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For the situation inference in the internet of the things environment, this research suggests a method to utilize relations between various events that compose data stream. Connecting various events in respect of mutual correlation and connectivity of various events can provide good clue for situation inference. To divide and connect various events in respect of mutual correlation and connectivity can be solved with the method to add identification characteristic value or position value, etc. on the event value reported from the sensor and adding them. When giving the identification value, in case of providing estimation on correlation and connectivity between the procedure that divides each event based on identification value and the sensors, efficient situation inference is possible. This research showed that various events from various sensors could be divided each other based on correlation and connectivity on the event and practice situation inference by using this.
Nowadays utilization of big data is a mandatory condition for agriculture. Open data usually published by government is big data that anyone can access, use, or share. Agricultural open data can be a promising source for the agricultural value chain. Therefore, it is important to grasp current state of the agricultural open data. In Korea, Open Data Portal provided 996 datasets in Agriculture livestock and fishery category as of September 30, 2017. These datasets consisted of 808 file data and 188 open APIs. The datasets were labeled as 14 classes which were identified by Global Open Data for Agriculture & Nutrition (GODAN). Official records accounted for 23.5% of the total, whereas Government, agricultural law and regulations, Meteorological data, Elevation data, and Hydrological data were insufficient. Categories of agricultural data that many people access, or use should be reinforced, moreover, classes with few items need to be complemented. Since utilization of agricultural open data would be important, it is necessary to find an activation plan. Systematic evaluation based on characteristics of agriculture should be conducted and it is necessary to identify new items for agricultural open data and to suggest it.
The bone mass is known to be decreased in patients with type 1 diabetes, and this is primarily due to osteoblastic dysfunction. A number of epidemiologic studies have consistently shown a significantly higher risk of fractures in type 1 diabetic patients as compared to that of healthy subjects. The data on bone mineral density (BMD) in patients with type 2 diabetes has been inconsistent. However, many recent epidemiologic studies have shown that the osteoporotic fracture risk, and especially at the hip, is also increased in patients with type 2 diabetes, and even in patients with normal or higher BMD. Meanwhile, several studies have shown higher bone mass and a lower fracture risk in subjects with recent onset type 2 diabetes or impaired glucose tolerance with hyperinsulinemia. Poor bone quality and an increased risk of falling are thought to be important contributing factors for the higher fracture risk in patients with type 2 diabetes. Collagen overglycosylation by accumulation of advanced glycation end products (AGE) is thought to be one of the possible mechanisms underlying poor bone quality. The risk of falling in patients with diabetes is increased due to hypoglycemia, visual impairment from retinopathy and cataracts, altered balance, gait problems due to neuropathy and foot ulcers, associated cardiovascular diseases and medication use. Insulin-sensitizing agents, such as thiazolidinediones, are also associated with a higher fracture risk through an increase in bone marrow adiposity and a decrease in osteoblastogenesis. Because diabetes and osteoporosis are highly prevalent chronic diseases in the aging population and the incidences are increasing worldwide, understanding the risk factors that predispose patients to such conditions is very important. On considering the potential mechanisms associated with bone metabolism, adequate glycemic control while minimizing the episodes of hypoglycemia is the most important first step in the medical management to prevent osteoporotic fractures in patients with diabetes.
Numerical Weather Prediction (NWP) models such as the Weather Research and Forecasting (WRF) model are essential for forecasting one-day-ahead solar irradiance. In order to evaluate the performance of the WRF in forecasting solar irradiance over the Korean Peninsula, we compared WRF prediction data from 2008 to 2010 corresponding to weather observation data (OBS) from the Korean Meteorological Administration (KMA). The WRF model showed poor performance at polluted regions such as Seoul and Suwon where the relative Root Mean Square Error (rRMSE) is over 30%. Predictions by the WRF model alone had a large amount of potential error because of the lack of actual aerosol radiative feedbacks. For the purpose of reducing this error induced by atmospheric particles, i.e., aerosols, the WRF model was coupled with the Community Multiscale Air Quality (CMAQ) model. The coupled system makes it possible to estimate the radiative feedbacks of aerosols on the solar irradiance. As a result, the solar irradiance estimated by the coupled system showed a strong dependence on both the aerosol spatial distributions and the associated optical properties. In the NF (No Feedback) case, which refers to the WRF-only stimulated system without aerosol feedbacks, the GHI was overestimated by 50-200 W m<sup>-2</sup> compared with OBS derived values at each site. In the YF (Yes Feedback) case, in contrast, which refers to the WRF-CMAQ two-way coupled system, the rRMSE was significantly improved by 3.1-3.7% at Suwon and Seoul where the Particulate Matter (PM) concentrations, specifically, those related to the PM<sub>10</sub> size fraction, were over 100 μg m<sup>-3</sup>. Thus, the coupled system showed promise for acquiring more accurate solar irradiance forecasts.
( Dong Hyeok Kim ), ( Seung-eun Song ), ( Se-mi Jeon ), ( Gil-soo Lee ), ( Sung-kyeong Lee ), ( Seong-han Kim ), ( Jae-il Yoo ), ( Dong Hyeok Kim ), ( Jae-ok Kim ) 대한결핵 및 호흡기학회 2017 대한결핵 및 호흡기학회 추계학술대회 초록집 Vol.124 No.-
Rapid, accurate diagnosis of drug resistant-TB is critical for timely initiation of treatment and control of the disease. Since WHO endorsed commercial rapid drug susceptibility test (DST) to identify mutations conferring resistance to the anti-mycobacterial drugs, several discrepant cases between rapid and conventional DST results were reported. Therefore, analysis of the prevalence of mutations associated with drug-resistance is important to understanding the current status of DR-TB as well as treatment. In this study, we established the MIC distribution with 476 clinical isolates from drug resistant risk group, namely retreatment TB patients, and MDR patients in South Korea. And we determined the resistance pattern of the anti-mycobacterial drugs and frequencies of resistance-associated mutations by sequencing analysis with rpoB genes for RIF, katG, inhA, and ahpC genes for INH, gyrA and gyrB genes for moxifloxacin, and rrs for kanamycin. Our results showed that 96% and 89.9% of RIF and INH resistance was associated with rpoB and katG (89.9%), inhA (31%), and/or ahpC (4.4%) gene mutation. And 95.1% of MOX resistance was related with gyrA (63.4%) and gyrB (6.4%) gene mutation and 46% KAN resistance were associated with rrs gene. Among the antibiotics resistance related gene mutations, Ser-531 of rpoB (60.8%), Ser315Thr of KatG (68%), -15 promoter region of inhA (92.1%), and point mutation of 21Glu, 94Asp and 95Ser at gyrA gene were the predominant mutation sites. Our database would help the interpretation of DST results and developing new diagnostic test.
The magnetic properties and mineral composition of black burnished pottery and reddish-brown pottery with soot unearthed from Pungnaptoseong, and restored black burnished pottery were investigated to determine the black coloring mechanism and firing condition. Results indicate that an increase in the amount of magnetic iron oxide (especially Fe₃O₄) by the thermal reduction reaction of hematite influences the development of black color on the surface. Furthermore, for each sample, the black surface was determined to contain the highest amount of magnetic iron oxide, followed by the black to dark gray matrix, and then the brownish matrix. These results suggested that the ancient black burnished pottery was produced by a stronger reduction reaction on the surface, as compared to the matrix during the firing process. Further, the pottery with a black to dark gray matrix was produced through intense and prolonged reduction firing, compared to the pottery with a brownish matrix.