Modeling the joint choice of access modes and flight routes with parallel structure and random heterogeneity

2016 ◽  
Vol 95 ◽  
pp. 19-31 ◽  
Author(s):  
Chih-Wen Yang ◽  
Pei-Han Liao
Keyword(s):  
Parallel Structure ◽  
Random Heterogeneity

Increasing the information capacity of a fiber-optic multi-sensor converter of binary mechanical signals into electrical signals

2020 ◽  
pp. 15-23
Author(s):  
V. M. Grechishnikov ◽  
E. G. Komarov
Keyword(s):  
Fiber Optic ◽  
Information Capacity ◽  
Parallel Structure ◽  
Optical Scheme ◽  
Digital To Analog Converter ◽  
Electrical Signals ◽  
Mechanical Signals ◽  
Analog Converter ◽  
Output Code ◽  
Digital To Analog

The design and operation principle of a multi-sensor Converter of binary mechanical signals into electrical signals based on a partitioned fiber-optic digital-to-analog Converter with a parallel structure is considered. The digital-to-analog Converter is made from a set of simple and technological (three to five digit) fiber-optic digital-to-analog sections. The advantages of the optical scheme of the proposed. Converter in terms of metrological and energy characteristics in comparison with single multi-bit converters are justified. It is shown that by increasing the number of digital-analog sections, it is possible to repeatedly increase the information capacity of a multi-sensor Converter without tightening the requirements for its manufacturing technology and element base. A mathematical model of the proposed Converter is developed that reflects the features of its operation in the mode of sequential time conversion of the input code vectors of individual fiber-optic sections into electrical analogues and the formation of the resulting output code vector.

Parallel and sequential structures of manipulators in robotic surgery

2019 ◽  
Vol 485 (2) ◽  
pp. 166-170
Author(s):  
E. I. Veliev ◽  
R. F. Ganiev ◽  
V. A. Glazunov ◽  
G. S. Filippov
Keyword(s):  
Robotic Surgery ◽  
Robotic System ◽  
Parallel Structure ◽  
Manipulation System ◽  
Surgical Manipulation ◽  
Surgical Operations

The problems of modern robotics associated with the requirements for devices designed for various purposes are considered. The daVinci robotic surgical manipulation system is analyzed. The developed robotic system with a parallel structure designed for various kinds of surgical operations is proposed.

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

A Novel Automatic Modulation Classification Method Using Attention Mechanism and Hybrid Parallel Neural Network

2021 ◽  
Vol 11 (3) ◽  
pp. 1327
Author(s):  
Rui Zhang ◽  
Zhendong Yin ◽  
Zhilu Wu ◽  
Siyang Zhou
Keyword(s):  
Neural Network ◽  
Communication Systems ◽  
Parallel Structure ◽  
Modulation Classification ◽  
Automatic Modulation Classification ◽  
Spatial Features ◽  
Temporal Features ◽  
Different Types ◽  
In Series ◽  
Parallel Network

Automatic Modulation Classification (AMC) is of paramount importance in wireless communication systems. Existing methods usually adopt a single category of neural network or stack different categories of networks in series, and rarely extract different types of features simultaneously in a proper way. When it comes to the output layer, softmax function is applied for classification to expand the inter-class distance. In this paper, we propose a hybrid parallel network for the AMC problem. Our proposed method designs a hybrid parallel structure which utilizes Convolution Neural Network (CNN) and Gate Rate Unit (GRU) to extract spatial features and temporal features respectively. Instead of superposing these two categories of features directly, three different attention mechanisms are applied to assign weights for different types of features. Finally, a cosine similarity metric named Additive Margin softmax function, which can expand the inter-class distance and compress the intra-class distance simultaneously, is adopted for output. Simulation results demonstrate that the proposed method can achieve remarkable performance on an open access dataset.

Sentence similarity evaluation using Sent2Vec and siamese neural network with parallel structure

2021 ◽  
pp. 1-10
Author(s):  
Hye-Jeong Song ◽  
Tak-Sung Heo ◽  
Jong-Dae Kim ◽  
Chan-Young Park ◽  
Yu-Seop Kim
Keyword(s):  
Neural Network ◽  
Language Processing ◽  
Short Term Memory ◽  
Parallel Structure ◽  
Short Term ◽  
Similarity Estimation ◽  
Accurate Judgment ◽  
Proposed Model ◽  
Sentence Similarity ◽  
Long Short Term Memory

Sentence similarity evaluation is a significant task used in machine translation, classification, and information extraction in the field of natural language processing. When two sentences are given, an accurate judgment should be made whether the meaning of the sentences is equivalent even if the words and contexts of the sentences are different. To this end, existing studies have measured the similarity of sentences by focusing on the analysis of words, morphemes, and letters. To measure sentence similarity, this study uses Sent2Vec, a sentence embedding, as well as morpheme word embedding. Vectors representing words are input to the 1-dimension convolutional neural network (1D-CNN) with various sizes of kernels and bidirectional long short-term memory (Bi-LSTM). Self-attention is applied to the features transformed through Bi-LSTM. Subsequently, vectors undergoing 1D-CNN and self-attention are converted through global max pooling and global average pooling to extract specific values, respectively. The vectors generated through the above process are concatenated to the vector generated through Sent2Vec and are represented as a single vector. The vector is input to softmax layer, and finally, the similarity between the two sentences is determined. The proposed model can improve the accuracy by up to 5.42% point compared with the conventional sentence similarity estimation models.

scholarly journals An MEA-Tuning Method for Design of the PID Controller

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongli Zhang ◽  
Lijun Zhang ◽  
Zhiliang Dong
Keyword(s):  
Pid Controller ◽  
Industrial Process ◽  
Optimal Solution ◽  
Design Feature ◽  
Parameter Tuning ◽  
Parallel Structure ◽  
Evolutionary Information ◽  
Tuning Method ◽  
Efficiency And Effectiveness ◽  
Global Optimal

The optimization and tuning of parameters is very important for the performance of the PID controller. In this paper, a novel parameter tuning method based on the mind evolutionary algorithm (MEA) was presented. The MEA firstly transformed the problem solutions into the population individuals embodied by code and then divided the population into superior subpopulations and temporary subpopulations and used the similar taxis and dissimilation operations for searching the global optimal solution. In order to verify the control performance of the MEA, three classical functions and five typical industrial process control models were adopted for testing experiments. Experimental results indicated that the proposed approach was feasible and valid: the MEA with the superior design feature and parallel structure could memorize more evolutionary information, generate superior genes, and enhance the efficiency and effectiveness for searching global optimal parameters. In addition, the MEA-tuning method can be easily applied to real industrial practices and provides a novel and convenient solution for the optimization and tuning of the PID controller.

Dynamic Formulation and Performance Evaluation of the 6-d.o.f. Parallel Structure Seismic Simulator

2009 ◽  
Vol 23 (12-13) ◽  
pp. 1617-1640
Author(s):  
Yongjie Zhao ◽  
Feng Gao ◽  
Xianchao Zhao ◽  
Nengsheng Bao
Keyword(s):  
Performance Evaluation ◽  
Parallel Structure ◽  
Dynamic Formulation ◽  
And Performance

Research on the Pose Detection and Control Methods of Robot with Series-Parallel Structure

2013 ◽  
Vol 303-306 ◽  
pp. 1685-1690 ◽  
Author(s):  
Dong Yang ◽  
Tie Jun Li ◽  
Jin Yue Liu ◽  
Hai Wen Zhao
Keyword(s):  
Structural Features ◽  
Hybrid Structure ◽  
Parallel Structure ◽  
Sensing Systems ◽  
Position Detection ◽  
Pose Detection ◽  
Building Environment ◽  
Automated Installation ◽  
And Control ◽  
Structured Light Vision

Aiming at the load requirements, positioning accuracy and workflow of building panels installed robot, developed a 6 DOF of a series-parallel hybrid structure installed robot. According to the structural features of parallel mechanism to the installation manipulator, designed a robot attitude sensing system based on the inclination and laser ranging sensor information feedback; according to the characteristics of the building environment, proposed the position detection method of panels to be installed based on the structured light vision; constructed the control system of the installation manipulator, and used teaching mode to achieve robot control and system calibration. The experimental data prove that, the control and sensing systems of panels installed robot, overcome the complexity of the building environment and the diversity of installation object, and can achieve the automated installation of building panels.

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