Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

A platform for initial testing of multiple camouflage patterns

The human visual system is still an important factor in military warfare; military personnel receive training on effective search strategies, and camouflage that can effectively conceal objects and personnel is a key component of a successful integrated survivability strategy. Previous methods of camouflage assessment have, amongst others, used psychophysics to generate distinctiveness metrics. However, the population from which the human observers are drawn is often not well defined, or necessarily appropriate. In this experiment we designed a new platform for testing multiple patterns based on a camouflaged object detection task, and investigate whether trained military observers perform better than civilians. We use a two-alternative forced choice paradigm, with participants searching images of woodland for a replica military helmet displaying Olive Green, Multi Terrain Pattern, US Marine Pattern or, as a conspicuous control, UN Peacekeeper Blue. Our data show that there is no difference in detection performance between the two observer groups but that there are clear differences in the effectiveness of the different helmet colour patterns in a temperate woodland environment. We conclude that when tasks involve very short stimulus presentation times, task-specific training has little effect on the success of target detection and thus this paradigm is particularly suitable for robust estimates of camouflage efficacy.     

Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical-military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical-military experts.Both the design and the results of the evaluation are revealed in this article.     

ECONOMIC GROWTH AND VIOLENT INTERNATIONAL CONFLICT: 1875–1999

This paper extends the joint product model of military alliances to apply to the new strategic doctrine adopted by NATO in the 1990s. In particular, a choice must be made between protecting one's own territory and pooling forces for an alliancewide rapid reaction force. This new model accounts for a host of externalities and their implications for burden sharing, full financing, and allocative efficiency. The Pigouvian taxes that adjust for force thinning and attack deflection are shown to finance optimal border‐protecting forces under a variety of circumstances. Second‐best considerations arise owing to the pure publicness of rapid reaction forces. The ideal toll arrangement does not currently characterize NATO financing, nor is it likely to do so.     

ACQUIRING FOREIGN NUCLEAR ASSISTANCE IN THE MIDDLE EAST

The United Arab Emirates (UAE) has laid out an ambitious plan to become the first Arab country to possess a civilian nuclear energy program. Central to that effort has been the Emirati government's ability to obtain foreign nuclear assistance. This article traces the UAE's strategies for overcoming the obstacles that stood in the way of nuclear suppliers providing assistance. It examines the approach taken by the UAE to assuage the safety and security concerns of nuclear suppliers, how the UAE leveraged its alliances with France and the United States to obtain their cooperation, and its strategies for engaging domestic interest groups in supplier states. The generalizable elements of the UAE's strategies are discussed and used to provide insight into the prospects for other Middle Eastern states' bids to obtain similar assistance. The article concludes with a discussion of the potentially transformative aspects of the strategies employed by the UAE in shaping other countries' pursuit of nuclear energy in the region.     

Nuclear weapons,existential threats,and the stability–instability paradox

Recent scholarship has largely ignored systematic differences in the existential threats that nuclear-weapon possessors pose to other states. This study theorizes that the capacity to pose existential threats shapes nuclear-armed states’ willingness to use military force against one another. We explore three hypotheses regarding how nuclear-based existential threats can deter conflict or encourage it, including under the conditions proposed by the stability–instability paradox. We rely on a statistical analysis of nuclear-armed dyads from 1950 to 2001 and employ the Nuclear Annihilation Threat (NAT) Index to capture variation in the existential threats nuclear-armed states pose to one another. We find that being able to pose an existential threat to another state emboldens potential initiators to use military force but does not deter attacks. The emboldening effects are particularly strong under the hypothesized conditions of the stability–instability paradox. Our study provides unique contributions to ongoing debates over the political effects of nuclear weapons.     

The Problem of Weak Nuclear States

Governments are increasingly recognizing the problem posed by internally weak nuclear-capable states. The problem, however, is under-theorized. This article brings together literature on sovereignty and international order, the nonproliferation regime, and weak states, and introduces new concepts to provide a more structured understanding of this problem. Insight comes from focusing attention on the function and governance of two nuclear estates (termed the production and operational estates), and on their resilience to decay and disorder occurring within the state and society. Drawing on empirical observation, the authors suggest a typology of weakness in nuclear states, involving state fragmentation typified by the former Soviet Union, the “hard weak state” typified by North Korea, and the internally conflicted state typified by Pakistan. Although these types give rise to distinctive difficulties, their alleviation depends heavily on the maintenance of internal authority within the state and estates, the presence or absence of cooperative relations, and the international regulatory framework's vitality.     

MILITARY EXPENDITURE AND GRANGER CAUSALITY: A CRITICAL REVIEW

A large literature has used tests for Granger (1969) non‐causality, GNC, to examine the interaction of military spending with the economy. Such tests answer a specific although quite limited question: can one reject the null hypothesis that one variable does not help predict another? If one can reject, there is said to be Granger causality, GC. Although the limitations of GNC tests are well known, they are often not emphasised in the applied literature and so may be forgotten. This paper considers the econometric and methodological issues involved and illustrates them with data for the US and other countries. There are three main issues. First, the tests may not be informative about the substantive issue, the interaction of military expenditure and the economy, since Granger causality does not correspond to the usual notion of economic causality. To determine the relationship of the two notions of causality requires an identified structural model. Second, the tests are very sensitive to specification. GNC testing is usually done in the context of a vector autoregression, VAR, and the test results are sensitive to the variables and deterministic terms included in the VAR, lag length, sample or observation window used, treatment of integration and cointegration and level of significance. Statistical criteria may not be very informative about these choices. Third, since the parameters are not structural, the test results may not be stable over different time periods or different countries.     

Patents and Dual-use Technology: An Empirical Study of the World's Largest Defence Companies

Abstract

This paper examines the generation of technological knowledge by leading companies in the defence industry. In particular, we test whether the characteristics of large defence companies are related to both the production of different types of patents (civilian, military and mixed), and the generation of dual-use technologies. To explore these links, we rely on economic data for the top 100 defence companies from the Stockholm International Peace Research Institute database, and patent information from the Worldwide Patent Statistical Database. Our results show that the relationship between the production of civilian patents and the size of the company is positive and significant. However, this relationship does not hold for the production of military patents. Furthermore, the military commercial profile is unrelated to the generation of military patents. Regarding the involvement in dual-use technologies, firms engaged in dual-use are those with higher military sales, a greater number of employees and a larger number of patents (civilian, military and mixed) than those not engaged in dual-use. Furthermore, we found a skill effect (more involvement in dual-use per employee) in European firms compared to US firms. These findings help to identify which firms should be targeted by government policies if increasing dual-use technologies becomes a political objective.