In this study, GaN powders were synthesized from gallium oxide-hydroxide (GaOOH) through an ammonification process in an NH3 flow with the variation of B2O3 additives within a temperature range of 300-1050˚C. The additive effect of B2O3 on the hexagonal phase GaN powder synthesis route was examined by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Fourier transformation infrared transmission (FTIR) spectroscopy. With increasing the mol% of B2O3 additive in the GaOOH precursor powder, the transition temperature and the activation energy for GaN powder formation increased while the GaN synthesis limit-time (tc) shortened. The XPS results showed that Boron compounds of B2O3 and BN coexisted in the synthesized GaN powders. From the FTIR spectra, we were able to confirm that the GaN powder consisted of an amorphous or cubic phase B2O3 due to bond formation between B and O and the amorphous phase BN due to B-N bonds. The GaN powder synthesized from GaOOH and B2O3 mixed powder by an ammonification route through β-Ga2O3 intermediate state. During the ammonification process, boron compounds of B2O3 and BN coated β-Ga2O3 and GaN particles limited further nitridation processes.

The purpose of this study is to investigate the crystalline structure and optical properties of (GaZn)(NO) powders prepared by solid-state reaction between GaOOH and ZnO mixture under NH3 gas flow. While ammoniation of the GaOOH and ZnO mixture successfully produces the single phase of (GaZn)(NO) solid solution within a GaOOH rich composition of under 50 mol% of ZnO content, this process also produces a powder with coexisting (GaZn)(NO) and ZnO in a ZnO rich composition over 50 mol%. The GaOOH in the starting material was phase-transformed to α-, β-Ga2O3 in the NH3 environment; it was then reacted with ZnO to produce ZnGa2O4. Finally, the exchange reaction between nitrogen and oxygen atoms at the ZnGa2O4 powder surface forms a (GaZn)(NO) solid solution. Photoluminescence spectra from the (GaZn)(NO) solid solution consisted of oxygen-related red-emission bands and yellow-, green- and blue-emission bands from the Zn acceptor energy levels in the energy bandgap of the (GaZn)(NO) solid solutions.

This study was conducted to investigate on bone density and nutrient intake of university students in Seoul area. Nutrient intake data were obtained by using the 24-hour recall method to evaluate the usual diet of the subjects. BQI(bone quality index) of the subjects was measured by an Quantitative Ultrasound (QUS). The results are summarized as follows: The average height, weight, BMI of the male and female student were 173.3 cm, 68.5 kg, 22.7; 161.4 cm, 54.2 kg, 20.8, respectively. The BQI and Z-score of the subjects were 99.50, -0.69 in male student group, and 82.6, -1.15 in female student group, respectively. Normal, osteopenia and osteoporosis percentage by bone status were 73.8%, 24.9%, 1.3% in male student group, and 39.8%, 57.6%, 2.6% in female student group, respectively. Energy intake of male and female group were 71.7%, 79.1% of EER(estimated energy requirement) respectively. Fiber, Ca, Vit B2, niacin, folic acid, Vit C intake were less than RI(recommended intake) and protein, phosphorus intake were higher than RI in subjects. Nutrient intake were not significantly related with BQI in male and female groups generally.

목적：본 연구의 목적은 새로 개발된 척수손상-기능실현평가지수(SCI-ARMI)를 만성 척수손상환자들에게 적용하여 척수손상-기능실현평가지수 추정식을 산출하고, 추정식의 추정력에 대한 신뢰도와 타당도를 알아보는 데 있다. 연구방법：본 연구는 S병원에서 2006년 1월에서 동년 6월 사이에 입원치료를 받은 손상 후 6개월 이상 경과한 ASIA A-C인 만성 척수손상환자 66명을 선정하여 입·퇴원 시 ASIA 근력점수와 SCIMⅡ를 이용하여 신경학적 상태와 기능적 상태를 평가하여 회귀분석으로 통계 처리하였다. 결과：ASIA 근력점수가 SCIMⅡ 점수에 통계적으로 유의한 영향을 미쳤다. ASIA 근력점수로 각각의 손상레벨별 SCIMⅡ 최고 점수를 예측하는 회귀식을 이용하여 척수손상-기능실현평가지수를 쉽게 계산할 수 있는 추정식을 구하였다. 추정식에 의해 구한 기능실현평가지수 값과 기능실현평가지수 정의에 의해 구한 기능실현평가지수 값 사이에 높은 상관관계(r=.723, p<.05)를 보였다. ASIA 근력점수, 나이, 손상원인, 재활기간, 손상레벨과 기능실현 평가지수 값 사이에는 유의한 상관관계가 없었다. 결론：ASIA 척도 A-C인 경우의 만성 척수손상환자들에게서 구한 척수손상-기능실현평가지수 추정식은 신뢰도와 타당도가 높았으며, 이 추정식을 이용하여 만성 척수손상환자의 기능변화 및 재활치료효과를 객관적으로 측정하는데 효과적임을 알 수 있었다. 또한 SCIMⅡ 평가 점수의 결과 해석을 위해 개개인의 SCIMⅡ 점수를 손상레벨별로 비교할 수 있는 기준 자료가 될 수 있음을 알 수 있었다.

This study was conducted to investigate factors affecting gone density of university students in Seoul area. Data for food habits, exercise and health-related behaviors were obtained by self administered questionnaires. BQI(bone quality index) of the subjects was measured by an Quantitative Ultrasound(QUS). The results are summarized as follows: The average hight, weight BMI and osteopenia percentage of the male and female student were 173.3cm, 68.6kg, 22.7 and 24.2%; 161.4cm, 54.4kg, 20.9 and 55.5%, respectively. The BQI and Z-score of the subjects were 99.6, -0.3 in male student group, and 82.7, -1.1 in female student group, respectively. Height, weight, fat weight, fat mass and BMI were positively related with BQI in female group. BQI was positively affected by breakfast and frequence exercise in male student group. In female student group, frequency exercise was positively related with BQI. The result of this study revealed that the desirable food habits, dietary behaviors and health-related lifestyles may have a beneficial effect on bone density. They should have practically and systematically organized nutritional education on optimum body weight, good eating habits, weight bearing exercise for higher bone density level.

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.