Review of Adaptive Leadership in the Military Context: International Perspectives by Lt.-Col. Douglas Lindsay and Cmdr. Dave Woycheshin, eds.

Review of Adaptive Leadership in the Military Context: International Perspectives by Lt.-Col. Douglas Lindsay and Cmdr. Dave Woycheshin, eds

Augmented Sustainability Measures for Scotland

We estimate and compare two empirical measures of the weak sustainability of an economy for the first time: the change in augmented green net national product (GNNP), and the interest on augmented genuine savings (GS). Yearly calculations are given for each measure for Scotland during 1992-99. Augmentation means including, using projections to 2020, production possibilities enabled by exogenous technical progress or changing terms of trade. In passing, we clarify the treatment of environmental expenditures in green accounting. The change in augmented GNNP and interest on augmented GS are both always positive, showing no sustainability problem for Scotland; but the former greatly exceeds the latter, showing an unresolved problem with the theorysustainability, Scotland, genuine savings, green NNP, augmentation

Swelling Effects in Dynamic Equi-Biaxial Testing of EPDM Elastomers by the Bubble Inflation Method

The thesis describes the effect of oil swelling on the fatigue life of EPDM under conditions of multi-axial fatigue using bubble inflation. The motivation for the research is outlines, along with a review of previous research conducted on the topic. Initial test results are presented and the evolution of the procedure for the final set of tests is described. One principal requirement identified when carrying out the fatigue tests was the need for constant stress control. Following development of the final test procedure, specimens were subjected to varying degrees of swelling in reference oils and cycled at constant engineering stress amplitudes at a frequency of 1Hz. The degree of rubber swell was controlled by using reference oils for the swelling tests. Sample swelling during cycling was minimised by using silicone based oil as the inflation fluid. Three specimen sets were used in the fatigue tests, one dry set and two other sets with different degrees of oil swelling. S-N (alternating stress versus cycles to failure) curves were generated for the dry and swollen specimens, with the fatigue life of the EPDM reduced in proportion to the amount of swelling. The changes in complex elastic modulus E* and dynamic stored energy were analysed and a relationship between the stored energy and the cycles to failure for the dry EPDM was observed. However, the stored energy at failure is reduced as the degree of swelling increases. Moreover, it was found that if the residual, or specific moduli for the swollen test pieces were considered against a datum of the initial conditioned modulus of the dry rubber at a similar stress amplitude, a limiting range of E*residual, was established for both the dry and swollen specimens, E* for differing levels of swelling was also calculated using models generated from the experimental data. Additionally, the differences in the fracture surfaces of the specimens due to swelling were analysed using scanning electron microscopy showing that the morphology of the failure surfaces are greatly influenced by the degree of oil swellin

Augmented Sustainability Measures for Scotland

We estimate and compare two empirical measures of the weak sustainability of an economy for the first time: the change in augmented green net national product (GNNP), and the interest on augmented genuine savings (GS). Yearly calculations are given for each measure for Scotland during 1992-99. Augmentation means including, using projections to 2020, production possibilities enabled by exogenous technical progress or changing terms of trade. In passing, we clarify the treatment of environmental expenditures in green accounting. The change in augmented GNNP and interest on augmented GS are both always positive, showing no sustainability problem for Scotland; but the former greatly exceeds the latter, showing an unresolved problem with the theory.

A New Evolutionary Algorithm For Mining Noisy, Epistatic, Geospatial Survey Data Associated With Chagas Disease

The scientific community is just beginning to understand some of the profound affects that feature interactions and heterogeneity have on natural systems. Despite the belief that these nonlinear and heterogeneous interactions exist across numerous real-world systems (e.g., from the development of personalized drug therapies to market predictions of consumer behaviors), the tools for analysis have not kept pace. This research was motivated by the desire to mine data from large socioeconomic surveys aimed at identifying the drivers of household infestation by a Triatomine insect that transmits the life-threatening Chagas disease. To decrease the risk of transmission, our colleagues at the laboratory of applied entomology and parasitology have implemented mitigation strategies (known as Ecohealth interventions); however, limited resources necessitate the search for better risk models. Mining these complex Chagas survey data for potential predictive features is challenging due to imbalanced class outcomes, missing data, heterogeneity, and the non-independence of some features. We develop an evolutionary algorithm (EA) to identify feature interactions in Big Datasets with desired categorical outcomes (e.g., disease or infestation). The method is non-parametric and uses the hypergeometric PMF as a fitness function to tackle challenges associated with using p-values in Big Data (e.g., p-values decrease inversely with the size of the dataset). To demonstrate the EA effectiveness, we first test the algorithm on three benchmark datasets. These include two classic Boolean classifier problems: (1) the majority-on problem and (2) the multiplexer problem, as well as (3) a simulated single nucleotide polymorphism (SNP) disease dataset. Next, we apply the EA to real-world Chagas Disease survey data and successfully archived numerous high-order feature interactions associated with infestation that would not have been discovered using traditional statistics. These feature interactions are also explored using network analysis. The spatial autocorrelation of the genetic data (SNPs of Triatoma dimidiata) was captured using geostatistics. Specifically, a modified semivariogram analysis was performed to characterize the SNP data and help elucidate the movement of the vector within two villages. For both villages, the SNP information showed strong spatial autocorrelation albeit with different geostatistical characteristics (sills, ranges, and nuggets). These metrics were leveraged to create risk maps that suggest the more forested village had a sylvatic source of infestation, while the other village had a domestic/peridomestic source. This initial exploration into using Big Data to analyze disease risk shows that novel and modified existing statistical tools can improve the assessment of risk on a fine-scale

Implications of the Changing Nature of Conflict for the Submarine Force

We are in a time of great change. Among naval forces, this change will most affect the U.S. attack submarine (SSN) force

Changing DoD’s Analysis Paradigm

War gaming and military modeling have a well documented history covering over two centuries, a period that coincides with the inception and evolution of formal professional development for military officers. The term war game used here refers to “a warfare model or simulation that does not involve the operations of actual forces, in which the flow of events affects and is affected by decisions made during the course of those events by players representing opposing sides.