<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; layout-grid-mode: char;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">In this paper, we propose a method to simulate soft bodies by using gravitational force, spring and damping forces between surface points, and internal molecular pressure forces. We consider a 3D soft body model composed of mesh points that define the body’s surface such that the points are connected by springs and influenced by internal molecular pressure forces. These pressure forces have been modeled on gaseous molecular interactions. Simulation of soft body with internal pressure forces is known to become unstable when high constants are used and is averted using an implicit integration method. We propose an approximation to this implicit integration method that considerably reduces the number of computations in the algorithm. Our results show that the proposed method realistically simulates soft bodies and improves performance of the implicit integration method.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p>
Sensor networks are mostly deployed in unsecured environments, thus protecting a sensor network from any attack is critical in order to maintain the health of the network. Recently, many researchers have focused on making security for sensor networks available and reliable. In this paper, a secured nodeto-node key agreement protocol is proposed to generate secured communication among principle nodes A and B, a ticket granting server, and a key server.Since a sensor network is usually a resource-constrained infrastructure, it is not suitable for computationally expensive asymmetric key protocols such as public-private key cryptography. Therefore, setting up a shared key in our proposed protocol is based on a symmetric key protocol processed by two trusted agents, which are the ticket granting server and the key server. The data confidentiality, authentication, and freshness of the network security are also considered in the design of the proposed protocol.
In soft body simulation with fluid modeling, smooth particle hydrodynamics (SPH) is one of the most efficient methods to simulate the soft body for real time applications. In this paper, we introduce a general model of soft bodies with SPH fluid modeling as one of the components for interaction among particles. The fluid force in SPH depends on the density of neighboring fluid particles in the kernel of the considered particle. The fluid force is related to fluid attributes such as fluid density, fluid pressure, and fluid viscosity. Computation becomes faster if the neighboring fluid particles are known during the computations of the fluid attributes. In our simulation of soft body model, the kernels of the fluid attributes are identical, and hence we use the same neighboring fluid particles to evaluate the fluid attributes. In this paper we introduce partitioning and hashing schemes to identify the neighboring fluid particles for SPH to compute the fluid force in the soft body simulation. The suitable parameters for the partitioning and hashing schemes are presented for the modeling. Experimental results show that the grid based scheme can reduce time computation in SPH for fluid modeling in real time applications. We also present a result of a soft body in which the model includes all forces.
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