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System-theoretical methods are already used for the control of computing systems, but much more can be done exploiting said methods for their design. This requires to express in control-theoretical terms desires and specifications that originate in the computer science do- main, which may not be immediate. It also requires to accept that part of the addressed system be modified, which may pose som

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Microdosing is a new concept in drug development that-if implemented in the pharmaceutical industry-would mean that new drugs can be tested earlier in humans than done today. The human microdosing concept-or 'Phase 0'-may offer improved candidate selection, reduced failure rates in the drug development line and a reduction in the use of laboratory animals in early drug development, factors which w

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Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only line flows have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constrai

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This paper addresses the need of continued education of process industry practitioners such as operators and instrumentation engineers. The process industry regulatory control tuning situation of today is reviewed. Areas of potential improvement are identified. A course, aimed at fulfilling these needs is presented. Especially, useful laboratory experiments are outlined. The suggested course was g

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In this paper we investigate the problem of embedding a number of points given certain (but typically not all) inter-pair distance measurements. This problem is relevant for multi-dimensional scaling problems with missing data, and is applicable within anchor-free sensor network node calibration and anchor-free node localization using radio or sound TOA measurements. There are also applications wi

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Closed-loop control of anesthesia is expected to decrease drug dosage and wake up time while increasing patient safety and decreasing the work load of the anesthesiologist. The potential of closed-loop control in anesthesia has been demon- strated in several clinical studies. One of the challenges in the development of a closed-loop system that can be widely accepted by clinicians and regulatory a

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Two main topics are considered in this thesis: Machining with industrial robots and optimal control of road-vehicles in critical maneuvers. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of strong

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For many assembly operations force control is needed, but force sensors may be expensive and add mass to the system. An alternative is to use the motor torques, though friction causes large disturbances. The Coulomb friction can be quite well known when a joint is moving, but has much larger uncertainties for velocities close to zero. This paper presents a method for force estimation that account

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One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this pa

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We investigate dual decomposition approaches for optimization problems arising in low-level vision. Dual decomposition can be used to parallelize existing algorithms, reduce memory requirements and to obtain approximate solutions of hard problems. An extensive set of experiments are performed for a variety of application problems including graph cut segmentation, curvature regularization and more

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We consider the problem of distributed convergence to efficient outcomes in coordination games through dynamics based on aspiration learning. Our first contribution is the characterization of the asymptotic behavior of the induced Markov chain of the iterated process in terms of an equivalent finite-state Markov chain. We then characterize explicitly the behavior of the proposed aspiration learnin

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The four major autoantigens (IA-2, IA-2 beta, GAD65 and insulin) of type 1 diabetes are all associated with dense core or synaptic vesicles. This raised the possibility that other secretory vesicle-associated proteins might be targets of the autoimmune response in type 1 diabetes. To test this hypothesis 56 proteins, two-thirds of which are associated with secretory vesicles, were prepared by in v

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Addressing the challenges of extreme scale computing re- quires holistic design of new programming models and sys- tems that support those models. This paper discusses the Angstrom processor, which is designed to support a new Self-aware Computing (SEEC) model. In SEEC, applications explicitly state goals, while other systems components provide actions that the SEEC runtime system can use to meet

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We consider the classical 3-state Moore-Greitzer model, which is commonly used for approximating dynamics of deviations of flow and pressure variables in an axial compressor from their nominal steady-state values. The linearization of the nonlinear system is not controllable and, therefore, even local asymptotic stability cannot be achieved using methods of linear control theory. We propose a fami

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Distributed Decision Making and Control is a mathematical treatment of relevant problems in distributed control, decision and multi-agent systems, The research reported was prompted by the recent rapid development in large-scale networked and embedded systems and communications. One of the main reasons for the growing complexity in such systems is the dynamics introduced by computation and communi

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A particle filter based solution to the out-of-sequence measurement (OOSM) problem is proposed. The solution is storage efficient, while being computationally fast. The filter approaches the multi-OOSM problem by not only updating the estimate at the most recent time, but also for all times between the OOSM time and the most recent time. This is done by exploiting the complete in-sequence informat

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To the purpose of marine seismic acquisition, new acoustic sources have been developed to reduce the environmental impact. The use of marine vibrators makes it possible to define emission frequency ranges, consequently allowing limitation of the frequencies that disturb marine animal life. Constructing marine vibrators with high efficiency and linear dynamics is however difficult, and the vibrator