Due to pandemic spreads of COVID-19 and increasing populations of seniors, exercises or performance practices at home have become important to maintain healthy lives around the world. World Health Organization (WHO) has announced the physical health determines the Quality of Life (QoL) of a human. Unfortunately, a lot of people have no exercise and may be in unhealthy conditions. In this paper, we propose an Exercise and Performance Learning Assistant System (EPLAS) to assist people practicing exercises or learning performances by themselves at home. EPLAS adopts inexpensive devices and free software for low-cost implementation. It offers a video content of model actions by an instructor to be followed by the user, where the reaction is rated by comparing the feature points of the human bodies extracted by an open-source software OpenPose. For evaluations, we conduct experiments of applying EPLAS with five Yoga poses to 41 persons in Indonesia, Japan, and Taiwan, and confirm the effectiveness of the proposal.
Currently, the User-PC computingsystem (UPC) has been studied as a low-cost and high-performance distributed computing platform. It uses idling resources of personal computers (PCs) in a group.The job-worker assignment for minimizing makespan is critical to determine the performance of the UPC system.Some applications need to execute a lot of uniform jobs that use the identical program but with slightly different data, where they take the similar CPU time on a PC. Then, the total CPU time of a worker is almost linear to the number of assigned jobs. In this paper, we propose a static assignment algorithm of uniform jobs to workers in the UPC system, using simultaneous linear equations to find the lower bound on makespan, where every worker requires the same CPU time to complete the assigned jobs. For the evaluations of the proposal, we consider the uniform jobs in three applications. In OpenPose, the CNN-based keypoint estimation program runs with various images of human bodies. In OpenFOAM, the physics simulation program runs with various parameter sets. In code testing, two open-source programs run with various source codes from students for the Android programming learning assistance system (APLAS). Using the proposal, we assigned the jobs to six workers in the testbed UPC system and measured the CPU time. The results show that makespan was reduced by 10% on average, which confirms the effectiveness of the proposal.
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