3D Particle Image Velocimetry Test of Inner Flow in a Double Blade Pump Impeller

The double blade pump is widely used in sewage treatment industry,however,the research on the internal flow characteristics of the double blade pump with particle image velocimetry（PIV） technology is very little at present.To reveal inner flow characteristics in double blade pump impeller under off-design and design conditions,inner flows in a double blade pump impeller,whose specific speed is 111,are measured under the five off-design conditions and design condition by using 3D PIV test technology.In order to ensure the accuracy of the 3D PIV test,the external trigger synchronization system which makes use of fiber optic and equivalent calibration method are applied.The 3D PIV relative velocity synthesis procedure is compiled by using Visual C＋＋ 2005.Then absolute velocity distribution and relative velocity distribution in the double blade pump impeller are obtained.Test results show that vortex exists in each condition,but the location,size and velocity of vortex core are different.Average absolute velocity value of impeller outlet increases at first,then decreases,and then increases again with increase of flow rate.Again average relative velocity values under 0.4,0.8,and 1.2 design condition are higher than that under 1.0 design condition,while under 0.6 and 1.4 design condition it is lower.Under low flow rate conditions,radial vectors of absolute velocities at impeller outlet and blade inlet near the pump shaft decrease with increase of flow rate,while that of relative velocities at the suction side near the pump shaft decreases.Radial vectors of absolute velocities and relative velocities change slightly under the two large flow rate conditions.The research results can be applied to instruct the hydraulic optimization design of double blade pumps.

Use of digital image analysis combined with fractal theory to determine particle morphology and surface texture of quartz sands

The particle morphology and surface texture play a major role in influencing mechanical and hydraulic behaviors of sandy soils. This paper presents the use of digital image analysis combined with fractal theory as a tool to quantify the particle morphology and surface texture of two types of quartz sands widely used in the region of Vitória, Espírito Santo, southeast of Brazil. The two investigated sands are sampled from different locations. The purpose of this paper is to present a simple, straightforward,reliable and reproducible methodology that can identify representative sandy soil texture parameters.The test results of the soil samples of the two sands separated by sieving into six size fractions are presented and discussed. The main advantages of the adopted methodology are its simplicity, reliability of the results, and relatively low cost. The results show that sands from the coastal spit(BS) have a greater degree of roundness and a smoother surface texture than river sands(RS). The values obtained in the test are statistically analyzed, and again it is confirmed that the BS sand has a slightly greater degree of sphericity than that of the RS sand. Moreover, the RS sand with rough surface texture has larger specific surface area values than the similar BS sand, which agree with the obtained roughness fractal dimensions. The consistent experimental results demonstrate that image analysis combined with fractal theory is an accurate and efficient method to quantify the differences in particle morphology and surface texture of quartz sands.

Image Mathematics—Mathematical Intervening Principle Based on “Yin Yang Wu Xing” Theory in Traditional Chinese Mathematics (I)

By using mathematical reasoning, this paper demonstrates the mathematical intervening principle: “Virtual disease is to fill his mother but real disease is to rush down his son” (虚则补其母, 实则泄其子) and “Strong inhibition of the same time, support the weak” (抑强扶弱) based on “Yin Yang Wu Xing” Theory in image mathematics of Traditional Chinese Mathematics (TCMath). We defined generalized relations and generalized reasoning, introduced the concept of steady multilateral systems with two non-compatibility relations, and discussed its energy properties. Later based on the intervention principle in image mathematics of TCMath and treated the research object of the image mathematics as a steady multilateral system, it has been proved that the mathematical intervening principle is true. The kernel of this paper is the existence and reasoning of the non-compatibility relations in steady multilateral systems, and it accords with the oriental thinking model.

Remote Sensing Image Fusion Using Bidimensional Empirical Mode Decomposition and the Least Squares Theory

Due to the data acquired by most optical earth observation satellite such as IKONOS, QuickBird-2 and GF-1 consist of a panchromatic image with high spatial resolution and multiple multispectral images with low spatial resolution. Many image fusion techniques have been developed to produce high resolution multispectral image. Considering panchromatic image and multispectral images contain the same spatial information with different accuracy, using the least square theory could estimate optimal spatial information. Compared with previous spatial details injection mode, this mode is more accurate and robust. In this paper, an image fusion method using Bidimensional Empirical Mode Decomposition (BEMD) and the least square theory is proposed to merge multispectral images and panchromatic image. After multi-spectral images were transformed from RGB space into IHS space, next I component and Panchromatic are decomposed by BEMD, then using the least squares theory to evaluate optimal spatial information and inject spatial information, finally completing fusion through inverse BEMD and inverse intensity-hue-saturation transform. Two data sets are used to evaluate the proposed fusion method, GF-1 images and QuickBird-2 images. The fusion images were evaluated visually and statistically. The evaluation results show the method proposed in this paper achieves the best performance compared with the conventional method.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Novel welding image processing method based on fractal theory

Computer vision has come into used in the fields of welding process control and automation. In order to improve precision and rapidity of welding image processing, a novel method based on fractal theory has been put forward in this paper. Compared with traditional methods, the image is preliminarily processed in the macroscopic regions then thoroughly analyzed in the microscopic regions in the new method. With which, an image is divided up to some regions according to the different fractal characters of image edge, and the fuzzy regions including image edges are detected out, then image edges are identified with Sobel operator and curved by LSM (Lease Square Method). Since the data to be processed have been decreased and the noise of image has been reduced, it has been testified through experiments that edges of weld seam or weld pool could be recognized correctly and quickly.

New Image Recognition Method Based on Rough-Sets and Fuzzy Theory

A new image recognition method based on fuzzy rough sets theory is proposed, and its implementation discussed. The performance of this method as applied to ferrography image recognition is evaluated. It is shown that the new method gives better results than fuzzy or rough sets method when used alone.

Comprehensive Evaluation of Modern Enterprise Image with Theory of Fuzzy Mathematics

The multi layered indexes for modern enterprise images are summarized to overcome the shortness of single layered ones in evaluating modern enterprise images. The relevant multi layered evaluation model and algorithm are proposed. As an example, an electrical appliance enterprise in Qingdao city is evaluated with the proposed model and evaluation indexes to show the reasonability of the proposed indexes.

A NEW UNSUPERVISED CLASSIFICATION ALGORITHM FOR POLARIMETRIC SAR IMAGES BASED ON FUZZY SET THEORY

In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classifica-tion accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by ex-periments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.

Geometry model construction in infrared image theory simulation of buildings

Geometric model construction is the basis of infrared image theory simulation. Taking the construction of the geometric model of one building in Harbin as an example, this paper analyzes the theoretical groundings of simplification and principles of geometric model construction of buildings. It then discusses some particular treatment methods in calculating the radiation transfer coefficient in geometric model construction using the Monte Carlo Method.

Image Perception and Emotional Evaluation of Tourists for Desert Tourism Destinations in Inner Mongolia——Content Analyses Based on Network Travel Notes

Recent years have witnessed the popularity of desert tourism as a fashion tourism product in the 21^(st) century along with the increasing demand for personalized tourism for tourists. The academic community is paying growing attention to desert tourism research, but there is little research on the perception of tourists about the image of desert tourism destinations in Inner Mongolia. With Inner Mongolia as the object of the study, this paper analyzed the image perception and evaluation of tourists for Inner Mongolia desert tourism destinations from three aspects of cognitive image perception, emotional image perception, and overall image perception according to the "cognitive-emotional" model, with the help of relevant network text analysis methods, and proposed some suggestions for the future development of desert tourism destinations in Inner Mongolia from the aspects of increasing desert humanities tourism resources and product development, improving scenic spot management ability, improving tourism service quality, improving tourism infrastructure construction and strengthening environmental protection. It is hoped that this paper can provide a reference for improving the image of Inner Mongolia desert tourism destinations and improving the tourist experience.

Sora时代:重审“形象”(image)问题

海德格尔的“世界图像”是理解形象问题的一个至关重要的哲学起点,而米歇尔和波姆提出的“图像转向”则是讨论这一问题的直接语境。从中涌现出三组核心关系:在真实与虚假的关系方面,关于形象真实性的争论早已有之,形象是通往真实的中介还是阻碍?Sora的出现进一步加速了两种态度——偶像崇拜症和偶像恐惧症的转换和融合。在文字与形象的关系方面,Sora的文生视频特点一方面体现出文字对形象的统治,另一方面也体现出两者的耦合。在技术与主体的关系方面,Sora延续并强化了麦克卢汉和斯蒂格勒意义上的体外器官学,它既是毒药也是解药,在图像行为理论的视野下,Sora可以被视为一种新的技术主体,从而进一步推动形象问题的讨论。

SAR images classification method based on Dempster-Shafer theory and kernel estimate

To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxametric Probability Density Function （PDF） estimate method is introduced, to describe the scene of SAR images. And then under the Maxkov context, both the determinate PDF and the kernel estimate method axe adopted respectively, to form a primary classification. Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification. Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification. Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results. Experimental results on real SAR images illustrate a rather impressive performance.

Application of the Dempster-Shafer Theory to the Classification of Pixels from Aster Satellite Images and Spectral Indices

In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations (rocks, breastplates, regolith, etc.). The proposed approach consists in aggregating information by using the DST. From pretreated Aster satellite images (geo-referencing, geometric correction and resampling at 15 m), new channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI. Then, the DST formalism was modeled and generated under the MATLAB software, an image segmented into six classes including three absolute classes (E,V,M) and three classes of confusion ({E,V}, {M,V}, {E,M}). The control on the land, based on geographic coordinates of pixels of different classes on said image, has made it possible to make a concordant interpretation thereof. Our contribution lies in taking into account imperfections (inaccuracies and uncertainties) related to source information by using mass functions based on a simple support model (two focal elements: the discernment framework and the potential set of belonging of the pixel to be classified) with a normal law for the good management of these.

A Fuzzy Cluster and Retinex Theory-based Variation Model for Inhomogenous Image Segmentation

A variational inhomogeneous image segmentation model based on fuzzy membership functions and Retinex theory is proposed by introducing the fuzzy membership function.The existence of the solution of the proposed model is proved theoretically.A valid algorithm is designed to make numerical solution of the model under the framework of alternating minimization.The last experimental results show that the model can make segmentation of the real image with intensity inhomogeneity effectively.

SVM-based Filter Using Evidence Theory and Neural Network for Image Denosing

This paper presents a novel decision-based fuzzy filter? based on support vector machines and Dempster-Shafer? evidence theory for effective noise suppression and detail preservation. The proposed filter uses an SVM impulse detector to judge whether an input pixel is noisy. Sources of evidence are extracted, and then the fusion of evidence based on the evidence theory provides a feature vector that is used as the input data of the proposed SVM impulse detector. A fuzzy filtering mechanism, where the weights are constructed using a counter-propagation neural network, is employed. Experimental results shows that the proposed filter has better performance in terms of noise suppression and detail preservation.

An Analysis Into Ba Sentences Under Image Schema Theory——A Case Study of Words of Fire——Poems by Jidi Majia

The Ba sentence is unique existence in Chinese. There is no corresponding sentence pattern in English. Thus, the translation of Ba sentences is a challenge for translators. Even with the myriad analyses on the translation of Ba sentences, small quantity of them demonstrates the correctness and the reading effect of the translation by using a specific theory. And the image schema theory reflects the projects between the source domain and the target domain, while in the translation analysis there are schemata in the source language and the target language. So the paper does comparisons of schemata between the source text and the target text of Ba sentences, which are chosen from the English translation of Words of Fire—Poems by Jidi Majia translated by Denis Mair. After the demonstration, the following conclusions are found: First, the schema of the sentence is decided by verbs of the Ba sentences, rather than by the sentence structures;second, the image schema is a feasible tool to check correctness of Ba sentences translation.

The Farther Image of the Hotel Keeper in Cat in the Rain—Analyze with Speech Act Theory

It analyzes the father image of the hotel keeper in Hemingway's short story Cat in the Rain from the perspective of Speech Act Theoy.Firstly,it presents the frame work of Speech Act Theory.According to Austin,there are two types of sentences: performatives and constatives.Yule further presents the action performed by producing an utterance will consist of three related acts: locutionary act,illocutionary act,and perlocutionary act.Then it analyzes respectively the speech act of the husband,the hotel keeper,and the wife.Through the analysis,the daughter image of the wife and the coldness of the husband the reveal and accentuate the father image of the hotel keeper who is considerate to his daughter and gives his daughter selfless love.Furthermore,it unfolds a broader horizon for readers to understand and appreciate the story.

Modeling and Characterization of Vegetation, Aquatic and Mineral Surfaces Using the Theory of Plausible and Paradoxical Reasoning from Satellite Images: Case of the Toumodi-Yamoussoukro-Tiébissou Zone in V Baoulé(Côte d’Ivoire)

In this paper, the theory of plausible and paradoxical reasoning of Dezert- Smarandache (DSmT) is used to take into account the paradoxical charac-ter through the intersections of vegetation, aquatic and mineral surfaces. In order to do this, we developed a classification model of pixels by aggregating information using the DSmT theory based on the PCR5 rule using the ∩NDVI, ∩MNDWI and ∩NDBaI spectral indices obtained from the ASTER satellite images. On the qualitative level, the model produced three simple classes for certain knowledge (E, V, M) and eight composite classes including two union classes characterizing partial ignorance ({E,V}, {M,V}) and six classes of intersection of which three classes of simple intersection (E∩V, M∩V, E∩M) and three classes of composite intersection (E∩{M,V}, M∩{E,V}, V∩{E,M}), which represent paradoxes. This model was validated with an average rate of 93.34% for the well-classified pixels and a compliance rate of the entities in the field of 96.37%. Thus, the model 1 retained provides 84.98% for the simple classes against 15.02% for the composite classes.

A General(k,n)Threshold Secret Image Sharing Construction Based on Matrix Theory

Shamir proposed a classic polynomial-based secret sharing(SS)scheme,which is also widely applied in secret image sharing(SIS).However,the following researchers paid more attention to the development of properties,such as lossless recovery,rather than the principle of Shamir’s polynomial-based SS scheme.In this paper,we introduce matrix theory to analyze Shamir’s polynomial-based scheme as well as propose a general(k,n)threshold SIS construction based on matrix theory.Besides,it is proved that Shamir’s polynomial-based SS scheme is a special case of our construction method.Both experimental results and analyses are given to demonstrate the effectiveness of the proposed construction method.