From 1945 until the fall of the Berlin Wall in 1989, the Church of Jesus Christ of Latter-day Saints (LDS) in the former German Democratic Republic (GDR) endured the hardships of existing as a religious organization under a Communist regime. An evaluation of the LDS Church within the category of general and minority religions, which serves as a microcosmic evaluation of religion in the GDR, constitutes one part of this study. The uniqueness of the LDS Church and its experience - especially its American ties, ironically earlier a liability and later an asset - make it a candidate for a more independent evaluation, and the second part of this study. The social aspect of religion in the GDR, as it related to those of faith - including the lives of LDS members, constitutes the final aspect of this study. The Leipzig branch of the LDS Church, upon which most of this reserach is based, serves as an example of religious conformity, while proving itself socially, politically, and culturally unique. By placing the LDS Church in the context of religion in general, as well as examinng the atypical experience of the Leipzig branch, a greater understanding can be had of the religious, political and social life within the former German Democratic Republic.

This thesis is a study of the members of the Manchester Branch of the Church of Jesus Christ of Latter-day Saints from 1838 – 1860. It is a social examination of the converts and reveals that Manchester Mormons were prototypes of many members who joined the Church throughout England.Most Mormons were young, and were baptized in their twenties or early thirties. Many were single. The Mormon congregation was representative of the working class citizenry of town. Almost all worked with their hands. Living conditions varied. Some members were affluent by working class standards and some barely survived. However, the majority were able to live.Manchester Mormons were people in a community within a community. Despite their diverse economic circumstances, they were united by a common bond, their religion. They were able to help each other economically and spiritually. While most of their neighbors were apathetic to religion, Mormons were seekers for truth, and found it in their new religion.

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The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control principles is the discrete-time method Model Predictive Control (MPC). The main advantage with MPC, compared to most other control principles, is that constraints on control signals and states can easily be handled. In each time step, MPC requires the solution of a Quadratic Programming (QP) problem. To be able to use MPC for large systems, and at high sampling rates, optimization routines tailored for MPC are used. In recent years, the range of application of MPC has been extended from constrained linear systems to so-called hybrid systems. Hybrid systems are systems where continuous dynamics interact with logic. When this extension is made, binary variables are introduced in the problem. As a consequence, the QP problem has to be replaced by a far more challenging Mixed Integer Quadratic Programming (MIQP) problem. Generally, for this type of optimization problems, the computational complexity is exponential in the number of binary optimization variables. In modern communication systems, multiple users share a so-called multi-access channel, where the information sent by different users is separated by using almost orthogonal codes. Since the codes are not completely orthogonal, the decoded information at the receiver is slightly correlated between different users. Further, noise is added during the transmission. To estimate the information originally sent, a maximum likelihood problem involving binary variables is solved. The process of simultaneously estimating the information sent by multiple users is called multiuser detection. In this thesis, the problem to efficiently solve MIQP problems originating from MPC is addressed. Two different algorithms are presented. First, a polynomial complexity preprocessing algorithm for binary quadratic programming problems is presented. By using the algorithm, some, or all, binary variables can be computed efficiently already in the preprocessing phase. In simulations, the algorithm is applied to unconstrained MPC problems with a mixture of real and binary control signals. It has also been applied to the multiuser detection problem, where simulations have shown that the bit error rate can be significantly reduced by using the proposed algorithm as compared to using common suboptimal algorithms. Second, an MIQP algorithm tailored for MPC is presented. The algorithm uses a branch and bound method where the relaxed node problems are solved by a dual active set QP algorithm. In this QP algorithm, the KKT-systems are solved using Riccati recursions in order to decrease the computational complexity. Simulation results show that both the QP solver and the MIQP solver proposed have lower computational complexity than corresponding generic solvers. / <p>Report code: LiU-TEK-LIC-2005:71.</p>

Marksamfälligheter är enligt 1 kap. 3 § fastighetsbildningslagen (1970:988) markområden som ägs av flera fastigheter. För samfälligheter generellt finns två förvaltningsformer, delägar- eller föreningsförvaltning. För föreningsförvaltade marksamfälligheter ställer lagen om förvaltning av samfälligheter (1973:1150) krav på att inkomster och utgifter ska särredovisas vid flera verksamhetsgrenar. Idag beaktas inte hur marksamfälligheter förvaltas av Lantmäteriet, det sker inte heller en utpräglad lämplighetsprövning vid omdisponering av andelar. Syftet med studien är att ta fram förslag till hur lantmäterimyndigheten bör hantera marksamfälligheter inom förrättningar. Kopplat till hanteringen utreds om en lämplighetsprövning enligt 3 kap. FBL ska införas i sin helhet samt om aktsamhet ska tas kring hur marksamfälligheten förvaltas vid hanteringen inom förrättningen. Studien genomförs genom tillämpning av rättsdogmatisk metod kombinerat med en kvantitativ och kvalitativ intervju- och enkätstudie med yrkesverksamma på Lantmäteriet och samfällighetsföreningar. Studien visar brister i konkreta riktlinjer hos Lantmäteriet om hur marksamfälligheter ska hanteras i förrättningar. Resultatet visar också på att små medel kan förbättra hanteringen av marksamfälligheter inom förrättningar genom att tydliggöra hur lämplighetsprövningen ska tillämpas och att i rimlig grad undersöka hur föreningen förvaltas. Ett nytt rättsfall om sakägarbegreppet från HD framförs. Lantmäteriet som myndighet behöver ta ställning till om en lämplighetsprövning enligt 3 kap. FBL ska genomföras i sin helhet enligt lag eller om omdisponering av andelar inom förrättningar ska avse ett undantag från lagen. Ett tydliggörande hade skapat enhetlig och korrekt handläggning nationellt som gynnar medarbetare och föreningar. / Joint property units are under the 1st chapter 3 § Real Property Formation Act (1970:988) land areas owned by several properties. These units can be managed through either co-owner or association administration. For association-managed units, the Joint Property Units Act (1973:1150) requires that income and expenses are reported separately for different branches of activity. Today the management of land property units is not considered by the Land Survey, and there is not a distinct suitability test when reallocating shares. The purpose of the study is producing a suggestion how the cadastral authorities should handle land joint property units in cadastral procedures. Regarding this there is an analysis if suitability test according to 3rd chapter FBL should be introduced and care taken on how the unit is managed when handling in the cadastral procedures. The study is performed by applying legal dogmatic method combined with a quantitative and qualitative interview and survey study with professionals on the Land Survey and joint property associations. The study show lack in concrete guidelines at the Land Survey on how joint property units should be handled in cadastral procedures. The result also shows that small funds can improve the management of joint property units in the cadastral procedures by instructing how to apply the suitability test and to a reasonable extent examine how the association is managed. A judgment of interested party from The Supreme Court is presented. The Land Survey as an authority needs to decide on if a suitability test according to 3rd chapter FBL must be implemented in its entirety as the law states or if redistribution of shares within cadastral procedures must refer to an exception from the law. A clarification would create a uniform and correct procedure throughout the country that benefits both employees and associations.

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"S. Dooley: Tertiary Reader" / Approved for public release, distribution is unlimited / This study provides analysis, conclusions and recommendations to assist the Deputy Commandant (DC), Manpower and Reserve Affairs Department (M&RA) and DC, Programs and Resources Department (P&R) in structure and process decisions concerning Marine Corps Manpower budget execution. DC, M&RA is the owner of the Marine Human Resource Development Process (HRDP) and the Military Personnel Marine Corps (MPMC) appropriation sponsor, while the DC, P&R has budgetary (1517) authority for MPMC budget execution. In contrast, the Navy has both sponsorship and 1517 authority within one cell at N1. By comparing these two services' organizational factors and Planning, Programming, Budgeting, and Execution Systems (PPBES), relevant differences surface, conclusions are drawn, and recommendations offered for improvements. Recommendations include realignment of 1517 authority within MPMC execution, and the melding of the Programs and Budget Branch of Manpower Plans Division, M&RA with the Military Personnel Branch, Fiscal Division, P&R (RFM). This new office will be responsible for all facets of MPMC programming, budgeting, and execution. / Captain, United States Marine Corps

Dans cette thèse, nous étudions trois types de problèmes stochastiques : les problèmes avec contraintes probabilistes, les problèmes distributionnellement robustes et les problèmes avec recours. Les difficultés des problèmes stochastiques sont essentiellement liées aux problèmes de convexité du domaine des solutions, et du calcul de l’espérance mathématique ou des probabilités qui nécessitent le calcul complexe d’intégrales multiples. A cause de ces difficultés majeures, nous avons résolu les problèmes étudiées à l’aide d’approximations efficaces.Nous avons étudié deux types de problèmes stochastiques avec des contraintes en probabilités, i.e., les problèmes linéaires avec contraintes en probabilité jointes (LLPC) et les problèmes de maximisation de probabilités (MPP). Dans les deux cas, nous avons supposé que les variables aléatoires sont normalement distribués et les vecteurs lignes des matrices aléatoires sont indépendants. Nous avons résolu LLPC, qui est un problème généralement non convexe, à l’aide de deux approximations basée sur les problèmes coniques de second ordre (SOCP). Sous certaines hypothèses faibles, les solutions optimales des deux SOCP sont respectivement les bornes inférieures et supérieures du problème du départ. En ce qui concerne MPP, nous avons étudié une variante du problème du plus court chemin stochastique contraint (SRCSP) qui consiste à maximiser la probabilité de la contrainte de ressources. Pour résoudre ce problème, nous avons proposé un algorithme de Branch and Bound pour calculer la solution optimale. Comme la relaxation linéaire n’est pas convexe, nous avons proposé une approximation convexe efficace. Nous avons par la suite testé nos algorithmes pour tous les problèmes étudiés sur des instances aléatoires. Pour LLPC, notre approche est plus performante que celles de Bonferroni et de Jaganathan. Pour MPP, nos résultats numériques montrent que notre approche est là encore plus performante que l’approximation des contraintes probabilistes individuellement.La deuxième famille de problèmes étudiés est celle relative aux problèmes distributionnellement robustes où une partie seulement de l’information sur les variables aléatoires est connue à savoir les deux premiers moments. Nous avons montré que le problème de sac à dos stochastique (SKP) est un problème semi-défini positif (SDP) après relaxation SDP des contraintes binaires. Bien que ce résultat ne puisse être étendu au cas du problème multi-sac-à-dos (MKP), nous avons proposé deux approximations qui permettent d’obtenir des bornes de bonne qualité pour la plupart des instances testées. Nos résultats numériques montrent que nos approximations sont là encore plus performantes que celles basées sur les inégalités de Bonferroni et celles plus récentes de Zymler. Ces résultats ont aussi montré la robustesse des solutions obtenues face aux fluctuations des distributions de probabilités. Nous avons aussi étudié une variante du problème du plus court chemin stochastique. Nous avons prouvé que ce problème peut se ramener au problème de plus court chemin déterministe sous certaine hypothèses. Pour résoudre ce problème, nous avons proposé une méthode de B&B où les bornes inférieures sont calculées à l’aide de la méthode du gradient projeté stochastique. Des résultats numériques ont montré l’efficacité de notre approche. Enfin, l’ensemble des méthodes que nous avons proposées dans cette thèse peuvent s’appliquer à une large famille de problèmes d’optimisation stochastique avec variables entières. / In this thesis, we studied three types of stochastic problems: chance constrained problems, distributionally robust problems as well as the simple recourse problems. For the stochastic programming problems, there are two main difficulties. One is that feasible sets of stochastic problems is not convex in general. The other main challenge arises from the need to calculate conditional expectation or probability both of which are involving multi-dimensional integrations. Due to the two major difficulties, for all three studied problems, we solved them with approximation approaches.We first study two types of chance constrained problems: linear program with joint chance constraints problem (LPPC) as well as maximum probability problem (MPP). For both problems, we assume that the random matrix is normally distributed and its vector rows are independent. We first dealt with LPPC which is generally not convex. We approximate it with two second-order cone programming (SOCP) problems. Furthermore under mild conditions, the optimal values of the two SOCP problems are a lower and upper bounds of the original problem respectively. For the second problem, we studied a variant of stochastic resource constrained shortest path problem (called SRCSP for short), which is to maximize probability of resource constraints. To solve the problem, we proposed to use a branch-and-bound framework to come up with the optimal solution. As its corresponding linear relaxation is generally not convex, we give a convex approximation. Finally, numerical tests on the random instances were conducted for both problems. With respect to LPPC, the numerical results showed that the approach we proposed outperforms Bonferroni and Jagannathan approximations. While for the MPP, the numerical results on generated instances substantiated that the convex approximation outperforms the individual approximation method.Then we study a distributionally robust stochastic quadratic knapsack problems, where we only know part of information about the random variables, such as its first and second moments. We proved that the single knapsack problem (SKP) is a semedefinite problem (SDP) after applying the SDP relaxation scheme to the binary constraints. Despite the fact that it is not the case for the multidimensional knapsack problem (MKP), two good approximations of the relaxed version of the problem are provided which obtain upper and lower bounds that appear numerically close to each other for a range of problem instances. Our numerical experiments also indicated that our proposed lower bounding approximation outperforms the approximations that are based on Bonferroni's inequality and the work by Zymler et al.. Besides, an extensive set of experiments were conducted to illustrate how the conservativeness of the robust solutions does pay off in terms of ensuring the chance constraint is satisfied (or nearly satisfied) under a wide range of distribution fluctuations. Moreover, our approach can be applied to a large number of stochastic optimization problems with binary variables.Finally, a stochastic version of the shortest path problem is studied. We proved that in some cases the stochastic shortest path problem can be greatly simplified by reformulating it as the classic shortest path problem, which can be solved in polynomial time. To solve the general problem, we proposed to use a branch-and-bound framework to search the set of feasible paths. Lower bounds are obtained by solving the corresponding linear relaxation which in turn is done using a Stochastic Projected Gradient algorithm involving an active set method. Meanwhile, numerical examples were conducted to illustrate the effectiveness of the obtained algorithm. Concerning the resolution of the continuous relaxation, our Stochastic Projected Gradient algorithm clearly outperforms Matlab optimization toolbox on large graphs.