In this paper, a higher order continuum model is presented based on the Cosserat continuum theory in 3D numerical simulation of shear band LOCALIZATION. As the classical continuum models suffer from the pathological mesh-dependence in strain softening models, the governing equations are regularized by adding the rotational degrees-of-freedom to conventional degrees-of-freedom. The fundamental relations in three-dimensional Cosserat continuum are presented and the internal length parameters are introduced in the elasto-plastic constitutive matrix to control the shear bandwidth. Finally, the efficiency of proposed model and computational algorithm is demonstrated by a 3D strip in tensile. A comparison is performed between the classical and Cosserat theories and the effect of internal length parameter is demonstrated. Clearly, a finite shear bandwidth is achieved and the load-displacement curves are uniformly converged upon different mesh sizes.

Free-form surfaces are usually described using the relationships of parametric surfaces such as Bezier, BSpline and NURBS. The computer-aided design systems use NURBS to describe complex (complicated) geometries. Free-form surfaces known as complex (complicated) surfaces are widely used in a variety of industries such as ship-building and molding, inspection of these surfaces is therefore of high importance (very important). Considering that measured free-form surfaces and design models are located in two different coordinate systems, finding the similarity of free-form surfaces and placing them in an identical coordinates system is necessary to compare these surfaces, this process is called LOCALIZATION. This paper introduces a feature and curvature based method for the automatic LOCALIZATION and comparison of free-form surfaces for inspection with coordinate measuring machine (CMM). This method localizes the measurement surface to the design model through two steps. The first step is general LOCALIZATION which is accomplished based on the relation and similarity between curvatures of free-form surfaces and zoning these surfaces to concave, convex and saddle areas. The second step is fine LOCALIZATION based on genetic algorithm which considers correspondence in the form of point to point. The simulation results show that the LOCALIZATION accuracy of the proposed method for the 50 × 50 mm aluminum workpiece of was about 0. 02 mm, which is 56 percent less than the value obtained from the iterative closest point method.

Abstract; in this paper, shear LOCALIZATION due to strain softening in sidepressed cylinders, is inverstigated. Shear LOCALIZATION causes formation of macroscopic shear bands, which can be obsserved in the metallographic cross-section. In this paper, for the first time a method is presented in which a simple two-slice model is used to study the formation of shears bands. The results obtained form this model are in perfect agreement with the results obtatained form experimental works force-a#+B# and B#` micrcrostructures in Ti-6242Si alloy.

Background: Endoscopic sinus surgery because of its close relation with vital elements and complicated anatomy of the region, is a dangerous procedure. Initial cadaveric study and attention to identical anatomic landmarks in the continuity with the visual endoscopic experience will pave the way in prevention of surgical complications.Materials and Methods: Forty Nasal fossae in twenty cadavers were dissected endoscopically. After fronto-ethmoidectomy, the distance between the anterior ethmoidal artery at the base of the skull and two identical anatomic landmarks was measured with colis.Results: The anterior ethmoidal artery was always present. The mean distance between the artery and the anterior turbinate axilla was 19.6mm on the right side and 19.98 mm on the left side. The anterior ethmoidial edge artery the middle turbinate axilla, and the superomedial edge of the nostril were in a straight line.Conclusion: In comparison between our results and the results of Chinese study (Lee etal). The distance measurement between the anterior ethmoidal artery and the anterior turbinate axilla is similar (20 mm) and should be more useful in the clinical setup.

Cadmium selenide nanoparticle films were deposited on usual glass substrate by chemical bath deposition method.Temperature dependence of dc conductivity of the present samples was studied. In the nanocrystalline materials due to small size of grains and confined charge carriers, the electronic states near the Fermi level are localized.When states are localized, the conduction occurs by hopping of carriers between the occupied and unoccupied localized states. Variable range hopping was identified as a predominant conduction mechanism and occurs above room temperature. The density of localized states near the Fermi level was observed to increase with increase of average grain size in the film.

Large image databases are used as training datain visual artificial intelligence applications and deep learning algorithms. Tasvirnet image network is a hierarchical image database in accordance with Iranian and Islamic culture that provides about 8 million images for over 30, 000 words. Synset hierarchy of Tasvirnet is based on hierarchy of ImageNet anditssynsets are translated to Persian using automatic translation. There are 7890745 images in Tasvirnet (for 32295 Persian Synsets) which are collected using auromatic downloading of image links provided by ImageNet. Moreover, 71873 images for up to 1000 synsets related to Iranian and Islamic Culture are prepared using crowdsourcing method and they are added to Tasvirnet. The purpose of this paper is transferring of experiences, production challenges, and developed tools to create a hierarchical image database called Tasvirnet, as well as an outline of the crowdsourcing process used to provide the extraimages for Iranian and Islamic Culture. based synsets.

LOCALIZATION with differential received signal strength measurement in recent years has been very much considered. Due to the fact that the probability density function is known for given observations, the maximum likelihood estimator is used. This estimator can be asymptotically represented the optimal estimation of the location. After the formation of this estimator, it is observed that the corresponding cost function is highly nonlinear and non-convex and has a lot of minima, so there is no possibility of achieving the global minimum with Newton method and the LOCALIZATION error will be high. There is no analytical solution for this cost function. To overcome this problem, two methods are existed. First, the cost function is approximated by a linear estimator. But this estimator has poor accuracy. The second method is to replace the non-convex cost function with a convex one with the aid of convex optimization methods, in which case the global minimum is obtained. In this paper, we proposed new convex estimator to solve cost function of maximum likelihood estimator. The results of the simulations show that the proposed estimator has up to 20 percent performance improvement compared with existing estimators, moreover, the execution time of proposed estimator is 30 percent faster than other convex estimators.