In this article, generalized differential quadrature method (GDQM) is used to study the free vibrational behavior of variable cross section nano beams. Eringen's nonlocal elastic theory is taken into account to model the small scale effects and nonuniformity is assumed by exponentially varying the width of nano beam. Governing equation of motion is solved using generalized differential quadrature method with different numbers of sampling points. Effects of increasing the sampling points in reaching more accurate results for first three frequency parameters are presented and it is shown that after a specific number of sampling points, results merge to a certain accurate number. It is concluded that generalized differential quadrature method is able to reach the correct answers comparing to analytical results. Moreover, due to the stiffness softening behavior of small-scale structures, necessity of using Eringen's nonlocal elastic theory to model the small scale effects due to the frequency variation is observed. |
The size effect on the free vibration and bending of a curved FG micro/nanobeam is studied in this paper. Using the Hamilton principle the differential equations and boundary conditions is derived for a nonlocal Euler-Bernoulli curved micro/nanobeam. The material properties vary through radius direction. Using the Navier approach an analytical solution for simply supported boundary conditions is obtained where the power index law of FGM, the curved micro/nanobeam opening angle, the effect of aspect ratio and nonlocal parameter on natural frequencies and the radial and tangential displacements were analyzed. It is concluded that increasing the curved micro/nanobeam opening angle results in decreasing and increasing the frequencies and displacements, respectively. To validate the natural frequencies of curved nanobeam, when the radius of it approaches to infinity, is compared with a straight FG nanobeam and showed a good agreement.
The Nevado de Toluca Flora and Fauna Protection Area presents a constant fragmentation of its forests. The objective of the research was to identify the processes of forest deterioration and the role of local stakeholders in its conservation. Geographic information systems were used as a basis for the generation of thematic maps, in addition to the application of a flow diagram that defines the problems of the forest and another that describes and analyzes them for the search of solutions. The results show that the main factors affecting deterioration are forest fires, immoderate logging, pests and diseases. Finally, strategies and scenarios for forest management are proposed based on the articulation of local stakeholders.
This paper contributes to a long-standing debate in development practice: under what conditions can externally established participatory groups engage in the collective management of services beyond the life of a project? Using 10 years of panel data on water point functionality from Indonesia’s rural water program, the Program for Community-Based Water Supply and Sanitation, the paper explored the determinants of subnational variation in infrastructure sustainability. It then investigated positive and negative deviance cases to answer why some communities successfully engaged in system management despite being located in difficult conditions as per quantitative findings and vice versa. The findings show that differences in the implementation of community participation, driven by local social relations between frontline service providers, that is, village authorities and water user groups, explain sustainable management. This initial condition of state-society relations influences how the project is initiated, kicking off negative or positive reinforcing pathways, leading to community collective action or exit. The paper concludes that the relationships between frontline government representatives and community actors are important and are an underexamined aspect of the ability of external projects to generate successful community-led management of public goods.
This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.
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