جستجوی مقالات مرتبط با کلیدواژه « shape » در نشریات گروه « ریاضی »

The particle size distribution provides important information about soil engineering properties. Finer particles are usually determined by classical sedimentation methods such as hydrometer tests. These methods are based on simplifying assumptions and despite operational complexities, the obtained results are not precise. At this time, Image Processing methods were used in dierent industries to obtain various information about size distributions and particle shape analysis. The present research suggests the image processing method based on the analysis of microscopic images of stable particles (static method) for determining the size and shape distribution of the ne-grained fraction of the soil. The images of ne-grained soil particles prepared with optical microscopes were analyzed to generate information about particle size and shape. By comparing gradation curves obtained with image processing and hydrometric methods, we found that there is more adaptation in the range of 40 to 70 microns of particle sizes. Investigations have shown that in this range, the shape of the particles has less diversity and is closer to the perfect sphere form. This study found that image processing while reducing costs, could provide more comprehensive information and would be expected to be used in geotechnical laboratories.

We propose a beta exponential distribution that is formed from the logarithm of a random variable with a beta value, as well as a thorough investigation of the distribution's mathematical characteristics. Because we dealt with the beta exponential distribution, we have a clear and understandable way to comprehend the equation and apply it to the actual problem. To do this, we gathered the questions that statisticians find interesting and studied the most significant properties and statistics related to the distribution. Future research will utilize this data to identify specific industrial flaws or inefficiencies as a function of survival. Included are system statistics, BE distributions for graphs, generation functions, moments, and Hazard functions.

‎In some fields‎, ‎there is an interest in distinguishing different geometrical objects from each other‎. ‎A field of research that studies the objects from a statistical point of view‎, ‎provided they are‎ ‎invariant under translation‎, ‎rotation and scaling effects‎, ‎is known as the statistical shape analysis‎. ‎Having some objects that are registered using key points on the outline of the objects‎, ‎the main purpose‎ ‎of this paper is to compare two popular clustering procedures to cluster objects‎. ‎We also use some indexes‎ ‎to evaluate our clustering application‎. ‎The proposed methods are applied to the real life data.