Computational imaging di↵ers from traditional imaging system by integrating an encoded measurement system and a tailored computational algorithm to extract interesting scene features. This dissertation demonstrates two approaches which apply computational imaging methods to the fluid domain. In the first approach, we study the problem of reconstructing time-varying 3D- 3C fluid velocity vector fields. We extend 2D Particle Imaging Velocimetry to three dimensions by encoding depth into color (a “rainbow”). For reconstruction, we derive an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. This velocity field can be used to refine the position estimate by adding physical priors that tie together all the time steps, forming a joint reconstruction scheme. In the second approach, we study the problem of reconstructing the 3D shape of underwater environments. The distortions from the moving water surface provide a changing parallax for each point on the underwater surface. We utilize this observation by jointly estimating both the underwater geometry and the dynamic shape of the water surface. To this end, we propose a novel di↵erentiable framework to tie together all parameters in an integrated image formation model. To our knowledge, this is the first solution that is capable to simultaneously retrieve the structure of dynamic water surfaces and static underwater scene geometry in the wild.

Five years ago, a massive earthquake and its subsequent aftershocks rocked the core of Nepal. Recovery from these quakes has been a long and difficult process. This thesis will explore findings from a qualitative evaluation of Lumanti Support Group for Shelter, an NGO in Kathmandu, Nepal that implemented a residential reconstruction program in four peri-urban communities in Kathmandu Valley. These findings are a culmination of 26 semi-structured interviews and document analysis. This research highlights the processes of reconstruction and the forms of resistance that occurred through disaster governance.

This master thesis put its focus on analysis that is based on the creation of complaints in the filed of the construction company that has been used for this research. The researched company core business activities lie in the construction and reconstruction of the roofs. This analysis is based on the comparison of already established procedures and consequently their actual execution. The shortcomings that were found in the analytical part of this research papers, will be used as suggestions that ought to improve the current situation of the researched company.

The mainstay of treatment for injuries to the anterior cruciate ligament (ACL) is with a tendon graft harvested from elsewhere in the knee. This procedure, known as ACL reconstruction (ACLR), has excellent reported outcomes in terms of restoring the gross stability of the knee. However there are reported rates of graft failure in the pediatric population.1 ACL reconstruction also does not provide full protection from developing premature osteoarthritis, which is often seen in patients after ACL injury. A new method must be found in order to find a solution to these adverse outcomes from the current standard treatment of ACL injuries. The Bridge-enhanced anterior cruciate ligament repair (BEAR) technique is a new innovation on primary repair of a torn ACL. It avoids the requirement for autograft harvesting and use of an allograft by combining a primary suture repair with an extraceullular matrix scaffold (the BEAR scaffold). This scaffold is placed between the two torn ends of the ACL to help facilitate natural healing of the ligament in order to restore the intrinsic functions of the ACL to protect the knee from trauma and instability. This ability to repair the native ACL maintains the proper anatomy of its insertion points, avoids donor site morbidity, and helps to prevent early osteoarthritis by maintaining innate proprioceptive functions of the ACL. Our study will prove the BRIDGE repair to be a promising step in the direction of preserving the native ACL.

Magister Artium (Development Studies) - MA(DVS) / The study examines the role of ecotourism in the reconstruction of post-war Rwanda. This is in the context of widespread poverty throughout Rwanda, and the government's efforts to improve the population's welfare, following years of civil war .. The study is based on secondary data review, including government's policies on poverty alleviation, literature on the role of ecotourism in development and a case study of a national park where ecotourism is seen as bringing in much needed revenue. The study concludes that ecotourism in Rwanda has potential to contribute to economic growth, and this is in part due to the country's unique flora and fauna. However, the study also points out that several challenges to this potential remain. These include the country's still shaky security and the widespread poverty itself.

Variational methods, which have proven to be very useful to solve the ill-posed inverse problems, have been generating a lot of research interest in the image restoration problem. It transforms the restoration problem into the optimization of a well-designed variational model. While the designed model is convex, the recovered image is the global solution found by an appropriate numerical algorithm and the quality of the restored image depends on the accuracy of the designed model. Thus, a lot of efforts have been put to propose a more precise model that can produce a result with more pleasing visual quality. Besides, due to the high- dimension and the nonsmoothness of the imaging model, an efficient algorithm to find the exact solution of the variational model, is also of the research interest, since it influences the efficiency of the restoration techniques in the practical applications. In this thesis, we are interested in the designing of both the variational models for image restoration problems and the numerical algorithms to solve these models. The first objective of this thesis is to make improvements on two models for image denoising. For the multiplicative noise removal, we designed a regularizer based on the statistical property of the speckle noise, which can transform the traditional model (named by AA) into a convex one. Therefore, a global solution can be found independent of the initialization of the numerical algorithm. Moreover, the regularization term added on the AA model can help produce a sharper result. The second model is improved on the traditional ROF model by adding an edge regularization which incorporates an edge prior obtained from the observed image. Extensive experiments show that designed edge regularization has superiority to increase the texture of the recovered result and remove the staircase artifacts in the meanwhile. It is also presented that the edge regularization designed can be easily adapted into other restoration task, such as image deblurring. The second objective of this thesis is to study the numerical algorithms for a general nonsmooth imaging restoration model. As the imaging models are usually high-dimensional, the existing algorithms usually only use the first-order information of the image. Differently, a novel numerical algorithm based on the inexact Lagrangian function is proposed in this thesis, which exploits the second-order information to reach a superlinear convergence rate. Experiments show that the proposed algorithm is able to efficiently reach the solution with higher accuracy compared to the state-of-the-art algorithm

Variational methods, which have proven to be very useful to solve the ill-posed inverse problems, have been generating a lot of research interest in the image restoration problem. It transforms the restoration problem into the optimization of a well-designed variational model. While the designed model is convex, the recovered image is the global solution found by an appropriate numerical algorithm and the quality of the restored image depends on the accuracy of the designed model. Thus, a lot of efforts have been put to propose a more precise model that can produce a result with more pleasing visual quality. Besides, due to the high- dimension and the nonsmoothness of the imaging model, an efficient algorithm to find the exact solution of the variational model, is also of the research interest, since it influences the efficiency of the restoration techniques in the practical applications. In this thesis, we are interested in the designing of both the variational models for image restoration problems and the numerical algorithms to solve these models. The first objective of this thesis is to make improvements on two models for image denoising. For the multiplicative noise removal, we designed a regularizer based on the statistical property of the speckle noise, which can transform the traditional model (named by AA) into a convex one. Therefore, a global solution can be found independent of the initialization of the numerical algorithm. Moreover, the regularization term added on the AA model can help produce a sharper result. The second model is improved on the traditional ROF model by adding an edge regularization which incorporates an edge prior obtained from the observed image. Extensive experiments show that designed edge regularization has superiority to increase the texture of the recovered result and remove the staircase artifacts in the meanwhile. It is also presented that the edge regularization designed can be easily adapted into other restoration task, such as image deblurring. The second objective of this thesis is to study the numerical algorithms for a general nonsmooth imaging restoration model. As the imaging models are usually high-dimensional, the existing algorithms usually only use the first-order information of the image. Differently, a novel numerical algorithm based on the inexact Lagrangian function is proposed in this thesis, which exploits the second-order information to reach a superlinear convergence rate. Experiments show that the proposed algorithm is able to efficiently reach the solution with higher accuracy compared to the state-of-the-art algorithm

This dissertation examines Ulysses S. Grant’s Reconstruction policy, both the domestic and foreign policies, as an integrated whole. He focused on the broad application of citizenship rights, not only for African Americans in the South, but for all peoples in the United States’ sphere of influence. The centerpiece of Grant’s Reconstruction policy was the “Grant Doctrine,” articulated in his 1869 memorandum considering whether to annex the Dominican Republic to the United States. In it, Grant delineated his determination to export the republican policies of Reconstruction to the Caribbean by the acquisition of the island territory. Grant envisioned exporting the ideals of Reconstruction, the rights of citizenship, and the republican values of the Reconstruction Amendments, to people never previously considered for full membership in the body politic of the United States. Grant’s decisions to annex the Dominican Republic and grant the Dominicans citizenship reflect the responsibilities Grant had to enforce equal rights for those seeking to join the Union. Grant’s desire to provide a path to citizenship for Native Americans (whether they wanted it or not) and his effort to withhold citizenship from Mormons due to the immorality of their practice of polygamy, added to the changing views of citizenship in this era. Grant’s Reconstruction policy also included his desire to help Chinese immigrants break the bonds of forced labor, though that ultimately led to their eventual exclusion. This dissertation examines all of these initiatives as well as the position of African American leaders who questioned the president’s decision-making and argued against his policies, while never wavering in their political support of him or his party. Together, Grant’s foreign and domestic policies represented a singular Reconstruction effort centered on the question of citizenship. The Grant administration sought to export Reconstruction beyond the borders of the American South, restoring and strengthening the Union while, at the same time, offering republicanism, liberty, equality, and free labor, to peoples of the Western Hemisphere writ large and the peoples of the world migrating to the United States.

From 1847 to 1891, Guy Morrison Bryan was a prominent Texas politician who influenced many of the policies and events that shaped the state. Raised in his Uncle Stephen F. Austin's shadow, he was a Texas nationalist who felt responsible for promoting the interests of his state, its earliest settlers, and his family. During his nineteen years in the Texas Legislature and two years in the United States House of Representatives, he safeguarded land grants, supported internal improvements and education, and challenged northern hostility towards slavery. Convinced that abolitionists would stop at nothing to destroy the institution and Texas, he led his state's walkout of the National Democratic Convention in 1860 and became a leading proponet of secession. During the Civil War, he served as a staff officer, and his ability to mediate conflicts between local and national leaders propped up the isolated Confederate Trans-Mississippi Department. Finally as Speaker of the House, he helped oust Governor Edmund J. Davis in 1874 and "redeem" the state from Republican rule before convincing President Rutherford B. Hayes to adopt a conciliatory policy towards Texas and the South. Despite the tremendous influence Bryan wielded, scholars have largely ignored his contributions. This dissertation establishes his significance, uses his willingness to transfer national allegiances to consider nationalism--whether Texan, American, or Confederate--in the United States-Mexico Borderlands, and sheds light on neglected subjects like the role of staff officers in the Civil War.

No description available.