This study has suggested an image analysis system based on the Deep Learning for CCTV pedestrian detection and tracing improvement and did experiments for objective verification by designing study model and evaluation model. The study suggestion is that if someone’s face did not be recognized in crime scene CCTV footage, the same pedestrian would be traced and found in other image data from other CCTV by using Color Intensity Classification method for clothes colors as body features and body fragmentation technique into 7 parts (2 arms, 2 legs, 1 body, 1 head, and 1 total). If one of other CCTV footage has recorded its face, the identity of the person would be secured. It is not only detection but also search from stored bulk storage to prevent accidents or cope with them in advance by cost reduction of manpower and a fast response. Therefore, CIC7P(Color Intensity Classification 7 Part Base Model) had been suggested by learning device such as Machine Learning or Deep Learning to improve accuracy and speed for pedestrian detection and tracing. In addition, the study has proved that it is an advanced technique in the area of pedestrian detection through experimental proof.

미강 추출 상업용 유통 감마오리자놀의 콜레스테롤 자동산화에 의한 C-7 산화 콜레스테롤 유도체 생성 저해 효과가 수용성 모델 시스템을 이용하여 검토되었다. C-7 콜레스테롤 산화 유도체 (C-7 oxidized cholesterol derivatives: C-7 OCDs) 생성을 위해 콜레스테롤과 감마오리자놀이 분산된 수용성 모델시스템은 구리이온을 촉매로 pH 5.5와 80ºC의 가혹 조건에서 20시간 동안 반응되었다. 산화 유도 기간에 따른 C-7콜레스테롤 산화 유도체 (7-ketocholesterol, 7α-hydroxy-cholesterol 과 7b-hydroxycholesterol)의 생성 정도와 감마오리자놀 및 콜레스테롤 변화 추이 정도가 핵산과 에틸아세테이트를 이용한 용매 추출법과 고속액체크로마토그래프 (high-performance liquid chromatography) 테크닉을 이용 정량적으로 분석되었다. 분석 결과 콜레스테롤 산화 유도 기간에 따른7-ketocholesterol 생성비율은 7-hydroxycholesterol 이성체 (α-형:β-형) 대비 약 2:1의 비율로 생성되었으며, 7-hydroxycholesterol 이성체에 있어서는 α-형 대비 β-형의 생성 정도가 약 1:2의 비율로 나타났고, 총 C-7 산화콜레스테롤의 생성은 상대적인 고농도(300 ppm) 감마오리자놀 처리 모델 시스템에서 효과적으로 저해되었다.

We describe a method for the in-orbit calibration of body-mounted magnetometers based on the CHAOS-7 geomagnetic field model. The code is designed to find the true calibration parameters autonomously by using only the onboard magnetometer data and the corresponding CHAOS outputs. As the model output and satellite data have different coordinate systems, they are first transformed to a Star Tracker Coordinate (STC). Then, non-linear optimization processes are run to minimize the differences between the CHAOS-7 model and satellite data in the STC. The process finally searches out a suite of calibration parameters that can maximize the model-data agreement. These parameters include the instrument gain, offset, axis orthogonality, and Euler rotation matrices between the magnetometer frame and the STC. To validate the performance of the Python code, we first produce pseudo satellite data by convoluting CHAOS-7 model outputs with a prescribed set of the ‘true’ calibration parameters. Then, we let the code autonomously undistort the pseudo satellite data through optimization processes, which ultimately track down the initially prescribed calibration parameters. The reconstructed parameters are in good agreement with the prescribed (true) ones, which demonstrates that the code can be used for actual instrument data calibration. This study is performed using Python 3.8.5, NumPy 1.19.2, SciPy 1.6, AstroPy 4.2, SpacePy 0.2.1, and ChaosmagPy 0.5 including the CHAOS-7.6 geomagnetic field model. This code will be utilized for processing NextSat-1 and Small scale magNetospheric and Ionospheric Plasma Experiment (SNIPE) data in the future.

Inflammation is the first response of the immune system to infection or irritation in our body. The use of medicinal plants has been widely applied as an alternative source for drug development. One of marine natural resources, the anti-inflammatory effect of Ishige sinicola ethanol extract (ISEE), was evaluated by using LPS-induced RAW 264.7 cell and mice model. As a result, the production of nitric oxide (NO) and pro-inflammatory cytokines (IL-6, IL-1β, TNF-α) were inhibited with increasing concentration of ISEE without any cytotoxicity. Furthermore, ISEE suppressed the expression of not only inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), nuclear factor-kappa B (NF-κB) p65, and mitogen-activated protein kinases (MAPKs), including extracellular signal-regulated kinase (ERK) 1/2, p38, and c-Jun N-terminal kinase (JNK) in a dose-dependent manner. In mice ear edema test, the formation of edema was reduced at the highest dosage of ISEE and the reduction of the number of infiltrated mast cells was observed in histological analysis. These results indicate that ISEE has a potent anti-inflammatory activity and can be used as a pharmaceutical material for many kinds of inflammatory disease.

This study intends to provide the necessary basic data needed for predicting the water quality and examining changes in water quality on the basis of the hydrological changes: an outflow or the character of a flow by investigating the interaction of the parameters through the estimation of optimal parameters need for predicting the water quality of the dam basin and the sensitivity among those estimated parameters. Im-Ha Dam in the upstream area of the Nakdong River was selected for analysis, and the water quality survey data necessary for parameter estimation was based on the monthly water quality data (water temperature, BOD, T-N and T-P) between December 1, 2005~November 31, 2006. K1C(the saturated growth rate of plant plankton), K1RC (endogenous respiratory quotient of plankton), KDC(deoxidized ratio), K71C(minealized ratio of dissolved organic phosphorus), K83C(mineralized ratio of dissolved organic nitrogen) have been considered as the factors of the water quality performed in this water quality simulation, that is, the most effective parameters on BOD, T-N and T-P. In the result of the analysis of the sensitivity, KDC(deoxidized ratio) was the most sensitively reacted parameter on BOD and it was K71C(mineralized ratio of dissolved organic phosphorus) and K83C(mineralized ratio of dissolved organic nitrogen) on T-N and T-P. It is considered that it will be possible to apply the most optimal parameter to an analysis of the water quality simulation at Im-Ha Ho basin in the goal year by examining the interaction of the parameters through the parameters sampling which are able to applicable to prediction of the water quality and the analysis of the its sensitivity, in the future, also the analysis on the basis of the hydrological conditions: an outflow or the character of a flow will be needed.