Economic-statistical design of the X¯ chart used to control a wandering process mean using genetic algorithm

This research considers the process mean wanders according to a first-order autoregressive model. During the in-control period the process mean wanders around its target value, and after the assignable cause occurrence, around an off-target value. The cost model proposed by Duncan was used to select the X bar chart’s parameters and the genetic algorithm to meet their optimum values. The wandering movement required a Markov chain to obtain the properties of the control chart. The autocorrelation among mean values increases the monitoring costs and reduces significantly the chart’s efficiency.     

An integration of NSGA-II and DEA for economic–statistical design of T2-Hotelling control chart with double warning lines

Control charts are the most applicable tools for monitoring the quality of processes. The day-to-day changes in industrial processes and customers’ expectations motivate the process engineers to monitor multiple correlated quality characteristics, simultaneously. Hence, in this paper, the design of a “double warning lines T²-Hotelling” control chart is studied because of the advantages of this multivariate control chart in detecting moderate and small shifts in a process. In this regard, this research aims to optimize a multi-objective economic–statistical design model that considers monitoring costs and statistical features of control chart, concurrently. The non-dominated sorting genetic algorithm II is utilized to obtain a suitable Pareto set for the model. Since it is difficult for the decision makers to select the most efficient solution among the Pareto set, three different methods of data envelopment analysis consisting of Charnes–Cooper–Rhodes model, cross-efficiency technique and aggressive formulation are used to rank the members of Pareto set and to select the most efficient one. Also, in this research the performance of these three methods in discriminating between the efficient solutions is compared to each other. Eventually, a comparative study is conducted to show the better performance of the suggested model in comparison with the corresponding economic design model.

     

State feedback with fractional integral control design based on the Bode’s ideal transfer function

State feedback technique through a gain matrix has been a well-known method for pole assignment of a linear system. The technique could encounter a difficulty in eliminating the steady-state errors in some states. Introducing an integral element can effectively eliminate these errors. State feedback with fractional integral control is proposed, in this work, for pole placement of a linear time invariant system. The proposed method yields simple gain formulae. The paper presents the derivation of the design formulae. The method is applied to stabilise an inherently unstable inverted pendulum-cart system. Simulation and experimental results show the effectiveness of the proposed method for set-point tracking, disturbance rejection and stabilising the inverted pendulum. Comparison with the results obtained from applying Achermann’s formula is also presented.     

Definition of sizes for the design of school furniture for Bogotá schools based on anthropometric criteria

The current paper deals with the definition of sizes for the design of school furniture for schools in Bogotá, Colombia, based on an analysis of available anthropometric data on Latin American children. State-of-the-art anthropometric, national and international standards were considered, in order to define the anthropometric variables that were to be used for defining the furniture. Matrices relating age and specific anthropometric dimensions were constructed, as a visualization method for establishing the dimensional differences between children of the same age and the ranges that should be covered by the items of furniture. Dimensional data were grouped by establishing the minimum sizes and general dimensions of furniture needed to cover the 5-95th percentile of school children between the ages of 5 and 18 years. The distribution of the furniture in the different school grades was also indicated. Apart from the need for an adequate match between child anthropometry and school furniture dimensions, this study shows the importance of a proper distribution of furniture sizes in the different school grades, as a complementary and decisive aspect to be considered in order to meet the heterogenic, anthropometrical requirements of children of the same age and school grade.     

A stress–based approach to the optimal design of structures with unilateral behavior of material or supports

The paper presents a stress-based approach that copes with the optimal design of truss-like elastic structures in case of unilateral behavior of material or ground supports. The conventional volume-constrained minimization of compliance is coupled with a set of local stress constraints that are enforced, all over the domain or along prescribed boundaries, to control the arising of members with tension-only or compression-only strength. A Drucker–Prager failure criterion is formulated to provide a smooth approximation of the no-tension or no-compression conditions governing the stress field. A selection strategy is implemented to handle efficiently the multi-constrained formulation that is solved through mathematical programming. Benchmark examples are investigated to discuss the features of the achieved optimal designs, as compared with problems involving material and ground supports with equal behavior in tension and compression. Numerical simulations show that a limited set of constraints is needed in the first iterations to steer the solution of the energy-driven optimization towards designs accounting for the prescribed assumption of unilateral strength.     

Estimation the parameters of Lotka–Volterra model based on grey direct modelling method and its application

In this paper, based on the grey direct modelling method, we present linear programming method to estimate the parameters of the Lotka–Volterra model under the criterion of the minimization of mean absolute percentage error (MAPE) (some authors called average relative error). Then use Lotka–Volterra model to analysis the relationship between two variables, and use discrete Lotka–Volterra model to forecast the two variables respectively, two practical examples are chosen for practical tests of this method, the results show that this method can provide empirical support for long-term qualitative analysis and obtain short-term quantitative prediction results, these have shown that this method is effective and applicable.     

Fully coupled algorithm for heat and water transport – Estimation of non-linear parameters based on the experimental data

We solve the problem of coupled heat conduction and water transport in bentonite with water present in vapour and adsorbed form in a non-equilibrium state. The problem is governed by a system of two parabolic PDE and one ODE. Most of the coefficients are non-linear functions, defined either by underlying physical phenomena or empirically. We present a numerical scheme using FEM with linear base functions, implicit time discretization, and simple iterations for the non-linear terms. The model is verified against experiments (one 1D and one 3D) and we demonstrate the use of optimization algorithm for parameter calibration. Some of the parameters could be estimated successfully while others with limited confidence, which is explained by the particular character of the non-linear parameter dependence and resulting small sensitivity of the model on some parameters.     

Remarks on the paper “Optimal control of a class of linear multivariable systems with integral quadratic energy constraint ”

An optimal periodic control problem for a system described by differential equations is considered. Control units are assumed to generate control actions with the square-integrable derivative. The above problem is approximated by a sequence of discretized problems containing trigonometric polynomials, which approximate the state and control variables, and the functions in the criterion and differential equations. The conditions for a sequence of optimal solutions to discretized problems, which are to be a generalized minimizing sequence for the basic problem, are given. Extensions to more general problem formulations are presented. The possibility of application is illustrated by the example of an optimal periodic control problem for a chemical reactor.     

An empirical study on the utility of BRDF model parameters and topographic parameters for mapping vegetation in a semi‐arid region with MISR imagery

In this study we show that multiangle remote sensing is useful for increasing the accuracy of vegetation community type mapping in desert regions. Using images from the National Aeronautics and Space Administration (NASA) Multiangle Imaging Spectroradiometer (MISR), we compared roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with those played by topographic parameters in improving vegetation community type classifications for the Jornada Experimental Range and the Sevilleta National Wildlife Refuge in New Mexico, USA. The BRDF models used were the Rahman–Pinty–Verstraete (RPV) model and the RossThin‐LiSparseReciprocal (RTnLS) model. MISR nadir multispectral reflectance was considered as baseline because nadir observation is the most basic remote sensing observation. The BRDF model parameters and the topographic parameters were considered as additional data. The BRDF model parameters were obtained by inversion of the RPV model and the RTnLS model against the MISR multiangle reflectance data. The results of 32 classification experiments show that the BRDF model parameters are useful for vegetation mapping; they can be used to raise classification accuracies by providing information that is not available in the spectral‐nadir domain, or from ancillary topographic parameters. This study suggests that the Moderate Resolution Imaging Spectroradiometer (MODIS) and MISR BRDF model parameter data products have great potential to be used as additional information for vegetation mapping.     

Segmentation of abnormal liver region based on earth mover’s distance between histograms with mapping of the distances by multidimensional scaling

In this paper, we propose using earth mover’s distance (EMD) to obtain the appropriate similarity between each histogram for segmentation of abnormal liver regions with mapping of the distances by multidimensional scaling. Conventionally, the similarity between each histogram is calculated by integrating the difference between each bin of the histograms. However, this similarity is unsuitable for appropriate comparison of the histograms because the number of bins for calculating the local histograms of computed tomography images varies. We used EMD to resolve this problem regarding the difference in bin numbers, and the obtained distances are used for mapping the local histograms by multidimensional scaling to low-dimensional space. In the low-dimensional space, the abnormal liver region was well segmented by support vector machine in the test datasets.     

Modeling of a proton exchange membrane fuel cell based on the hybrid particle swarm optimization with Levenberg–Marquardt neural network

This paper presents a nonlinear modeling approach of a proton exchange membrane fuel cell (PEMFC) based on the hybrid particle swarm optimization with Levenberg–Marquardt algorithm neural network (PSO-LM NN). The PSO algorithm converges rapidly during the initial stages of a global search, while it becomes extremely slow around the global optimum. On the contrary, the LM algorithm can achieve faster convergent speed around the global optimum, while it is prone to being trapped in the local minimum. Therefore the hybrid algorithm with a transition from PSO search to LM training is proposed to train the weights and thresholds of neural network, which aims to exploit the advantage of the both algorithms. An accurate mathematical model is an extremely useful tool for the fuel cell design, and neural network is an excellent optional tool for complex nonlinear dynamic system modeling such as PEMFC. In the paper, firstly a highly reduced PEMFC dynamic physical model is established to generate the data for the PSO-LM NN model training and validation, and then the neural network nonlinear autoregressive model based on the PSO-LM algorithm is applied in modeling PEMFC voltage and temperature model, and finally the validation test result demonstrates that the trained PSO-LM NN model can efficiently approach the dynamic behavior of a PEMFC.     

A note on stability analysis of 2-D linear discrete systems based on the Fornasini–Marchesini second model: Stability with asymmetric Lyapunov matrix

A recently reported Lyapunov based criterion (Singh (2014) [7]) for the asymptotic stability of two-dimensional (2-D) linear discrete systems described by the Fornasini–Marchesini second local state-space (FMSLSS) model is reviewed. It is established in this paper that, despite utilizing a more general Lyapunov matrix, Singh's criterion will never lead to an enhanced stability region in the parameter-space as compared to that obtainable via Hinamoto–Lu's criterion.     

Examining the effects of field dependence–independence on learners' problem-solving performance and interaction with a computer modeling tool: Implications for the design of joint cognitive systems

An investigation was carried out to examine the effects of cognitive style on learners' performance and interaction during complex problem solving with a computer modeling tool. One hundred and nineteen undergraduates volunteered to participate in the study. Participants were first administered a test, and based on their test scores they were classified into three groups, namely field-dependent, field-mixed, and field-independent learners. Participants then received the same set of integrated-format materials and were asked to use a computer modeling tool to solve a complex problem about immigration policy. A multivariate analysis of variance was performed with field type as the independent variable, and cognitive load, problem-solving performance, and learner interaction with the computer tool as the dependent variables. The results indicated that there was no significant difference in terms of the amount of cognitive load reported. However, there was a significant difference in terms of learner problem-solving performance. Specifically, field-independent learners outperformed field-dependent learners, and field-mixed learners outperformed field-dependent learners. The results also indicated significant differences in computer interaction between field-independent and field-dependent learners, and between field-mixed and field-dependent learners. The qualitative findings of the study showed that students who interacted poorly with the software were unsure about how to systematically use the affordances of the computer tool to solve the problem, did not have a goal-directed plan or strategy in mind about how to investigate the issue at hand, and had difficulty with testing the immigration policies by appropriately controlling variables in order to collect data to inform decision making. Implications are discussed in terms of designing computer systems that scaffold learners' complex problem solving by considering the cognitive demands of the task.     

Stability analysis of 2-D linear discrete systems based on the Fornasini–Marchesini second model: Stability with asymmetric Lyapunov matrix

The stability of two-dimensional (2-D) linear discrete systems based on the Fornasini–Marchesini local state-space (LSS) model is considered. A stability criterion using the asymmetric Lyapunov matrix P is presented. A special case of the criterion is discussed.     

Linking objective design factors with subjective aesthetics: An experimental study on how structure and color of websites affect the facets of users’ visual aesthetic perception

The present study examines how objective design factors of a website are linked to different facets of subjective aesthetic perception. Five online experiments based upon the screenshots of real-existing websites with a total of N = 194 participants were conducted to isolate and analyze the effects of two objective structural factors (vertical symmetry, visual complexity) and three objective color factors (hue, saturation, brightness) on the different facets of subjective aesthetic perception (simplicity, diversity, colorfulness, craftsmanship) measured with the Visual Aesthetics of Website Inventory (Moshagen & Thielsch, 2010). Although all investigated factors are apparent features in website design, their effects on different facets of subjective aesthetic perception are not yet well understood. Our results show that websites of high symmetry, low complexity, blue hue, medium brightness or medium and high saturation received the highest overall aesthetics ratings. Furthermore, data reveal that structural factors compared to color factors have a manifold and greater impact on the different facets of subjective aesthetic perception than the color factors. Both structural factors have a great impact on simplicity, diversity and craftsmanship whereas the color factors have a great impact especially on colorfulness. Only complexity affects all facets of subjective aesthetic perception. The other objective design factors had effects on specific facets. Our findings shed light on the relationship between objective and subjective factors of aesthetic perception and may help designers to systematically target specific facets of visual aesthetics.