Fractal analysis and control in the predator–prey model

The two-dimensional predator–prey Lotka–Volterra model is discussed from the point of fractal theory. Julia set of the discrete version of the model is introduced. Then, the linear feedback control is taken to control the Julia set. By controlling the Julia set, the attractive domain of the attractive fixed point is controlled indirectly. To associate two different Julia sets of the model with different parameters, nonlinear coupling items are designed to make one Julia set change to be another. The simulations illustrate the efficacy of these methods.     

Performance analysis of an inventory–production system with shipment consolidation in the production facility

We consider an inventory–production system consisting of a warehouse and a production facility. The warehouse is used to store products to satisfy customer demands, and its inventory is controlled by an (r,Q)$(r,Q)$ policy. Products ordered by the warehouse are processed in the production facility on a one-by-one basis, and finished products are consolidated into batches to be shipped from the production facility to the warehouse. Using the matrix-analytic methods, explicit solutions are obtained and computational methods are developed for analyzing system performance measures.     

Route instructions in map-based human–human and human–computer dialogue: A comparative analysis

When conveying information about spatial situations and goals, speakers adapt flexibly to their addressee in order to reach the communicative goal efficiently and effortlessly. Our aim is to equip a dialogue system with the abilities required for such a natural, adaptive dialogue. In this paper we investigate the strategies people use to convey route information in relation to a map by presenting two parallel studies involving human–human and human–computer interaction. We compare the instructions given to a human interaction partner with those given to a dialogue system which reacts by basic verbal responses and dynamic visualization of the route in the map. The language produced by human route givers is analyzed with respect to a range of communicative as well as cognitively crucial features, particularly perspective choice and references to locations across levels of granularity. Results reveal that speakers produce systematically different instructions with respect to these features, depending on the nature of the interaction partner, human or dialogue system. Our further analysis of clarification and reference resolution strategies produced by human route followers provides insights into dialogue strategies that future systems should be equipped with.     

A priori and a posteriori error analysis of an augmented mixed-FEM for the Navier–Stokes–Brinkman problem

We introduce and analyze an augmented mixed finite element method for the Navier–Stokes–Brinkman problem with nonsolenoidal velocity. We employ a technique previously applied to the stationary Navier–Stokes equation, which consists of the introduction of a modified pseudostress tensor relating the gradient of the velocity and the pressure with the convective term, and propose an augmented pseudostress–velocity formulation for the model problem. The resulting augmented scheme is then written equivalently as a fixed point equation, so that the well-known Banach fixed point theorem, combined with the Lax–Milgram lemma, are applied to prove the unique solvability of the continuous and discrete systems. We point out that no discrete inf–sup conditions are required for the solvability analysis, and hence, in particular for the Galerkin scheme, arbitrary finite element subspaces of the respective continuous spaces can be utilized. For instance, given an integer $k\ge 0$, the Raviart–Thomas spaces of order $k$ and continuous piecewise polynomials of degree $\le k+1$ constitute feasible choices of discrete spaces for the pseudostress and the velocity, respectively, yielding optimal convergence. We also emphasize that, since the Dirichlet boundary condition becomes a natural condition, the analysis for both the continuous an discrete problems can be derived without introducing any lifting of the velocity boundary datum. In addition, we derive a reliable and efficient residual-based a posteriori error estimator for the augmented mixed method. The proof of reliability makes use of a global inf–sup condition, a Helmholtz decomposition, and local approximation properties of the Clément interpolant and Raviart–Thomas operator. On the other hand, inverse inequalities, the localization technique based on element-bubble and edge-bubble functions, approximation properties of the $L^2$-orthogonal projector, and known results from previous works, are the main tools for proving the efficiency of the estimator. Finally, some numerical results illustrating the performance of the augmented mixed method, confirming the theoretical rate of convergence and properties of the estimator, and showing the behavior of the associated adaptive algorithms, are reported.     

Gauss–Galerkin quadrature rules for quadratic and cubic spline spaces and their application to isogeometric analysis

We introduce Gaussian quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. By definition, these spaces are of even degrees. The optimal quadrature rules we recently derived (Bartoň and Calo, 2016) act on spaces of the smallest odd degrees and, therefore, are still slightly sub-optimal. In this work, we derive optimal rules directly for even-degree spaces and therefore further improve our recent result. We use optimal quadrature rules for spaces over two elements as elementary building blocks and use recursively the homotopy continuation concept described in Bartoň and Calo (2016) to derive optimal rules for arbitrary admissible numbers of elements. We demonstrate the proposed methodology on relevant examples, where we derive optimal rules for various even-degree spline spaces. We also discuss convergence of our rules to their asymptotic counterparts, these are the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains.     

Hamilton–Jacobi–Bellman Quasi-Variational Inequality arising in an environmental problem and its numerical discretization

A Hamilton–Jacobi–Bellman Quasi-Variational Inequality (HJBQVI) for a river environmental restoration problem with wise-use of sediment is formulated and its mathematical properties are analyzed. A finite difference scheme with a penalization technique is then established for solving the HJBQVI. The scheme is free from any iterative solvers and is unconditionally stable and convergent in the viscosity sense under certain conditions. A demonstrative application example of the HJBQVI is finally presented.     

Finite element method analysis of Fokker–Plank equation in stationary and evolutionary versions

The problems that often arise in stochastic dynamics can be investigated using the Fokker–Planck (FP) equation. The response of a such systems being subjected to additive and/or multiplicative random noise is represented by probability density function (PDF) that gives the full information about a response random character. Various analytic and semi-analytic solution methods have been developed for various systems to obtain results requested. However numerical approaches offer a powerful alternative. In particular the Finite Element Method (FEM) seems to be very effective. A couple of single dynamic linear/non-linear (Duffing and Van Der Pol type) systems under additive and multiplicative random excitations are discussed using FEM as a solution tool of the FP equation. The resulting PDFs are analyzed and if the analytic results exist mutually compared.     

Effect of cycle to cycle task variations in mixed-model assembly lines on workers’ upper body and lower back exertions and recovery time: A simulated assembly study

Differences in cycle-to-cycle work content in mixed-model assembly lines (MMAL) may increase exposure to risk factors of work-related musculoskeletal disorders (WMSD). This study investigated the effect of conveyor type and product mix/sequence in MMALs on joint loads and recovery time. An assembly task was simulated using 9 conveyor (continuous moving, synchronous indexing, and asynchronous indexing) and product mix/sequence (single product, 3 products with fixed sequence, and 3 products with random sequence) configurations. Results show the self-paced conveyor resulted in the least frequency of reaching. However, subjects did not use the available time for recovery and worked at a faster pace than in the continuous and synchronous indexing conveyors. In conclusion, an asynchronous indexing conveyor provided workers the flexibility they needed to complete their job correctly without reaching but recovery time was not sufficient.Practitioner summaryCycle-to-cycle task variations in MMAL may increase workers’ risk of developing WMSDs. An asynchronous indexing conveyor, with a minimum work time built in, may allow workers to complete their job with less reaching outside the reach envelope while providing sufficient recovery time.     

Spatial–temporal compression and recovery in a wireless sensor network in an underground tunnel environment

In an exciting new application, wireless sensor networks (WSNs) are increasingly being deployed to monitor the structure health of underground subway tunnels, promising many advantages over traditional monitoring methods. As a result, ensuring efficient data communication, transmission, and storage have become a huge challenge for these systems as they try to cope with ever increasing quantities of data collected by ever growing numbers of sensor nodes. A key approach of managing big data in WSNs is through data compression. Reducing the volume of data traveling between sensor nodes can reduce the high energy cost of data transmission, as well as save space for storage of big data. In this paper, we propose an algorithm for the compression of spatial–temporal data from one data type of sensor node in a WSN deployed in an underground tunnel. The proposed algorithm works efficiently because it considers temporal as well as spatial features of sensor data. A recovery process is required for recovering the data with a close approximation to the original data form nodes. We validate the proposed recovery technique through computational experiments carried out using the data acquired from a real WSN.     

Automatic spatial analysis and pedestrian flow control for real-time crowd simulation in an urban environment

Distributing a collection of virtual humans throughout a large urban environment, where limited semantic information is available, poses a problem when attempting to create a visually realistic real-time environment. Randomly positioning agents within an urban environment will not cover the environment with virtual humans in a plausible way. For example, areas of the urban space that are more frequently used should have a higher population density both at the start and during the simulation. It is infeasible to manually identify all the areas in the urban environment which should be crowded or sparsely populated when considering a scalable method, suitable for large environments. Consequently, this paper combines and extends techniques from spatial analysis and virtual agent behaviour simulations to develop a system capable of automatically distributing pedestrians in an urban environment. In particular, it extends the Point-Based Space Syntax technique to enable the automatic analysis of a large urban environment in the presence of limited contextual information. This analysis specifies a set of population densities for areas in the environment and these values are used to initialise the locations of all the virtual humans in the environment. In addition to the initialisation stage the population densities in each area are consulted to ensure that the correct distribution of virtual humans is maintained throughout the simulation. The system is tested on an arbitrary section of a real city and comparisons of the characteristic parts of the test environment are correlated with the pedestrian movements.

An analysis of students�� gaming behaviors in an intelligent tutoring system: predictors and impacts

Students who exploit properties of an instructional system to make progress while avoiding learning are said to be ??gaming?? the system. In order to investigate what causes gaming and how it impacts students, we analyzed log data from two Intelligent Tutoring Systems (ITS). The primary analyses focused on six college physics classes using the Andes ITS for homework and test preparation, starting with the research question: What is a better predictor of gaming, problem or student? To address this question, we developed a computational gaming detector for automatically labeling the Andes data, and applied several data mining techniques, including machine learning of Bayesian network parameters. Contrary to some prior findings, the analyses indicated that student was a better predictor of gaming than problem. This result was surprising, so we tested and confirmed it with log data from a second ITS (the Algebra Cognitive Tutor) and population (high school students). Given that student was more predictive of gaming than problem, subsequent analyses focused on how students gamed and in turn benefited (or not) from instructional features of the environment, as well as how gaming in general influenced problem solving and learning outcomes.     

Experimental determination of phase equilibria in the Y–Co–Ti system through diffusion couples and equilibrium alloys

Two isothermal sections of the Y–Co–Ti system at 600 °C and 800 °C were constructed for the first time using the diffusion couple technique and the equilibrium alloy method in combination with scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), electron probe microanalysis (EPMA), and X-ray diffraction (XRD). The stable ternary intermetallic compound YCo_12-xTi_x was detected and was confirmed to have a ThMn₁₂-type structure. The composition range in this ternary compound was measured to be 8.3–18.2 at.% at 600 °C and 8.9–19.1 at.% at 800 °C, resulting in the stable formation of YCo_12-xTi_x with x = 1.1–2.4 at 600 °C and x = 1.2–2.5 at 800 °C. The experimental results measured by EDS and EPMA demonstrate that the maximum solubilities of Ti in YCo₂, YCo₃, Y₂Co₇ and Y₂Co₁₇ compounds at 600 °C are 3.3, 5.6, 5.7 and 6.6 at.%, respectively, while the maximum solubilities of Y in Co₃Ti, Co₂Ti(h), Co₂Ti(c) and CoTi compounds are 2.7, 2.1, 2.6, 3.8 and 1.1 at.%. Meanwhile, the maximum solubilities of Ti in YCo₃, Y₂Co₇, YCo₅ and Y₂Co₁₇ compounds at 800 °C were determined to be 5.4, 3.2, 2.5 and 5.4 at.%, respectively, while the maximum solubilities of Y in Co₂Ti(c), Co₂Ti(h) and Co₃Ti compounds were measured to be 2.5, 2.1 and 3.8 at.%. The phase equilibria of the Y–Co–Ti system obtained in this work would provide the experimental information for phase stability of YCo_12-xTi_x compound and then explore the design of Y–Co–Ti based magnetic alloys with good magnetic properties.     

Towards an intelligent system for generating an adapted verbal and nonverbal combined behavior in human–robot interaction

In human–robot interaction scenarios, an intelligent robot should be able to synthesize an appropriate behavior adapted to human profile (i.e., personality). Recent research studies discussed the effect of personality traits on human verbal and nonverbal behaviors. The dynamic characteristics of the generated gestures and postures during the nonverbal communication can differ according to personality traits, which similarly can influence the verbal content of human speech. This research tries to map human verbal behavior to a corresponding verbal and nonverbal combined robot behavior based on the extraversion–introversion personality dimension. We explore the human–robot personality matching aspect and the similarity attraction principle, in addition to the different effects of the adapted combined robot behavior expressed through speech and gestures, and the adapted speech-only robot behavior, on interaction. Experiments with the humanoid NAO robot are reported.     

A novel approach to calculate diffusion matrix in ternary systems: Application to Ag–Mg–Mn and Cu–Ni–Sn systems

Diffusion behavior is of fundamental importance in material science and engineering. As a result, extensive attention has been paid to develop methodologies for obtaining the composition-dependent interdiffusivities. The present work proposed a novel approach with two steps to extract the interdiffusion coefficients from a single ternary diffusion couple. The concept of basis function is introduced, and this novel method is based on the utilization of both finite element method and optimization algorithm. Utilizing eight groups of diffusion couples together with electron probe microanalysis technique, the composition-dependent interdiffusion coefficients in fcc Ag–Mg–Mn alloys at 973 and 1073 K were determined via both the present method and Matano-Kirkaldy method. A home-made code is written to implement the novel numerical approach. The obtained interdiffusion coefficients based on the present method agree with the reliable ones from the Matano-Kirkaldy method better than previous methods for fcc Ag–Mg–Mn alloys in the present work as well as fcc Cu–Ni–Sn alloys from the literature, especially for the main interdiffusivities. In most cases, the presently computed main interdiffusivities by means of the composition-dependent diffusivities agree with the reliable ones from the Matano-Kirkaldy method within 50%. Besides, the sign of cross interdiffusivities using this novel method is usually the same as that from the Matano-Kirkaldy method. Such a high calculation precision and efficiency cannot be obtained using previous methods.     

Signal detection based on empirical mode decomposition and Teager–Kaiser energy operator and its application to P and S wave arrival time detection in seismic signal analysis

Neural Computing and Applications - Determining P and S wave arrival times while minimizing noise is a major problem in seismic signal analysis. Precise determination of earthquake onset arrival...