<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>
In this paper, an evolutionary algorithm is presented to develop a solution for the variable radii sensor placement optimization problem. Sensor nodes are placed in a sensor field such that maximum coverage of the target region is achieved. Coverage is defined in terms of monitoring points of interest. In point coverage, it is desired to place the sensor nodes such that certain target points in the area to be monitored are efficiently covered. The sensors are assumed to have varying communication and sensing radii within specified ranges. To attain a certain degree of fault tolerance, the network is required to have k-connectivity. Therein, the challenge lies in finding a solution that provides the optimal choice and arrangement of sensor nodes with a minimized overall energy consumption. Our devised algorithm places the sensors to form an energy-efficient and fault tolerant network that provides coverage of the given query points.
Research Computing and Data (RCD) professionals play a crucial role in supporting and advancing research that involve data and/or computing, however, there is a critical shortage of RCD workforce, and organizations face challenges in recruiting and retaining RCD professional staff. It is not obvious to people outside of RCD how their skills and experience map to the RCD profession, and staff currently in RCD roles lack resources to create a professional development plan. To address these gaps, the CaRCC RCD Career Arcs working group has embarked upon an effort to gain a deeper understanding of the paths that RCD professionals follow across their careers. An important step in that effort is a recent survey the working group conducted of RCD professionals on key factors that influence decisions in the course of their careers. This survey gathered responses from over 200 respondents at institutions across the United States. This paper presents our initial findings and analyses of the data gathered. We describe how various genders, career stages, and types of RCD roles impact the ranking of these factors, and note that while there are differences across these groups, respondents were broadly consistent in their assessment of the importance of these factors. In some cases, the responses clearly distinguish RCD professionals from the broader workforce, and even other Information Technology professionals.
CCS CONCEPTS• Social and professional topics → Computing occupations.
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