SIMULATING STRUCTURAL CHANGE IN ADAPTIVE ORGANIZATIONS

This paper presents an agent-based model of an organization. The model is made of a social network—composed of the different organization workers—and a knowledge network. Workers are assigned tasks, for which they have to use information in the knowledge network. We have modeled the quality of the information by assigning each information item a probability of being wrong. Agents can interact with other agents, who can recommend to them new information items in the knowledge network for the task to be performed. Workers are assigned different information-seeking behavior (passive, active, and learning), governing the way in which they interact with each other. Moreover, indirect interaction is also possible, as a publicly accessible knowledge base contains each agent's preferred information items.

The model was implemented in SDML, and its simulation shows that agents quickly learn to discern the better information items for the given task. However, group formation (agents' collaborating by exchanging information) takes longer to stabilize. Additionally, when the quality of items is changed, agents can quickly select the better new knowledge items, and organization performance improves again to a maximum that is only randomly disturbed.     

Dynamic tabletop interfaces for increasing creativity

We designed a tabletop brainwriting interface to examine the effects of time pressure and social pressure on the creative performance. After positioning this study with regard to creativity research and human activity in dynamic environments, we present our interface and experiment. Thirty-two participants collaborated (by groups of four) on the tabletop brainwriting task under four conditions of time pressure and two conditions of social pressure. The results show that time pressure increased the quantity of ideas produced and, to some extent, increased the originality of ideas. However, it also deteriorated user experience. Besides, social pressure increased quantity of ideas as well as motivation, but decreased collaboration. We discuss the implications for creativity research and Human–Computer Interaction. Anyhow, our results suggest that the Press factor, operationalized by Time- or Social-pressure, should be considered as a powerful lever to enhance the effectiveness of creative problem solving methods.     

Meta-modelling and graph grammars for multi-paradigm modelling in AToM<Superscript>3</Superscript>

This paper presents the combined use of meta-modelling and graph grammars for the generation of visual modelling tools for simulation formalisms. In meta-modelling, formalisms are described at a meta-level. This information is used by a meta-model processor to generate modelling tools for the described formalisms. We combine meta-modelling with graph grammars to extend the model manipulation capabilities of the generated modelling tools: edit, simulate, transform into another formalism, optimize and generate code. We store all (meta-)models as graphs, and thus, express model manipulations as graph grammars.We present the design and implementation of these concepts in AToM³ (A_To_ol for M_ulti-formalism, M_eta-M_odelling). AToM³ supports modelling of complex systems using different formalisms, all meta-modelled in their own right. Models in different formalisms may be transformed into a single common formalism for further processing. These transformations are specified by graph grammars. Mosterman and Vangheluwe [18] introduced the term multi-paradigm modelling to denote the combination of multiple formalisms, multiple abstraction levels, and meta-modelling. As an example of multi-paradigm modelling we present a meta-model for the Object-Oriented Continuous Simulation Language OOCSMP, in which we combine ideas from UML class diagrams (to express the OOCSMP model structure), Causal Block Diagrams (CBDs), and Statecharts (to specify the methods of the OOCSMP classes). A graph grammar is able to generate OOCSMP code, and then a compiler for this language (C-OOL) generates Java applets for the simulation execution.     

Quick fixing ATL transformations with speculative analysis

Model transformations are central components of most model-based software projects. While ensuring their correctness is vital to guarantee the quality of the solution, current transformation tools provide limited support to statically detect and fix errors. In this way, the identification of errors and their correction are nowadays mostly manual activities which incur in high costs. The aim of this work is to improve this situation. Recently, we developed a static analyser that combines program analysis and constraint solving to identify errors in ATL model transformations. In this paper, we present a novel method and system that uses our analyser to propose suitable quick fixes for ATL transformation errors, notably some non-trivial, transformation-specific ones. Our approach supports speculative analysis to help developers select the most appropriate fix by creating a dynamic ranking of fixes, reporting on the consequences of applying a quick fix, and providing a pre-visualization of each quick fix application. The approach integrates seamlessly with the ATL editor. Moreover, we provide an evaluation based on existing faulty transformations built by a third party, and on automatically generated transformation mutants, which are then corrected with the quick fixes of our catalogue.     

DRYING OF BIOLOGICAL PRODUCTS WITH SIGNIFICANT VOLUME VARIATION. EXPERIMENTAL AND MODELING RESULTS FOR POTATO DRYING.

This work is devoted to the experimental investigation and theoretical modeling of biological products with high initial moisture content which implies significant volume contraction. Firstly, experimental equipment which was designed to continuously determine variations in the global moisture content and in the temperature of the sample is introduced. Furthermore, the equipment is controlled by a PC which records experimental information in real time. In particular, measurement of the radial and temporal distributions of moisture content and temperature during the drying process of the homogeneous porous media potato are given. The mean moisture content and temperature curves are also given.     

A New Approach to Quantify Na-Fluorescein (Uranine) in Acid Mine Waters

Sodium fluorescein (uranine) is one of the most popular fluorescent dyes for tracer experiments due to its chemical properties, low detection limits and low costs. As a limiting factor, it is generally assumed that Na-fluorescein cannot be properly detected under acid conditions because of weak fluorescence intensities at the standard excitation wavelength (490 nm). This laboratory study introduces a method to quantify Na-fluorescein in low pH waters without having to raise pH to alkaline conditions, which spares the time- and cost-intensive filtration of hydroxide precipitates prior to analysis. It was applied for recovery tests in water samples from five mining sites in Germany. These were buffered to pH 1.5 where Na-fluorescein shows a second fluorescence intensity maximum at an excitation wavelength of 438 nm. The method had satisfying recovery rates although, as expected, a higher detection limit compared to standard wavelength and pH. High Fe contents in the waters are a limiting factor—the impact of increasing Fe concentrations at a constant dye spike was evaluated and yielded a distinct negative trend between Fe and detected Na-fluorescein, probably due to Fe-fluorescein complexation. However, good recovery can be expected in mine waters with up to ≈100 mg L⁻¹ Fe. The method of standard addition offers a potential calculative solution for higher Fe concentrations, resulting in significantly better Na-fluorescein recovery rates, compared to direct measurements. The method introduced here represents a promising approach for improving Na-fluorescein applicability in acid environments.