Sharing power? Prospects for a U.S. concert-balance strategy

The Pax Americana and the grand strategy of hegemony (or “Primacy”) that underpins it may be becoming unsustainable. Particularly in the wake of exhausting wars, the Global Financial Crisis, and the shift of wealth from West to East, it may no longer be possible or prudent for the United States to act as the unipolar sheriff or guardian of a world order. But how viable are the alternatives, and what difficulties will these alternatives entail in their design and execution? This analysis offers a sympathetic but critical analysis of alternative U.S. National Security Strategies of “retrenchment” that critics of American diplomacy offer. In these strategies, the United States would anticipate the coming of a more multipolar world and organize its behavior around the dual principles of “concert” and “balance,” seeking a collaborative relationship with other great powers, while being prepared to counterbalance any hostile aggressor that threatens world order. The proponents of such strategies argue that by scaling back its global military presence and its commitments, the United States can trade prestige for security, shift burdens, and attain a more free hand. To support this theory, they often look to the 19th-century concert of Europe as a model of a successful security regime and to general theories about the natural balancing behavior of states. This monograph examines this precedent and measures its usefulness for contemporary statecraft to identify how great power concerts are sustained and how they break down. The project also applies competing theories to how states might behave if world politics are in transition: Will they balance, bandwagon, or hedge? This demonstrates the multiple possible futures that could shape and be shaped by a new strategy. viii A new strategy based on an acceptance of multipolarity and the limits of power is prudent. There is scope for such a shift. The convergence of several trends—including transnational problems needing collaborative efforts, the military advantages of defenders, the reluctance of states to engage in unbridled competition, and hegemony fatigue among the American people—means that an opportunity exists internationally and at home for a shift to a new strategy. But a Concert-Balance strategy will still need to deal with several potential dilemmas. These include the difficulty of reconciling competitive balancing with cooperative concerts, the limits of balancing without a forward-reaching onshore military capability, possible unanticipated consequences such as a rise in regional power competition or the emergence of blocs (such as a Chinese East Asia or an Iranian Gulf), and the challenge of sustaining domestic political support for a strategy that voluntarily abdicates world leadership. These difficulties can be mitigated, but they must be met with pragmatic and gradual implementation as well as elegant theorizing and the need to avoid swapping one ironclad, doctrinaire grand strategy for another.

Soft balancing in the Americas: Latin American opposition to U.S. intervention, 1898–1936

In the aftermath of the 2003 U.S.-led invasion of Iraq, scholars of international relations debated how to best characterize the rising tide of global opposition. The concept of “soft balancing” emerged as an influential, though contested, explanation of a new phenomenon in a unipolar world: states seeking to constrain the ability of the United States to deploy military force by using multinational organizations, international law, and coalition building. Soft balancing can also be observed in regional unipolar systems. Multinational archival research reveals how Argentina, Mexico, and other Latin American countries responded to expanding U.S. power and military assertiveness in the early twentieth century through coordinated diplomatic maneuvering that provides a strong example of soft balancing. Examination of this earlier case makes an empirical contribution to the emerging soft-balancing literature and suggests that soft balancing need not lead to hard balancing or open conflict.

Wetland restoration within agricultural watersheds: Balancing water quality protection with habitat conservation

Peat wetlands that have been restored from agricultural Land have the potential to act as Long term sources of phosphorus (P) and, therefore have to potenital to accelerate freshwater eutrophication. During a two-year study the water table in a eutrophic fen peat that was managed by pump drainage fluctuated annually between +20 cm and -60 cm relative to ground Level. This precise management was facilitated by the high hydraulic conductivity (K) of the humified peat (1.1 x 10(-5) m s(-1)) below around 60 cm depth. However, during one week of intermittent pumping, as much as 50 g ha(-1) dissolved P entered the pumped ditch. Summer. rainfall events and autumn reflooding also triggered P losses. The P Losses were attributed to the low P sorption capacity (217 mg kg(-1)) of the saturated peat below 60 cm, combined with its high K and the reductive dissolution of Fe bound P.

Dynamic load balancing for the distributed mining of molecular structures

In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids.

Decentralized load balancing for highly irregular search problems

In this paper, we present a distributed computing framework for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available. The framework is based on a peer-to-peer computing environment and dynamic load balancing. The system allows for dynamic resource aggregation, does not depend on any specific meta-computing middleware and is suitable for large-scale, multi-domain, heterogeneous environments, such as computational Grids. Dynamic load balancing policies based on global statistics are known to provide optimal load balancing performance, while randomized techniques provide high scalability. The proposed method combines both advantages and adopts distributed job-pools and a randomized polling technique. The framework has been successfully adopted in a parallel search algorithm for subgraph mining and evaluated on a molecular compounds dataset. The parallel application has shown good calability and close-to linear speedup in a distributed network of workstations.

DTM generation from LIDAR data using skewness balancing

LIght Detection And Ranging (LIDAR) data for terrain and land surveying has contributed to many environmental, engineering and civil applications. However, the analysis of Digital Surface Models (DSMs) from complex LIDAR data is still challenging. Commonly, the first task to investigate LIDAR data point clouds is to separate ground and object points as a preparatory step for further object classification. In this paper, the authors present a novel unsupervised segmentation algorithm-skewness balancing to separate object and ground points efficiently from high resolution LIDAR point clouds by exploiting statistical moments. The results presented in this paper have shown its robustness and its potential for commercial applications.

Design, implementation and characterisation of a contactless power transfer system for rotating applications

This paper describes the design, implementation and characterisation of a contactless power transfer system for rotating applications. The power transfer system is based upon a zero-voltage-switched, full-bridge, DC-DC converter, but utilises a non-standard transformer. This transformer allows power transfer between its primary and secondary windings while also allowing free rotation between these windings. The aim of this research is to develop a solution that could replace mechanical slip-rings in certain applications where a non-contacting system would be advantageous. Based upon the design method presented in this paper, a 2 kW prototype system is constructed. Results obtained from testing the 2 kW prototype are presented and discussed. This discussion considers how the performance of the transformer varies with rotation and also the overall efficiency of the system

Contactless power transfer system for rotating applications

In applications such as radar and wind turbines, it is often necessary to transfer power across a constantly rotating interface. As the rotation is continuous, it would be impossible to use wires to transfer the power as they would soon become twisted and stretched and the system would fail. The widespread solution to this problem is to use a slip-ring.

Dynamic load balancing in parallel KD-tree k-means

One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Techniques for improving the efficiency of k-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting geometrical constraints and an efficient data structure, notably a multidimensional binary search tree (KD-Tree). These techniques allow to reduce the number of distance computations the algorithm performs at each iteration. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient k-Means variants in parallel computing environments. In this work, we provide a parallel formulation of the KD-Tree based k-Means algorithm for distributed memory systems and address its load balancing issue. Three solutions have been developed and tested. Two approaches are based on a static partitioning of the data set and a third solution incorporates a dynamic load balancing policy.