All Swedish state-owned companies have been mandated by the state to establish sustainability targets within 2013. This thesis intends to shed light on the sustainability targets adopted by Vattenfall AB in the areas of carbon emissions, renewables and energy efficiency. In contact with the company, the thesis evaluates the targets in terms of practicability, adequacy and market competition. In other words, it assesses how Vattenfall intends to achieve the targets, whether they raise the “sustainability bar” high enough for the company and how they compare with targets set by competitor companies such as E.ON and Fortum. Furthermore, the thesis identifies room for improvement within Vattenfall’s sustainability work, and makes recommendations to the company, on how to seek improvement. Having the targets and their related plan of action as the focal point, a number of different areas within the domain of corporate sustainability are covered, such as sustainability approach, strategy, work, performance and reporting, while the Swedish state-ownership policy works as a key guideline. The thesis work is based primarily on literature review and analysis of material published by Vattenfall, E.ON and Fortum, the Swedish state ownership policy, corporate energy target setting, and climate and energy policies of the European Union. / Alla svenska statligt ägda företag har av staten ålagts att under 2013 definiera hållbarhetsmål, och att målen ska vara i bruk fr. o m 2014. Föreliggande studie analyserar de hållbarhetsmål som Vattenfall AB har specificerat inom koldioxidutsläpp, förnyelsebara energikällor och energieffektivisering. I samarbete med företaget, utvärderar studien de tre målen utifrån praktiskt genomförande, relevans och marknadskonkurrens. Med andra ord, studien bedömer Vattenfall´s intentioner hur man ska uppnå målen, huruvida de lyfter ”hållbarhetsambitionen” tillräckligt högt för företaget och hur målen är i jämförelse med de mål som satts av konkurrentföretagen E.ON och Fortum. Dessutom, studien identifierar förbättringsutrymmen för Vattenfall´s hållbarhetsarbete och ger rekommendationer för hur företaget kan hitta förbättringsområdena. Genom att ha målen och de kopplade åtgärdsförslagen i centrum, inkluderas ett antal andra områden inom hållbar utveckling, såsom hållbarhetsinriktning, strategi, arbetsinsatser, genomförande och redovisning, samtidigt som den svenska statens ägarpolicy ska fungera som vägledning. Studien är primärt baserad på en litteraturgenomgång och analys av information publicerat av Vattenfall, E.ON och Fortum, den svenska statens ägarpolicy, företagens presenterade energimål, samt klimat- och energipolicies presenterade av Europeiska Unionen.

Unmanned aerial systems (UAS) are effective for surveillance and monitoring, but struggle with persistent, long-term tracking, especially without GPS, due to limited flight time. Persistent tracking can be accomplished using multiple vehicles if one vehicle can effectively hand off the tracking information to another replacement vehicle. This work presents a solution to the moving-target handoff problem in the absence of GPS. The proposed solution (a) a nonlinear complementary filter for self-pose estimation using only an IMU, (b) a particle filter for relative pose estimation between UAS using a relative range (c) visual target tracking using a gimballed camera when the target is close to the handoff UAS, and (d) track correlation logic using Procrustes analysis to perform the final target handoff between vehicles. We present hardware results of the self-pose estimation and visual target tracking, as well as an extensive simulation result that demonstrates the effectiveness of our full system, and perform Monte-Carlo simulations that indicate a 97% successful handoff rate using the proposed methods.

RNA interference (RNAi) is widely used to specifically silence the expression of any gene to study its function and to identify and validate therapeutic targets. Despite the popularity of this technology, recent studies have shown that RNAi may also silence non-targeted genes. Here we demonstrate the utility of a quick, efficient and robust approach to directly validate the specificity of RNAi as an alternative to indirect validation of RNAi through gene expression profiling. Our approach involves reversing (complementing) the RNAi-induced phenotype by introducing a synthetic version of the target gene that is designed to escape silencing. This synthetic gene complementation approach can also be used for mutational analysis of the target gene, or to provide a functional version of a defective protein after silencing the defective gene by RNAi. Using this approach we demonstrate that the loss of systemic acquired resistance, a form of innate immunity in plants, is indeed due to the silencing of salicylic acid-binding protein 2 rather than to off-target effects.

This dissertation is concerned with solving large-scale, ill-structured linear programming (LP) problems via Lagrangian dual (LD) reformulations. A principal motivation for this work arises in the context of solving mixed-integer programming (MIP) problems where LP relaxations, sometimes in higher dimensional spaces, are widely used for bounding and cut-generation purposes. Often, such relaxations turn out to be large-sized, ill-conditioned problems for which simplex as well as interior point based methods can tend to be ineffective. In contrast, Lagrangian relaxation or dual formulations, when applied in concert with suitable primal recovery strategies, have the potential for providing quick bounds as well as enabling useful branching mechanisms. However, the objective function of the Lagrangian dual is nondifferentiable, and hence, we cannot apply popular gradient or Hessian-based optimization techniques that are commonly used in differentiable optimization. Moreover, the subgradient methods that are popularly used are typically slow to converge and tend to stall while yet remote from optimality. On the other hand, more advanced methods, such as the bundle method and the space dilation method, involve additional computational and storage requirements that make them impractical for large-scale applications. Furthermore, although we might derive an optimal or near-optimal solution for LD, depending on the dual-adequacy of the methodology used, a primal solution may not be available. While some algorithmically simple primal solution recovery schemes have been developed in theory to accompany Lagrangian dual optimization, their practical performance has been disappointing. Rectifying these inadequacies is a challenging task that constitutes the focal point for this dissertation. Many practical applications dealing with production planning and control, engineering design, and decision-making in different operational settings fall within the purview of this context and stand to gain by advances in this technology. With this motivation, our primary interests in the present research effort are to develop effective nondifferentiable optimization (NDO) methods for solving Lagrangian duals of large-sized linear programs, and to design practical primal solution recovery techniques. This contribution would then facilitate the derivation of quick bounds/cuts and branching mechanisms in the context of branch-and-bound/cut methodologies for solving mixed-integer programming problems. We begin our research by adapting the Volume Algorithm (VA) of Barahona and Anbil (2000) developed at IBM as a direction-finding strategy within the variable target value method (VTVM) of Sherali et al. (2000). This adaptation makes VA resemble a deflected subgradient scheme in contrast with the bundle type interpretation afforded by the modification of VA as proposed by Bahiense et al. (2002). Although VA was originally developed in order to recover a primal optimal solution, we first present an example to demonstrate that it might indeed converge to a nonoptimal primal solution. However, under a suitable condition on the geometric moving average factor, we establish the convergence of the proposed algorithm in the dual space. A detailed computational study reveals that this approach yields a competitive procedure as compared with alternative strategies including the average direction strategy (ADS) of Sherali and Ulular (1989), a modified Polyak-Kelley cutting-plane strategy (PKC) designed by Sherali et al. (2001), and the modified Volume Algorithm routines RVA and BVA proposed by Bahiense et al. (2002), all embedded within the same VTVM framework. As far as CPU times are concerned, the VA strategy consumed the least computational effort for most problems to attain a near-optimal objective value. Moreover, the VA, ADS, and PKC strategies revealed considerable savings in CPU effort over a popular commercial linear program solver, CPLEX Version 8.1, when used to derive near-optimal solutions. Next, we consider two variable target value methods, the Level Algorithm of Brännlund (1993) and VTVM, which require no prior knowledge of upper bounds on the optimal objective value while guaranteeing convergence to an optimal solution. We evaluate these two algorithms in conjunction with various direction-finding and step-length strategies such as PS, ADS, VA, and PKC. Furthermore, we generalize the PKC strategy by further modifying the cut's right-hand-side values and additionally performing sequential projections onto some previously generated Polyak-Kelley's cutting-planes. We call this a generalized PKC (GPKC) strategy. Moreover, we point out some latent deficiencies in the two aforementioned variable target value algorithms in regard to their target value update mechanisms, and we suggest modifications in order to alleviate these shortcomings. We further explore an additional local search procedure to strengthen the performance of the algorithms. Noting that no related convergence analyses have been presented, we prove the convergence of the Level Algorithm when used in conjunction with the ADS, VA, or GPKC schemes. We also establish the convergence of VTVM when employing GPKC. Based on our computational study, the modified VTVM algorithm produced the best quality solutions when implemented with the GPKC strategy, where the latter performs sequential projections onto the four most recently generated Polyak-Kelley cutting-planes as available. Also, we demonstrate that the proposed modifications and the local search technique significantly improve the overall performance. Moreover, the VTVM procedure was observed to consistently outperform the Level Algorithm as well as a popular heuristic subgradient method of Held et al. (1974) that is widely used in practice. As far as CPU times are concerned, the modified VTVM procedure in concert with the GPKC strategy revealed the best performance, providing near-optimal solutions in about 27.84% of the effort at an average as that required by CPLEX 8.1 to produce the same quality solutions. We next consider the Lagrangian dual of a bounded-variable equality constrained linear programming problem. We develop two novel approaches for solving this problem, which attempt to circumvent or obviate the nondifferentiability of the objective function. First, noting that the Lagrangian dual function is differentiable almost everywhere, whenever the NDO algorithm encounters a nondifferentiable point, we employ a proposed <i>perturbation technique</i> (PT) in order to detect a differentiable point in the vicinity of the current solution from which a further search can be conducted. In a second approach, called the <i>barrier-Lagrangian dual reformulation</i> (BLR) method, the primal problem is reformulated by constructing a barrier function for the set of bounding constraints such that an optimal solution to the original problem can be recovered by suitably adjusting the barrier parameter. However, instead of solving the barrier problem itself, we dualize the equality constraints to formulate a Lagrangian dual function, which is shown to be twice differentiable. Since differentiable pathways are made available via these two proposed techniques, we can advantageously utilize differentiable optimization methods along with popular conjugate gradient schemes. Based on these constructs, we propose an algorithmic procedure that consists of two sequential phases. In Phase I, the PT and BLR methods along with various deflected gradient strategies are utilized, and then, in Phase II, we switch to the modified VTVM algorithm in concert with GPKC (VTVM-GPKC) that revealed the best performance in the previous study. We also designed two target value initialization methods to commence Phase II, based on the output from Phase I. The computational results reveal that Phase I indeed helps to significantly improve the algorithmic performance as compared with implementing VTVM-GPKC alone, even though the latter was run for twice as many iterations as used in the two-phase procedures. Among the implemented procedures, the PT method in concert with certain prescribed deflection and Phase II initialization schemes yielded the best overall quality solutions and CPU time performance, consuming only 3.19% of the effort as that required by CPLEX 8.1 to produce comparable solutions. Moreover, we also tested some ergodic primal recovery strategies with and without employing BLR as a warm-start, and observed that an initial BLR phase can significantly enhance the convergence of such primal recovery schemes. Having observed that the VTVM algorithm requires the fine-tuning of several parameters for different classes of problems in order to improve its performance, our next research investigation focuses on developing a robust variable target value framework that entails the management of only a few parameters. We therefore design a novel algorithm, called the <i>Trust Region Target Value</i> (TRTV) method, in which a trust region is constructed in the dual space, and its center and size are adjusted in a manner that eventually induces a dual optimum to lie at the center of the hypercube trust region. A related convergence analysis has also been conducted for this procedure. We additionally examined a variation of TRTV, where the hyperrectangular trust region is more effectively adjusted for normalizing the effects of the dual variables. In our computational study, we compared the performance of TRTV with that of the VTVM-GPKC procedure. For four direction-finding strategies (PS, VA, ADS, and GPKC), the TRTV algorithm consistently produced better quality solutions than did VTVM-GPKC. The best performance was obtained when TRTV was employed in concert with the PS strategy. Moreover, we observed that the solution quality produced by TRTV was consistently better than that obtained via VTVM, hence lending a greater degree of robustness. As far as computational effort is concerned, the TRTV-PS combination consumed only 4.94% of the CPU time required by CPLEX 8.1 at an average in order to find comparable quality solutions. Therefore, based on our extensive set of test problems, it appears that the TRTV along with the PS strategy is the best and the most robust procedure among those tested. Finally, we explore an outer-linearization (or cutting-plane) method along with a trust region approach for refining available dual solutions and recovering a primal optimum in the process. This method enables us to escape from a jamming phenomenon experienced at a non-optimal point, which commonly occurs when applying NDO methods, as well as to refine the available dual solution toward a dual optimum. Furthermore, we can recover a primal optimal solution when the resulting dual solution is close enough to a dual optimum, without generating a potentially excessive set of constraints. In our computational study, we tested two such trust region strategies, the Box-step (BS) method of Marsten et al. (1975) and a new Box Trust Region (BTR) approach, both appended to the foregoing TRTV-PS dual optimization methodology. Furthermore, we also experimented with deleting nonbinding constraints when the number of cuts exceeds a prescribed threshold value. This proposed refinement was able to further improve the solution quality, reducing the near-zero relative optimality gap for TRTV-PS by 20.6-32.8%. The best strategy turned out to be using the BTR method while deleting nonbinding constraints (BTR-D). As far as the recovery of optimal solutions is concerned, the BTR-D scheme resulted in the best measure of primal feasibility, and although it was terminated after it had accumulated only 50 constraints, it revealed a better performance than the ergodic primal recovery scheme of Shor (1985) that was run for 2000 iterations while also assuming knowledge of the optimal objective value in the dual scheme. In closing, we mention that there exist many optimization methods for complex systems such as communication network design, semiconductor manufacturing, and supply chain management, that have been formulated as large-sized mixed-integer programs, but for which deriving even near-optimal solutions has been elusive due to their exorbitant computational requirements. Noting that the computational effort for solving mixed-integer programs via branch-and-bound/cut methods strongly depends on the effectiveness with which the underlying linear programming relaxations can be solved, applying theoretically convergent and practically effective NDO methods in concert with efficient primal recovery procedures to suitable Lagrangian dual reformulations of these relaxations can significantly enhance the overall computational performance of these methods. We therefore hope that the methodologies designed and analyzed in this research effort will have a notable positive impact on analyzing such complex systems. / Ph. D.

京都大学 / 0048 / 新制・論文博士 / 博士(農学) / 乙第12881号 / 論農博第2808号 / 新制||農||1028(附属図書館) / 学位論文||H26||N4880(農学部図書室) / 31599 / (主査)教授 冨永 達, 教授 奥本 裕, 教授 宮川 恒 / 学位規則第4条第2項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

No description available.

STUDENT NO: 9811739R MASTERS HUMANITIES / ABSTRACT The objective of this paper is to investigate how linguistic variations in a literary text can be translated by analysing and comparing the strategies employed by two different French translators when dealing with the works of the Italian author, Andrea Camilleri. Much has been written about the possibility/ impossibility of translation itself, with many writers and critics taking opposing sides on the issue. The intention of this study is not to fuel or further this, in our view, sterile discussion. The point is that translations do exist and have existed for thousands of years: that is, texts in one (source) language have in some way been recreated and rewritten into another (target) language1. By contrast, what has been explored only superficially is how linguistic variations and dialects present in literary texts have been reproduced in the target language. Textual analyses relative to this study will be carried out on selected passages of two different novels (one for each translator). 1 The abbreviations SL and TL will be used to indicate ‘source language’ and ‘target language’ respectively, while ST and TT will be used to indicate ‘target text’ and ‘source text’.

Företagsledningar har incitament att manipulera resultat för att belönas internt eller av marknaden. Då resultatmanipulation utförs för att nå specifika mål kallas detta target beating. Resultatmanipulation, eller target beating, kan utföras genom diskretionära periodiseringar där avsättningar ligger inom ramen för att kunna påverka resultatet. Denna studie utreder dels om indikationer på target beating förekommer bland svenska börsnoterade företag, dels om ett samband finns mellan företagen med indikationer och årliga förändringar i avsättningsposter. Vi finner indikationer på att target beating förekommer bland svenska börsnoterade företag, och bland de företag där sannolikheten är störst att target beating används, finns även indikationer på att avsättningar används som medel för att nå målet. Storleken på avsättningsförändringarna i sig påvisar dock inget samband med target beating, men vi upptäcker däremot potential för två andra oväntade samband.

The importance of physical motion in simulators for pilot training is strongly debated. The present experiment isolated different types of motion, a potentially important variable contributing to the controversy. Participants used a joystick to perform a target tracking task in a motion simulator built using a MOOG Stewart platform. Five training conditions compared training without motion (as one would train in a stationary simulator), with correlated motion, with disturbance motion, with disturbance motion isolated to the visual display, and with both correlated and disturbance motion. The test condition involved the full motion model with both correlated and disturbance motion. We analyzed speed and accuracy across training and test as well as strategic differences in joystick control. We found that training with disturbance provided better transfer to test conditions that included disturbance motion for accuracy, but not speed, and that training with disturbance motion produced different joystick control strategies compared to training without disturbance. / Thesis / Master of Science (MSc)

No description available.