Systematic modeling and model handling for manpower planning systems

The primary purpose of this paper is to show an efficient way of handling models and model data in a decision support system, in which it is usual to consider several variants of a model. The model data primarily consist of model-defining data, but the same approach may be used for the generated results as well. By efficient handling is meant the handling by the computer as well as by the user. For the user it is particularly important that new models can be conveniently defined as variants of existing models. The approach is introduced within the context of a decision support system for manpower planning based on Markov models. In the mean time the same approach has been used for the implementation of other decision support systems and has been found to be more generally applicable.     

智能化空调设计负荷计算软件的开发

为了解决目前已有空调负荷计算软件使用效率低，不符合设计人员思维习惯的弊病，本文将基于神经网络的专家系统技术与空调负荷“指标估算法”结合起来，开发了一套智能化空调负荷计算软件，对空调设计负荷计算的智能化进行了有益的尝试。该软件计算结果准确，特别适合于经验不足的设计人员使用。     

人造参考星系统设计

简述了人造参考星系统，并用该系统作为大型望远镜主动光学和自适应光学的Ｓｈａｃｋ－Ｈａｒｔｍａｎ波面探测系统的光源。     

Computer software as text

Participatory design strategies have placed the user at the center of the design process, leaving computer software designers without guidelines for how to design and implement the software system. This paper aims to bring the designer back to the center of the design process. and the way of doing it is to consider computer software as text. Three different text theories are presented in order to explain what is meant by text, namely pragmatics, structuralism and deconstructivism. Finally it is discussed how the design processes should be understood, and how they should be organized when taking the text point of view of computer software.     

Artificial intelligence and symbols

The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared with training. This can give more realistic goals for symbolic systems, particularly those based on logical foundations.     

Artificial Neural Network Modeling of Osmotic Dehydration Mass Transfer Kinetics of Fruits

Artificial neural network (ANN) models were developed for the prediction of transient moisture loss (ML) and solid gain (SG) in osmotic dehydration of fruits using process kinetics data from the literature. ANN models for ML and SG were developed based on data over a broad range of operating conditions and ten common processing variables: temperature and concentration of osmotic solution, immersion time, initial water and solid content of the fruit, porosity, surface area, characteristic length, solution-to-fruit mass ratio, and agitation level. The trained models were able to accurately predict the outputs with associated regression coefficients (r) of 0.96 and 0.93, respectively, for ML and SG. These ANN models performed much better than those obtained from linear multivariate regression analysis. The large number of process variables and their wide ranges considered along with their easy implementation in a spreadsheet make them very useful and practical for process design and control.     

Does positive affect influence the effective usage of a Decision Support System?

This study examines the impact of positive mood on the effective usage of a Decision Support System (DSS). Using current cognitive theories, a theoretical argument about DSS usage is developed. This argument is then investigated via a lab experiment. The results of the lab experiment show that decision makers in positive mood used a greater number of informational cues provided by the DSS and made more accurate judgments.     

Artificial added mass instabilities in sequential staggered coupling of nonlinear structures and incompressible viscous flows

Within this paper the so-called artificial added mass effect is investigated which is responsible for devastating instabilities within sequentially staggered Fluid-structure Interaction (FSI) simulations where incompressible fluids are considered.A discrete representation of the added mass operator M_A is given and ‘instability conditions’ are evaluated for different temporal discretisation schemes. It is proven that for every sequentially staggered scheme and given spatial discretisation of a problem, a mass ratio between fluid and structural mass density can be found at which the coupled system becomes unstable. The analysis is quite general and does not depend upon the particular spatial discretisation schemes used. However here special attention is given to stabilised finite elements employed on the fluid partition. Numerical investigations further highlight the results.