Search results for " Integration"
showing 10 items of 1034 documents
A review of thermochemical energy storage systems for power grid support
2020
Power systems in the future are expected to be characterized by an increasing penetration of renewable energy sources systems. To achieve the ambitious goals of the “clean energy transition”, energy storage is a key factor, needed in power system design and operation as well as power-to-heat, allowing more flexibility linking the power networks and the heating/cooling demands. Thermochemical systems coupled to power-to-heat are receiving an increasing attention due to their better performance in comparison with sensible and latent heat storage technologies, in particular, in terms of storage time dynamics and energy density. In this work, a comprehensive review of the state of art of theore…
Energy saving and user satisfaction for a new advanced public lighting system
2019
Abstract The retrofit of urban lighting systems is often an advantageous means of achieving notable energy savings and improvements in the quality of light. User habits, expectations and lifestyle can contribute to the design of these systems, for example in deciding on the most appropriate control strategies or the light quality. The influence of such variables can be extended to the overall system performance. This paper presents a method of street lighting design based on two kinds of analysis carried out in a defined test area: measurements (by means of a monitoring study) and user preferences (by means of a survey). The results of this data analysis create the basis for the final desig…
Single neuron binding properties and the magical number 7
2008
When we observe a scene, we can almost instantly recognize a familiar object or can quickly distinguish among objects differing by apparently minor details. Individual neurons in the medial temporal lobe of humans have been shown to be crucial for the recognition process, and they are selectively activated by different views of known individuals or objects. However, how single neurons could implement such a sparse and explicit code is unknown and almost impossible to investigate experimentally. Hippocampal CA1 pyramidal neurons could be instrumental in this process. Here, in an extensive series of simulations with realistic morphologies and active properties, we demonstrate how n radial (ob…
A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior.
2011
The neural mechanisms underlying schizophrenic behavior are unknown and very difficult to investigate experimentally, although a few experimental and modeling studies suggested possible causes for some of the typical psychotic symptoms related to this disease. The brain region most involved in these processes seems to be the hippocampus, because of its critical role in establishing memories for objects or events in the context in which they occur. In particular, a hypofunction of the N-methyl-D-aspartate (NMDA) component of the synaptic input on the distal dendrites of CA1 pyramidal neurons has been suggested to play an important role for the emergence of schizophrenic behavior. Modeling st…
UNIVERSITY IS ARCHITECTURE FOR THE RESEARCH EVALUATION SUPPORT
2017
The measuring of research results can be used in different ways e.g. for assignment of research grants and afterwards for evaluation of project’s results. It can be used also for recruiting or promoting research institutions’ staff. Because of a wide usage of such measurement, the selection of appropriate measures is important. At the same time there does not exist a common view which metrics should be used in this field, moreover many existing metrics that are widely used are often misleading due to different reasons, e.g. computed from incomplete or faulty data, the metric’s computation formula may be invalid or the computation results can be interpreted wrongly. To produce a good framewo…
Adaptive Population Importance Samplers: A General Perspective
2016
Importance sampling (IS) is a well-known Monte Carlo method, widely used to approximate a distribution of interest using a random measure composed of a set of weighted samples generated from another proposal density. Since the performance of the algorithm depends on the mismatch between the target and the proposal densities, a set of proposals is often iteratively adapted in order to reduce the variance of the resulting estimator. In this paper, we review several well-known adaptive population importance samplers, providing a unified common framework and classifying them according to the nature of their estimation and adaptive procedures. Furthermore, we interpret the underlying motivation …
Analysis of block random rocking on nonlinear flexible foundation
2020
Abstract In this paper the rocking response of a rigid block randomly excited at its foundation is examined. A nonlinear flexible foundation model is considered accounting for the possibility of uplifting in the case of strong excitation. Specifically, based on an appropriate nonlinear impact force model, the foundation is treated as a bed of continuously distributed springs in parallel with nonlinear dampers. The statistics of the rocking response is examined by an analytical procedure which involves a combination of static condensation and stochastic linearization methods. In this manner, repeated numerical integration of the highly nonlinear differential equations of motion is circumvent…
CLUSTER MONTE CARLO ALGORITHMS IN STATISTICAL MECHANICS
1992
The cluster Monte Carlo method, where variables are updated in groups, is very efficient at second order phase transitions. Much better results can be obtained with less computer time. This article reviews the method of Swendsen and Wang and some of its applications.
Group Metropolis Sampling
2017
Monte Carlo (MC) methods are widely used for Bayesian inference and optimization in statistics, signal processing and machine learning. Two well-known class of MC methods are the Importance Sampling (IS) techniques and the Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce the Group Importance Sampling (GIS) framework where different sets of weighted samples are properly summarized with one summary particle and one summary weight. GIS facilitates the design of novel efficient MC techniques. For instance, we present the Group Metropolis Sampling (GMS) algorithm which produces a Markov chain of sets of weighted samples. GMS in general outperforms other multiple try schemes…
Fusion of experimental data
1997
Abstract The integration of information from various sensory systems is one of the most difficult challenges in understanding both perception and cognition. For example, the problem of auditory-visual integration is a correspondence problem between perceived auditory and visual scenes. Two main questions arise when designing data analysis systems: what is the useful information to be integrated?, and what are the integration rules? The problem of integrating information becomes relevant whenever: (a) the same kind of data are detected by spatially distributed sensors; (b) heterogeneous data are detected by different sensors; (c) heterogeneous distributed data are involved. General problems …