A fuzzy clustering algorithm enhancing local model interpretability

In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach.     

Modeling language acquisition in atypical phenotypes.

An increasing number of connectionist models have been proposed to explain behavioral deficits in developmental disorders. These simulations motivate serious consideration of the theoretical implications of the claim that a developmental disorder fits within the parameter space of a particular computational model of normal development. The authors examine these issues in depth with respect to a series of new simulations investigating past-tense formation in Williams syndrome. This syndrome and the past-tense domain are highly relevant because both have been used to make strong theoretical claims about the processes underlying normal language acquisition. The authors conclude that computational models have great potential to advance psychologists' understanding of developmental deficits because they focus on the developmental process itself as a pivotal causal factor in producing atypical phenotypic outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Why is science difficult to learn? Things are seldom what they seem

Abstract The difficulties of learning science are related to the nature of science itself and to the methods by which science is customarily taught without regard to what is known about children's learning. An information processing model is proposed to guide thinking and research in this area.     

Wave propagation in two-phase flow of magnetic fluid under a nonuniform magnetic field

The effect of nonuniform magnetic field on the linear and nonlinear wave propagation phenomena in two-phase pipe flow of magnetic fluid is investigated theoretically to realize the effective energy conversion system using boiling two-phase flow of magnetic fluid. Firstly, the governing equations of two-phase flow based on the unsteady thermal nonequilibrium two-fluid model are presented and the linear void wave propagation phenomena in boiling two-phase flow are numerically analyzed by using the finite volume method. Next, the nonlinear pressure wave propagation in gas-liquid two-phase flow is numerically analyzed by using the finite different method. According to these theoretical studies on the wave propagation phenomena in two-phase flow of magnetic fluid, it seems to be a reasonable proposal that the precise control of the wave propagation in two-phase flow is possible by effective use of the magnetic force.     

Seeking the truth about ad hoc join costs

In this paper, we re-examine the results of prior work on methods for computing ad hoc joins. We develop a detailed cost model for predicting join algorithm performance, and we use the model to develop cost formulas for the major ad hoc join methods found in the relational database literature. We show that various pieces of “common wisdom” about join algorithm performance fail to hold up when analyzed carefully, and we use our detailed cost model to derive op timal buffer allocation schemes for each of the join methods examined here. We show that optimizing their buffer allocations can lead to large performance improvements, e.g., as much as a 400% improvement in some cases. We also validate our cost model's predictions by measuring an actual implementation of each join algorithm considered. The results of this work should be directly useful to implementors of relational query optimizers and query processing systems. Edited by M. Adiba. Received May 1993 / Accepted April 1996     

Automatic generation of IDEF0 models

This paper looks into a new area for knowledge-based system application, that of manufacturing modelling. Manual generation of IDEF0 models of manufacturing systems is time-consuming and inconsistent. However, the process can be automated to improve timeliness and consistency. In this paper, a knowledge-based manufacturing modelling system for the automatic generation of IDEF0 models is proposed. The system will not only greatly reduce the IDEF0 modelling time but will also eliminate the inconsistency problem of conventional IDEF0 modelling systems. The paper explains the knowledge-based approach and identifies the kinds of domain knowledge that are required for the construction of the knowledge-based manufacturing modelling system.     

钡酚醛树脂体系化学流变特性研究

在粘度实验和DSC热分析实验的基础上,对用于RTM工艺的钡酚醛树脂体系的化学流变特性进行研究,并根据双阿累尼乌斯方程建立树脂体系的流变模型。模型与实验结果具有良好的一致性。模型可揭示树脂体系在不同工艺条件下的粘度变化规律,定量预报RTM工艺树脂的低粘度平台工艺窗口,为合理制定RTM工艺参数、保证产品质量和实现工艺参数的全局优化提供必要的科学依据。     

Uncertainty in Quantitative Electron Probe Microanalysis

Quantitative electron probe analysis is based on models based on the physics or x-ray generation, empirically adjusted to the analyses of specimens of known composition. Their accuracy can be estimated by applying them to a set of specimens of presumably well-known composition.     

A TVD Scheme for Incompressible Flow Coupled With Different Turbulence Modles on A Ground-Mounted Square-RIB Flow

A finite-difference Total Variation Diminishing (TVD) numerical simulation model for coupling the Reynolds Averaged Navier-Stokes (RANS) equations, pressure-relative continuity equation and various k-ε turbulence models was developed to solve the incompressible flow based on the pseudo-compressibility method. The hyperbolicity of all these equations was studied and the discretization of the fully coupling equations with all the primal variables and source terms were made in this article. Numerical simulation for modeling the flow around a ground-mounted square rib was implemented and validated by comparing with the published wind tunnel experimental data. It is shown that such a numerical simulation method with a proper turbulence model has a very good accuracy to simulate the flow around a surface-mounted rib. It is concluded that the Renormalization Group (RNG) and Chen-Kim k-ε turbulence models have much better ability to predict the characteristics of the vortex structure and flow separation than the standard k-ε model.     

Reliability models for computer systems: An overview including dataflow graphs

The reliability of a system is the probability that the system will perform its intended mission under given conditions. This paper provides an overview of the approaches to reliability modelling and identifies their strengths and weaknesses. The models discussed include structure models, simple stochastic models and decomposable stochastic models. Ignoring time-dependence, structure models give reliability as a function of the topological structure of the system. Simple stochastic models make direct use of the properties of underlying stochastic processes, while decomposable models consider more complex systems and analyse them through subsystems. Petri nets and dataflow graphs facilitate the analysis of complex systems by providing a convenient framework for reliability analysis.