Australian foreign policy and the management of intelligence post-September 11

In the era since the September 11 terrorist attacks there has been an unprecedented appeal to intelligence as a justification for pre-emptive government action on the part of the Anglo-Saxon democracies. This paper discusses the management of intelligence by the Australian government in this era. In respect both of the ‘war on terrorism’ and other issues, the politicization of intelligence has been in evidence. Poor management practices (as evident, for example, in the Collins affair) have been a facilitating factor, but the main reasons have been the predominance of perceived alliance requirements and government recourse to the apparent expertise and objectivity of intelligence agencies for electoral advantage. The reforms proposed for the intelligence sector do not address the root causes of politicization but may actually facilitate this trend.This item was commisioned by Asia Pacific School of Economics and Government, AN

Owen Lattimore the Political geography of Asia

Owen Lattimore's earliest interest was in trade and colonisation in the frontier regions of China. This Interest led him to work on the history and contemporary condition of the nomadic frontier peoples, especially the Mongols, Lattimore rejecting the environmental determinism of Ellsworth Huntington and Arnold Toynbee in favour of a depiction of pastoral nomadism which stressed the role in its evolution of choice and invention within geographical parameters. Under the influence of the ideas of Oswald Spengler, and concerned with the difficult predicament of the Mongols, Lattimore became convinced of the inability of either Mongol or Chinese civilisation to survive without fundamental social renovation. In his historical work on nomadic-Chinese interactions he stressed the lack of integration between these peoples, relying largely upon the ideas of Karl Vittfogel for his account of the cyclic nature of the history of traditional China. During the Second World War Lattimore's appointment as adviser to Chiang Kai-shek led him to contemplate both the likely course of reform in China, and the future role of the United States in Asia, Disillusioned with Chiang by 1947,Lattimore grew increasingly critical of US failure to adjust policy to recognise the rise of nationalism in Asia and the emergence there and elsewhere of a "Third World" of nations outside the two ideological blocks. After the ordeal imposed upon him as a result of Senator McCarthy's charges that he had been a Soviet spy, Lattimore returned to work on the history of world frontiers, and on China and Mongolia. He now regarded the communists as having carried through the revolutionary changes in China that the Kuomintang had evaded; from 1962 he came to identify the national aspirations of the Mongol people with the Mongolian People's Republic, the policies of which could no longer be understood as those of a Soviet "satellite”. Throughout his career his attachment to the Mongols has been the chief influence on his work

Behavioral Antecedents of Fuel Efficiency

The US Department of Defense is the largest institutional petroleum consumer in the world. In addition to the financial cost of petroleum-based fuels, the US DoD generates more CO2-equivalent greenhouse gases than the entirety of modern, industrialized nations like Sweden and Norway. Other dangers and externalities arise from the fuels supply chain, like toxin risks to fuel handlers, and human costs to transport fuel in-theater. Within the DoD, the USAF alone often rivals or exceeds the consumption of all other services combined. While the USAF prefers technical, hardware-based solutions to problems, and has given increasing attention to logistical solutions like route planning and aircraft mix optimization, very little research both in and out of the military looks into the impact of human decision making on fuel consumption. Industrial/organizational psychology, or “IO Psych,” is a growing field in the civilian world. This project applies IO psychometric measurements to investigate the variability within fuel consumption stemming from the choices that human operators make. Three studies are presented, revolving around this common theme. These studies are based on the Theory of Planned Behavior (TPB), a behavioral science model emphasizing the kind of deliberate, informed decision making. The first study using meta-analysis indicates the TPB model strongly predicts fuel-efficient behavior. The second study examines car drivers’ eco-friendly behavior. The results of the second study are congruent with the findings of the first study. The third study investigates the ecofriendly behaviors of military cargo pilots in the Air Force. Survey responses were collected from the population of 62 active duty, reserve, and Guard cargo airlift pilots flying the C-130, C-17, and C-5 platforms who flew a combined 477 cargo sorties within the measurement period. The pilots’ responses were compared against a measure of fuel consumption corrected for change to cargo weight. The results of this study indicate that the link between intention and behavior is weak

Measuring Machine Learning Model Uncertainty with Applications to Aerial Segmentation

Machine learning model performance on both validation data and new data can be better measured and understood by leveraging uncertainty metrics at the time of prediction. These metrics can improve the model training process by indicating which training data need to be corrected and what part of the domain needs further annotation. The methods described have yet to reach mainstream adoption, and show great potential. Here, we survey the field of uncertainty metrics and provide a robust framework for its application to aerial segmentation. Uncertainty is divided into two types: aleatoric and epistemic. Aleatoric uncertainty arises from variations in training data and can be the result of poor training data or an inherently stochastic observation. Epistemic uncertainty arises from predicting on inputs that are out of class of the training data. Both measures inform the machine learning engineer on what areas of data need better or more training, and also help downstream processes quantify the usefulness of a prediction. We survey the current tools for measuring uncertainty, including the autoencoder for measuring epistemic uncertainty and the Bayesian neural network. The latter replaces each trained weight with a random variable with which we approximate the true, unknown distribution of each weight with a two parameter (mean and variance) normal distribution. Bayes by Backprop trains these parameters by minimizing the Kullback–Leibler divergence between the approximating normal distribution and the unknown distribution. Our contribution is a novel application of the Bayesian neural network with Gaussian weights applied to the U-Net model for aerial segmentation. Using the DroneDeploy dataset, we build and train our Bayesian U-Net model and gather epistemic and aleatoric uncertainty metrics. Experimentally, we find that these metrics are correlated to model performance on unseen data and thus provide immediate value to a modeling and prediction workflow. We show the usefulness of these metrics for both per-pixel uncertainty estimation and per-image uncertainty estimation

Antecedents of Fuel Efficiency

Reducing the United States Air Force (USAF)’s fuel use is a major budgetary concern, as the USAF consumes more fuel than the Army, Navy, Marine Corps and all other Department of Defense (DoD) agencies combined. This research focused on fuel efficiency of C-130 Hercules Aircraft Commanders (ACs) by proposing, constructing, and testing a survey measure of behavioral drivers of discretionary pro-environmental professional behaviors among USAF pilots

The influence of chromium on structure and mechanical properties of B2 nickel aluminide alloys

Major obstacles to the use of NiAl-based alloys and composites are low ductility and toughness. These shortcomings result in part from a lack of sufficient slip systems to accommodate plastic deformation of polycrystalline material (von Mises Criterion). It has been reported that minor additions of chromium to polycrystalline NiAl cause the predominant slip system to shift from the usual. If true, then a major step toward increasing ductility in this compound may be realized. The purpose of the present study was to verify this phenomenon, characterize it with respect to chromium level and Ni to Al ratio, and correlate any change in slip system with microstructure and mechanical properties. Compression and tensile specimens were prepared from alloys containing 0 to 5 percent chromium and 45 to 55 percent aluminum. Following about one percent strain, transmission electron microscopy foils were produced and the slip systems determined using the g x b = 0 invisibility criterion. Contrary to previous results, chromium was found to have no effect on the preferred slip system of any of the alloys studied. Possible reasons for the inconsistency of the current results with previous work are considered. Composition-structure-property relationships are discerned for the alloys, and good correlation are demonstrated in terms of conventional strengthening models for metallic systems