Task difficulty and team diversity on team creativity: Multi-agent simulation approach

Organizational structures are complex and vary according to sector, field, and type of business or service. In order to be effective, an organization needs to tailor its activities to the environment in which is it located. Based on contingency perspectives, this study is focused on investigating effective ways to design team diversity and maximize team creativity according to task difficulty levels. Considering the organizational team member as an agent, the study employed a multi-agent simulation method to understand the progress of creative manifestation, by observing the exploration and exploitation activity of team members over certain periods of time. The results first reveal that the level of team diversity influences the amount of creativity manifested by team members’ activities, such as exploration and exploitation. Second, managers have to properly facilitate either exploration or exploitation depending on task difficulty by striking a balance between them.     

The solvent (water) and metal effects on HOMO-LUMO gaps of guanine base pair: A computational study

The most stable structures of guanine dimer and metal-mediated guanine base pair complexes were determined both in vacuum and solvent (water). Density functional theory (DFT) method is generally used in the calculations. The calculations of systems containing C, H, N, O is described by 6-311 + +G(d,p) basis set and LANL2DZ basis set is used for transition metals. Some geometrical parameters, the LUMO, HOMO energy levels and energy gaps of compounds are calculated. Hydrogen bond stabilization energies in dimer and charge transfer in metal complexes are also determined using NBO analysis. The solvent and metal effects on energy gaps of molecules are found. Cu-mediated guanine complex can be preferred for nanotechnological applications due to its good electronic properties.     

A formulation of computational trust based on quantum decision theory

In this paper, we propose a new formulation of computational trust based on quantum decision theory (QDT). By using this new formulation, we can divide the assigned trustworthiness values to objective and subjective parts. First, we create a mapping between the QDT definitions and the trustworthiness constructions. Then, we demonstrate that it is possible for the quantum interference terms to appear in the trust decision making process. By using the interference terms, we can quantify the emotions and subjective preferences of the trustor in various contexts with different amounts of uncertainty and risk. The non-commutative nature of quantum probabilities is a valuable mathematical tool to model the relative nature of trust. In relative trust models, the evaluation of a trustee candidate is not only dependent on the trustee itself, but on the other existing competitors. In other words, the first evaluation is performed in an isolated context whereas the rest of the evaluations are performed in a comparative one. It is shown that a QDT-based model of trust can account for these order effects in the trust decision making process. Finally, based on the principles of risk and uncertainty aversion, interference alternation theorem and interference quarter law, quantitative values are assigned to interference terms. By performing empirical evaluations, we have demonstrated that various scenarios can be better explained by a quantum model of trust rather than the commonly used classical models.     

The effects of decision support and task contingencies on model formulation: A cognitive perspective

This paper takes a cognitive cost-benefit approach to understanding model formulation. Work in the behavioral decision literature on the role of effort and accuracy in choice tasks indicates that effort, or cognitive cost, is a key factor in understanding decision behavior. However, the model formulation literature does not discuss how effort interacts with other factors, such as task complexity and decision aids, to influence model formulation. In this paper, based on the work on the cost-benefit theories of cognition, we posit that two types of effort, namely that associated with building or formulating a model and that associated with utilizing that model in the solution of a problem, will influence model formulation. We then examine how the methods used in the behavioral decision making literature and the reported findings concerning the interaction of effort with task and decision aids can be utilized to understand model formulation.     

A computational study of vortex-airfoil interaction using high-order finite difference methods

Simulations of the interaction between a vortex and a NACA0012 airfoil are performed with a stable, high-order accurate (in space and time), multi-block finite difference solver for the compressible Navier-Stokes equations.We begin by computing a benchmark test case to validate the code. Next, the flow with steady inflow conditions are computed on several different grids. The resolution of the boundary layer as well as the amount of the artificial dissipation is studied to establish the necessary resolution requirements. We propose an accuracy test based on the weak imposition of the boundary conditions that does not require a grid refinement.Finally, we compute the vortex-airfoil interaction and calculate the lift and drag coefficients. It is shown that the viscous terms add the effect of detailed small scale structures to the lift and drag coefficients.     

The impact of instruction pointer corruption on program flow: A computational modelling study

Corruption of the instruction pointer, the main cause of program flow errors, is a common failure mode in the presence of high levels of electromagnetic interference. In this paper, results from a sub-cycle level simulator intended to provide an insight into the impact of EMI on such systems are described, and a detailed model of the impact on EMI on embedded processors is presented.     

The impact of replenishment parameters and information sharing on the bullwhip effect: A computational study

Demand variability amplification across the supply chain, known as the bullwhip effect, results in serious inefficiencies across the chain. Managers are expected to minimize this phenomenon in their chain in order to reduce costs and increase customer satisfaction by making critical decisions on replenishment policy. We study how specific replenishment parameters affect order variability amplification, product fill rates and inventory levels across the chain. Furthermore, we study how demand information sharing can help towards reducing order oscillations and inventory levels in upper nodes of a supply chain. A two-stage supply chain consisting of a warehouse and stores that face customer demand is modeled. Real demand data are used as the underlying customer demand during the experiments.     

Grouping efficiency measures and their impact on factory measures for the machine-part cell formation problem: A simulation study

Over the past 25 years, the machine-part cell formation problem has been the subject of numerous studies. Researchers have applied various methodologies to the problem in an effort to determine optimal clusterings of machines and optimal groupings of parts into families. The quality of these machine and part groupings have been evaluated using various objective functions, including grouping efficacy, grouping index, grouping capability index, and doubly weighted grouping efficiency, among others. In this study, we investigate how appropriate these grouping quality measures are in determining cell formations that optimize factory performance. Through the application of a grouping genetic algorithm, we determine machine/part cell formations for several problems from the literature. These cell formations are then simulated to determine their impact on various factory measures, such as flow time, wait time, throughput, and machine utilization, among others. Results indicate that it is not always the case that a “more efficient” machine/part cell formation leads to significant changes or improvements in factory measures over a “less efficient” cell formation. In other words, although researchers are working to optimize cell formations using efficiency measures, cells formed this way do not always demonstrate optimized factory measures.     

Team play with a powerful and independent agent: a full-mission simulation study

One major problem with pilot-automation interaction on modern flight decks is a lack of mode awareness; that is, a lack of knowledge and understanding of the current and future status and behavior of the automation. A lack of mode awareness is not simply a pilot problem; rather, it is a symptom of a coordination breakdown between humans and machines. Recent changes in automation design can therefore be expected to have an impact on the nature of problems related to mode awareness. To examine how new automation properties might affect pilot-automation coordination, we performed a full-mission simulation study on one of the most advanced automated aircraft, the Airbus A-320. The results of this work indicate that mode errors and "automation surprises" still occur on these advanced aircraft. However, there appear to be more opportunities for delayed or missing interventions with undesirable system activities, possibly because of higher system autonomy and coupling.     

A multiple comparative study of test-with development product changes and their effects on team speed and product quality

Researchers have typically studied the effects of Test-First Development (TFD), compared to Test-Last Development (TLD), across groups or projects, and for relatively short durations. We defined Test-With Development (TWD) as more general than the fine-grained step of TFD, but also in contrast to the large-grained phase of TLD. With our definition, we performed a multiple comparative study to explore and describe TWD product changes, and the effects of those changes on two attributes related to team speed and two attributes related to product quality, within six long-term open-source projects. Our results indicate that when developers exercised some of their changes with automated tests, on average they made significantly larger changes over time while significantly reducing their product’s complexity. And, when they exercised all of their changes with tests, on average they made significantly smaller changes over time. We interpret these results to indicate that practicing TWD supports faster simplification of a product. Therefore, we conclude that teams that need to reduce their product’s complexity can benefit from practicing TWD.     

Effect of WiFS viewing geometry on crop reflectance: A simulation study using SAIL model

The Wide-Field Sensor (WiFS) on board Indian Remote Sensing Satellites (IRS-1C, IRS-P3 and IRS-1D) has a wide swath (～810 km) and is thus able to provide high repetivity (5/3 days) data acquired from different orbits. The impact of variable viewing geometry from WiFS on crop reflectance was investigated for Delhi (77.2°E and 28.58°N) for all 122 possible acquisitions by IRS-1C during 1997. Using the SAIL simulation model, top-of-canopy red and near-infrared reflectances were simulated for partial and closed crop canopies over soils of different brightness. Results show significant variations in red and near-infrared reflectances. The effects are higher in partial canopies, and they are observed in Normalized Difference Vegetation Index (NDVI) also. For partial canopy, the seasonal variations with solar zenith angle are also significant. For closed canopy, these variations are less, and computed NDVI is relatively insensitive to viewing geometry.     

A case study of environmental modelling and simulation using transplantable components

Recent changes in environmental modelling practice have included adoption of modern software engineering concepts of model reuse, extensibility and flexibility, and development of better visual user interfaces. Additionally, the concepts of component-based software development and use of object-oriented programming have produced new environmental modelling methods. These changes have been supported by development of a range of modelling environments that allow rapid creation of environmental models from components. To date there has been little exploration of the opportunities that modelling environments offer in terms of flexible model construction by transplanting components. In the work reported here, simple catchment-based nonpoint source pollution models are constructed using the ICMS modelling environment, and a number of different data types and components are used within a single model structure to estimate pollution loads. Models include a bulk runoff-concentration load calculation, an export coefficient model, and land-use specific runoff and loads. It was found that, when applied using a powerful and flexible modelling environment, the component-based modelling concept provides not only an elegant method for model development, but also the opportunity to explore model expansion and refinement through use of transplantable components.     

Environmental effects on WBGT and HSI using a computer simulation

A computer simulation was used to investigate environmental effects on Wet Bulb Globe Temperature (WBGT) and to compare WBGT to Heat Stress Index (HSI). Constant values of WBGT (isometrics) were straight lines on a psychrometric chart with a slope of −1.17 mmHg/dgC. The intercept on the dry bulb axis (zero water vapor pressure) changed with WBGT value, air velocity (v), and mean wall temperature expressed as an increment above air temperature (ΔT_w); there was also an interaction between v and ΔT_w on changes in intercept. For a given target value of WBGT, HSI changed with environmental conditions, especially with v. Using effective air velocity (adding a component of air movement associated with activity) reduced much of the variation in HSI. Comparisons between WBGT and HSI suggested that the effect of increasing metabolism was either overestimated by HSI or underestimated by recommended WBGT action levels.     

The effect of simulation games on the learning of computational problem solving

Simulation games are now increasingly applied to many subject domains as they allow students to engage in discovery processes, and may facilitate a flow learning experience. However, the relationship between learning experiences and problem solving strategies in simulation games still remains unclear in the literature. This study, thus, analyzed the feedback and problem solving behaviors of 117 students in a simulation game, designed to assist them to learn computational problem solving. It was found that students when learning computational problem solving with the game were more likely to perceive a flow learning experience than in traditional lectures. The students’ intrinsic motivation was also enhanced when they learned with the simulation game. In particular, the results of the study found a close association between the students’ learning experience states and their problem solving strategies. The students who perceived a flow experience state frequently applied trial-and-error, learning-by-example, and analytical reasoning strategies to learn the computational problem solving skills. However, a certain portion of students who experienced states of boredom and anxiety did not demonstrate in-depth problem solving strategies. For instance, the students who felt anxious in the simulation game did not apply the learning-by-example strategy as frequently as those in the flow state. In addition, the students who felt bored in the simulation game only learned to solve the problem at a superficial level.     

A decision support system for paper making based on simulation and optimization

In this paper a model-driven decision support system related to paper making is introduced. The intention is to emphasize the necessity of coupling different modeling techniques, multiobjective optimization, and software engineering in order to make the end user application realistic, practical and usable. Firstly the paper making process and selected aspects concerning its mathematical modeling, numerical simulation, and multiobjective optimization are introduced, then the related computerized system, called a virtual paper making line, is described. In addition, the associated decision support system, which provides a suitable level of automation to improve the quality of decision making and support the user’s expertise is discussed. Finally, an example presents different ways of using such a software tool.     

Machine recognition efficiency study of safety signs based on image degradation simulation

This study focuses on the influence of image degradation on machine recognition of safety signs. This paper attempts to classify and grade the image degradation of safety signs. By the means of simulation, this paper also tries to break the limit of real-time image recognition. In this paper, the image degradation of safety signs is classified into 12 types. Each type is simulated by different ways of picture processing. All the pictures are performed machine recognition by convolutional neural network, and the accuracy is recorded. The mechanism of image degradation affecting the recognition efficiency is studied, and an A/B test with real-time safety signs is conducted to evaluate the performance. The results show that the effect of pixel displacement on the recognition efficiency is generally lower than the effect of pixel replacement by calculation. The effect on the recognition efficiency is smaller with less pixel displacement and simpler calculation. Overlay and fusion make the recognition efficiency unstable. The recognition efficiency of real-time safety signs will be higher when the test group contains degraded images as samples. The main part of a safety sign is very important in the recognition process and should be dealt with appropriate protection.

     

Interaction effects of consumers' product class knowledge and agent search strategy on consumer decision making in electronic commerce

This paper investigates the interaction effects between the search strategy of software agents and consumers' product class knowledge in the context of consumers seeking to purchase cars on the Internet. The research design used was a 2/spl times/4, between-groups, completely randomized, two-factor, factorial design. The independent variables that were manipulated were product class knowledge (HIGH KNOWLEDGE, LOW KNOWLEDGE) and agent search strategy [elimination by aspects (EBA STRATEGY), weighted average method (WAD STRATEGY), profile building (PROFILE STRATEGY), simple hypertext (HYPERTEXT STRATEGY)]. The dependent variables that were measured were satisfaction with the decision process (SATISFACTION), confidence in the decision (CONFIDENCE), trust in the agent's recommendations (TRUST), propensity to purchase (PURCHASE), perceived cost savings (SAVINGS), and cognitive decision effort (EFFORT). Significant differences were found in the affective reactions of the subjects toward the agent/application depending on the level of product class knowledge possessed by the subjects. Subjects with high product class knowledge had more positive affective reactions toward agents/applications that used the WAD and EBA strategies as compared to the PROFILE strategy. Subjects with low product class knowledge had more positive affective reactions to agents/applications that used the PROFILE strategy as compared to the EBA and WAD strategies.     

The effects of virtuality level on task-related collaborative behaviors: The mediating role of team trust

This study aims to analyze the mediating role of team trust in the relationship between virtuality level and task-related collaborative behaviors. Three types of task-related collaborative behaviors were studied, namely team coordination, team cooperation, and team information exchange. Drawing upon theory and research on virtual teams and trust, we hypothesized that team trust partially mediated the effects of virtuality level on team coordination, team cooperation, and team information exchange. A laboratory experiment was carried out with 65 four-person teams randomly assigned to three communication media with different virtuality levels (face-to-face, video conference and computer-mediated communication). The results showed that team trust partially mediated the relationship between virtuality level and team coordination, and fully mediated this relationship with team cooperation and team information exchange.