Search results for "Control system"
showing 10 items of 971 documents
Damage identification of a jacket support structure for offshore wind turbines
2020
Offshore jacket structures are regarded as a suitable type of support structure for offshore wind turbines in immediate water depths. Because of the welded tubular members used and environmental conditions, offshore jackets are often subjected to fatigue damages during their service life. Underwater sensors can provide measurements of the structural vibration signals and provide an efficient way to detect damages at early stages. In this work, simplified forms of the damages are assumed, random damages are imposed on the jacket structure, and damaged indicators are established from combination of modal shapes. Then, a response surface is constructed mapping the damage indicators and damages…
Efficient Protection for VDI Workstations
2019
Many enterprises migrate to a private cloud VDI environment. In such an environment multiple workstations are served by a single powerful server. On such an environment each VDI workstation receives only a limited CPU power. An average of less than a quarter of a core per planned VDI workstation is a common setup. Under such cases, anti-virus and application control software load is multiplied by the number of VDI workstation running on each server. These security applications take merely a few percentages of a single core on a normal desktop. However, on a VDI server where the multiple VDI workstations run on a single server, they may consume 20-25 percent the load. Naturally, such an incr…
Thermosensory mapping of skin wetness sensitivity across the body of young males and females at rest and following maximal incremental running
2019
Key points: Humans lack skin receptors for wetness (i.e. hygroreceptors), yet we present a remarkable wetness sensitivity. Afferent inputs from skin cold-sensitive thermoreceptors are key for sensing wetness; yet, it is unknown whether males and females differ in their wetness sensitivity across their body and whether high intensity exercise modulates this sensitivity. We mapped sensitivity to cold, neutral and warm wetness across five body regions and show that females are more sensitive to skin wetness than males, and that this difference is greater for cold than warm wetness sensitivity. We also show that a single bout of maximal exercise reduced the sensitivity to skin wetness (i.e. hyg…
Risk Assessment of Hip Fracture Based on Machine Learning
2020
[EN] Identifying patients with high risk of hip fracture is a great challenge in osteoporosis clinical assessment. Bone Mineral Density (BMD) measured by Dual-Energy X-Ray Absorptiometry (DXA) is the current gold standard in osteoporosis clinical assessment. However, its classification accuracy is only around 65%. In order to improve this accuracy, this paper proposes the use of Machine Learning (ML) models trained with data from a biomechanical model that simulates a sideways-fall. Machine Learning (ML) models are models able to learn and to make predictions from data. During a training process, ML models learn a function that maps inputs and outputs without previous knowledge of the probl…
Motor-skill learning in an insect inspired neuro-computational control system
2017
In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The ad…
On Switching between Motion and Force Control
2019
In motion control technologies, an automatic switching between trajectory following and set reference force, upon the impact, is a frequently encountered requirement. Despite both, motion and force controls, are something of well-understood and elaborated in the control theory and engineering practice, a reliable switching between them is not always self-evident. It can lead to undesired deadlocks, limit cycles, chattering around switching point and, as consequence, to wearing or damages in the controlled plant and its environment. This paper contributes to analysis and understanding of the autonomous switching from the motion to force control and vice versa. Simple output and state feedbac…
Hybrid Position/Force Control for Hydraulic Actuators
2020
In this paper a novel hybrid position/force control with autonomous switching between both control modes is introduced for hydraulic actuators. A hybrid position/force control structure with feed-forwarding, full-state feedback, including integral control error, pre-compensator of the deadzone, and low-pass filtering of the control value is designed. Controller gains are obtained via local linearization and pole placement accomplished separately for the position and force control. A hysteresis-based autonomous switching is integrated into the closed control loop, while multiple Lyapunov function based approach is applied for stability analysis of the entire hybrid control system. Experiment…
Evaluating the stability of pharmacophore features using molecular dynamics simulations.
2016
Abstract Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding PDB pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in …
Taxonomic Classification for Living Organisms Using Convolutional Neural Networks
2017
Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential f…
Fundamentals and implementation of Microbiological Diagnostic Stewardship Programs.
2021
Microbiological diagnostic stewardship programs promote coordinated measures aimed at optimizing the use of diagnostic techniques, thus favouring the adoption of adequate and cost-effective therapeutic, clinical and preventive decisions. The implementation of microbiological diagnostic stewardship relies upon the creation of multidisciplinary committees led by clinical microbiologists for the design of diagnostic algorithms, the adequacy of the laboratory computer system to monitor the relevance of the requested diagnostic tests, the implementation of a quality control system, the design and performance of studies of cost-effectiveness, the training of the petitioner and the technical and n…