Cyclical schedules for the joint replenishment problem with dynamic demands

The Joint Replenishment Problem (JRP) involves production planning for a family of items. The items have a coordinated cost structure whereby a major setup cost is incurred whenever any item in the family is produced, and an item-specific minor setup cost is incurred whenever that item is produced. This paper investigates the performance of two types of cyclical production schedules for the JRP with dynamic demands over a finite planning horizon. The cyclical schedules considered are: (1) general cyclical schedules—schedules where the number of periods between successive production runs for any item is constant over the planning horizon—and (2) power-of-two schedules—a subset of cyclical schedules for which the number of periods between successive setups must be a power of 2. The paper evaluates the additional cost incurred by requiring schedules to be cyclical, and identifies problem characteristics that have a significant effect on this additional cost. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 577–589, 1997.     

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.     

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.     

Equity in genetic newborn screening

State‐level newborn screening allows for early treatment of genetic disorders, which can substantially improve health outcomes for newborns. As the cost of genetic testing decreases, it is becoming an essential part of newborn screening. A genetic disorder can be caused by many mutation variants; therefore, an important decision is to determine which variants to search for (ie, the panel design), under a testing budget. The frequency of variants that cause a disorder and the incidence of the disorder vary by racial/ethnic group. Consequently, it is important to consider equity issues in panel design, so as to reduce disparities among different groups. We study the panel design problem using cystic fibrosis (CF) as a model disorder, considering the trade‐offs between equity and accuracy, under a limited budget. Most states use a genetic test in their CF screening protocol, but panel designs vary, and, due to cost, no state's panel includes all CF‐causing variants. We develop models that design equitable genetic testing panels, and compare them with panels that maximize sensitivity in the general population. Our case study, based on realistic CF data, highlights the value of equitable panels and provides important insight for newborn screening practices.     

A more complex and conventional victory: revisiting the Dhofar counterinsurgency, 1963–1975

Following the emergence of a communist regime in South Yemen and the multiplication of subversive movements in the United Kingdom's Gulf protectorates, British policymakers genuinely feared the spread of communism throughout southern Arabia. Defeating the People's Front for the Liberation for the Occupied Arabian Gulf (PFLOAG) insurgency in Oman's Dhofar province was considered central to preventing such an outcome. In their pursuit of victory, British officers overthrew the sultan of Oman, escalated the war by conducting attacks in South Yemen, and, ultimately, appealed to Islam as a means of rallying support against communism. However, lessons learned in previous counterinsurgencies (Malaya, Kenya, and Borneo) proved of only limited value in Oman's physical and cultural environment. Unfortunately, none of these measures worked as anticipated. Only Iran's direct military intervention and the dramatic growth of Oman's financial resources after the 1973 oil crisis provided the resources to conduct large-scale offensive operations. Even so, victory was only achieved in 1975 because the rebellion's leaders unwisely attempted to oppose the Anglo–Omani offensives conventionally.     

Croatia's bitter harvest: Total National Defence's role in the Croatian War of Independence

Croatia's successful bid for independence was one of the defining moments of the immediate post-Cold War period. Nevertheless, the means that Croatia used to obtain independence remains relatively unexamined by academics. This article focuses on the early period of Croatia's bid for secession, and specifically the role that Yugoslavia's policy of Total National Defence played in facilitating its independence. Unlike in Slovenia, where the legacies of Total National Defence facilitated Slovenia's bid for secession, in Croatia the decision of its political leaders meant that the country largely neglected its positive legacies, resulting in a protracted four-year struggle.     

Civil wars and economic growth: A regional comparison

The paper examines the impact of civil wars on income per-capita growth at home and in neighbors for four regional groupings of countries: Africa, Asia, Latin America, and a pooled Asian and Latin American sample. Both macroeconomic and civil-war influences on growth differ by region. With the use of a distance measure, we demonstrate that the spatial reach from the negative consequences of a civil war are region and time period specific. Generally, there was less dispersion in Africa than in Asia and Latin America. Moreover, Africa demonstrates a greater ability to recover from the adverse effects of civil wars than the other regions tested.     

Democracy and peace: Reply to oneal and russett

The criticism of James, Solberg and Wolfson (JSW) (1999) by Oneal and Russett (OR) is not responsive to the methodologica] issues at stake. JSW argued that war is an endogenous feature of the world political and economic system. If its causes are to be measured, it must be as a structural equation in a simultaneous system. Wedded to the idea that “democracies never fight each other,” OR rely on a single equation to justify their view. JSW claim that such an equation may be an ad hoc reduced form with no causal implications unless the equation is explicitly identified as a structural equation. JSW expand the model to explain democracy and conflict as two endogenous variables. JSW do not claim to have discovered the true relationships between these variables by their minimal expansion of the structural relation. They do show that unless these (and other) variables are treated as part of a system, the results are unstable, contradictory, of minimal size and not a reliable guide to public policy.