Modeling and simulation frameworks for use in different application domains, throughout the complete development process, and in different hardware environments need to be highly scalable. For achieving an efficient execution, different simulation algorithms and data structures must be provided to compute a concrete model on a concrete platform efficiently. The support of parallel simulation techniques becomes increasingly important in this context, which is due to the growing availability of multi-core processors and network-based computers. This leads to more complex simulation systems that are harder to configure correctly. We present an experimentation layer for the modeling and simulation framework JAMES II. It greatly facilitates the configuration and usage of the system for a user and supports distributed optimization, on-demand observation, and various distributed and non-distributed scenarios.
The prevention and treatment of drug-resistant malaria is becoming increasingly difficult. On the Thai-Myanmar border multi-drug resistant strains of falciparum malaria are increasing and, because the malaria vector Anopheles bite outdoors during early evening, insecticide house-spraying or impregnated bednets provide only limited protection. Therefore, the protective efficacy of repellent formulations containing di-methyl benzamide (deet) and permethrin against local vectors was estimated, when applied to the skin, and their acceptability amongst pregnant Karen women who are at relatively high risk from malaria was assessed. Human landing catches of mosquitoes showed that almost complete protection was achieved using different formulations of 20% deet and 0.5% permethrin for up to 6 h. All-night collections from human subjects indicated that this repellent combination reduced exposure to malaria parasites by at least 65 and 85% for those transmitted by Anopheles minimus and An. maculatus, respectively, the two principal vectors in this area. Pregnant women in the camps preferred repellents which were mixed with 'thanaka', a root paste made from pulp of the wood apple tree, Limonia acidissima, used locally as a cosmetic. Apart from a temporary warming sensation where repellent thanaka was applied to the skin, the repellents were well tolerated. An intervention trial is currently in progress to determine whether deet mixed with thanaka can protect pregnant women against malaria in this part of the world. Bioassays using a laboratory strain of Aedes aegypti demonstrated that thanaka is itself slightly repellent at high dosages and the mixture with deet provides protection for over 10 h. This treatment would therefore also provide some personal protection against dengue, which is increasing locally, transmitted by Ae. aegypti and Ae. albopictus biting during the daytime.
Simulation algorithm implementations are usually evaluated by experimental performance analysis. To conduct such studies is a challenging and time-consuming task, as various impact factors have to be controlled and the resulting algorithm performance needs to be analyzed. This problem is aggravated when it comes to comparing many alternative implementations for a multitude of benchmark model setups. We present an architecture that supports the automated execution of performance evaluation experiments on several levels. Desirable benchmark model properties are motivated, and the quasi-steady state property of such models is exploited for simulation end time calibration, a simple technique to save computational effort in simulator performance comparisons. The overall mechanism is quite flexible and can be easily adapted to the various requirements that different kinds of performance studies impose. It is able to speed up performance experiments significantly, which is shown by a simple performance study.
Simulations often depend heavily on random numbers, yet the impact of random number generators is recognized seldom. The generation of random numbers for simulations is not trivial, as the quality of each algorithm depends on the simulation scenario. Therefore, simulation environments for large-scale experimentation with safety-critical models require a reliable mechanism to cope with this aspect. We show how to address this problem by realizing a random number generation architecture for a general-purpose simulation system. It provides various random number generators (RNGs), probability distributions, and RNG tests. It is open to future additions, which allows the assessment of new generators in a simulation context and the re-validation of past simulation studies. We present a short example that illustrates why the features of such an architecture are essential for getting valid results.
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