scholarly journals Study on the Intelligent Selection Model of Fuzzy Semantic Optimal Solution in the Process of Translation Using English Corpus

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Li Bei
Keyword(s):  
English Translation ◽  
Feature Matching ◽  
Optimal Solution ◽  
Solution Vector ◽  
Registration Method ◽  
Feature Registration ◽  
Matching Degree ◽  
Semantic Ontology ◽  
Extraction Model ◽  
Link Relation

In order to improve the accuracy and reasonableness of using English corpus for translation, a method of using English corpus to perform translation tasks based on fuzzy semantic optimal solution intelligent selection and inspired computing for wireless networks is proposed. The information extraction model using English corpus for translation is constructed, and the fuzzy semantic keyword feature directivity model of English corpus translation is established. Fuzzy semantic ontology feature registration method is used to calculate the fuzzy semantic intelligence optimal solution vector in English translation. The semantic fuzzy feature matching and adaptive subject word registration are realized in English translation. The fuzzy link relation of semantic ontology is established, and the fuzzy semantic optimal solution is obtained. The accuracy of machine translation in English corpus is improved. The experimental results show that the fuzzy semantic optimal solution has better registration performance and the feature matching degree of the subject words is higher, which improves the reasonableness and accuracy of translation in English corpus. At the same time, it provides a new idea for intelligent computation and recognition of wireless network.

A new approach of surfaces registration considering form errors for precise assembly

2020 ◽  
Vol 40 (6) ◽  
pp. 789-800
Author(s):  
Qiushuang Zhang ◽  
Xin Jin ◽  
Zhihua Liu ◽  
Zhijing Zhang ◽  
Yan Fang ◽  
...  
Keyword(s):  
Manufacturing Industry ◽  
Optimal Solution ◽  
Registration Method ◽  
Content Type ◽  
Form Errors ◽  
Contact Points ◽  
Assembly Accuracy ◽  
Prediction And Control ◽  
Experimental Values ◽  
And Control

Purpose The modern manufacturing industry has put forward higher requirements for the assembly accuracy of components with the development of the industrial technology. For precision assembly, the traditional assembly process study based on tolerance has had difficulty in meeting these requirements. Hence, the distribution of the form errors must be considered. The registration between the two mating surfaces with form errors determines the parts’ assembly position, and is the basis for the prediction and control of the assembly accuracy. This study aims to provide a new surfaces registration method which takes form errors into consideration. Design/methodology/approach This study presents a new registration approach based on the minimum potential energy. A unique set of contact points on mating surfaces that meet the actual conditions can be obtained and the spatial position of the assembled part is calculated. Findings The experimental results show that the calculated values are in good agreement with the experimental values. Furthermore, the root mean square error is within 2%, which proves the validity and accuracy of the approach. Originality/value This paper provides an effective and new method for precision assembly which takes form errors into consideration. The method can give the optimal solution of the contact points, which is more consistent with the actual assembly situation and provides a basis for predicting assembly accuracy.

HYBRID REGISTRATION OF CORRESPONDING MAMMOGRAM IMAGES FOR AUTOMATIC DETECTION OF BREAST CANCER

2007 ◽  
Vol 19 (06) ◽  
pp. 359-374 ◽  
Author(s):  
Yih-Chih Chiou ◽  
Chern-Sheng Lin ◽  
Cheng-Yu Lin
Keyword(s):  
Breast Cancer ◽  
Image Registration ◽  
Early Detection ◽  
Feature Matching ◽  
Automatic Detection ◽  
Spatial Transformation ◽  
Registration Method ◽  
Feature Based ◽  
Mammogram Images ◽  
Hybrid Registration

Mammogram registration is a critical step in automatic detection of breast cancer. Much research has been devoted to registering mammograms using either feature-matching or similarity measure. However, a few studies have been done on combining these two methods. In this research, a hybrid mammogram registration method for the early detection of breast cancer is developed by combining feature-based and intensity-based image registration techniques. Besides, internal and external features were used simultaneously during the registration to obtain a global spatial transformation. The experimental results indicates that the similarity between the two mammograms increases significantly after a proper registration using the proposed TPS-registration procedures.

Artificial Fish Swarm Algorithm Based on Fast Image Matching

2011 ◽  
Vol 271-273 ◽  
pp. 297-302
Author(s):  
Miao Ma ◽  
Jiao He ◽  
Min Guo
Keyword(s):  
Image Matching ◽  
Feature Matching ◽  
Fitness Function ◽  
Optimal Solution ◽  
Fast Method ◽  
Artificial Fish Swarm Algorithm ◽  
Template Image ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm ◽  
Exclusive Or

Due to the large amount of calculation and high time-consuming in traditional grayscale matching, this paper combines artificial fish algorithm of swarm intelligence with edge detection and the operation of bitwise exclusive or, and presents a fast method on feature matching. The method regards the problem of image matching as a process of searching the optimal solution. In order to provide artificial fish swarm algorithm with an appropriate fitness function, the operation of bitwise exclusive or and addition is employed to deal with the edge information extracted from the template image and the searching image. Then the best matching position is gradually approaching by swarming, following and other behaviors of artificial fish. Experimental results show that the proposed method not only significantly shortens the matching time and guarantees the matching accuracy, but also is robust to noise disturbance.

Genetic Algorithms Study in Switch Electrical Appliances Electric Arc Feature Extraction

2013 ◽  
Vol 365-366 ◽  
pp. 165-169
Author(s):  
Jing Sheng Yu ◽  
Li Li ◽  
Ting Liu
Keyword(s):  
Genetic Algorithm ◽  
Feature Extraction ◽  
Optimal Solution ◽  
Electric Arc ◽  
Network Computing ◽  
Electrical Arc ◽  
Pool Formation ◽  
Extraction Model ◽  
Crossover And Mutation

The genetic algorithm applied to switch electrical appliances electric arc feature extraction, based on genetic algorithm, the switch electrical arc feature extraction model was established. The initial pool formation, evaluation individual, reproduction, crossover and mutation have done a detailed representation. This model can eliminate the slow convergence and so easy to fall into the local minimum shortcomings of BP neural network computing graphics weights. The experiment showed that genetic algorithm can better converge to the global optimal solution, more in line with the arc Feature Extraction fact, and more effectively improving the quality of graphics extraction.

scholarly journals EXCHANGE RATE AND PERFORMANCE OF THE RESIDENTIAL PROPERTY MARKET IN KENYA

2019 ◽  
Vol 8 (3) ◽  
pp. 88-100
Author(s):  
Charles Gitiya Njoroge ◽  
Willy Muturi ◽  
Oluoch Oluoch
Keyword(s):  
Exchange Rate ◽  
Optimal Solution ◽  
Secondary Data ◽  
Residential Property ◽  
Property Market ◽  
Solution Vector ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Long Run ◽  
Short Run

The purpose of the study was to establish the effect of exchange rate on the performance of the residential property market in Kenya. The study used secondary data that was accumulated using secondary data collection sheet from first quarter of 2005 to fourth quarter of 2018. The study conducted several test statistics and diagnostic tests in order to achieve the most optimal solution. Vector error correction model and auto-regressive distributed lag model were employed to test the hypothesis in the short run and long run respectively. The results found out that exchange rate had a negative effect on performance of residential properties in Kenya in both the short run and positive effect in long run. The study has narrowed down the research gap brought about by the conflicting emprical, theoretical and conceptual literature with regard to the effect of exchange rate on performance of residential property market in Kenya. Key Words: Exchange Rate, Performance, Residential Property

scholarly journals AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

2016 ◽  
Vol XLI-B7 ◽  
pp. 593-600
Author(s):  
C. Xu ◽  
H. G. Sui ◽  
D. R. Li ◽  
K. M. Sun ◽  
J. Y. Liu
Keyword(s):  
Image Registration ◽  
Feature Matching ◽  
Visual Saliency ◽  
Specific Area ◽  
Image Feature ◽  
Sar Image ◽  
Registration Method ◽  
Adaptive Parameter ◽  
Coarse Registration ◽  
Multi Level

Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM) to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

scholarly journals Automatic Defect Detection for Web Offset Printing Based on Machine Vision

2019 ◽  
Vol 9 (17) ◽  
pp. 3598 ◽  
Author(s):  
Erhu Zhang ◽  
Yajun Chen ◽  
Min Gao ◽  
Jinghong Duan ◽  
Cuining Jing
Keyword(s):  
Image Registration ◽  
Defect Detection ◽  
Feature Matching ◽  
Reference Image ◽  
Printing Industry ◽  
Offset Printing ◽  
Shape Context ◽  
Image Subtraction ◽  
Registration Method

In the printing industry, defect detection is of crucial importance for ensuring the quality of printed matter. However, rarely has research been conducted for web offset printing. In this paper, we propose an automatic defect detection method for web offset printing, which consists of determining first row of captured images, image registration and defect detection. Determining the first row of captured images is a particular problem of web offset printing, which has not been studied before. To solve this problem, a fast computational algorithm based on image projection is given, which can convert 2D image searching into 1D feature matching. For image registration, a shape context descriptor is constructed by considering the shape concave-convex feature, which can effectively reduce the dimension of features compared with the traditional image registration method. To tolerate the position difference and brightness deviation between the detected image and the reference image, a modified image subtraction is proposed for defect detection. The experimental results demonstrate the effectiveness of the proposed method.

scholarly journals Modality-Free Feature Detector and Descriptor for Multimodal Remote Sensing Image Registration

2020 ◽  
Vol 12 (18) ◽  
pp. 2937
Author(s):  
Song Cui ◽  
Miaozhong Xu ◽  
Ailong Ma ◽  
Yanfei Zhong
Keyword(s):  
Remote Sensing ◽  
Image Registration ◽  
Near Infrared ◽  
Feature Matching ◽  
Simulated Data ◽  
Remote Sensing Image ◽  
Surface Model ◽  
Phase Congruency ◽  
Remote Sensing Images ◽  
Registration Method

The nonlinear radiation distortions (NRD) among multimodal remote sensing images bring enormous challenges to image registration. The traditional feature-based registration methods commonly use the image intensity or gradient information to detect and describe the features that are sensitive to NRD. However, the nonlinear mapping of the corresponding features of the multimodal images often results in failure of the feature matching, as well as the image registration. In this paper, a modality-free multimodal remote sensing image registration method (SRIFT) is proposed for the registration of multimodal remote sensing images, which is invariant to scale, radiation, and rotation. In SRIFT, the nonlinear diffusion scale (NDS) space is first established to construct a multi-scale space. A local orientation and scale phase congruency (LOSPC) algorithm are then used so that the features of the images with NRD are mapped to establish a one-to-one correspondence, to obtain sufficiently stable key points. In the feature description stage, a rotation-invariant coordinate (RIC) system is adopted to build a descriptor, without requiring estimation of the main direction. The experiments undertaken in this study included one set of simulated data experiments and nine groups of experiments with different types of real multimodal remote sensing images with rotation and scale differences (including synthetic aperture radar (SAR)/optical, digital surface model (DSM)/optical, light detection and ranging (LiDAR) intensity/optical, near-infrared (NIR)/optical, short-wave infrared (SWIR)/optical, classification/optical, and map/optical image pairs), to test the proposed algorithm from both quantitative and qualitative aspects. The experimental results showed that the proposed method has strong robustness to NRD, being invariant to scale, radiation, and rotation, and the achieved registration precision was better than that of the state-of-the-art methods.

scholarly journals An Elite Decision Making Harmony Search Algorithm for Optimization Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Lipu Zhang ◽  
Yinghong Xu ◽  
Yousong Liu
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Solution Vector ◽  
Integer Variables ◽  
Design Variables ◽  
New Variant

This paper describes a new variant of harmony search algorithm which is inspired by a well-known item “elite decision making.” In the new algorithm, the good information captured in the current global best and the second best solutions can be well utilized to generate new solutions, following some probability rule. The generated new solution vector replaces the worst solution in the solution set, only if its fitness is better than that of the worst solution. The generating and updating steps and repeated until the near-optimal solution vector is obtained. Extensive computational comparisons are carried out by employing various standard benchmark optimization problems, including continuous design variables and integer variables minimization problems from the literature. The computational results show that the proposed new algorithm is competitive in finding solutions with the state-of-the-art harmony search variants.

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