Using virtual worlds for collaborative business process modeling

Purpose Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. In this paper we suggest a 3D environment for collaborative process modeling, using Virtual World technology. Design/methodology/approach We suggest a new collaborative process modeling approach based on Virtual World technology. We describe the design of an innovative prototype collaborative process modeling approach, implemented as a 3D BPMN modeling environment in Second Life. We use a case study to evaluate the suggested approach. Findings Based on our case study application, we show that our approach increases user empowerment and adds significantly to the collaboration and consensual development of process models even when the relevant stakeholders are geographically dispersed. Research limitations implications – We present design work and a case study. More research is needed to more thoroughly evaluate the presented approach in a variety of real-life process modeling settings. Practical implications Our research outcomes as design artifacts are directly available and applicable by business process management professionals and can be used by business, system and process analysts in real-world practice. Originality/value Our research is the first reported attempt to develop a process modeling approach on the basis of virtual world technology. We describe a novel and innovative 3D BPMN modeling environment in Second Life.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Evaluating effects of eco-driving at traffic intersections based on traffic micro-simulation

Eco-driving is an initiative driving behavior which aims to reduce fuel consumption and emissions from automobiles. Recently, it has attracted increasing interests and has been adopted by many drivers in Australia. Although many of the studies have revealed considerable benefits in terms of fuel consumption and emissions after utilising eco-driving, most of the literature investigated eco-driving effects on individual driver but not traffic flow. The driving behavior of eco-drivers will potentially affect other drivers and thereby affects the entire traffic flow. To comprehensively assess and understand how effectively eco-driving can perform, therefore, measurement on traffic flow is necessary. In this paper, we proposed and demonstrated an evaluation method based on a microscopic traffic simulator (Aimsun). We focus on one particular eco-driving style which involves moderate and smooth acceleration. We evaluated both traffic performance (travel time) and environmental performance (fuel consumption and CO2 emission) at traffic intersection level in a simple simulation model. The before-and-after comparisons indicated potentially negative impacts when using eco-driving, which highlighted the necessity to carefully evaluate and improve eco-driving before wide promotion and implementation.

Modeling intrinsic noise and delays in chemical kinetics of coupled autoregulated oscillating cells

Delays are an important feature in temporal models of genetic regulation due to slow biochemical processes, such as transcription and translation. In this paper, we show how to model intrinsic noise effects in a delayed setting by either using a delay stochastic simulation algorithm (DSSA) or, for larger and more complex systems, a generalized Binomial τ-leap method (Bτ-DSSA). As a particular application, we apply these ideas to modeling somite segmentation in zebra fish across a number of cells in which two linked oscillatory genes (her1 and her7) are synchronized via Notch signaling between the cells.

Patient-Specific Modeling of Scoliosis

Current complication rates for adolescent spinal deformity surgery are unacceptably high and in order to improve patient outcomes, the development of a simulation tool which enables the surgical strategy for an individual patient to be optimized is necessary. In this chapter we will present our work to date in developing and validating patient-specific modeling techniques to simulate and predict patient outcomes for surgery to correct adolescent scoliosis deformity. While these simulation tools are currently being developed to simulate adolescent idiopathic scoliosis patients, they will have broader applications in simulating spinal disorders and optimizing surgical planning for other types of spine surgery. Our studies to date have highlighted the need for not only patient-specific anatomical data, but also patient-specific tissue parameters and biomechanical loading data, in order to accurately predict the physiological behaviour of the spine. Even so, patient-specific computational models are the state-of-the art in computational biomechanics and offer much potential as a pre-operative surgical planning tool.

Advanced musculoskeletal simulation as an ergonomic design method

In recent years, the advent of new tools for musculoskeletal simulation has increased the potential for significantly improving the ergonomic design process and ergonomic assessment of design. In this paper we investigate the use of one such tool, ‘The AnyBody Modeling System’, applied to solve a one-parameter and yet, complex ergonomic design problem. The aim of this paper is to investigate the potential of computer-aided musculoskeletal modelling in the ergonomic design process, in the same way as CAE technology has been applied to engineering design.

Interfacing Jack and anybody : towards anthropometric musculoskeletal digital human modeling

Virtual prototyping emerges as a new technology to replace existing physical prototypes for product evaluation, which are costly and time consuming to manufacture. Virtualization technology allows engineers and ergonomists to perform virtual builds and different ergonomic analyses on a product. Digital Human Modelling (DHM) software packages such as Siemens Jack, often integrate with CAD systems to provide a virtual environment which allows investigation of operator and product compatibility. Although the integration between DHM and CAD systems allows for the ergonomic analysis of anthropometric design, human musculoskeletal, multi-body modelling software packages such as the AnyBody Modelling System (AMS) are required to support physiologic design. They provide muscular force analysis, estimate human musculoskeletal strain and help address human comfort assessment. However, the independent characteristics of the modelling systems Jack and AMS constrain engineers and ergonomists in conducting a complete ergonomic analysis. AMS is a stand alone programming system without a capability to integrate into CAD environments. Jack is providing CAD integrated human-in-the-loop capability, but without considering musculoskeletal activity. Consequently, engineers and ergonomists need to perform many redundant tasks during product and process design. Besides, the existing biomechanical model in AMS uses a simplified estimation of body proportions, based on a segment mass ratio derived scaling approach. This is insufficient to represent user populations anthropometrically correct in AMS. In addition, sub-models are derived from different sources of morphologic data and are therefore anthropometrically inconsistent. Therefore, an interface between the biomechanical AMS and the virtual human model Jack was developed to integrate a musculoskeletal simulation with Jack posture modeling. This interface provides direct data exchange between the two man-models, based on a consistent data structure and common body model. The study assesses kinematic and biomechanical model characteristics of Jack and AMS, and defines an appropriate biomechanical model. The information content for interfacing the two systems is defined and a protocol is identified. The interface program is developed and implemented through Tcl and Jack-script(Python), and interacts with the AMS console application to operate AMS procedures.

A simulation to describe the effects of in-shoe orthoses

The subtalar joint has been presumed to account for most of the pathologic motion in the foot and ankle, but research has shown that motion at other foot joints is greater than traditionally expected. Although recent research demonstrates the complexity of the kinematic variables in the foot and ankle, it still fails to expand our knowledge of the role of the musculotendinous structures in the biomechanics of the foot and ankle and how this is affected by in-shoe orthoses. The aim of this study was to simulate the effect of in-shoe foot orthoses by manipulation of the ground reaction force (GRF) components and centre of pressure (CoP) to demonstrate the resultant effect on muscle force in selected muscles during both the rearfoot loading response and stance phase of the gait cycle. We found that any medial wedge increases ankle joint load during gait cycle, while a lateral wedge decreases the joint load during the stance phase.

Modeling collision avoidance decisions in navigation

Due to grave potential human, environmental and economical consequences of collisions at sea, collision avoidance has become an important safety concern in navigation. To reduce the risk of collisions at sea, appropriate collision avoidance actions need to be taken in accordance with the regulations, i.e., International Regulations for Preventing Collisions at Sea. However, the regulations only provide qualitative rules and guidelines, and therefore it requires navigators to decide on collision avoidance actions quantitatively by using their judgments which often leads to making errors in navigation. To better help navigators in collision avoidance, this paper develops a comprehensive collision avoidance decision making model for providing whether a collision avoidance action is required, when to take action and what action to be taken. The model is developed based on three types of collision avoidance actions, such as course change only, speed change only, and a combination of both. The model has potential to reduce the chance of making human error in navigation by assisting navigators in decision making on collision avoidance actions.

Dynamics of rod and cone photoreceptor interactions under mesopic light levels

Visual adaptation regulates contrast sensitivity during dynamically changing light conditions (Crawford, 1947; Hecht, Haig & Chase, 1937). These adaptation dynamics are unknown under dim (mesopic) light levels when the rod (R) and long (L), medium (M) and short (S) wavelength cone photoreceptor classes contribute to vision via interactions in shared non-opponent Magnocellular (MC), chromatically opponent Parvocellular (PC) and Koniocellular (KC) visual pathways (Dacey, 2000). This study investigated the time-course of adaptation and post-receptoral pathways mediating receptor specific rod and cone interactions under mesopic illumination. A four-primary photostimulator (Pokorny, Smithson & Quinlan, 2004) was used to independently control the activity of the four photoreceptor classes and their post-receptoral visual athways in human observers. In the first experiment, the contrast sensitivity and time-course of visual adaptation under mesopic illumination were measured for receptoral (L, S, R) and post-receptoral (LMS, LMSR, L-M) stimuli. An incremental (Rapid-ON) sawtooth conditioning pulse biased detection to ON-cells within the visual pathways and sensitivity was assayed relative to pulse onset using a briefly presented incremental probe that did not alter adaptation. Cone.Cone interactions with luminance stimuli (L cone, LMS, LMSR) reduced sensitivity by 15% and the time course of recovery was 25± 5ms-1 (μ ± SEM). PC mediated (+L-M) chromatic stimuli sensitivity loss was less (8%) than for luminance and recovery was slower (μ = 2.95 ± 0.05 ms-1), with KC mediated (S cone) chromatic stimuli showing a high sensitivity loss (38%) and the slowest recovery time (1.6 ± 0.2 ms-1). Rod-Rod interactions increased sensitivity by 20% and the time course of recovery was 0.7 ± 0.2 ms-1 (μ ± SD). Compared to these interaction types, Rod-Cone interactions reduced sensitivity to a lesser degree (5%) and showed the fastest recovery (μ = 43 ± 7 ms-1). In the second experiment, rod contribution to the magnocellular, parvocellular and koniocellular post-receptoral pathways under mesopic illumination was determined as a function of incremental stimulus duration and waveform (rectangular; sawtooth) using a rod colour match procedure (Cao, Pokorny & Smith, 2005; Cao, Pokorny, Smith & Zele, 2008a). For a 30% rod increment, a cone match required a decrease in [L/(L+M)] and an increase in [L+M] and [S/(L+M)], giving a greenish-blue and brighter appearance for probe durations of 75 ms or longer. Probe durations less than 75 ms showed an increase in [L+M] and no change in chromaticity [L/(L+M) or S/(L+M)], uggesting mediation by the MC pathway only for short duration rod stimuli. s We advance previous studies by determining the time-course and nature of photoreceptor specific retinal interactions in the three post-receptoral pathways under mesopic illumination. In the first experiment, the time-course of adaptation for ON cell processing was determined, revealing opponent cell facilitation in chromatic PC and KC pathways. The Rod-Rod and Rod-Cone data identify previously unknown interaction types that act to maintain contrast sensitivity during dynamically changing light conditions and improve the speed of light adaptation under mesopic light levels. The second experiment determined the degree of rod contribution to the inferred post-eceptoral pathways as a function of the temporal properties of the rod signal. r The understanding of the mechanisms underlying interactions between photoreceptors under mesopic illumination has implications for the study of retinal disease. Visual function has been shown to be reduced in persons with age-related maculopathy (ARM) risk genotypes prior to clinical signs of the disease (Feigl, Cao, Morris & Zele, 2011) and disturbances in rod-mediated adaptation have been shown in early phases of ARM (Dimitrov, Guymer, Zele, Anderson & Vingrys, 2008; Feigl, Brown, Lovie-Kitchin & Swann, 2005). Also, the understanding of retinal networks controlling vision enables the development of international lighting standards to optimise visual performance nder dim light levels (e.g. work-place environments, transportation).

Mixed-dimensional consistent coupling by multi-point constraint equations for efficient multi-scale modeling

Finding an appropriate linking method to connect different dimensional element types in a single finite element model is a key issue in the multi-scale modeling. This paper presents a mixed dimensional coupling method using multi-point constraint equations derived by equating the work done on either side of interface connecting beam elements and shell elements for constructing a finite element multiscale model. A typical steel truss frame structure is selected as case example and the reduced scale specimen of this truss section is then studied in the laboratory to measure its dynamic and static behavior in global truss and local welded details while the different analytical models are developed for numerical simulation. Comparison of dynamic and static response of the calculated results among different numerical models as well as the good agreement with those from experimental results indicates that the proposed multi-scale model is efficient and accurate.

Modeling train delays in urban networks

The reliability of urban passenger trains is a critical performance measure for passenger satisfaction and ultimately market share. A delay to one train in a peak period can have a severe effect on the schedule adherence of other trains. This paper presents an analytically based model to quantify the expected positive delay for individual passenger trains and track links in an urban rail network. The model specifically addresses direct delay to trains, knock-on delays to other trains, and delays at scheduled connections. A solution to the resultant system of equations is found using an iterative refinement algorithm. Model validation, which is carried out using a real-life suburban train network consisting of 157 trains, shows the model estimates to be on average within 8% of those obtained from a large scale simulation. Also discussed, is the application of the model to assess the consequences of increased scheduled slack time as well as investment strategies designed to reduce delay.