An accurate interest matching algorithm based on prediction of the space–time intersection of regions for the distributed virtual environment

Interest matching is an important data-filtering mechanism for a large-scale distributed virtual environment. Many of the existing algorithms perform interest matching at discrete timesteps. Thus, they may suffer the missing-event problem: failing to report the events between two consecutive timesteps. Some algorithms solve this problem, by setting short timesteps, but they have a low computing efficiency. Additionally, these algorithms cannot capture all events, and some spurious events may also be reported. In this paper, we present an accurate interest matching algorithm called the predictive interest matching algorithm, which is able to capture the missing events between discrete timesteps. The PIM algorithm exploits the polynomial functions to model the movements of virtual entities, and predict the time intervals of region overlaps associated with the entities accurately. Based on the prediction of the space–time intersection of regions, our algorithm can capture all missing events and does not report the spurious events at the same time. To improve the runtime performance, a technique called region pruning is proposed and used in our algorithm. In experiments, we compare the new algorithm with the frequent interest matching algorithm and the space–time interest matching algorithm on the HLA/RTI distributed infrastructure. The results prove that although an additional matching effort is required in the new algorithm, it outperforms the baselines in terms of event-capturing ability, redundant matching avoidance, runtime efficiency and scalability.     

Design of a modified repetitive-control system based on a continuous–discrete 2D model

This paper concerns the problem of designing a modified repetitive-control system for a class of strictly proper plants. Repetitive control involves two types of actions: control and learning; but the insertion of a low-pass filter in a modified repetitive controller, which is employed to guarantee the stability of the system, mixes the two actions together. In this paper, a continuous–discrete two-dimensional model is first constructed. Next, the continuity of repetitive control and Lyapunov stability theory are applied to the model to establish two linear-matrix-inequality (LMI) based sufficient stability conditions, one for the design of the cutoff angular frequency and one for the design of the feedback gains. The features of these conditions are exploited to develop an iterative algorithm that searches for the best combination of the maximum cutoff angular frequency of the low-pass filter and the feedback gains. A numerical example illustrates the design procedure and demonstrates the validity of the method.     

Agent–cellular automata model for the dynamic fluctuation of EV traffic and charging demands based on machine learning algorithm

Neural Computing and Applications - Electric vehicles (EV) comprise one of the foremost components of the smart grid and tightly link the power system with the road network. Spatial and temporal...     

Cryptanalysis of a remote user authentication scheme for mobile client–server environment based on ECC

Understanding security failures of cryptographic protocols is the key to both patching existing protocols and designing future schemes. The design of secure remote user authentication schemes based on elliptic curve crypto-graphy (ECC) for mobile applications is still quite a challenging problem, though many schemes have been published lately. In this paper, we analyze an efficient ID-based scheme for mobile client–server environment without the MapToPoint function introduced by He et al. in 2012. This proposal attempts to overcome many of the well known security and efficiency shortcomings of previous schemes, and it also carries a claimed proof of security in the random oracle model. However, notwithstanding its formal security arguments, we show that He et al.’s protocol even cannot attain the basic goal of mutual authentication by demonstrating its vulnerabilities to reflection attack and parallel session attack. Besides these two security vulnerabilities, their scheme also suffers from some practical pitfalls such as user anonymity violation and clock synchronization problem. In addition, we carry out an investigation into their security proof and propose some changes to the scheme so that it can achieve at least its basic security goal, in the hope that similar mistakes are no longer made in the future.     

Process planning for Floor machining of 2½D pockets based on a morphed spiral tool path pattern

This work proposes a process planning for machining of a Floor which is the most prominent elemental machining feature in a 2½D pocket. Traditionally, the process planning of 2½D pocket machining is posed as stand-alone problem involving either tool selection, tool path generation or machining parameter selection, resulting in sub-optimal plans. For this reason, the tool path generation and feed selection is proposed to be integrated with an objective of minimizing machining time under realistic cutting force constraints for given pocket geometry and cutting tool. A morphed spiral tool path consisting of G¹ continuous biarc and arc spline is proposed as a possible tool path generation strategy with the capability of handling islands in pocket geometry. Proposed tool path enables a constant feed rate and consistent cutting force during machining in typical commercial CNC machine tool. The constant feed selection is based on the tool path and cutting tool geometries as well as dynamic characteristics of mechanical structure of the machine tool to ensure optimal machining performance. The proposed tool path strategy is compared with those generated by commercial CAM software. The calculated tool path length and measured dry machining time show considerable advantage of the proposed tool path. For optimal machining parameter selection, the feed per tooth is iteratively optimized with a pre-calibrated cutting force model, under a cutting force constraint to avoid tool rupture. The optimization result shows around 32% and 40% potential improvement in productivity with one and two feed rate strategies respectively.     

CASQUS: A new simulation tool for coupled 3D finite element modeling of tectonic and surface processes based on ABAQUS™ and CASCADE

CASQUS is a numerical simulation tool to model the feedback mechanism between surface and tectonic processes. It includes the surface processes model CASCADE into the finite element solver ABAQUS/Standard?. The finite element method allows for geomechanical simulations of the subsurface with geometrically complex structures in 3D. Additionally, in the commercial software ABAQUS? various types of rheological behavior are already implemented. CASCADE simulates erosion and sedimentation as the combination of fluvial transport and hillslope processes. For the integration of CASCADE into ABAQUS/Standard? an Arbitrary Lagrangian–Eulerian modeling technique is used, which makes a coupled and automated simulation possible. Two benchmark models that are easy to reproduce demonstrate the functionality of CASQUS. Our tool aims at a better understanding of the feedback between mass redistribution at the Earth's surface and processes within a heterogenous subsurface, and at a quantification of the involved processes.     

Development and evaluation of an ergonomic software package for predicting multiple-task human performance and mental workload in human–machine interface design and evaluation

Predicting human performance and mental workload in multiple task situations at an early stage of system design can save a significant amount of time and cost. However, existing modeling tools either can only predict human performance or require users of tools to learn a new programming language. Queueing Network-Model Human Processor (QN-MHP) is a new cognitive architecture for modeling both human performance and mental workload in multiple tasks. This paper describes the development of a Visual Basic Application in Excel (VBA) software package and an illustrative case study to evaluate its effectiveness. The software package has an easy-to-use user interface for QN-MHP that assists users of the modeling tool to simulate a dual task including definition of the tasks and interfaces by clicking buttons to select options and filling texts in a table, with no need to learn a simulation language. It allows the model user to intuitively observe the information processing state of the model during simulation, and conveniently compare the simulated human performance and mental workload for different designs. The illustrative case study showed that naïve users without prior simulation language programming experience can model human performance and mental workload in a complex multitask situation within 3 min; and this software package can save 71% of modeling time and reduce 30% of modeling errors. Further developments of the VBA software package of QN-MHP are also discussed on how to make it a comprehensive proactive ergonomic design and analysis tool.     

Dynamic modeling of parallel manipulators based on Lagrange–D’Alembert formulation and Jacobian/Hessian matrices

Multibody System Dynamics - This paper describes the development of a dynamic model for parallel manipulators based on the Lagrange–D’Alembert equation, the Hessian matrix of the...     

Oil holdup prediction of oil–water two phase flow using thermal method based on multiwavelet transform and least squares support vector machine

Oil holdup of oil–water two phase flow (OWTPF) was measured using thermocouple based on the thermal method. A new model based on least square support vector machines (LSSVM) and multiwavelet transform has been proposed for the first time, which is capable of forecasting oil holdup of oil–water two phase flow. The temperature signal of OWTPF is greatly disturbed by noises from external interference, which results in a limited measurement range of oil holdup. In order to solve the problem, a new signal processing method based on the multiwavelet transform is used. Multiwavelet transform has several scaling functions and corresponding wavelet functions, which can simultaneously achieve orthogonality, symmetry. With ideal performance, noises were removed and actual temperature signal was effectively retained. The fluctuated amplitude signal denoised and total flux of OWTPF were employed as inputs and the oil holdup was used as output of LSSVM model. In order to improve the predictive accuracy and generalization ability of the LSSVM model, a Genetic Arithmetic (GA) has been adopted to determine the optimal parameters of LSSVM model automatically. The experiment results indicate that the performance of LSSVM–GA model outperforms those of artificial neural network (ANN), LSSVM–GA model can be used for estimating the oil holdup of OWTPF with reasonable accuracy.     

A novel offline programming approach of robot welding for multi-pipe intersection structures based on NSGA-Ⅱ and measured 3D point-clouds

The multi-pipe intersection structure in form of co-main pipe is widely used in various industries. To improve its welding quality and efficiency, this paper is devoted to proposing an offline programming approach to the robot trajectory based on NSGA-Ⅱ and measured 3D point-clouds. First, considering the existence of deviation between the actual workpiece and its ideal model, this paper selects the actual 3D point-cloud of weld seam as the research object and extracts its feature points by combining the characteristic of the spatial curve, which can reduce the data density while preserving their geometric characteristics. Second, to ensure the continuity of motion parameters while taking the calculation and fitting accuracy into account, the cubic NURBS is applied to fit the actual weld position, and a fast-adaptive fitting nodes configuration scheme is designed according to the variation characteristics of the spatial curve and the fitting error restriction. Third, this paper introduces a trajectory adaptive discretization method based on the chord error constraint for robot program generation, and establishes an optimization model of the robot welding trajectory based on NSGA-Ⅱ frame, which gives the robot joint's motion trajectories with optimal welding quality and cable twisting fluctuation. Finally, the experiments are designed to verify the correctness of the aforementioned approach.     

A multiscale urban complexity index based on 3D wavelet transform for spectral–spatial feature extraction and classification: an evaluation on the 8-channel WorldView-2 imagery

The three-dimensional wavelet transform (3D-WT) processes a multispectral remotely sensed image as a cube and hence it is able to simultaneously represent variation information in joint spectral–spatial feature space. The urban complexity index (UCI) built on the 3D-WT is defined by comparing the amount of spectral and spatial variation, since natural features have relatively smaller spatial changes than spectral changes but urban areas show more variation in the spatial domain. The calculation of the UCI is subject to the selection of window sizes; therefore, in this study, a multiscale UCI (M-UCI) is proposed by integrating the UCI features in different moving windows and decomposition levels. The performance of the M-UCI was evaluated on two WorldView-2 data sets over urban and suburban areas, respectively. Experimental results showed that the M-UCI was effective in integrating multiscale information contained in different windows and gave higher accuracies than the single-scale UCI. In experiments, the proposed M-UCI was compared with a pixel shape index (PSI), which is a texture measure extracted from the spatial domain alone. It was revealed that the PSI was more effective for the classification of urban areas than natural landscapes, whereas the M-UCI was applicable for both urban and natural areas since it represented the joint spectral–spatial domains.     

A new high-accuracy method based on off-step cubic polynomial approximations for the solution of coupled Burgers’ equations and Burgers–Huxley equation

Engineering with Computers - Using two off-step points and a central point, we discuss a new two-time-level implicit method of order three based on polynomial cubic spline approximations for the...     

A decision support system based on fuzzy reasoning and AHP–FPP for the ecodesign of products: Application to footwear as case study

The design stage represents one of the most critic steps for product development. Here, a great number of considerations have to be borne in mind, e.g., technical, functional, aesthetic or economic criteria. More recently, the increasing concerns on environmental aspects have added complexity to the process, known as ecodesign. In this respect, a framework to integrate the criteria provided by quantitative environmental indicators has been proposed on the basis of Fuzzy Preference Programming method features and fuzzy logic reasoning. As a result, an integrated Ecodesign Index (EcoInd) is obtained. This idea enables the decision making at process and product level taking into account different indicators at a time. The ecodesign of children's footwear was taken as case study and an ecodesign tool (decision support system) that included the estimation of environmental indicators and their integration was developed. Different models of shoes were analyzed to identify the most environmentally friendly design and to test the tool. In this case, the Ecological Footprint and two Environmental Risk Assessment indicators, namely Hazard Quotient and Cancer Risk, were selected as relevant environmental indicators and they were computed from data provided by a shoes manufacturer. Then, these indicators were integrated in the ecodesign tool and the EcoInd values were appraised for the children's footwear models analyzed. According to these figures, they were ranked as Red Leather > White Leather > White Synthetic > Pink Synthetic, from best to worst.     

A novel group decision model based on mean–variance–skewness concepts and interval-valued fuzzy sets for a selection problem of the sustainable warehouse location under uncertainty

Recently, sustainable warehouse location has been regarded as one of the most critical and significant decision problems for long-term planning in the supply chain. This strategic decision can be effected by different quantitative and qualitative evaluation criteria via three dimensions of the sustainability. Main theme of the paper is to select the most optimal location decision from a number of potential sustainable warehouse candidates. For this purpose, this paper presents a novel multi-criteria decision-making model by a group of supply chain experts or decision makers with interval-valued fuzzy setting and asymmetric uncertainty information. Concepts of mean, variance and skewness are introduced into the proposed group decision model, and their mathematical relations are defined based on a fuzzy possibilistic statistical approach. Then, new relations in this model are presented for obtaining ideal solutions under uncertainty with two high and low values of the possibilistic mean and possibilistic standard deviation, along with the possibilistic cube root of skewness. In addition, novel separation measures and new fuzzy ranking index of hybridized relative closeness coefficients are presented to provide final preference order of warehouse location candidates under uncertain conditions. Finally, a sustainable warehouse location selection problem in a pharmaceutical company is presented and solved by the proposed group decision model to demonstrate its applicability and suitability.

     

The effect of different π-bridge configuration on bi-anchored triphenylamine and phenyl modified triphenylamine based dyes for dye sensitized solar cell (DSSC) application: A theoretical approach

Twenty eight bi-anchored triphenylamine (TH-1 to TH-14) and phenyl modified triphenylamine (PH-TH-1 to PH-TH-14) based metal free organic dyes are designed for DSSC application. The electronic effect of different π-bridge configurations in donor-π-bridge-acceptor (D-π-A)₂ structure was theoretically simulated and verified using density functional theory (DFT) and time dependent density functional theory (TD-DFT). The triphenylamine and phenyl modified triphenylamine groups are used as donor and cyanoacrylic acid group is used as acceptor. Thiophene and cyanovinyl groups are used as π-bridge. The ground state molecular structure was optimized by density functional theory and the electronic absorption spectra were calculated by time dependent density functional theory. The light harvesting efficiency (LHE), dye regeneration energy (ΔG_reg) and electron injection energy (ΔG_inject) are determined by computational examination. It is observed that, when the number of π-bridge increases, the band gap of the dye decreases. Also the absorption maximum and molar extinction coefficient of the dyes are increased. Theoretical result shows that the thiophene-cyanovinyl and thiophene-thiophene-cyanovinyl–cyanovinyl configurations give broader and red shifted absorption spectrum compared to other configurations. Also the results of phenyl modified triphenylamine (PH-TH) dyes clearly show better absorption and dye regeneration energy compared to TH dyes.     

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.     

2–2 composites based on [011]-poled relaxor-ferroelectric single crystals: analysis of the piezoelectric anisotropy and squared figures of merit for energy harvesting applications

In this paper we explore the effect of the orientation of the main crystallographic axes in relaxor-ferroelectric single crystals (SCs) on the piezoelectric anisotropy and squared figures of merit of 2–2 parallel-connected SC/auxetic polymer composites. The single-crystal component for the composite is chosen from the perovskite-type solid solutions with compositions near the morphotropic phase boundary and poled along the perovskite unit-cell [011] direction (mm ² symmetry of domain-engineered SCs). The orientation of the main crystallographic axes in the single-crystal component is observed to strongly influence the piezoelectric coefficients $d_{3j}^{*}$ , squared figures of merit $d_{3j}^{*}$ $g_{3j}^{*}$ , electromechanical coupling factors $k_{3j}^{*}$ , and hydrostatic analogs of these parameters of the 2–2 composite. Inequalities $| {d_{33}^{*} /d_{3f}^{*} } | > 5$ and $| {k_{33}^{*} /k_{3f}^{*} } | > 5$ (f = 1 and 2) are achieved at specific orientations of the main crystallographic axes due to the significant anisotropy of the elastic and piezoelectric properties of the single-crystal component. The use of an auxetic polyethylene (a polymer component with a negative Poisson’s ratio) leads to a significant increase in the hydrostatic parameters. Particular advantages of such composites over conventional ceramic/polymer composites are taken into account for transducer, hydroacoustic, energy harvesting, and other applications.     

A hybrid SCA–VNS meta-heuristic based on Iterated Hungarian algorithm for physicians and medical staff scheduling problem in outpatient department of large hospitals with multiple branches

This paper investigates the scheduling problem of physicians and medical staff in outpatient department of large hospitals with multi-branch. The large hospital has several branches and each branch has its own medical staff, while the physicians need to serve in all the branches affiliated to the hospital. In order to improve the working efficiency of physicians, each physician would be equipped with a medical staff during his working hours. The working time of physicians and medical staff have several requirements considering the satisfaction of them. The paper takes into account the demand and the available resources of the hospital, the workload of physicians and medical staff, etc. as the constraints, and the purpose is to minimize the dissatisfaction of physicians, the cost of physicians and the deviation of the frequency of physicians at work in different clinics. Then, a hybrid meta-heuristic algorithm SCA–VNS combining a Sine Cosine Algorithm (SCA) and variable neighborhood search (VNS) based on Iterated Hungarian algorithm, which is incorporated to solve the physicians and medical staff assignment, is proposed to solve this problem. Through computational experiments that available physicians and medical staff scheduling have been generated and perform better than other compared algorithms.