Continuance Intention on Mobile Social Networking Service: Examine the Effects of Habit and Gratifications

By integrating the uses and gratifications theory and habit theory, this study develops a theoretical model to explore factors affecting continuance intention of mobile social networking service. 218 valid data were collected in China. The empirical results show that, cognitive need and affective need have significant impacts on continuance intention. In addition, habit is significantly determined by affective need, tension-release need and prior use, which further significantly influences continuance intention

Optimization of Induction Quenching Processes for HSS Roll Based on MMPT Model

To improve the comprehensive performance of high speed steel (HSS) cold rolls, the induction hardening processes were analyzed by numerical simulation and experimental research. Firstly, a modified martensitic phase transformation (MMPT) model of the tested steel under stress constraints was established. Then, the MMPT model was fed into DEFORM to simulate the induction quenching processes of working rolls based on an orthogonal test design and the optimal dual frequency of the induction quenching process was obtained. The results indicate that the depth of the roll’s hardened layer increases by 32.5% and the axial residual tensile stress also becomes acceptable under the optimized process. This study provides guidance for studying phase transformation laws under stress constraints and the optimization of complex processes in an efficient manner

Formability of a HSAS Based on Hot Processing Maps and Texture Analyses

Aiming to improve the formability of a HSAS Docol 1500 Bor, hot processing maps were obtained based on Prasad, Babu and Murty instability criteria. The hot processing maps based on the above instability criteria are similar and the explanation of its similarity is given. Recrystallization and misorientation in typical quenched specimens were observed by using SEM with a EBSD system. It was found that the fraction values of HAGBs in quenched martensite are all below 0.4 under experimental conditions. Flow location bands occurs at lower deformation temperatures and higher strain rates. The textures in martensite mainly include ⟨110⟩ / / ND and ⟨110⟩ / / RD components. Based on N-W OR, the textures in deformed austenite are mostly ⟨111⟩ / / ND and ⟨112⟩ / / RD⟩ components. Prasad and Babu instability criteria are more conservative than Murty instability criterion in obtaining the processing maps of the tested steel. To reduce the anisotropy of quenched workpieces because of the textures at room temperature, the quenching temperature in the stamping process of the tested steel should be lower

A linear recursive state of power estimation for fusion model component analysis with constant sampling time.

The state of power of lithium-ion batteries, as the main product of choice for electric and hybrid electric vehicle energy storage systems, is one of the precise feedback control parameters for the battery management system. The proposed research establishes a method for the analysis of charging and discharging constitutive factors under the sampling time, realizes the online identification of parameters by building an adaptive forgetting factor recursive least-squares method based on the Thevenin model, and uses the online parameters to achieve an effective characterization of the power state under voltage and current limitations. The results demonstrate that the accuracy error of online parameter identification is less than 0.03 V. Combining the analysis of charging and discharging constitutive factors under-sampling time with the fusion model of voltage and current limitation makes the power state estimation more reliable and accurate. The results demonstrate that the power state estimation error in the discharging state is less than 8%

An improved robust function correction-adaptive extended Kalman filtering algorithm for SOC estimation of lithium-ion batteries.

State of Charge (SOC) is one of the key indicators for evaluating the state of electric vehicles. In order to cope with the uncertainty of random noise in nonlinear systems, an improved robust function correction-adaptive extended Kalman filtering (RFC-AEKF) algorithm is proposed for SOC prediction. Using FFRLS method to verify the Dual Polarization model established in this paper. The robust function is an abstract method that describes system state noise and observation noise, and performs real-time correction, combined with adaptive methods to estimate SOC. The experimental results show that the proposed RFC-AEKF algorithm has the smallest mean absolute error (MAE) and root mean square error (RMSE) compared to other algorithms. Under the Beijing bus dynamic stress test (BJDST) conditions, the MAE and RMSE of the RFC-AEKF are 0.354% and 0.658%, respectively, indicating that the RFC-AEKF algorithm can improve SOC estimation accuracy and enhance robustness

A novel high-fidelity unscented particle filtering method for the accurate state of charge estimation of lithium-ion batteries.

Power Li-ion batteries are one of the core "three powers" systems of new energy vehicles, and its accurate batteries modeling and state prediction have become the core technology of the scientific and technological progress in the industry. This paper takes the ternary Li-ion batteries as the research subject. Aiming at the mathematical expressions of different structural features, innovatively construct a second-order Thevenin equivalent circuit model with autoregressive effect. This model can characterize the internal reaction mechanism of Li-ion batteries and fit the complex electrochemical reactions inside the battery. An improved particle filter model, namely a new high-fidelity unscented particle filter method, is designed and established. By introducing a suitable suggested density function, the model can accurately calculate the mean and variance, solve the particle degradation problem, and find out the Li-ion batteries state of charge, which is suitable for complex charging and discharging conditions. By further improving the theoretical analysis and combining with experiments under different working conditions, this method studies the Li-ion batteries state of charge. The test results show that the average absolute error of the improved equivalent circuit model is reduced by 0.00457 V, and the error rate is stably kept within 1%, which has the ability to describe Li-ion batteries well. When using the high-fidelity unscented particle filter algorithm to estimate the state of charge of the lithium battery, the robustness of the system is improved, the following effect is better, and the estimation error is controlled within 1.5%, which brings good practical value to the power Li-ion batteries

Online full-parameter identification and SOC estimation of lithium-ion battery pack based on composite electrochemical-dual circuit polarization modeling.

A new composite electrochemistry-dual circuit polarization model (E-DCP) is proposed by combining the advantages of various electrochemical empirical models in this paper. Then, the multi-innovation least squares (MILS) algorithm is used to perform online full parameter identification for the E-DCP model in order to improve data usage efficiency and parameter identification accuracy. In addition, on the basis of the E-DCP model, the MILS and the extended Kalman filter (EKF) are combined to enhance the state estimation accuracy of the battery management system (BMS). Finally, the model and the algorithm are both verified through urban dynamometer driving schedule (UDDS) and the complex charge-discharge loop test. The results indicate that the accuracy of E-DCP is relatively high under different working conditions, and the errors of state of charge (SOC) estimation after the combination of MILS and EKF are all within 2.2%. This lays a concrete foundation for practical use of the BMS in the future

Adaptive iterative working state prediction based on the double unscented transformation and dynamic functioning for unmanned aerial vehicle lithium-ion batteries.

In lithium-ion batteries, the accuracy of estimation of the state of charge is a core parameter which will determine the power control accuracy and management reliability of the energy storage systems. When using unscented Kalman filtering to estimate the charge of lithium-ion batteries, if the pulse current change rate is too high, the tracking effects of algorithms will not be optimal, with high estimation errors. In this study, the unscented Kalman filtering algorithm is improved to solve the above problems and boost the Kalman gain with dynamic function modules, so as to improve system stability. The closed-circuit voltage of the system is predicted with two non-linear transformations, so as to improve the accuracy of the system. Meanwhile, an adaptive algorithm is developed to predict and correct the system noises and observation noises, thus enhancing the robustness of the system. Experiments show that the maximum estimation error of the second-order Circuit Model is controlled to less than 0.20V. Under various simulation conditions and interference factors, the estimation error of the unscented Kalman filtering is as high as 2%, but that of the improved Kalman filtering algorithm are kept well under 1.00%, with the errors reduced by 0.80%, therefore laying a sound foundation for the follow-up research on the battery management system

PHARMACOLOGICAL EXPERIMENTAL STUDY OF THE ANTI-DEPRESSANT EFFECT OF TOTAL SAIKOSAPONINS.

Background: Chai Hu has the hepato-protective, choleretic, anti-tussive, analgesic, anti-inflammatory, anti-viral, hypotensive, hypolipidemic, and anti-tumor pharmacological effects. In this study, the objective of this paper was to study the anti-depressant effect of total saikosaponins. Materials and Methods: Total saikosaponins were extracted by reflux method, and were identified by thin layer chromatography (TLC). The anti-depressant effect of total saikosaponins was investigated in vitro by tail suspension test, forced swimming test, and reserpine antagonism test in mice. Results: Two times of reflux extraction, temperature of 70℃, and extraction time of 4hrs, for each extraction could improve the yield of saikosaponins. Each treatment group (100, 200, and 300 mg/kg), could significantly shorten the immobility time of mice in the tail suspension test in a somewhat dose-dependent manner. The total saikosaponins antagonized the reserpine-induced akinesia, and ptosis in mice. Conclusion: Total saikosaponins have an anti-depressant effect

A rapid and robust method for shot boundary detection and classification in uncompressed MPEG video sequences

Abstract Shot boundary and classification is the first and most important step for further analysis of video content. Shot transitions include abrupt changes and gradual changes. A rapid and robust method for shot boundary detection and classification in MPEG compressed sequences is proposed in this paper. We firstly only decode I frames partly in video sequences to generate DC images and then calculate the difference values of histogram of these DC images in order to detect roughly the shot boundary. Then, for abrupt change detection, shot boundary is precisely located by movement information of B frames. Shot gradual change is located by difference values of successive N I frames and classified by the alteration of the number of intra coding macroblocks (MBs) in P frames. All features such as the number of MBs in frames are extracted from uncompressed video sequences. Experiments have been done on the standard TRECVid video database and others to reveal the performance of the proposed method