Hybrid artificial bee colony algorithm with variable neighborhood search and memory mechanism

Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC.

Study on Motivational Factors in L2 Learning

This study is an intrinsic study of EFL motivation at the tertiary level by the use of a combination of quantitative and qualitative approaches. Three parts are involved in this study： 1） variables that constitute learners＇ motivation of EFL learning; 2） the relationships among motivational components; 3） the differences between high achievers and low achievers.

Variability of Pesticide Residues in Vegetables from the Marketplaces in Jinan City

In order to provide technological support for risk estimation of pesticide residues taken from vegetables, the residues of pesticide in vegetables in Jinan City, China, were investigated. Moreover, the variability of pesticide residues in vegetables was explored, and the variability factor was calculated. The level of pesticide residue was studied by statistical method. The variability factor was calculated using the Harrell-Davis method in accordance with principles recommended by the JMPR. In addition, the procedure of evaluation was validated according to the principles laid down by the JMPR （Joint Meeting on Pesticide Residues）. The detection rate of pesticide residues in all marketplace samples was less than 20% in Jinan City. The unqualified rate of vegetables was low （0.6%）. The chlorothalonil was found as the pesticide with the highest rate of detection. The vegetables with the highest rate of pesticide residues detected were leafy vegetables. The relationship between variability factor and mean value of concentrations of contaminations was expressed by the formula, v=4.9×Cmean. The pesticide residues in vegetables from Jinan City is low. The evaluated variability factor is larger than that the value recommended by the JMPR, however, less than the default value used for acute intake assessment of pesticide residues in UK in most cases.

Anti-plane analysis of semi-infinite crack in piezoelectric strip

Using the complex variable function method and the technique of the conformal mapping, the fracture problem of a semi-infinite crack in a piezoelectric strip is studied under the anti-plane shear stress and the in-plane electric load. The analytic solutions of the field intensity factors and the mechanical strain energy release rate are presented under the assumption that the surface of the crack is electrically impermeable. When the height of the strip tends to infinity, the analytic solutions of an infinitely large piezoelectric solid with a semi-infinite crack are obtained. Moreover, the present results can be reduced to the well-known solutions for a purely elastic material in the absence of the electric loading. In addition, numerical examples are given to show the influences of the loaded crack length, the height of the strip, and the applied mechanical/electric loads on the mechanical strain energy release rate.

Fault Detection Based on FIR Filters with Variable Discount Factors for Industrial Robot Drive Systems

To enhance dynamic tracking performance and anti-disturbance capacity of finite impulse response(FIR) filters, variable discount factors are introduced to the recursive least squares(RLS) algorithm. By employing improved FIR filters to conduct modelling of industrial robot drive systems, dynamic characteristics of the target systems are identified. Then the fault detection for a target system can be utilized by analyzing the coefficients of the FIR filter. Finally, an application of the fault detection scheme to a kind of brushless DC motor drive system is described. Compared with reference methods, the proposed scheme achieves effective fault detection and performs better in dynamic tracking and robustness according to the final simulation results.

New code match strategy for wideband code division multiple access code tree management

Orthogonal variable spreading factor channelization codes are widely used to provide variable data rates for supporting different bandwidth requirements in wideband code division multiple access (WCDMA) systems. A new code match scheme for WCDMA code tree management was proposed. The code match scheme is similar to the existing crowed-first scheme. When choosing a code for a user, the code match scheme only compares the one up layer of the allocated codes, unlike the crowed-first scheme which perhaps compares all up layers. So the operation of code match scheme is simple, and the average time delay is decreased by 5.1%. The simulation results also show that the code match strategy can decrease the average code blocking probability by 8.4%.

Locality Preserving Discriminant Projection for Speaker Verification

In this paper, a manifold subspace learning algorithm based on locality preserving discriminant projection (LPDP) is used for speaker verification. LPDP can overcome the deficiency of the total variability factor analysis and locality preserving projection (LPP). LPDP can effectively use the speaker label information of speech data. Through optimization, LPDP can maintain the inherent manifold local structure of the speech data samples of the same speaker by reducing the distance between them. At the same time, LPDP can enhance the discriminability of the embedding space by expanding the distance between the speech data samples of different speakers. The proposed method is compared with LPP and total variability factor analysis on the NIST SRE 2010 telephone-telephone core condition. The experimental results indicate that the proposed LPDP can overcome the deficiency of LPP and total variability factor analysis and can further improve the system performance.

Iterative identification of output error model for industrial processes with time delay subject to colored noise

To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.

An FPGA-based LDPC decoder with optimized scale factor of NMS decoding algorithm

Considering that the hardware implementation of the normalized minimum sum(NMS)decoding algorithm for low-density parity-check(LDPC)code is difficult due to the uncertainty of scale factor,an NMS decoding algorithm with variable scale factor is proposed for the near-earth space LDPC codes(8177,7154)in the consultative committee for space data systems(CCSDS)standard.The shift characteristics of field programmable gate array(FPGA)is used to optimize the quantization data of check nodes,and finally the function of LDPC decoder is realized.The simulation and experimental results show that the designed FPGA-based LDPC decoder adopts the scaling factor in the NMS decoding algorithm to improve the decoding performance,simplify the hardware structure,accelerate the convergence speed and improve the error correction ability.

Responses of Grassland Net Primary Productivity to Environmental Variables in Northern China

Various environmental factors affect net primary productivity （NPP） of grassland ecosystem. Extensive reports on the effects of environmental variables on NPP can be found in literature. However, the agreement on the relative importance of various factors in shaping the spatial pattern of grassland NPP has not yet been reached. Here a grassland in situ NPP database comprising 602 samples in northern China for 1980-1999 was developed based on a literature review of published biomass and forage yield field measurements. Correlation analyses and dominance analysis were used to quantify the separate and combined effects of environmental variables （climate topography and soil） on spatial variation in NPP separately. Grassland NPP ranged from 4.76 g C m-2a-1 to 975.94gCm-2a-1, showing significant variations in space. NPP increased with annual precipitation and declined with annual mean temperature significantly. Specifically, precipitation had the greatest impact on deserts, followed by steppes and meadows. Grassland NPP decreased with increasing altitude because of water limitation, and positively correlated with slope, but weakly correlated with aspect. Soil quality showed positive effects on NPP. Annual precipitation was the dominant factor affecting the spatial variability of net primary productivity, followed by elevation.

Modeling and state of charge estimation of lithium-ion battery

Modeling and state of charge （SOC） estimation of lithium-ion （Li-ion） battery are the key techniques of battery pack management system （BMS） and critical to its reliability and safety operation. An auto-regressive with exogenous input （ARX） model is derived from RC equivalent circuit model （ECM） due to the discrete-time characteristics of BMS. For the time-varying environmental factors and the actual battery operating conditions, a variable forgetting factor recursive least square （VFFRLS） algorithm is adopted as an adaptive parameter identifica- tion method. Based on the designed model, an SOC estimator using cubature Kalman filter （CKF） algorithm is then employed to improve estimation performance and guarantee numerical stability in the computational procedure. In the battery tests, experimental results show that CKF SOC estimator has a more accuracy estimation than extended Kalman filter （EKF） algorithm, which is widely used for Li-ion battery SOC estimation, and the maximum estimation error is about 2.3%.