Brazilian National Defence Policy: foreign policy,national security,economic growth,and technological innovation

ABSTRACT

With the world’s ninth largest economy and comprising nearly 60% of South America’s GDP, 47% of its territory, and 49% of its population, Brazil has become a regional power and an important actor in world affairs over recent decades. This scenario has led the government to re-evaluate its role in the world order, resulting in the enactment of the National Defence Policy, whose objective was to consolidate the country as a regional power while at the same time addressing national security issues, promoting economic development through a series of defence programmes, restructuring the defence industrial base, fostering innovation through technology and knowledge transfer to Brazil, and indigenous research and development. However, the policy’s implementation suffers from several challenges discussed in this article, which may test the capability and competence of Brazilian policymakers, military, industrialists, and other individuals and organisations involved in its implementation.     

Accuracy assessment of detection performance for sidescan sonars

Sidescan sonars are used in detecting hostile targets on the seabed. An accurate representation of the sensor performance is required to carefully plan and execute searches. We studied several confidence interval methods for assessing the accuracy of detection performance as a function of range from hostile targets. Using simulation, we determined that the best approach for modeling sensor data was piecewise logistic regression with cubic B‐splines at carefully selected knots. This method was demonstrated on real data collected from the CITADEL sea trial. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Derivation and application of unit cost expressions perturbed by design changes

Learning curves have been used extensively to predict future costs in the airframe and other industries. This paper deals with the effect of perturbations induced by design changes on the learning curves. Equations that are developed and applied make it possible to predict future costs accurately in a perturbed environment. The formulations can be used effectively in EDP programs.     

Cost-based due-date assignment with the use of classical and neural-network approaches

Traditional methods of due-date assignment presented in the literature and used in practice generally assume cost-of-earliness and cost-of-tardiness functions that may bear little resemblance to true costs. For example, practitioners using ordinary least-squares (OLS) regression implicitly minimize a quadratic cost function symmetric about the due date, thereby assigning equal second-order costs to early completion and tardy behavior. In this article the consequences of such assumptions are pointed out, and a cost-based assignment scheme is suggested whereby the cost of early completion may differ in form and/or degree from the cost of tardiness. Two classical approaches (OLS regression and mathematical programming) as well as a neural-network methodology for solving this problem are developed and compared on three hypothetical shops using simulation techniques. It is found for the cases considered that: (a) implicitly ignoring cost-based assignments can be very costly; (b) simpler regression-based rules cited in the literature are very poor cost performers; (c) if the earliness and tardiness cost functions are both linear, linear programming and neural networks are the methodologies of choice; and (d) if the form of the earliness cost function differs from that of the tardiness cost function, neural networks are statistically superior performers. Finally, it is noted that neural networks can be used for a wide range of cost functions, whereas the other methodologies are significantly more restricted. © 1997 John Wiley & Sons, Inc.     

Does Terrorism Increase after a Natural Disaster? An Analysis based upon Property Damage

Does an emergency such as a natural disaster lead to a surge of terrorism? This paper contributes to the emerging literature on this issue. We consider the experience of 129 countries during the period 1998–2012 to determine the effect of a natural disaster on both domestic as well as transnational terrorism. We also control for endogeneity using expenditure on health care and land area in a country as instruments. In contrast to the existing literature, we measure the extent of terrorism by the value of property damage. The results indicate that after natural disasters, (a) transnational terrorism increases with a lag, and (b) a statistically significant impact on domestic terrorism is not observed.