Complex Solutions to Local Problems: Constructed Narratives and External Intervention in Somalia’s Crisis

Complex Solutions to Local Problems: Constructed Narratives and External Intervention in Somalia’s Crisis, by Jude Cocodia

External intervention has frustrated and continues to frustrate peace and stability in the Horn of Africa and Somalia, adding various adverse layers to an already complicated and complex conflict. The level of forceful military engagement intended for regional domination has profoundly affected negatively the efforts of peacebuilding and statebuilding in Somalia. This article examines how the earlier Ethiopian policies towards Somalia has reshaped the (post)-Cold War politics of the Horn. In doing so, it traces the roots of the Ethiopian intervention in Somalia vis-à-vis new non-state armed groups to chart the changing political dynamics of the conflict in Somalia. By using historical approach, the article argues that Ethiopia’s agenda is central to understanding why the ‘War on Terror’ has strengthened and subsequently midwifed armed militant movements (e.g. new insurgency groups) in Somalia, starting from Al-Itihaad to today’s Al-Shabaab. In focusing upon various regional actors and groups, the article moves from the emphasis of internal systems to external power structures, considering the wider historical and political factors in the region that must be closely examined if the regional and local conflicts are to be deeply understood. While it is a context-specific study, the article aims to contribute fresh perspectives and insights to ongoing discussions on the consequences of the Ethiopian intervention in Somalia.

Introduction Emma Leonard & Gilbert Ramsay SECTION ONE: THE FAILURE OF THE INTERNATIONAL The United Nations, Peacekeeping, and the Globalization of the Conflict in Somalia Kate Seaman Contextual Disconnect: The Failure of the 'International Community' in Somalia Karl Sandstrom SECTION TWO: THE RISE OF THE TRANSNATIONAL Is all Jihad Local? Transnational Contention and Political Violence in Somalia Peter S. Henne Involving Foreign Fighters in Somalia David Malet, Bryan Priest, & Sarah Staggs Somali Piracy and International Crime Peter Lehr SECTION THREE: THE NEW MULTIPOLAR POLITICS AS A RESPONSE TO TRANSNATIONAL DISORDER Re-crossing the Mogadishu Line: U.S. Policy toward Somalia 1994-2012 Michael J. Boyle Somalia-China Relations: China Claiming its Place as a Global Actor? Monika Thakur Japan's Aspirations as a Global Security Actor: the anti-piracy mission off Somalia and the dynamics of Great Power intervention Yee-Kuang Heng Opposing Interests? The Geopolitics of the Horn of Africa Stig Jarle Hansen The European Union Comprehensive Intervention in Somalia: Turning Ploughs into Swords? Maria-Luisa Sanchez-Barrueco SECTION FOUR: RE-IMAGINING INTERVENTION - MUST HISTORY REPEAT ITSELF IN SOMALIA? Identity, Stability, and the Somali State: Indigenous Forms and External Intervention Michael Walls & Steve Kibble Conclusion Gilbert Ramsay & Emma Leonard Bibliography Index

Locally conceived and initiated development projects are more successful than externally imposed projects, but outside intervention is sometimes necessary to bring about change for a societal good as well as helping to alleviate a local problem. Even with external intervention, however, there is a need to create and sustain local involvement and commitment. The dilemma is to cultivate the local involvement, commitment and ownership without compromising the integrity of the program. Examination of the Little Sioux watershed project implementation in western Iowa, basically a technical assistance project, yielded eight key factors relating to the external agency—local actor relationship with potential negative effects on externally initiated programs. These concepts are discussed in the context of the Little Sioux watershed project, and several strategies to overcome their potential negative effects are suggested.

Dynamic Security assessment: Challenges (An European TSO perspective)

We consider nonlocal reaction--diffusion equations in $m$--dimensional space. An existence theory is established using standard techniques. It is shown that when local monotonicity conditions are imposed, the stationary solutions that can be stable are those that are stable for an auxiliary local problem. This contrasts with what happens in the general case, where more complex solutions may be stable. An example of such a case is given. These results are obtained using comparison techniques and a generalization of previous results to the $m$--dimensional case.

The need to efficiently accommodate over the Internet the ever exploding (user-generated) content and services, calls for the development of service placement schemes that are distributed and of low complexity. As the derivation of the optimal placement in such environments is prohibitive due to the global topology and demand requirement and the large scale and dynamicity of the environment, feasible and efficient solutions of low complexity are necessary even at the expense of non-guaranteed optimality. This chapter presents three such approaches that migrate the service along cost-reducing paths by utilizing topology and demand information that is strictly local or confined to a small neighborhood: the neighbor hopping migration requires strictly local information and guarantees optimality for topologies of unique shortest path tree; the r-hop neighborhood migration appears to be more effective for general topologies and can also address jointly the derivation of both the number and locations of services to be deployed; the generalized neighborhood migration approach opens up new possibilities in defining localities, other than topological ones, that contain the most relevant candidates for the optimal placement, by exploiting emerging metrics and structures associated with complex and social networks. The underlying assumptions, strengths, efficiency and applicability of each of these approaches are discussed and some indicative results are shown.KeywordsShort PathNetwork NodeFacility LocationFacility Location ProblemService DemandThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Wireless source localization has found a number of applications in wireless sensor networks. In this work, we investigate robust and low complexity solutions to the problem of source localization based on the time-difference of arrivals (TDOA) measurement model. By adopting a min-max approximation to the maximum likelihood source location estimation, we develop two low complexity algorithms that can be reliably and rapidly solved through semi-definite relaxation. Our approach hinges on the use of a reference sensor node which can be optimized according to the Cramer-Rao lower bound or selected heuristically. Our low complexity estimate can be used either as the final location estimation output or as the initial point for other traditional search algorithms.

Numerical implementation and assessment of the GLPD micromorphic model of ductile rupture

Several estimation methods used in the range measurement based wireless localization area have individual problems. These problems may not occur according to certain application areas. However, these problems may give rise to serious problems in particular applications. In this paper, three methods, ILS (Iterative Least Squares), DS (Direct Solution), and DSRM (Difference of Squared Range Measurements) methods are considered. Problems that can occur in these methods are defined and a simple hybrid solution is presented to solve them. The ILS method is the most frequently used method in wireless localization and has local minimum problems and a large computational burden compared with closed-form solutions. The DS method requires less processing time than the ILS method. However, a solution for this method may include a complex number caused by the relations between the location of reference nodes and range measurement errors. In the near-field region of the complex solution, large estimation errors occur. In the DSRM method, large measurement errors occur when the mobile node is far from the reference nodes due to the combination of range measurement error and range data. This creates the problem of large localization errors. In this paper, these problems are defined and a hybrid localization method is presented to avoid them by integrating the DS and DSRM methods. The defined problems are confirmed and the performance of the presented method is verified by a Monte-Carlo simulation.

In this paper we study blind source localization problem based on the joint received signal strength difference (RSSD) and angle of arrival (AOA) measurements with unknown transmit power of source. Since RSSD and AOA measurements are uncorrelated, combining two methods leads to a better performance for source localization. This paper focus on the pseudo linear estimator (PLE) with a closed-form and low complexity solution. One of the main limitations in this estimator is the bias created from the correlation between system matrix and error vector, which is not vanished by increasing the number of measurements. To overcome this problem first, we present a bias compensated PLE using the closed instrumental variable (IV). Then, for improving the localization performance a weighting IV estimator (WIV) is presented. Finally, for achieving the Cramer–Rao lower bound (CRLB) an improved WIV (IWIV) estimator is used based on the known relation between the estimated parameters of WIV estimator. The proposed IWIV estimator is proved to be asymptotically efficient (i.e., obtaining zero bias and the Cramer–Rao lower bound). Numerical simulations also verify the theoretical development and show source localization using hybrid information RSSD/AOA has a superior performance than RSSD and AOA solely.

This chapter has developed mainstreaming and alienation as the two central conceptual and theoretical lenses on the governance of migration and diversity. Referring more broadly to the literature on complex policy problems, the key theoretical argument is that complex problems require complex solutions that are embedded as much as possible in an integral (cross-sectoral) approach. This is reflected in the concept of mainstreaming, which refers to the embedding of governance into generic policy areas and the targeting of the whole population. Such a mainstreamed approach, as argued in this chapter, allows not only for the type of ‘messy solutions’ that complex problems require, but also allows for flexibility regarding local problem circumstances and policy preferences: there is no ‘one-size-fits-all’ policy model associated with mainstreaming. Instead, it involves a governance strategy that embeds migration and diversity governance into mainstream governance and politics, rather than singling it out as a stand-alone topic, thereby reducing its complexities.However, as hypothesized throughout this book, precisely because of the complexities of migration and diversity governance, there are many factors that may prevent such governance mainstreaming. Elaborating on Schneider and Ingram’s approach to ‘degenerative policy designs’, I will refer to various forms of alienation in reference to how complex policy problems may involve various structural factors (knowledge, power, ideas, institutions) that prevent mainstreaming from occurring. In this regard, I distinguish between problem alienation, social alienation, political alienation and institutional alienation.

GPS-based systems have the potential to make air travel safer and more efficient, but they are vulnerable to jamming and interference. Localizing signal sources such as jammers can be accomplished cost-effectively using small unmanned aerial vehicles (UAVs). When equipped with a directional antenna, a multirotor UAV can rotate to obtain a bearing measurement to the signal source. This paper presents a control scheme for such a platform, which uses prior observations to determine where new observations should be made. The signal source localization problem is modeled as a partially observable Markov decision process (POMDP). The POMDP formulation allows for a principled approach to optimally solving sequential decision-making problems. Signal source localization problems involve large belief spaces that render such optimal solutions computationally intractable, but recent advances have made approximation methods feasible. This paper presents a POMDP model for signal source localization and explores offline methods to approximate optimal solutions. Simple approximations such as QMDP outperform heuristic strategies if the reward function is carefully selected. More complex solution methods incorporating distribution entropy result in better performance but have greater computational cost.