An agent-based platform for simulating complex human–aquifer interactions in managed groundwater systems

This paper presents and illustrates FlowLogo, an interactive modelling environment for developing coupled agent-based groundwater models (GW-ABMs). It allows users to simulate complex socio-environmental couplings in groundwater systems, and to explore how desirable patterns of groundwater and social development can emerge from agent behaviours and interactions. GW-ABMs can be developed using a single piece of software, addressing common issues around data transfer and model analyses that arise when linking ABMs to existing groundwater codes. FlowLogo is based on a 2D finite-difference solution of the governing groundwater flow equations and a set of procedures to represent the most common types of stresses and boundary conditions of regional aquifer flow. The platform is illustrated using a synthetic example of an expanding agricultural region that depends on groundwater for irrigation. The implementation and analysis of scenarios from this example highlight the possibility to: (i) deploy agents at multiple scales of decision-making (farmers, waterworks, institutions), (ii) model feedbacks between agent behaviours and groundwater dynamics, and (iii) perform sensitivity and multi-realisation analyses on social and physical factors. The FlowLogo interface allows interactively changing parameters using ‘tuneable’ dials, which can adjust agent decisions and policy levers during simulations. This flexibility allows for live interaction with audiences (role-plays), in participatory workshops, public meetings, and as part of learning activities in classrooms. FlowLogo's interactive features and ease of use aim to facilitate the wider dissemination and independent validation of GW-ABMs.     

An iterative predictor–corrector approach for modeling static and kinetic friction in interactive simulations

In this paper we propose a novel iterative predictor–corrector (IPC) approach to model static and kinetic friction during interactions with deformable objects. The proposed IPC method works within the purview of the implicit mixed linear complementarity problem (MLCP) formulation of collision response. In IPC, first the potential directions of frictional force are determined at each contact point by leveraging the monotonic convergence of an iterative MLCP solver. All the contacts are then categorized into either static or kinetic frictional states. Linear projection constraints (LPCs) are used to enforce ‘stiction’ for contacts in static friction. We propose a modified iterative constraint anticipation (MICA) approach that can resolve the LPCs while simultaneously solving the MLCP. Our method can handle arbitrary models including asymmetric and anisotropic friction models. IPC requires low memory and is highly tunable. Multiple example problems are solved to demonstrate the method.     

Automatic domain modeling for human–robot interaction

Intelligent Service Robotics - This paper introduces an approach to automatic domain modeling for human–robot interaction. The proposed approach is symbolic and intended for semantically...     

An improved model along with a spectral numerical simulation for fractional predator–prey interactions

Predator–prey models appear in various fields of bio-mathematics used for the analysis of interactions of biological systems. Due to the complexities of the physical context for the real-world problems of food chain dynamics, introducing new models compatible with experimental results stays ongoing research. Many models have been proposed and analyzed for these systems in recent years. In this paper, we propose a new fractional-order predator–prey model with negative feedback on both species with memory-dependent effects, which increases the compatibility level of the model. Then we present a novel Laguerre spectral numerical simulation for the proposed model by introducing Laguerre modal basis functions with collocation and Galerkin techniques. We then transfer the nonlinear model into a system of algebraic equations, which is solved by efficient numerical solvers. Finally, we provide some test problems to show the efficiency of the proposed model and the computational method.

     

An adaptive XIGA with locally refined NURBS for modeling cracked composite FG Mindlin–Reissner plates

Engineering with Computers - This paper is devoted to numerical investigations on mechanical behavior of cracked composite functionally graded (FG) plates. We thus develop an efficient adaptive...     

An Embedded Co-AdaBoost based construction of software document relation coupled resource spaces for cyber–physical society

Software is a very important means of achieving the vision of the cyber–physical society. Software document relation coupled Resource Spaces prompts the cyber–physical society by facilitating the reuse of software design knowledge. The establishment of software document relation coupled Resource Spaces faces the scarcity of labeled data that helps discovering software document relations between resources dwelling in different Resource Spaces. This paper proposes the Embedded Co-AdaBoost algorithm to overcome this challenge by making the best use of easily available unlabeled data, integrating multi-view learning into the AdaBoost and leveraging the advantages of Co-training for performance enhancement. Compared with conventional AdaBoost, the experiment illustrates the effectiveness of the Embedded Co-AdaBoost in the convergence rate, the accuracy and the steady performance. The empirical experience demonstrates the ability of the Embedded Co-AdaBoost in prompting the development of software document relation coupled Resource Spaces.     

Loss estimation for landslides in mountain areas – An integrated toolbox for vulnerability assessment and damage documentation

Global environmental change includes changes in a wide range of global scale phenomena, which are expected to affect a number of physical processes, as well as the vulnerability of the communities that will experience their impact. Decision-makers are in need of tools that will enable them to assess the loss of such processes under different future scenarios and to design risk reduction strategies. In this paper, a tool is presented that can be used by a range of end-users (e.g. local authorities, decision makers, etc.) for the assessment of the monetary loss from future landslide events, with a particular focus on torrential processes. The toolbox includes three functions: a) enhancement of the post-event damage data collection process, b) assessment of monetary loss of future events and c) continuous updating and improvement of an existing vulnerability curve by adding data of recent events. All functions of the tool are demonstrated through examples of its application.     

An adaptive FIR filter for trajectory prediction and latency reduction in direct Human–Computer interactions

The problem of latency reduction in direct Human–Computer interactions is considered. The proposed method is based on a frequency-domain approximation of a non-causal ideal predictor with a finite impulse response filter. Given a sufficiently rich dataset, the parameters of the filter can be either optimized off-line or tuned on-line with the proposed adaptive algorithm. The performance of the proposed solution is evaluated in an experimental study consisting of drawings on a touchscreen.     

A unified particle model for fluid–solid interactions

We present a new method for the simulation of melting and solidification in a unified particle model. Our technique uses the Smoothed Particle Hydrodynamics (SPH) method for the simulation of liquids, deformable as well as rigid objects, which eliminates the need to define an interface for coupling different models. Using this approach, it is possible to simulate fluids and solids by only changing the attribute values of the underlying particles. We significantly changed a prior elastic particle model to achieve a flexible model for melting and solidification. By using an SPH approach and considering a new definition of a local reference shape, the simulation of merging and splitting of different objects, as may be caused by phase change processes, is made possible. In order to keep the system stable even in regions represented by a sparse set of particles we use a special kernel function for solidification processes. Additionally, we propose a surface reconstruction technique based on considering the movement of the center of mass to reduce rendering errors in concave regions. The results demonstrate new interaction effects concerning the melting and solidification of material, even while being surrounded by liquids. Copyright © 2007 John Wiley & Sons, Ltd.     

GPU-based high-performance computing for integrated surface–sub-surface flow modeling

The widespread availability of high-resolution lidar data provides an opportunity to capture micro-topographic control on the partitioning and transport of water for incorporation in coupled surface – sub-surface flow modeling. However, large-scale simulations of integrated flow at the lidar data resolution are computationally expensive due to the density of the computational grid and the iterative nature of the algorithms for solving nonlinearity. Here we present a distributed physically based integrated flow model that couples two-dimensional overland flow and three-dimensional variably saturated sub-surface flow on a GPU-based (Graphic Processing Unit) parallel computing architecture. Alternating Direction Implicit (ADI) scheme modified for GPU structure is used for numerical solutions in both models. Boundary condition switching approach is applied to partition potential water fluxes into actual fluxes for the coupling between surface and sub-surface models. The algorithms are verified using five benchmark problems that have been widely adopted in literature. This is followed by a large-scale simulation using lidar data. We demonstrate that the method is computationally efficient and produces physically consistent solutions. This computational efficiency suggests the feasibility of GPU computing for fully distributed, physics-based hydrologic models over large areas.     

OCTBEC—A Matlab toolbox for optimal quantum control of Bose–Einstein condensates

OCTBEC is a Matlab toolbox designed for optimal quantum control, within the framework of optimal control theory (OCT), of Bose–Einstein condensates (BEC). The systems we have in mind are ultracold atoms in confined geometries, where the dynamics takes place in one or two spatial dimensions, and the confinement potential can be controlled by some external parameters. Typical experimental realizations are atom chips, where the currents running through the wires produce magnetic fields that allow to trap and manipulate nearby atoms. The toolbox provides a variety of Matlab classes for simulations based on the Gross–Pitaevskii equation, the multi-configurational Hartree method for bosons, and on generic few-mode models, as well as optimization problems. These classes can be easily combined, which has the advantage that one can adapt the simulation programs flexibly for various applications.     

An adjustable subdivision surface modeling scheme

Based on triangle and quadrilateral meshes, this paper presents an adjustable subdivision surface scheme. The scheme can produce subdivision surface of Cl continuity of limit surface Since an adjustable parameter is introduced to the scheme, the surface modeling is flexible. Depended on given initial data, the limited surface shape can be adjusted and controlled through selecting appropriate parameters. The method is effective in generating smooth surfaces.     

An accelerated algorithm for Navier–Stokes equations

In this paper, the numerical solution of the Navier–Stokes equations by the Characteristic-Based-Split (CBS) scheme is accelerated with the Minimum Polynomial Extrapolation (MPE) method to obtain the steady state solution for evolution incompressible and compressible problems.The CBS is essentially a fractional time-stepping algorithm based on an original finite difference velocity-projection scheme where the convective terms are treated using the idea of the Characteristic-Galerkin method. In this work, the semi-implicit version of the CBS with global time-stepping is used for incompressible problems whereas the fully-explicit version is used for compressible flows.At the other end, the MPE is a vector extrapolation method that transforms the original sequence into another sequence converging to the same limit faster then the original one without the explicit knowledge of the sequence generator.The developed algorithm, tested on two-dimensional benchmark problems, demonstrates the new computational features arising from the introduction of the extrapolation procedure to the CBS scheme. In particular, the results show a remarkable reduction of the computational cost of the simulation.     

The challenge of conceptual modeling for product–service systems: status-quo and perspectives for reference models and modeling languages

Confronted with decreasing margins and a rising customer demand for integrated solutions, manufacturing companies integrate complementary services into their portfolio. Offering value bundles (consisting of services and physical goods) takes place in integrated product–service systems, spanning the coordinated design and delivery of services and physical goods for customers. Conceptual Modeling is an established approach to support and guide such efforts. Using a framework for the design and delivery of value bundles as an analytical lens, this study evaluates the current support of reference models and modeling languages for setting up conceptual models for an integrated design and delivery of value bundles. Consecutively, designing modeling languages and reference models to fit the requirements of conceptual models in product–service systems are presented as upcoming challenges in Service Research. To guide further research, first steps are proposed by exemplarily integrating reference models and modeling languages stemming from the service and manufacturing domains.     

Three-stage performance modeling using DEA–BPNN for better practice benchmarking

This paper proposes an innovative three-stage model using data envelopment analysis (DEA) and backpropagation neural network (BPNN) for supporting ‘better practice’ benchmarking as contrasted with the traditional ‘best practice’ benchmarking. Research has shown that DEA models have the capability of setting optimal goals, but the drawback of the standard DEA approach is its inability to propose actionable targets necessary for incremental improvement. Overcoming the shortfalls of DEA and its superiority-driven practices, the neural network approach accommodates stepwise improvement through adaptive learning and prediction capability. Consequently, the proposed three-stage model is capable of generating feasible improvement options for managers as an intelligent decision support tool. At its core, the innovative approach provides a sound methodological foundation for shaping a ‘better practice’ paradigm and contributes to the literature through methodological advancement. The effectiveness of the model is empirically tested through the use of data from the healthcare industry, and the results confirm a practical utility of the model.     

Dempster–Shafer structure based fuzzy logic system for stochastic modeling

The Dempster–Shafer (D–S) theory of evidence is introduced to improve fuzzy inference under the complex stochastic environment. The Dempster–Shafer based fuzzy set (DFS) is first proposed, together with its union and intersection operations, to capture the principal stochastic uncertainties. Then, the fuzzy inference will be modified based on the extensional Dempster rule of combination. This new approach is able to capture the stochastic disturbance acting on fuzzy membership function, and provide a more effective inference under strong stochastic uncertainty. Finally, the numerical simulation and the experimental prediction of the wind speed are conducted to show the potential of the proposed method in stochastic modeling.