A practical approach to object based requirements analysis

Presented here is an approach developed at the Unisys Houston Operation Division, which supports the early identification of objects. This domain oriented analysis and development concept is based on entity relationship modeling and object data flow diagrams. These modeling techniques, based on the GOOD methodology developed at the Goddard Space Flight Center, support the translation of requirements into objects which represent the real-world problem domain. The goal is to establish a solid foundation of understanding before design begins, thereby giving greater assurance that the system will do what is desired by the customer. The transition from requirements to object oriented design is also promoted by having requirements described in terms of objects. Presented is a five step process by which objects are identified from the requirements to create a problem definition model. This process involves establishing a base line requirements list from which an object data flow diagram can be created. Entity-relationship modeling is used to facilitate the identification of objects from the requirements. An example is given of how semantic modeling may be used to improve the entity-relationship model and a brief discussion on how this approach might be used in a large scale development effort

Hybrid church best practice : engagement and discipleship of 18-35 year olds

https://place.asburyseminary.edu/ecommonsatsdissertations/2714/thumbnail.jp

On resonance line profiles predicted by radiation driven disk wind models

We report on resonance line profiles predicted by radiation driven disk wind models which extend radially one order of magnitude farther out than our previous models. Our main result is that the inclusion of a disk wind at larger radii changes qualitatively and quantitatively the line profiles predicted by the models. Our new models predict line absorption that is significantly stronger than those predicted by old models. Some of the previous line profiles exhibit a doubled-humped structure near the line center which is now replaced by a more plausible single, blueshifted minimum. We emphasize that the improvements in the shape as well as the strength of the absorption were achieved without changing the gross properties of the wind. In particular, our new models do not predict a higher mass-loss rate than the previous models. The main changes in the line profiles are due to the fact that the ratio between the rotational velocity and poloidal velocity of the wind decreases downstream. The new line profiles reproduce well the line absorption of the nova-like variable, IX~Vel, and promise to reproduce observations of other cataclysmic variables. This success of the radiation driven disk wind model provides an important link between outflows in OB stars and outflows in active galactic nuclei.Comment: to appear in ApJ Lette

Effects of Prolonged Load Carriage of Knee Adduction Biomechanics

Introduction: Incidence of knee osteoarthritis (OA) in service members is twice that of the general population. Yet, it is currently unknown how body borne load and duration of walking with body borne load impact knee adduction, biomechanics linked to progression and severity of OA. Purpose: This study sought to examine magnitude and variability of knee adduction joint angle and moment throughout a prolonged walking task with body borne load. Methods: Eighteen participants had knee biomechanics quantified every five minutes while they walked at 1.3 m/s during a 60-minute over-ground walking task with three body-borne loads (unloaded, 15 kg and 30 kg). Statistical Analysis: Thirteen participants with complete data sets were submitted to statistical analysis. Peak of stance (0-100%) knee adduction joint angle and moment, initial contact and range of adduction motion, and coefficient of variation of peak knee adduction angle and moment, and range of adduction motion were submitted to a repeated measures ANOVA to test the main effect and interaction between time (0, 15, 30, 45 and 60 min) and load (0 ,15 and 30 kg). Results: Body borne load significantly increased peak knee adduction moment (p0.05); whereas duration of walking task significantly increased peak stance (p0.05). Conclusion: Prolonged walking with body borne load increased knee adduction biomechanics related to knee OA pathogenesis. The larger knee adduction moment exhibited with the addition of load and the larger knee adduction angle exhibited towards the end of the prolonged walking task may increase loading of the medial knee joint compartment and increase risk of knee OA

Plasticity in transmission strategies of the malaria parasite, Plasmodium chabaudi : environmental and genetic effects

Parasites may alter their behaviour to cope with changes in the within-host environment. In particular, investment in transmission may alter in response to the availability of parasite resources or host immune responses. However, experimental and theoretical studies have drawn conflicting conclusions regarding parasites' optimal (adaptive) responses to deterioration in habitat quality. We analyse data from acute infections with six genotypes of the rodent malaria species to quantify how investment in transmission (gametocytes) is influenced by the within-host environment. Using a minimum of modelling assumptions, we find that proportional investment in gametocytogenesis increases sharply with host anaemia and also increases at low parasite densities. Further, stronger dependence of investment on parasite density is associated with greater virulence of the parasite genotype. Our study provides a robust quantitative framework for studying parasites' responses to the host environment and whether these responses are adaptive, which is crucial for predicting the short-term and evolutionary impact of transmission-blocking treatments for parasitic diseases

Low-dimensional space- and time-coupled power system control policies driven by high-dimensional ensemble weather forecasts

Many predictive control problems can be solved at lower cost if the practitioner is able to make use of a high-dimensional forecast of exogenous uncertain quantities. For example, power system operators must accommodate significant short-term uncertainty in renewable energy infeeds. These are predicted using sophisticated numerical weather models, which produce an ensemble of scenarios for the evolution of atmospheric conditions. We describe a means of incorporating such forecasts into a multistage optimization framework able to make use of spatial and temporal correlation information. We derive an optimal procedure for reducing the size of the look-ahead problem by generating a low-dimensional representation of the uncertainty, while still retaining as much information as possible from the raw forecast data. We then demonstrate application of this technique to a model of the Great Britain grid in 2030, driven by the raw output of a real-world high-dimensional weather forecast from the U.K. Met Office. We also discuss applications of the approach beyond power systems