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The accurate analysis of human dynamic behavior is very important for overcoming the limitations of movement diversity and behavioral adaptability. In this paper, a wearable device-based human dynamic behavior recognition method is proposed. The method collects acceleration and angular velocity data through a six-axis sensor to identify information containing specific behavior characteristics in a time series. A human movement data acquisition platform, the DMP attitude solution algorithm, and the threshold algorithm are used for processing. In this experiment, ten volunteers wore wearable sensors on their bilateral forearms, upper arms, thighs, calves, and waist, and movement data for standing, walking, and jumping were collected in school corridors and laboratory environments to verify the effectiveness of this wearable human movement recognition method. The results show that the recognition accuracy for standing, walking, and jumping reaches 98.33%, 96.67%, and 94.60%, respectively, and the average recognition rate is 96.53%. Compared with similar methods, this method not only improves the recognition accuracy but also simplifies the recognition algorithm and effectively saves computing resources. This research is expected to provide a new perspective for the recognition of human dynamic behavior and promote the wider application of wearable technology in the field of daily living assistance and health management.

An image processing-based Firebug Swarm Optimization (FSO) algorithm is developed in this article to detect maximum power point tracking (MPPT) under shadowing conditions on PV arrays. After capturing an image and applying image processing techniques, the proposed method can detect the shading portion of photovoltaic array (PV). The image processing results can then be used to modify the current rating in power equations. The Firebug swarm optimization (FSO) algorithm is metaheuristic algorithm that identifies and controls switching configurations under partial shading patterns by detecting the maximum global peak point (GPP) of output power generated by multiple configurations. This research is proposed with an image processing edge detection algorithm called the Otsu-Canny algorithm for detecting the partial shade on PV array. The FSO algorithm is used to rearrange the shaded photovoltaic array to significantly reduce the power and efficiency losses. MATLAB simulations were carried out using a 280 W PV panel to verify the efficiency of the proposed FSO MPPT technique with an image processing-based algorithm. The proposed FSO MPPT scheme's performance is compared to current cutting-edge MPPT methods. Under partial shading conditions, the proposed algorithm successfully detected the maximum peak point of a photovoltaic array, increasing power output and efficiency. [ABSTRACT FROM AUTHOR]

This paper addresses congestion avoidance using enhanced blue algorithm (EBA) for data transferring in a network. The congestion of data always affects the data transmission on the internet for various applications. For developing data transmission performance, the congestion of data is a challenging task. Although, different approaches have been used to avoid data congestion, yet we have considered a data transmission framework for better performance compare to existing approaches. Thus, we considered the advanced Blue Algorithm which is used to determine the node's capacity with middle path and it prevents congestion by monitoring of data during data transmission. The role of gateway is considered to supervise status of congestion for both data sending and receiving based on positive or negative acknowledgment as well as data size. The gateway is also used for a congestion notification system to alleviate congestion and enhance throughput. During experimental analysis, we have taken comparative performance between existing and our proposed model. For example, in Enhanced Ad hoc On-demand Distance Vector (EAODV), during the packet size of 10, the average end-to-end delay is 32.63 ms whereas in proposed advanced Blue algorithm, the average delay is only 19.11 ms. Thus, the proposed model using Blue algorithm is performed better than existing method. [ABSTRACT FROM AUTHOR]

The difficulties in obtaining the Right-of-Way have led to the development of multi-terminal transmission systems and these transmission systems are more vulnerable to faults and required to be cleared immediately as soon as they do occur for minimizing the power system disturbances and for efficient transmission. This paper aims in the systematic approach for fault detection, classification, faulty terminal identification, and fault location estimation of a four-terminal transmission system compensated with Unified Power Flow Controller (UPFC) based on frequency domain approach employing wavelet multi resolution analysis with the variations in fault inception angle, fault distance, and fault impedance by extracting the fault indices of current signals of all the three phases at all terminals. These fault indices were then compared with threshold value to detect and classify the faults and also identify the faulty terminal. The fault indices were used as inputs to the Fuzzy Inference System (FIS) for approximate fault location estimation from the respective terminals. Bior 1.5 wavelet has been chosen as mother wavelet as it has given the accurate results when compared with other members of wavelet family. The entire simulation was carried out in MATLAB environment within 110 km, 400 KV four-terminal transmission system, and the classification and location algorithms can be used as effective tools for real time digital relaying purpose as it has taken less than half cycle to detect the faults. [ABSTRACT FROM AUTHOR]

Determination of the threshold value is the key to chaos-based weak signal detection. The precision of the threshold value invariably defined the precision of the detection. Currently, determining the threshold value by observing the phase space trajectory could hardly satisfy the demand for an accurate threshold value in a short time, while the Lyapunov index method was complicated and it took a lot of time and computing resources, which was not convenient to program on the GPU platform. Comparably, the detecting method based on zero-crossing number could achieve an accurate threshold value with lower computing resources and complexity, which could well applied to the modern high performance programmable GPU. By using the zero-crossing number criterion, this paper proposed a new parallel algorithm of detecting the accurate threshold value based on GPU platform. Experiments show that the parallel algorithm based on GPU can accelerate the determination of the threshold value up to 90 times compared with the single-thread algorithm at the amplitude step length of 10. This parallel algorithm brings light to the quick detection of the threshold value of different chaos detecting system. [ABSTRACT FROM AUTHOR]

Abstract: In Image segmentation, the boundary of threshold segmentation would be deviated from the true edge points with regional growth segmentation, which based on dual cores is proposed employing local contrast information. By analyzing the threshold segmentation and edge detection segmentation, the fused segmentation algorithm is proposed integrating of them. Region growing segmentation based on dual-core is researched, the Gaussian noise effect on the segmentation is analyzed, and contrast with Otsu segmentation or Sobel operator segmentation; the dual-core segmentation principle is analyzed, high and low threshold segmentation method is designed. The characteristics of the transition region are studied; and whose pixels assigned algorithm is designed based on the local contrast. Experimental results show that the algorithm not only considers the adjacent uniformity of image information, but also takes into account the local contrast, which improves the effect of a simple threshold; it is an effective and practical image segmentation algorithm. [Copyright &y& Elsevier]

This paper studies local connectivity of neutral networks of RNA secondary and pseudoknot structures. A neutral network denotes the set of RNA sequences that fold into a particular structure. It is called locally connected, if in the limit of long sequences, the distance of any two of its sequences scales with their distance in the n-cube. One main result of this paper is that λn = n-1/2+δ is the threshold probability for local connectivity for neutral networks, considered as random subgraphs of n-cubes. Furthermore, we analyze local connectivity for finite sequence length and different alphabets. We show that it is closely related to the existence of specific paths within the neutral network. We put our theoretical results into context with folding algorithms into minimum-free energy RNA secondary and pseudoknot structures. Finally, we relate our structural findings with dynamics by discussing the role of local connectivity in the context of neutral evolution. [ABSTRACT FROM AUTHOR]

Abstract: For more exact navigation and positioning on the navigation systems, this paper discusses the improvement of statistical algorithms based on fuzzy knowledge with a brand-new theory. The improved fusion algorithms based on Bayesian theory and fuzzy methods on the track recognition are also given, respectively. However, this paper mainly makes a comparison of the improved new algorithms and two old algorithms for track recognition. The computer simulation shows the validity and feasibility of two improved algorithms. At the same time, the simulation results show that the overall performance of two improved algorithms for the track recognition all is better than that of the probabilistic algorithms. Based on the experiments in the dense target environment, the correct average recognition rate of statistical algorithms is 66.96% at the highest; that of the improved new algorithm based on fuzzy knowledge is 77.98%, that of the Bayesian fusion algorithm is 86.75%, however, that of the fuzzy fusion algorithm can be 90.14%. These results support the usefulness of the two improved algorithms. © 2002 Elsevier Science. All rights reserved. [Copyright &y& Elsevier]

We present an adaptive algebraic multigrid algorithm. The method is intended for large sparse matrix equations that arise from finite-element discretizations of the stray field in three-dimensional micromagnetism on nonuniform or unstructured grids. It uses a varying threshold value to control the grid ratio, trying to optimize the overall efficiency of the algebraic multigrid solver. We present numerical results and compare them with the preconditioned conjugate gradient method. [ABSTRACT FROM AUTHOR]

Summary: We present an algorithm of automatic vision inspection to solve the problems in a rapid bio-test strips reader. The image inspection area of a rapid bio-test strip includes control line testing zone, test line testing zone, and the assist-measuring zone of reference. By determining the central line of control line testing zone, we can calculate the central line of test line testing zone, and can calculate the characteristics of control line, test line and the reference light-field out further. We set different threshold values for each division for the different light-field to identify whether the reaction has occurred or not. The number of pixels in positive condition is usually less than that in negative condition for the divisions in the testing zone. In this bio-strips reader we can acquire the result within 0.3 seconds computer judgment after specimen rose to test line in 10–15 minutes. [Copyright &y& Elsevier]

The rank of channel matrix would be deficient as a result of antenna correlation or special scattering structure in wireless MIMO channels, in which the traditional QRD-M detection can not be applied directly. Aiming at this problem, this paper used channel regulation algorithm to expand the matrix, but this preprocessing would also bring new detection interference. It proposed the improved QRD-M keeping algorithm to alleviate the influence of this interference. Be different with the traditional QRD-M only M nodes, the proposed algorithm would keep all nodes whose weigh was larger than Mth node and the differential was in range of some threshold value. It gave the theoretical analysis to select the threshold value. The simulation results show that the proposed algorithm can still achieve better solution by selecting lower M. [ABSTRACT FROM AUTHOR]