Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

Classification of cardiac sound signals using constrained tunable-Q wavelet transform

The features extracted from the cardiac sound signals are commonly used for detection and identification of heart valve disorders. In this paper, we present a new method for classification of cardiac sound signals using constrained tunable-Q wavelet transform (TQWT). The proposed method begins with a constrained TQWT based segmentation of cardiac sound signals into heart beat cycles. The features obtained from heart beat cycles of separately reconstructed heart sounds and murmur can better represent the various types of cardiac sound signals than that from containing both. Therefore, heart sounds and murmur have been separated using constrained TQWT. Then the proposed novel raw feature set has been created by the parameters that have been optimized while constraining the output of TQWT together with that of extracted by using time-domain representation and Fourier–Bessel (FB) expansion of separated heart sounds and murmur. However, the adaptively selected features have been used to obtain the final feature set for subsequent classification of cardiac sound signals using least squares support vector machine (LS-SVM) with various kernel functions. The performance of the proposed method has been validated with publicly available datasets and the results have been compared with the existing short-time Fourier transform (STFT) based method. The proposed method shows higher percentage classification accuracy of 94.01 as compared to 93.53 of STFT based method. In comparison with STFT based method, it is noteworthy that the proposed method uses well defined and lower dimensionality of feature vector that can reduce the computational complexity.     

Isothermal crystallization and spherulite structure of partially miscible polypropylene–linear low-density polyethylene blends

Polypropylene (PP) was blended with a linear low-density polyethylene (LLDPE, containing 5% hexene comonomer) over a composition range of 10–90% of PP. The crystallization and morphology of the PP–LLDPE blends were studied by differential scanning calorimetry (DSC), polarized optical microscopy with a hot stage (HSOM), and scanning electron microscopy (SEM). In particular, the isothermal crystallization of PP in molten LLDPE was investigated. It was observed that the crystallization and melting behavior of PP and LLDPE changed in the blends, indicating that there was some degree of miscibility between the PP and the LLDPE. A depression of the equilibrium melting temperature (T) of PP in the blends with no more than 15% of PP confirmed that PP was miscible with LLDPE at and below 15% of PP. In addition, a drastic decrease in T from the 25% PP blend to the 20% blend led us to conclude that the miscible behavior between PP and LLDPE became favorable at a PP concentration of 20%. The optical microscopic images showed that, in the blends with 10 and 15% of PP, the PP crystallized as open-armed diffuse spherulites, similar to those in the miscible blends. In contrast, the PP crystallized in a phase-separated matrix or droplets with more than 25% of PP, when obvious phase separation occurred. The SEM image revealed that the PP lamella was able to penetrate the PP and LLDPE phase boundary and grow in the LLDPE phase. The above results displayed that the PP dissolved in the LLDPE, and, particularly, when the PP concentration was below 20%, the dissolution was substantial. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 628–639, 2001     

L2 disturbance attenuation for highly dissipative nonlinear spatially distributed processes via HJI approach

For many practical industrial spatially distributed processes (SDPs), their dynamics are usually described by highly dissipative nonlinear partial differential equations (PDEs). In this paper, we address the L₂ disturbance attenuation problem of nonlinear SDPs using the Hamilton–Jacobi–Isaacs (HJI) approach. Firstly, by collecting an ensemble of PDE states, Karhunen–Loève decomposition (KLD) is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. Subsequently, these EEFs together with singular perturbation (SP) technique are used to obtain a finite-dimensional slow subsystem of ordinary differential equation (ODE) that accurately describes the dominant dynamics of the PDE system. Secondly, based on the slow subsystem, the L₂ disturbance attenuation problem is reformulated and a finite-dimensional H_∞ controller is synthesized in terms of the HJI equation. Moreover, the stability and L₂-gain performance of the closed-loop PDE system are analyzed. Thirdly, since the HJI equation is a nonlinear PDE that has proven to be impossible to solve analytically, we combine the method of weighted residuals (MWR) and simultaneous policy update algorithm (SPUA) to obtain its approximate solution. Finally, the simulation studies are conducted on a nonlinear diffusion-reaction process and a temperature cooling fin of high-speed aerospace vehicle, and the achieved results demonstrate the effectiveness of the developed control method.     

Modeling for soft sensor systems and parameters updating online

Soft sensor technology is an important means to estimate important process variables in real-time. Modeling for soft sensor system is the core of this technology. Most nonlinear dynamic modeling methods integrate the processes of building the dynamic and static relationships between secondary and primary variables, which limits the estimation accuracy for primary variables. To avoid the problem, a kind of soft sensor model consisting of a dynamic model in cascade with a static one is proposed. The model identification and update online are conducted in substep way. In order to improve the model update efficiency, two improved Gauss–Newton recursive algorithms, which avoid nonsingular covariance matrix, are proposed for time-invariant and time-variant soft sensor systems. The uniform convergence for dynamic model parameter and the existence of estimation deviations for static model parameters are proved for time-invariant soft sensor system. The parameters of time-variant soft sensor system would be boundedly convergent. Case study confirms that, on the basis of the proposed model and recursive algorithms, the dynamic and static characteristics of soft sensor system can be described efficiently, and the primary variables are ensured to be estimated accurately.     

A Dantzig–Wolfe decomposition algorithm for linear economic model predictive control of dynamically decoupled subsystems

This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers. It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ₁-regularization term. In the presence of process and measurement noise, such a regularization term is critical for achieving a well-behaved closed-loop performance.     

硫硒化镉大红釉的研究

综述了硫硒化镉大红釉的研究状况，分析了各种充硒化镉釉制备方法的优缺点。提出了独特的硫硒化镉系列色釉的制备工艺－－多熔块反应法。     

Investigation of the effect of surface phosphate ester dispersant on viscosity by coarse-grain modeling of BaTiO slurry

To understand the role of phosphate ester dispersant, we investigated the rheology of a BaTiO slurry. For the model case, a coarse-grain molecular dynamics (CGMD) simulation was performed with the butyral polymer didodecyl hydrogen phosphate (DHP) in the toluene/ethanol solvent. By systematically analyzing the effect of DHP from an atomic-scale first principle and from all-atom MD to microscale CGMD simulation, we investigated how the adsorption of a DHP dispersant on a BaTiO surface affects the microstructure rheology of a BaTiO slurry. The first-principle and all-atom MD simulation suggests that DHP molecules prefer to locate near the BaTiO surface. CGMD simulation shows a reduction in viscosity with an increase in dispersants, suggesting that the dispersant population near the BaTiO surface plays a key role in controlling the rheology of the BaTiO slurry. In this study, we propose an approach for understanding the BaTiO slurry with molecular-level simulations, which would be a useful tool for efficient optimization of slurry preparation.     

利用废旧锌锰电池制取锌盐和氧化锌的研究

以废旧锌锰电池为研究对象,采用湿法回收技术,制备ZnSO4.7H2O,ZnCO3和ZnO。结果表明,Zn溶解时间随着H2SO4浓度而变,当H2SO4浓度为3 mol/L时,溶解耗时仅为5 h,ZnSO4.7H2O产率可达93.44%。在Na2CO3,NaHCO3,(NH4)2CO3三种沉淀剂中,(NH4)2CO3的沉淀效果最好,制备的ZnCO3颗粒细小,在1 073.2 K条件下,其分解效率可达88.75%。     

Optimal control of the production–inventory system with deteriorating items and tradable emission permits

Using the well-known Arrow and Karlin (1958) Arrow, K.J., and Karlin, S. (1958), ‘Production over Time with Increasing Marginal Costs’, in Studies in the Mathematical Theory of Inventory and Production, eds. K.J. Arrow and S. Karlin, Stanford: Stanford University Press, pp. 61–69. [Google Scholar] dynamic production–inventory model and the model with tradable emission permits which was presented by Dobos (2005 Dobos, I. (2005), ‘The Effects of Emission Trading on Production and Inventories in the Arrow–Karlin Model’, International Journal of Production Economics, 93–94, 301–308.[Crossref], [Web of Science ®] , [Google Scholar], 2007) Dobos I. (2007), ‘Tradable Emission Permits and Production-inventory Strategies of the Firm’, International Journal of Production Economics, 108, 329–333.[Crossref], [Web of Science ®] , [Google Scholar], we develop a model of the production–inventory system with deteriorating items and tradable emission permits. The objective of this paper is to apply the optimal control theory to solve the production–inventory problem with deteriorating items and tradable emission permits, and derive the optimal inventory level and the optimal production rate that minimise the total cost. The results are discussed with a numerical example and a sensitivity analysis of the optimal solution with respect to the parameters of the production–inventory system is carried out.