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RFID/USN기반 물류/유통 시스템의 평가를 위한 BSC 프레임워크
박정선 대한안전경영과학회 2014 대한안전경영과학회지 Vol.16 No.4
Many systems using RFID/USN were and are being developed. Some systems are used in practice and some are not. Generally, the main reasons not being used are: The prices of chips are too high considering the effects. The application domain is not appropriate for RFID/USN. So, various skills for higher sensing precision have been introduced like using multiple sensors and avoiding metals which deter sensings seriously. Now, it is time to evaluate systems which were developed using RFID/USN technology. However, no systematic approach has been made for the evaluation. In this paper, a framework using BSC is introduced for the evaluation of systems using RFID/USN. In this framework, some Critical Success Factors(CSF) are derived and some Key Performance Indices(KPI) are developed for each CSF.
유비쿼터스 컴퓨팅을 위한 센서 디바이스 Plug & Play
박정선,은성배,윤현주,Park, Jung-Sun,Eun, SeongBae,Yoon, Hyeon-Ju 대한임베디드공학회 2012 대한임베디드공학회논문지 Vol.7 No.3
When mounting the sensor device in the way of Plug&Play, sensor device drivers need to be loaded and linked dynamically. Since a sensor node platform is based on small 8 bit MCU, dynamic loading and linking technique used in Windows and Linux can not be applied. In this paper, we present how to link and load dynamically sensor device drivers for sensor device Plug&Play. We implement a prototype and evaluate it to make sure that there is no performance degradation like sensor device driver connection speed and memory usage. Connection speed overhead increases to 0.2ms. Memory usage overhead increases to hundreds byte. It shows that there is no heavy influence in running the actual program.
KL 변환을 이용한 multilayer perceptron에 의한 한국어 연속 숫자음 인식
박정선,권장우,권정상,이응혁,홍승홍 대한전자공학회 1996 전자공학회논문지-B Vol.b33 No.8
In this paper, a new korean digita speech recognition technique was proposed using muktolayer perceptron (MLP). In spite of its weakness in dynamic signal recognition, MLP was adapted for this model, cecause korean syllable could give static features. It is so simle in its structure and fast in its computing that MLP was used to the suggested system. MLP's input vectors was transformed using karhunen-loeve transformation (KLT), which compress signal successfully without losin gits separateness, but its physical properties is changed. Because the suggested technique could extract static features while it is not affected from the changes of syllable lengths, it is effectively useful for korean numeric recognition system. Without decreasing classification rates, we can save the time and memory size for computation using KLT. The proposed feature extraction technique extracts same size of features form the tow same parts, front and end of a syllable. This technique makes frames, where features are extracted, using unique size of windows. It could be applied for continuous speech recognition that was not easy for the normal neural network recognition system.