Visual interactive image clustering:a target-independent approach for configuration optimization in machine vision measurement

Machine vision measurement(MVM)is an essential approach that measures the area or length of a target efficiently and non-destructively for product quality control.The result of MVM is determined by its configuration,especially the lighting scheme design in image acquisition and the algorithmic parameter optimization in image processing.In a traditional workflow,engineers constantly adjust and verify the configuration for an acceptable result,which is time-consuming and significantly depends on expertise.To address these challenges,we propose a target-independent approach,visual interactive image clustering,which facilitates configuration optimization by grouping images into different clusters to suggest lighting schemes with common parameters.Our approach has four steps:data preparation,data sampling,data processing,and visual analysis with our visualization system.During preparation,engineers design several candidate lighting schemes to acquire images and develop an algorithm to process images.Our approach samples engineer-defined parameters for each image and obtains results by executing the algorithm.The core of data processing is the explainable measurement of the relationships among images using the algorithmic parameters.Based on the image relationships,we develop VMExplorer,a visual analytics system that assists engineers in grouping images into clusters and exploring parameters.Finally,engineers can determine an appropriate lighting scheme with robust parameter combinations.To demonstrate the effiectiveness and usability of our approach,we conduct a case study with engineers and obtain feedback from expert interviews.

Forming different planetary systems

With the increasing number of detected exoplanet samples, the statistical properties of planetary systems have become much clearer. In this review, we sum- marize the major statistical results that have been revealed mainly by radial velocity and transiting observations, and try to interpret them within the scope of the classical core-accretion scenario of planet formation, especially in the formation of different orbital architectures for planetary systems around main sequence stars. Based on the different possible formation routes for different planet systems, we tentatively classify them into three major catalogs： hot Jupiter systems, standard systems and distant giant planet systems. The standard systems can be further categorized into three sub-types under different circumstances： solar-like systems, hot Super-Earth systems, and sub- giant planet systems. We also review the theory of planet detection and formation in binary systems as well as planets in star clusters.

THE GEOMETRY AND ORBITAL INTERACTION OF TRIATOMIC CLUSTERS FOR Cu,Ag,Au(Ⅱ)

In the previous paper,the geometry of the triatomic clusters for Cu, Ag,and An was obtained using the Dy-Xa method. In this investigation the atomic. orbital interactions of atom Cu, Ag, An in the triatomic clusters are analyzed. The magnitudes of the atomic orbital interactions of the atoms in the clusters are measured by the splitting of corresponding atomic orbital. The calculation results show the atomic orbital interactions of Cu triatomic cluster differ greatly from those of Ag and Au triatomic cluster house of the mixture radio of 4s-Orbital with 3d-Orbital in the Cu cluster more than those in the Ag and Au cluster. The values of atomic orbital interactions of Au in the of cluster are larger than corresponding atomic Orbital interactions of Ag in the cluster.

THE GEOMETRY AND ORBITAL INTERACTIONS OF TRIATOMIC CLUSTERS OF Cu, Ag(I)

In this paper, the total energies and the density of the states of triatomic systems of Cu. Ag. and An were calculated by discret-variational Xa method. Furthermore, the optimized geometry of triatomic copper,silver, and gold clusters were obtained. The results showed that the optimaaed geometry of Cu3 was different from that of Ag3. and An3. Cu3 cluster has two nearlydegenerate candidates for the ground state. Ag3 and Au3 clusters have bent isosceles triangular structure only. The ground configuration for the triatomic clusters is and the ground state is 2B2. The present evidences arc in agreement results with the experimental and with those by other complex theoretical method.

The Long-term Survival Chances of Young Massive Star Clusters

We review the long-term survival chances of young massive star clusters （YMCs）, hallmarks of intense starburst episodes often associated with Violent galaxy interactions. We address the key question as to whether at least some of these YMCs can be considered protoglobular clusters （GCs）, in which case these would be expected to evolve into counterparts of the ubiquitous old GCs believed to be among the oldest galactic building blocks. In the absence of significant external perturbations, the key factor determining a cluster＇s long-term survival chances is the shape of its stellar initial mass function （IMF）. It is, however, not straightforward to assess the IMF shape in unresolved extragalactic YMCs. We discuss in detail the promise of using high-resolution spectroscopy to make progress towards this goal, as well as the numerous pitfalls associated with this approach. We also discuss the latest progress in worldwide efforts to better understand the evolution of entire cluster systems, the disruption processes they are affected by, and whether we can use recently gained insights to determine the nature of at least some of the YMCs observed in extragalactic starbursts as proto-GCs. We conclude that there is an increasing body of evidence that GC formation appears to be continuing until today; their long-term evolution crucially depends on their environmental conditions, however.

About One Discrete Mathematical Model of Perfect Fluid

In work, it is constructed a discrete mathematical model of motion of a perfect fluid. The fluid is represented as an ensemble of identical so-called liquid particles, which are in the form of extended geometrical objects: circles and spheres for two-dimensional and three-dimensional cases, respectively. The mechanism of interaction between the liquid particles on a binary level and on the level of the n-cluster is formulated. This mechanism has previously been found by the author as part of the mathematical modeling of turbulent fluid motion. In the turbulence model was derived and investigated the potential interaction of pairs of liquid particles, which contained a singularity of the branch point. Exactly, this is possible to build in this article discrete stochastic-deterministic model of an ideal fluid. The results of computational experiment to simulate various kinds of flows in two-dimensional and three-dimensional ensembles of liquid particles are presented. Modeling was carried out in the areas of quadratic or cubic form. On boundary of a region satisfies the condition of elastic reflection liquid particles. The flows with spontaneous separation of particles in a region, various kinds of eddy streams, with the quite unexpected statistical properties of an ensemble of particles characteristic for the Fermi-Pasta-Ulam effect were found. We build and study the flow in which the velocity of the particles is calibrated. It was possible using the appropriate flows of liquid particles of the ensemble to demonstrate the possibility to reproduce any prescribed image by manipulating the parameters of the interaction. Calculations of the flows were performed with using MATLAB software package according to the algorithms presented in this article.

Fast Community Detection Based on Distance Dynamics

The distance dynamics model is excellent tool for uncovering the community structure of a complex network. However, one issue that must be addressed by this model is its very long computation time in large-scale networks. To identify the community structure of a large-scale network with high speed and high quality, in this paper, we propose a fast community detection algorithm, the F-Attractor, which is based on the distance dynamics model. The main contributions of the F-Attractor are as follows. First, we propose the use of two prejudgment rules from two different perspectives： node and edge. Based on these two rules, we develop a strategy of internal edge prejudgment for predicting the internal edges of the network. Internal edge prejudgment can reduce the number of edges and their neighbors that participate in the distance dynamics model. Second, we introduce a triangle distance to further enhance the speed of the interaction process in the distance dynamics model. This triangle distance uses two known distances to measure a third distance without any extra computation. We combine the above techniques to improve the distance dynamics model and then describe the community detection process of the F-Attractor. The results of an extensive series of experiments demonstrate that the F-Attractor offers high-speed community detection and high partition quality.