Dynamic Programming Algorithms solve many standard problems of RNA bioinformatics in polynomial time. In this contribution we discuss a series of variations on these standard methods that implement refined biophysical models, such as a restriction of RNA folding to canonical structures, and an extension of structural alignments to an explicit scoring of stacking propensities. Furthermore, we demonstrate that a local structural alignment can be employed for ncRNA gene finding. In this context we discuss scanning variants for folding and alignment algorithms.

In this thesis we will focus on a problem of length bounded cut, also known as L-bounded cut. We are going to show a combinatorial algorithm for finding a minimal L-bounded cut on graphs with bounded treewidth based on dynamic programming. Then we going to show that this algorithm can also be used for finding minimal L-bounded cut on plannar graphs. We are also going to look at problem of (dG(s, t) + 1)-bounded cut. This problem is known to be NP-hard for general graphs. But it is an open problem whether this problem is also NP-hard on plannar graphs with special vertices on the outer face. We will try to outline a way, which might lead to showing that this problem is solvable in a polynomial time.

We are currently witnessing a rapid expansion of renewable power production, an increase dominated by wind and solar power. These intermittent energy sources, while having low production costs, increases the uncertainty on the electrical markets. Hydropower is a renewable source of electricity that is capable of controlled production. It is assumed that hydropower will take a more central role in terms of balancing deficiencies caused by intermittent sources. In this thesis, we present a detailed model of a single hydropower plant consisting of 𝑛 turbines. This model is then used as input of solving the optimisation problem of revenue maximisation for the hydro plant owner. The model used takes into account head effects as well as stochastic inflow of water and the stochastic fluctuations of electricity prices.

In a time where people tend to retire earlier and live longer in combination with an augmented personal responsibility of allocating or at least choosing adequately composed pension funds, the importance of a deeper understanding of long term investment strategies is inevitably accentuated. On the background of discrepancies in suggested pension fund strategies by influential fund providers, professional advisers and previous literature, this thesis aims at addressing foremost one particular research question: How should an investor optimally allocate between risky and risk-less assets in a pension fund depending on age? In order to answer the question the sum of Human wealth, defined as the present value of all expected future incomes, and ordinary Financial wealth is maximized by applying a mean-variance and a expected utility approach. The latter, and mathematically more sound method yields a strategy suggesting 100% of available capital to be invested in risky assets until the age of 47 whereafter the portion should be gradually reduced and reach the level of 32% at the last period before retirement. The strategy is clearly favorable to solely holding a risk-free asset and it just outperforms the commonly applied "100 minus age"-strategy.

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The urge to consume does not seem to stop, thus, the need for transportation of goods will most likely not decrease. At the same time jurisdictions and regulations around greenhouse gas emissions are sharpening and pushing the industry towards a more environmentally friendly state. The freight and transportation industry is facing a huge challenge in the upcoming years and solutions are needed to feed the demand of society. Two, of many, proposals of solving, at least, parts of the above mentioned problem is platooning and the look-ahead controller. Platooning denotes the concept of slipstream where maximum utilization of aerodynamic drag reduction is endeavoured. The lookahead controller exploits the surrounding topographical information in order to yield an optimal driving strategy, often resulting in that the vehicle initiates the phenomenon of pulse and glide, which denotes alternating between high load operation points and freewheeling, i.e. engaging neutral gear. This work has sought to investigate these concepts to determine whether or not additional fuel-efficiency can be added by manipulating and re-designing the control unit of the system. The proposed addition is built upon the look-ahead controller and supplements it by enabling communication between vehicles such that micro-transactions may occur in order to aid decision making regarding the choice of driving strategies. A vehicle model, a platoon model and the novel optimization based look-ahead-controller was synthesized and developed, where dynamic programming was used as the optimization solver of the controller. The look-ahead controller was verified such that one can conclude that it behaves according to the assumptions of such a system. The proposed micro-transaction system was also verified to conclude that it behaves as assumed, yielding a reduction in fuel consumption. For a platoon of two members, a 1.2% and 1.7% reduction in fuel consumption for the leading and following vehicle respectively was obtained, compared to an identical platooning setup, using a lookahead controller, but where no negotiations using micro-transactions are allowed between the vehicles.

The new emission regulations for new trucks was made to decrease the CO2 emissions by 30% from 2020 to 2030. One of the solutions is hybridizing the truck powertrain with 48V or 600V that can recover brake energy with electrical machines and batteries. The control of this hybrid powertrain is key to increase fuel efficiency. The idea behind this approach is to combine two different power sources, an internal combustion engine and a battery driven electric machine, and use both to provide tractive forces to the vehicle. This approach requires a HEV controller to operate the power flow within the systems. The HEV controller is the key to maximize fuel savings which contains an energy management strategy. It uses the knowledge of the road profile ahead by GPS and maps, and strongly interacts with the control of the cruise speed, automated gear shifts, powertrain modes and state of charge. In this master thesis, the dynamic programming strategy is used as predictive energy management for hybrid electric truck in forward- facing simulation environment. An analysis of predictive energy management is thus done for receding and full horizon length on flat and hilly drive cycle, where fuel consumption and recuperation energy will be regarded as the primary factor. Another important factor to consider is the powertrain mode of the vehicle with different penalty values. The result from horizon study indicates that the long receding horizon length has a benefit to store more recuperative energy. The fuel consumption is decreased for all drive cycle in the comparison with existing Volvo’s strategy.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Peter Gregory Furth. / Ph.D.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19336号 / 情博第588号 / 新制||情||103(附属図書館) / 32338 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 阿久津 達也, 教授 山本 章博, 教授 岡部 寿男 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21356号 / 工博第4515号 / 新制||工||1703(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 藤井 聡, 准教授 QURESHI,Ali Gul, 准教授 SCHMOECKER,Jan-Dirk / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM