Conventional video coding methods have been developed based on the human visual system (HVS). However, in recent years, video has occupied a huge portion of internet traffic, and the mount of video data for machine consumption has increased rapidly due to the progress of neural networks. This paper proposes a novel machine-attention-based video coding method for machines. Inspired by the saliency-driven research, we first extract attention regions, sensitively affecting the machine vision performance, from the object detection network. Subsequently, a maximum a posterior (MAP)-based bit allocation method is applied to assign more bits to the attention regions. Our proposed method helps to maintain high machine vision performance whereas reducing the bitrate. Experimental results show that our proposed method achieves up to 34.89% bjøntegaard delta (BD)-rate reduction for the video dataset and up to 44.70% BD-rate reduction for the image dataset compared to state-of-the-art video coding technology.

Solid state pulsed power modulator (SSPPM) with fast switching speed and short pulse width is proposed in this paper. In the proposed SSPPM, semiconductor switches which have relatively low voltage rating and fast switching characteristic than those of mechanical switches are used as their main switches for generating pulse output voltage. Furthermore, it can generate high voltage output pulse beyond the voltage rating of the semiconductor switch by stacking the semiconductor switches in series based on power cell structure. Moreover, a new gate driving circuit has been applied to generate high-speed short pulse, and it can supply isolated power and synchronized gate signal to the series stacked switches. Therefore, the proposed SSPPM can generate high-speed/high-voltage pulse output, and it is possible to control pulse width from very short pulse (tens of ns) to a few microseconds for wide applications. The feasibility of the proposed pulse generator is verified by simulation results with pulse rising/falling time under 30ns and minimum pulse width of 50ns and by experiment results of the resonant converter with 10kV, 1kW rated DC (Direct Current) operation.

Describes the implementation of an Internet-based personal robot with direct Internet control architecture which is insensitive to the inherent Internet time delay. The personal robot can be controlled by using a simulator provided at a local site. However, a large Internet time delay may make some control inputs distorted. Moreover, since it is affected by the number of the Internet nodes and loads, this delay is variable and unpredictable. The proposed control architecture guarantees that the personal robot can reduce the path error and the time difference between a virtual robot at the local site and a real robot at the remote site. Simulations and experimental results in the real Internet environment demonstrate the effectiveness and applicability of the Internet-based personal robot with the proposed Internet control architecture.