong relationship with yield, indicating its potential usefulness in determining digging timing. Results also showed red edge indices were more sensitive to changes in pod maturity and grade. Peanut genotype selection is critical for maximizing peanut grade and yield on farm. Experiments were conducted to evaluate 32 genotypes for maturity, grade, and yield. Several early maturing genotypes showed promise for improving yield and grade without reducing quality, particularly 'UF11x23-3-6-1-1', '16-1-2147', '16-1-2142', '14x029-1-5-1-1', and '14x022-1-2-1-2'. The results suggest earlier maturing genotypes may be a solution to the late-season harvest risk of crop loss due to poor digging conditions, rain, and frost, while maintaining similar pod grades and yield to the current market-leading cultivars. The findings of this study contribute to the ongoing effort to optimize digging timing and improve peanut yields in Mississippi, where peanut farmers face the dual challenges of climatic variability and genotype selection. Future research is needed to examine the adaptability of genotypes on differing soil types, management, and climates throughout Mississippi. Overall, this study highlights the need for more effective and accurate methods for determining digging timing in peanut crops, which is crucial for their grade, and yield.

A linear space is a set of points and lines such that any pair of points lie on exactly one line together. This is equivalent to a pairwise balanced design PBD(v, K), where there are v points, lines are regarded as blocks, and K ⊆ Z≥2 denotes the set of allowed block sizes. The dimension of a linear space is the maximum integer d such that any set of d points is contained in a proper subspace. Specifically for K = {3, 4, 5}, we determine which values of v admit PBD(v,K) of dimension at least three for all but a short list of possible exceptions under 50. We also observe that dimension can be reduced via a substitution argument. / Graduate / 0405 / jniezen@uvic.ca

When creating computer games it is necessary to use extensive documentation so that everybody involved in the creative process is up to date. This paper has investigated what prospects there are to improve the GDD process to a more updated version that would be less linear in its format and more user-friendly to everybody involved.  This paper evaluates the game designers’ available tools which were found to be inadequate to do an effective job, mostly because they are not suited for the complex task that is contemporary GDD creation and maintenance.  It was also found that there exists software technology and methodology to address some of these problems; but no evidence has been found that it has been implemented for the computer game industry in a useful manner.  Lastly, a suggestion for a framework that would use a more visual and amorphous workflow derived from the discussed theory is presented. This framework uses an open nomenclature in a node-graph structure where every node represents different entities/objects in the game and is connected to each other by their interaction between attributes.

TerraSAR-X images have been tested for agricultural fields of corn and wheat. The main purpose was to evaluate the impact of daily temperatures in crop development to optimize climate induced factors on the plant growth anomalies. The results are completed by utilizing Geographic Information Science, e.g. tools of ArcMap 10.3.1 and databases of ground truth and meteorological information. Synthetic Aperture Radar (SAR) images from German Aerospace Center (DLR) are acquired and the field survey datasets are sampled, each per month for three years (2010-2012) but only for the crop seasons (April-October). Correlation between SAR images and farmland anomalies is investigated in accordance with daily heat accumulations and a comparison of the three years’ SAR backscatter signatures is explained for corn and wheat. Finding the influence of daily temperatures on crops and hence on the TerraSAR-X backscatter is developed by Growing Degree Days (GDD) which appears to be the most suitable parameter for this purpose. Observation of GDD permits that the coolest year was 2010, either rest of the years were warmer and GDD accumulated in 2011 was higher as compared to that of 2012 in the first half of the year, however 2012 had rather more heat accumulation in the second half of the year. SAR backscatter from farmland depicts the crop development stages which depend upon the time when satellite captures data during the crop season. It varies with different development stages of crop plants. Backscatter of each development stage changes as the roughness and the moisture content (dielectric property) of the plants changes and local temperature directly impacts crop growth and hence the development stages.

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