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Korea Multi-Purpose Satellite-3A (KOMPSAT-3A), the first Korean satellite with optical and infrared sensor, was launched by a Dnepr on 26 March 2015 at Yasny, Russia. Once it was separated from the launch vehicle at 528km mean altitude, autonomous initial operation was activated for solar array deployment, gyro selection, safe-hold mode heater control and thruster-based sun pointing attitude control. Since the first contact by a ground station, the initial activation and checkout was started. For stable early operation using at least one contact per an orbit, several ground stations including KARI station, Sejong station and some abroad stations were utilized. The overall satellite characteristics were demonstrated by first imaging operation results on second day after launch. The initial activation and checkout was performed for 1 week which is relatively short period than that of previous KOMPSAT series. For example, the bus IAC was finished in 3 days which was took 6 days for KOMPSAT-3. Based on successful early operation experience of KOMPSAT-3 and KOMPSAT-5, the IAC procedures could be simplified and absolute timed commands (ATCs) which can be activated during non-contact period by commanding during contact were utilized. The checkout result done by ATC was verified by analyzing playback file. Although the procedures were quickly performed, the satellite was operated safely by prepared contingency operation for every possible unwanted situation. About thirty ready procedures were prepared for various satellite situations which can be occurred during early operation. Eight contingency action sheets were prepared for possible failures during early operation. Furthermore, because the early operation members had been trained by six LEOP rehearsals, any unwanted situation could be controlled immediately. In this paper, the early operation results of KOMPSAT-3A were described. Especially, specific explanation for the bus initial activation and checkout results might give an example of safe and efficient early operation methodology. The described technical details would be reference for the future KOMPSAT mission operation or other similar missions.

As an emerging human-computer interaction (HCI) technology, recognition of human hand gesture is considered a very powerful means for human intention reading. To construct a system with a reliable and robust hand gesture recognition algorithm, it is necessary to resolve several major difficulties of hand gesture recognition, such as inter-person variation, intra-person variation, and false positive error caused by meaningless hand gestures. This paper proposes a learning algorithm and also a classification technique, based on multivariate fuzzy decision tree (MFDT). Efficient control of a fuzzified decision boundary in the MFDT leads to reduction of intra-person variation, while proper selection of a user dependent (UD) recognition model contributes to minimization of inter-person variation. The proposed method is tested first by using two benchmark data sets in UCI Machine Learning Repository and then by a hand gesture data set obtained from 10 people for 15 days. The experimental results show a discernibly enhanced classification performance as well as user adaptation capability of the proposed algorithm.