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To solve the problem of insufficient energy consumption for multi-priority tasks in the computing and unloading environments of mobile devices, we designed evaluation methods to improve the traditional simulated annealing algorithm and obtain the optimal allocation scheme for these tasks under multiple computing resources. Firstly, we proposed the task model and discussed the classification and definition of task priority as well as the procedure of task processing in detail. Secondly, a calculation model for the energy consumption of mobile devices is provided. Thirdly, an evaluation mechanism is designed to evaluate the unloading distribution scheme of mobile devices effectively. Finally, the improved traditional simulated annealing algorithm was applied to find the optimal distribution scheme for this computing environment. All allocation schemes obtained in this study were compared and analyzed via simulation. The results showed that the proposed algorithm can reduce the energy consumption of mobile devices more significantly, shorten the system response time, and complete high-priority tasks based on time constraints. [ABSTRACT FROM AUTHOR]

To improve the efficiency of traditional face recognition techniques, this paper proposes a novel face recognition algorithm called Image Gradient Feature Compensation (IGFC). Based on the gradients along four directions in an image, a fusion algorithm and a compensation method are implemented to obtain features of the original image. In this study, gradient magnitude maps of a face image are calculated along four directions. Fusion gradients and differential fusion gradients are produced by fusing the four gradient magnitude maps of a face image in multiple ways, and they are used as compensation variables to compensate the appropriate coefficients on the original image and build IGFC feature maps of the original face image. Subsequently, IGFC feature maps are divided into several blocks to calculate the concatenated histogram over all blocks, which is in turn utilized as the feature descriptor for face recognition. Principal component analysis (PCA) is used to cut down the number of dimensions in high-dimensional features, which are recognized by the Support Vector Machine (SVM) classifier. Finally, the proposed IGFC method is superior to traditional methods as suggested by verification studies on YALE, ORL, CMU_PIE, and FERET face databases. When the LibSVM parameter was set to '-s 0 -t 2 -c 16 -g 0.0009765625', the algorithm achieved 100% recognition on Yale and ORL data sets, 92.16% on CMU_PIE data sets, and 74.3% on FERET data sets. The average time for simultaneous completion of the data sets examined was 1.93 s, and the algorithm demonstrated a 70.71% higher running efficiency than the CLBP algorithm. Therefore, the proposed algorithm is highly efficient in feature recognition with excellent computational efficiency. [ABSTRACT FROM AUTHOR]

Conform and non-conformal contact problem in the face of piezoelectric motors can be hard to grasp, especially both the friction drive and wear lifespan are considered. Flowing the classical contact issue, an elastic brittle flat punch as the driving tip of the stator for piezoelectric devices is chosen and the contact behaviour under elliptical ultrasonic vibration is investigated using finite element method. A limited stress analysis is conducted after the quasi-static contact of the driving tip and the slider of the linear ultrasonic motors. After the analytical traces and experimental test on the fracture failure induced by the stress actions, the failure criteria of the elastic brittle driving tip are discussed. Results show that this quasi-static method can be applied to the complex contact analysis of an elliptical vibration device, and the failure characteristics induced by stress and strain can be obtained by FEM simulation and experiment verification. The pre-fracture stress map provides an important basis for the design of the geometrical mutation edge (e.g. edge fillet) of the elastic brittle punch and the composite structure for strength capacity. The failure analysis of brittle materials under ultrasonic vibration requires attention on quasi-brittle and quasi-plastic strength criterions. This study focus on determination of the contact stresses and the limited states during the elliptical vibration of a stator tip against slider. It also is important for the analysis on failure modes of frictional materials of ultrasonic devices, fretting wear of high-frequency connecting parts and machining process assisted with ultrasonic vibration. [ABSTRACT FROM AUTHOR]

In this study, we evaluated atmospheric particulate matter (PM) concentration predictions at a regional scale using a simplified Lagrangian particle dispersion modeling system and the Bayesian and multiplicative ratio correction optimization (Bayesian-RAT) method to improve the mixing ratio forecast of PM10 and PM2.5. We first examined the forecast performance of the LPD (i.e., the simplified FLEXPART model combined with the Bayesian-RAT method) by comparing the model predictions with the PM concentration observations from 95 observation stations in Xingtai city and its surrounding areas. The first 2 months (i.e., Oct. and Nov. 2017) of the study period represented the typical spin-up time period, and the analysis period was December 2017. The LPD forecast system was much better (correlation coefficient: R=0.64 vs. 0.48 and 0.67 vs. 0.50 for PM10 and PM2.5, respectively; root mean square error: RMSE = 74.98 vs. 105.96 μg/m3 for PM10 and 54.89 vs. 72.81 μg/m3 for PM2.5) than the pre-calibration results. We also compared the LPD forecasting model with other models (WRF-Chem and Camx) using data from monitoring stations in Xingtai, China, and the LPD forecasting model had higher accuracy than the other models. In particular, the RMSE scores for hourly PM10 concentrations were reduced by 36.51% and 42.21% compared to WRF-Chem and to Camx, respectively. The PM2.5 forecast results, as in the case of PM10, showed a better performance when applying the LPD model to the data from the monitoring stations. The RMSE was reduced by 26.44% and 18.47% relative to the WRF-Chem and Camx, respectively. The results confirm that there is much advantage of the LPD forecast system for predicting PM and may be for other pollutants. [ABSTRACT FROM AUTHOR]

An analytical model for the textured infinitely long slider is developed to study the influence of cross-hatched texture on hydrodynamic lubrication by considering the mass-conserving boundary condition. The three-dimensional morphology of the cross-hatched texture is characterized by a series of mathematical formulas. By using multigrid method and Gauss–Seidel iteration, the hydrodynamic pressure distribution of textured surface can be obtained to analyze the influence of width, depth, spacing, cross-hatched angle and overlapping coefficient of the cross-hatched texture on the hydrodynamic lubrication. The results show that hydrodynamic lubrication can be generated between two parallel plane surfaces with cross-hatched texture. Moreover, the geometrical parameters of the cross-hatched texture have prominent effect on hydrodynamic pressure distribution and load carrying capacity. [ABSTRACT FROM AUTHOR]

While high friction coefficients and good wear resistance are antagonistic properties of most materials, these properties are expected to promote excellent torque-speed characteristics and extend the life span of ultrasonic motors. Blending is an accepted technique for modifying tribological applications. p-Hydroxybenzoic acid polymer (Ekonol) blends with different compositions, and proportions were prepared through mechanical blending. Poly(tetrafluoroethylene) (PTFE), poly(etheretherketone), and poly(phylenesulfide) (PPS) were selected as dispersed phases. The mechanical properties of the blends were investigated, and their tribological performance was tested using a block-on-ring wear meter. The worn surfaces of Ekonol blends were observed using a scanning electron microscope to elucidate the relevant wear mechanisms. Results showed that the dispersed phases have distinct effects on the impact strength and hardness, as well as friction coefficient and wear rate, of the blends. Curves of hardness and friction coefficient versus the dispersed phase content showed apparent similarities, which indicates that hardness influences the friction of polymer blends in contact with carbon steel. Worn tracks on the surfaces of different polymer materials showed that the dominant wear mechanism transforms from fatigue and abrasion into adhesion with the addition of a dispersed phase; delamination was observed in the transfer films, especially those formed by the Ekonol/PTFE and Ekonol/PPS blends. [ABSTRACT FROM AUTHOR]