• Korean Journal of Environment and Ecology
• /
• v.11 no.1
• /
• pp.111-125
• /
• 1997

To investigate the climax forest structure and to construct the ecological basic data, forty nine plots were set up and surveyed in Mt. Minjuji, Chungchongpukdo. According to the analysis of classification by TWINSPAN, the community was divided by seven groups of Pinus densiflora-Carpinus laxiflora-Quercus serrata(community I), Q. mongolica-Q. serrata-Platycarya strobilacea(community II), Q. mongolica(community III), Fraxinus mandshurica-Acer mono(community IV), Cornus controversa-F. mandshurica(community V), F. mandshurica-Carpinus cordata(community VI), and F. mandshurica-C. laxiflora(community VII). In the results of the analysis of species structure, similarity, diversity and DBH, except for community I~III, it was founede out broadleaves-mixed-climax forest. Constructed basic data will be applied to sustainable development such as ecotourism, nature trail etc.

• Research in Community and Public Health Nursing
• /
• v.30 no.4
• /
• pp.528-538
• /
• 2019

Purpose: The purpose of this study was to follow-up the frailty of the old who received home health care by Registered Nurse in Public Health Center over 8 years. Methods: We used the second wave data which was a comprehensive longitudinal data set, Public Health Information System of a public health center located in Seoul from 2010 to 2018. For statistical analysis, a mixed model of repeated measures by R program was used. Results: Frailty (range: 0~31) was getting worse significantly from 5.38 on registration to 6.54 on 4th year, 7.40 on 7th year, 7.69 on 8th year with adjustment for age, sex, economic status, the number of family, and the number diseases. The coefficient of parameters with frailty change was serviced year (β=0.29, p<.001), age (70~79 to 60~69; β=0.98, p=.018) and sex (female to male; β=2.55, p<.001). Conclusion: This study showed that the home visiting health service needs to take attention to aged 70s and over, female. The home health care of public health center need to be extended more practical and effective services in terms of 'community care'and 'ageing in place'.

• Advances in materials Research
• /
• v.11 no.1
• /
• pp.75-90
• /
• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2524-2533
• /
• 2024

When analyzing containment thermal-hydraulics, computational fluid dynamics (CFD) is a powerful tool because multi-dimensional and local analysis is required for some accident scenarios. According to the previous study, neglecting steam bulk condensation in the CFD analysis leads to a significant error in boundary layer profiles. Validating the condensation model requires the experimental data near the condensing surface, however, available boundary layer data is quite limited. It is also important to confirm whether the heat and mass transfer analogy (HMTA) is still valid in the presence of bulk condensation. In this study, the boundary layer measurements on the vertical condensing surface in the presence of air were performed with the rectangular channel facility WINCS, which was designed to measure the velocity, temperature, and concentration boundary layers. We set the laminar flow condition and varied the Richardson number (1.0-23) and the steam volume fraction (0.35-0.57). The experimental results were used to validate CFD analysis and HMTA models. For the former, we implemented a bulk condensation model assuming local thermal equilibrium into the CFD code and confirmed its validity. For the latter, we validated the HMTA-based correlations, confirming that the mixed convection correlation reasonably predicted the sum of wall and bulk condensation rates.

• The Korean Journal of Applied Statistics
• /
• v.31 no.1
• /
• pp.13-28
• /
• 2018

The ministry of Environment of Korea initiated two follow-up surveys in 2005 and 2006 to investigate environmental effect on children's health. These two cohorts, referred to as the 2005 Cohort and 2006 Cohort, were followed up three times every two years. This data set was referred to as the Children's Health and Environmental Research (CHEER) data set. This paper reproduces the existing research results of Kim et al. (Journal of the Korean Data and Information Science Society, 25, 987-998, 2014) and Lee et al. (The Korean Journal of Applied Statistics, 29, 1295-1310, 2016) and derive a benchmark dose lower limit (BMDL) for blood lead level for attention deficit hyperactivity disorder (ADHD) after pooling two cohort data sets. The different ADHD rating scales were unified by applying the conversion formula proposed by Lee et al. (2016). The random effect model and AR(1) model were built to reflect the longitudinal characteristics and regression to the mean phenomenon. Based on these models the BMDLs for blood lead levels were derived using the BMDL formula and the simulation. We obtained a hight level of BMDLs when we pooled two independent cohort data sets.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.225-233
• /
• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

• Journal of Internet Computing and Services
• /
• v.17 no.4
• /
• pp.43-50
• /
• 2016

In this paper, we propose the protocol of Ethernet that will receive a popular interesting in the automotive intelligent network, it also attempts to implementation and verification through simulation and experiments to propose a fault tolerance algorithm when the data transfer on it. It has proven the usefulness of the system in order to apply toward an existing automotive communication system. In the case of actual real-time data for automotive industry, we generated a randomly-generated data which is the set of payload into a standard format to complete the experiment. Among the implemented existing algorithms performance, we confirmed the effectiveness of all range from a single data to mixed (Hybrid-type) data, to verify the proposed algorithm.

• Journal of Korea Foresty Energy
• /
• v.23 no.2
• /
• pp.1-8
• /
• 2004

This study looked into the change of tree growth of seven forest growth monitoring plots which were set up at the Undulyeong Hongchungun Kangwondo, and was accomplished to offer the basic data for the forest administration calculating carbon storage and removal in the Undulyeong area. Annual height and DBH growth were slowly progressed in the Pinus koraiensis and Larix kaempferi stand which was young stand, but the growth rate of the other stands was lower than those young stand. The diameter class of the mixed forest and Qurcus mongilica stand was predicted to be similar to the now and Pinus koraiensis and Larix kaempferi stand was predicted to move now diameter class to the high diameter class because thickening growth speed of the those stands were rapid. Now the end of 2003, total carbon storage of the Undulyeong model forest increased 149,000TC$(2.7\%)$ compared with the previous year. Seeing by forest types, occupied broad-leaved forest$(50\%)$, mixed forest$(34\%)$ and coniferous forest. During in 2003, total carbon which was removed and stored according to growth of the forest was 156,813TC and net carbon removal(148,664TC) increased into 2,613TC$(1.8\%)$ compared with the previous year. Seeing by forest types, occupied coniferous forest$(3.3\%)$, mixed forest$(3.1\%)$, broad-leaved forest$(2.8\%)$. Resultingly, the Undulyeong model forest is acting to net removal resource when see as green-gas side and net carbon removal are showing the tendency to increase recently little by little.

• Journal of KIISE:Information Networking
• /
• v.30 no.1
• /
• pp.24-29
• /
• 2003

In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing schemes, which represents the information from observations as a set of random variables in the from of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other. which can be utilized in linear projection.. However, it has been known that ICA does not establish good performance in source separation by itself. Thus, in order to overcome this limitation, there have been many techniques that are designed to reinforce the good properties of ICA, which improves the mixed image separation. Unfortunately, the innovation process still needs to be studied since it yields inconsistent innovation process that is attached to the ICA, the expectation and maximization process is added. The results presented in this paper show that the proposed improves the image separation as presented in experiments.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.111-111
• /
• 2022

According to data from the Ministry of Environment, food waste accounted for 27% of the nation5 s household waste in 2020, and 4.67 million tons of food waste is being discharged per year. According to the Food Waste Direct Landfill Prohibition Act, food waste must be incinerated, composted, fodder, and decomposed before landfilling. The cost of incineration and landfilling of food waste is considerable. Therefore, through the process of turning food waste into fertilizer, we are going to investigate the limit of crop application and the change in the growth of crops during continuous use of food waste fertilizer. This study investigated the growth of lettuce such as shoot length, root length, leaf number, fresh weight, and dry weight after treating lettuce with food waste dry powder mixed fertilizer. The experiment was carried out continuously in 2021 (1st year) and 2022 (2nd year), and the treatment groups were set to No Treatment (NT), Chemical Fertilizer (CF), Mixed Fertilizer (MF×1), and Mixed Fertilizer×2 (MF×2), was repeated 3 times. As a result of the 1st year growth survey, there was no significant difference between NT and CF in the case of shoot length, but MF×1 and MF×2 were significantly decreased compared to NT. Root length was not significantly different in all treatment groups. As for the leaf number, there was no significant difference between NT and MF×1, but CF and MF×2 were significantly decreased compared to NT. In fresh weight, MF×1 and MF×2 were significantly decreased compared to NT, and in the case of dry weight, there was no significant difference between NT, MF×1, and MF×2. As a result of the 2nd year growth survey, there was a significant difference in CF and MF×2 in leaf number, but there was no significant difference in all treatment groups with respect to shoot length, root length, fresh weight, and dry weight. Through continuous additional research, it is necessary to confirm the change in soil composition and the growth of crops due to food waste fertilizer treatment.