The purpose of this paper is to develop an effective method to identify upper limb motions based on EMG signal for community rehabilitation. The method will be applicable to the control system in the rehabilitation equipment and provide objective data for quantitative assessment. The recognition goal sets of upper limb motion are constructed by decomposing assessment activities of activity of daily living scale (ADL). The recognition feature vector space is established by Variance (VAR), Mean Absolute Value (MAV), the fourth-order Autoregressive (the 4thAR), Zero Crossings (ZC’s), integral EMG (IEMG), and Root Mean Square (RMS), and various feature sets are extracted to get the best classification. Locally linear embedding (LLE) algorithm is used to reduce the computational complexity, and upper limb motions about shoulder, elbow and wrist are quickly classified through extreme leaving machine (ELM), which obtained the average accuracy of 98.14%, 98.61% and 94.77%, respectively. Furthermore, when ELM is compared with Back-propagation (BP) and Support vector machine (SVM), it has performed relatively better than BP and SVM. The results show that the validity of the mixed model for recognition is verified. In addition, the method can also provide a basis for recognition and assessment of the angle of upper limb joint in the next study.

In the past few years, Battery Energy Storage System (BESS) has been found of great potential in supporting the frequency control. Increasing attentions have been given to the control strategy of BESS. In this paper, a distributed control method considering the life-loss cost is proposed for BESS. Based on the multi-agent system, the Incremental Cost Consensus (ICC) algorithm is applied to minimize the life-loss cost of BESS. In order to improve the control performance, parameters of the system are optimized by Genetic Algorithm (GA). The simulation results are provided to verify the effectiveness of the proposed approach.

Failures caused by acid erosion corrosion occur frequently in air cooler systems because of the use of increasingly low-quality crude oil with high sulfur, acid and chlorine content. The pH value is one of the key parameters used to evaluate the corrosion risk of an air cooler. However, this value is difficult to measure online because of the severe measurement environment, which includes high temperatures, high pressures and corrosion risks. In this paper, a pH soft-sensor modelling method for an air cooler system in a refinery production processing is developed. Using modelling and simulation in Aspen together with site data, the correlated influence factors are determined first. Then, a soft-sensor model based on a fast search pruned-extreme learning machine is proposed in which the pruning problem of hidden-layer nodes with random weights is solved by adopting the fast search density peak clustering algorithm. The proposed fast search pruned-extreme learning machine can improve the modelˈs prediction performance by pruning redundant hidden layer nodes with a simpler structure. The feasibility and efficiency of the developed method are demonstrated by the results in the form of benchmark data and real air cooler system data. Figure 3. Diagrams of the change in pH in the solution medium with temperature under different S, Cl and N content and water injection conditions. Asia-Pacific Journal of Chemical Engineering FSP-ELM BASED SOFT-SENSOR MODELING FOR PH VALUES 189

No abstract

In this paper, a block-based Hough transform is proposed to recognize the zebra crossing in natural scene images. Overlapping blocks are laid on the region of interest (ROI) in each image. For each patch in the block, two processes are performed successively. First, preprocessing is adopted for edge detection, whereas the adaptive thresholding is used to minimize the effect of various shadows. Second, parallel lines detection is adapted to recognize the zebra crossing, whereas the Hough transform is used for straight lines detection. When all the blocks are processed, the angles of parallel lines are averaged to provide the direction of the zebra crossing, and the accumulative scores are synthesized to provide the position of the zebra crossing. The performance of the proposed method is evaluated by testing results based on numerous images. INDEX TERMS Accumulative scoring evaluation, block-based Hough transform, zebra crossing recognition.