Nuclear Magnetic Resonance (NMR) provides noninvasive detection for molecular information. Recently, intermolecular Multiple Quantum Coherences (iMQCs) was proved to be a promising NMR method to get high-resolution in...
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Nuclear Magnetic Resonance (NMR) provides noninvasive detection for molecular information. Recently, intermolecular Multiple Quantum Coherences (iMQCs) was proved to be a promising NMR method to get high-resolution in vivo magnetic resonance spectroscopy (MRS) under inhomogeneous field. The simulation of NMR plays an important role in predicting the result of a complex experiment, developing new NMR experiments, etc. However, in the simulation of iMQC-MRS, there is obstacle of combining scalar couplings with the classic formalism. This paper introduces an iMQC simulation algorithm based on the combination of product operator matrix (POM) and nonlinear Bloch equation, and its applications in developing high-resolution spectroscopy with solvent suppression and region-localized in vivo molecular spectroscopy.
The present paper presents a new method for sizing and techno-economical optimization of an autonomous wind system. The main objective of the present study is to find the optimum size of system, able to accomplish the...
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The present paper presents a new method for sizing and techno-economical optimization of an autonomous wind system. The main objective of the present study is to find the optimum size of system, able to accomplish the energy requirements of a given load distribution, for a specific site, and to analyze the impact of different parameters on the system size. Modeling of the autonomous wind system is considered as the first step in the optimal sizing procedure. In this paper, more accurate mathematical models for characterizing the main subsystems (wind generator and unit of storage) are proposed. Based on lack of energy to generate probability (LEGP), percentage of the surplus of energy produced (PSEP) and the cost of the kilowatt-hour produced (C(kWh)). the second step consists in optimizing the sizing of a system. A simulation software code has been developed to carry out the analysis for optimizing the size of the system. Also, a case study using the software code has been presented to determine the optimal system configuration used to satisfy the requirements of a typical residential home (5 kWh/day) located in Sfax, Tunisia. (C) 2010 Elsevier Ltd. All rights reserved.
Background: Competing risks methodology allows for an event-specific analysis of the single components of composite time-to-event endpoints. A key feature of competing risks is that there are as many hazards as there ...
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Background: Competing risks methodology allows for an event-specific analysis of the single components of composite time-to-event endpoints. A key feature of competing risks is that there are as many hazards as there are competing risks. This is not always well accounted for in the applied literature. Methods: We advocate a simulation point of view for understanding competing risks. The hazards are envisaged as momentary event forces. They jointly determine the event time. Their relative magnitude determines the event type. 'Empirical simulations' using data from a recent study on cardiovascular events in diabetes patients illustrate subsequent interpretation. The method avoids concerns on identifiability and plausibility known from the latent failure time approach. Results: The 'empirical simulations' served as a proof of concept. Additionally manipulating baseline hazards and treatment effects illustrated both scenarios that require greater care for interpretation and how the simulation point of view aids the interpretation. The simulation algorithm applied to real data also provides for a general tool for study planning. Conclusions: There are as many hazards as there are competing risks. All of them should be analysed. This includes estimation of baseline hazards. Study planning must equally account for these aspects.
This paper presents a fast time-relaxation quasi-implicit algorithm to solve plasma fluid-type equations for the transport of electron particles and mean energy, the transport of heavy species (ions and neutrals), the...
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This paper presents a fast time-relaxation quasi-implicit algorithm to solve plasma fluid-type equations for the transport of electron particles and mean energy, the transport of heavy species (ions and neutrals), the balance of the gas thermal energy, and the description of the fields (space-charge electrostatic and electromagnetic) affecting the plasma. The algorithm separately solves and converges the different model equations, within quasi-independent calculation modules, taking advantage of their characteristic relaxation times. In particular, the full solutions to the electron and ion transport equations are sequentially obtained, contrary to the procedure usually adopted in plasma fluid-type models. The algorithm is applied to the 1-D modeling of atmospheric-pressure microplasmas in argon, produced within the end gap of a microstrip-like transmission line by a continuous microwave excitation (at 2.45-GHz frequency). The runtimes are of 25-60 min on a 2.66-GHz CPU for the convergence criteria imposing global errors smaller than 10(-4)-10(-7).
This study demonstrated preliminary results in diagnosis of the numerical model with reference to the TRMM/PR, examples of the GPM/DPR synthetic data, and application of the synthetic data to the algorithm development...
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ISBN:
(纸本)9781424495665
This study demonstrated preliminary results in diagnosis of the numerical model with reference to the TRMM/PR, examples of the GPM/DPR synthetic data, and application of the synthetic data to the algorithm development in the nonuniform beamfilling correction method. These were performed using a satellite radar simulation algorithm by the National Institute of Information and Communications Technology (NICT) and the Japan Aerospace Exploration Agency (JAXA) named as the Integrated Satellite Observation Simulator for Radar (ISOSIM-Radar) and a cloud-resolving model by the Japan Meteorological Agency (JMA-NHM).
Most modeling and simulation approaches applied in cell biology assume a homogeneous distribution of particles in space, although experimental studies reveal the importance of space to understand the dynamics of cells...
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ISBN:
(纸本)9781424498642
Most modeling and simulation approaches applied in cell biology assume a homogeneous distribution of particles in space, although experimental studies reveal the importance of space to understand the dynamics of cells. There are already numerous spatial approaches focusing on the simulation of cells. Recently, they have been complemented by a set of spatial modeling languages whose operational semantics are tied partly to existing simulation algorithms. These modeling languages allow an explicit description of spatial phenomena, and facilitate analysis of the temporal spatial dynamics of cells by a clear separation between model, semantics, and simulator. With the supported level of abstraction, each of those offers a different perception of the spatial phenomena under study. In this paper, we give an overview of existing modeling formalisms and discuss some ways of combining approaches to tackle the problem the computational costs induced by spatial dynamics.
Cellular automata are a well-known modeling formalism exploited in a wide range of application areas. In many of those, the complexity of models hampers a thorough analysis of the system under study. Therefore, effici...
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ISBN:
(纸本)9781424448630
Cellular automata are a well-known modeling formalism exploited in a wide range of application areas. In many of those, the complexity of models hampers a thorough analysis of the system under study. Therefore, efficient simulation algorithms are required. We present here a comparison of seven different simulation algorithms for cellular automata: the classical "full" simulator, the classical "discrete event" simulator, a threaded (multi core) variant of each of these, an adaptable threaded variant, and a GPU based algorithm with and without readback of calculated states. The comparison is done based on the M&S framework JAMES II by using a set of well-known models.
In milling process, surface topography is a significant factor that affects directly the surface integrity and constitutes a supplement to the form error associated with the workpiece deformation. Based on the tool ma...
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In milling process, surface topography is a significant factor that affects directly the surface integrity and constitutes a supplement to the form error associated with the workpiece deformation. Based on the tool machining paths and the trajectory equation of the cutting edge relative to the workpiece, a new and general iterative algorithm is developed here for the numerical simulation of the machined surface topography in multiaxis ball-end milling. The influences of machining parameters such as the milling modes, cutter runout, cutter inclination direction, and inclination angle upon the topography and surface roughness values are studied in detail. Compared with existing methods, the basic advantages and novelties of the proposed method can be resumed below. First, it is unnecessary to discretize the cutting edge and tool feed motion and rotation motion. Second, influences of cutting modes and cutter inclinations are studied systematically and explicitly for the first time. The generality of the algorithm makes it possible to calculate the pointwise topography value on any sculptured surface of the workpiece. Besides, the proposed method is proved to be more efficient in saving computing time than the time step method that is commonly used. Finally, some examples are presented and simulation results are compared with experimental ones.
In this paper, we discuss the class of generalized Birnbaum-Saunders distributions, which is a very flexible family suitable for modeling lifetime data as it allows for different degrees of kurtosis and asymmetry and ...
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In this paper, we discuss the class of generalized Birnbaum-Saunders distributions, which is a very flexible family suitable for modeling lifetime data as it allows for different degrees of kurtosis and asymmetry and unimodality as well as bimodality. We describe the theoretical developments on this model including properties, transformations and related distributions, lifetime analysis, and shape analysis. We also discuss methods of inference based on uncensored and censored data, diagnostics methods, goodness-of-fit tests, and random number generation algorithms for the generalized Birnbaum-Saunders model. Finally, we present some illustrative examples and show that this distribution fits the data better than the classical Birnbaum-Saunders model.
Agile manufacturing has become a topic of great interest over the past several years. The entire domain of modeling and analyzing different types of agile manufacturing environments and systems, however, remain largel...
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Agile manufacturing has become a topic of great interest over the past several years. The entire domain of modeling and analyzing different types of agile manufacturing environments and systems, however, remain largely unexplored. The objective of this paper is to provide fundamental insight into how manufacturing systems should be designed and reconfigured over time in order to cope with different agile manufacturing factors. To achieve this objective, three approaches are developed and integrated into one simulation-based model. The first approach is used to model different agile manufacturing environments. The second approach is used to define various ways in which manufacturing systems can be designed and reconfigured (i.e., design/reconfiguration strategies). The third comprises the cost and objective functions used to measure system performance when different design/reconfiguration strategies are used in different agile manufacturing environments. Based upon the assumptions adopted, the experimental work performed suggests that despite the fact that agility incurs high costs, agile manufacturing systems are indeed necessary for certain manufacturing environments in which product life cycles are short yet demand per product type is high. Therefore, it is important in certain manufacturing environments to focus on reconfiguration in short periods of time, even at the expense of higher reconfiguration costs.
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