• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.106-106
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• 2015

The information of flow regimes continues to be norm in water resource and watershed management, in that stream flow regime is a crucial factor influencing water quality, geomorphology, and the community structure of stream biota. The objectives of this study were to estimate Korean stream flows from landscape variables, classify stream flow gages using hydraulic characteristics, and then apply these methods to ungaged biological monitoring sites for effective ecological assessment. Here I used a linear modeling approach (MLR, PCA, and PCR) to describe and predict seasonal flow statistics from landscape variables. MLR models were successfully built for a range of exceedance discharges and time frames (annual, January, May, July, and October), and these models explained a high degree of the observed variation with r squares ranging from 0.555 (Q95 in January) to 0.899 (Q05 in July). In validation testing, predicted and observed exceedance discharges were all significantly correlated (p<0.01) and for most models no significant difference was found between predicted and observed values (Paired samples T-test; p>0.05). I classified Korean stream flow regimes with respect to hydraulic and hydrologic regime into four categories: flashier and higher-powered (F-HP), flashier and lower-powered (F-LP), more stable and higher-powered (S-HP), and more stable and lower-powered (S-LP). These four categories of Korean streams were related to with the characteristics of environmental variables, such as catchment size, site slope, stream order, and land use patterns. I then applied the models at 684 ungaged biological sampling sites used in the National Aquatic Ecological Monitoring Program in order to classify them with respect to basic hydrologic characteristics and similarity to the government's array of hydrologic gauging stations. Flashier-lower powered sites appeared to be relatively over-represented and more stable-higher powered sites under-represented in the bioassessment data sets.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.3
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• pp.294-299
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• 2017

The aim of this study was to detect the status of epilepticus and seizure based on the initial patterns observed in the first 30 minutes of continuous electroencephalogram (cEEG) monitoring. An cEEG was recorded digitally using electrodes applied according to the International 10~20 System. The EEG data were reviewed from January 2014 to December 2015. The baselines of the EEG patterns were characterized by lateralized periodic discharges, generalized periodic discharges, burst suppression, focal epileptiform, asymmetric background, generalized slowing, and generalized periodic discharges with a triphagic wave. The etiology was classified into five categories. The subjects of this study were 128 patients (age: $56.9{\pm}17.5years$, male:female, 74:54). The mean cEEG monitoring duration was $5.5{\pm}5.1$ (min:max, 1:33) days. The EEG pattern categories included lateralized periodic discharges (N=7), generalized periodic discharges (N=10), burst suppression (N=6), focal epileptiform (N=19), asymmetric background (N=24), generalized slowing (N=51), and generalized periodic discharges with a triphagic wave (N=11). The etiological classifications of the patients with status epilepticus were remote symptomatic (N=4), remote symptomatic with acute precipitant (N=9), acute symptomatic (N=6), progressive encephalopathy (N=2), and febrile seizure (N=1). cEEG monitoring was found to be useful for the diagnosis of non-convulsive epileptic seizures or status epilepticus. The seizure was confirmed by the EEG pattern.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.2
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• pp.1-12
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• 2013

This study reviews the current conditions of the completed 'Ecosystem Conservation Fund Return Project' sites to suggest management methods for their conservation and sustainability. For the scope of the study, five microsites of completed return projects in Seoul were selected and their project planning documents were reviewed to help with site surveying and analysis. To increase the accuracy of the site surveying and analysis, and to evaluate the management problems from different perspectives, the site managers were interviewed in-depth. The experts were surveyed as well to develop a realistic and practical improvement method. The survey results helped to categorize the post-management problems, and separate improvement methods were suggested for each category. First, the post-management guidelines are proposed for the ecosystem-based environment/ecosystem environment, user management, and monitoring. These guidelines will increase the expertise and practicality of the management principles. Second, the regulations for the participation of expert management enterprises and the development of separate monitoring or maintenance management team are suggested. These regulations will improve the participation of experts and consistency of management systems. Third, the post monitoring or maintenance management during the year after the project completion should be set as a separate project to secure budget. Furthermore, policies and/or institutions should be established to set a portion of ecosystem conservation return fund or a grant for post monitoring and maintenance management. Forth, as a way of adaptive management, at least more than three years of post-management should be evaluated under detailed categories and vigorous standard to improve the institutional operation for 'Ecosystem Conservation Fund Return Projects'.

• Smart Structures and Systems
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• v.17 no.6
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• pp.981-994
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• 2016

Two field research stations based upon atmospheric corrosivity monitoring combined with reinforced concrete corrosion rate sensors have been established in Kuwait. This was established for the purpose of remote monitoring of building materials performance for concrete under Kuwait atmospheric environment. The two field research sites for concrete have been based upon an outcome from a research investigation intended for monitoring the atmospheric corrosivity from weathering station distributed in eight areas, and in different regions in Kuwait. Data on corrosivity measurements are essential for the development of specification of an optimized corrosion resistance system for reinforced concrete manufactured products. This study aims to optimize, characterize, and utilize long-term concrete structural health monitoring through on line corrosion measurement and to determine the feasibility and viability of the integrated anode ladder corrosion sensors embedded in concrete. The atmospheric corrosivity categories supported with GSM remote data acquisition system from eight corrosion monitoring stations at different regions in Kuwait are being classified according to standard ISO 9223. The two nominated field sites where based upon time of wetness and bimetallic corrosion rate from atmospheric data where metals and rebar's concrete are likely to be used. Eight concrete blocks with embeddable anodic ladder corrosion sensors were placed in the atmospheric zone adjacent to the sea shore at KISR site. The anodic ladder corrosion rate sensors for concrete were installed to provide an early warning system on prediction of the corrosion propagation and on developing new insights on the long-term durability performance and repair of concrete structures to lower labor cost. The results show the atmospheric corrosivity data of the environment and the feasibility of data retrieval of the corrosion potential of concrete from the embeddable sets of anodic ladder corrosion sensors.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• Korean Institute of Interior Design Journal
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• v.22 no.2
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• pp.11-19
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• 2013

Korea Government have carried out various policies to save the Earth environment from global warming and environmental pollution. It has also executed the Green Building Certification Criteria(GBCC) in 2002. The GBCC of office building was executed in 2003 and was revised twice in 2010 and 2011. Concerns about green building construction were quite increasing to keep the building performances sustainable. The aims of this paper is to check the reliability of weighting factors and scoring difficulties in all assessment categories of GBCC and to suggest the amendment direction of the future assessment criteria for green building. For the study, the old and new version of GBCC were examined to present the revision direction of GBCC and the 10 cases certificated by the old and new version, respectively 5 were analysed to compare with the difficulties in obtaining the certification. According to the results of the study, the GBCC requires additional amendments about the assessment categories of the energy consumption monitoring and the building commissioning as required subjects in order to secure the building performances. In addition, the operation mamagement of the building need to be assessed more intensively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1793-1798
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• 2007

Recently there are some trends to construct smart home system infrastructure depending upon the development of Information and Communication Technology. Also requirements of the Ubiquitous Healthcare Systems at home which can monitor the status of health continuously are increased rapidly comparing with hospitals. Healthcare service can be divided into two categories. The first one is Alarm Service that can be used for the emergency status and the other one is Remote Support Service which can monitor the patient including home environments and give those diagnosis information to medical office or to his family. Generally wired networks and fixed healthcare measuring system have some limits to transmit reliable realtime based information for both categories described above comparing with portable monitoring system. Getting over the inefficiency we will design and implement portable healthcare system under the wireless Zigbee network environments.

• The Journal of Engineering Geology
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• v.26 no.4
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• pp.473-484
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• 2016

This study aims to establish a monitoring method for managing the effective maintenance of tailings dams. The monitoring of a tailings dump area involves several parameters and their investigation through a selection of evaluation items. The extents of defects and progressive failures also need to be effectively estimated. Therefore, the monitoring items can be subdivided into categories relating to the retaining wall structure (concrete wall, reinforcing stone wall, mesh gabions) and general facilities (liner, covering soil, slope, tailings, rain protection facility, leachate, planting), and quantitative evaluations can then be conducted for each condition. In doing so, we developed a systematic monitoring method that assesses the dam maintenance condition with grades and scores. The field application of the monitoring method results showed it to provide a more detailed evaluation than existing monitoring methods: the method detected an additional 16 defects missed by conventional methods. The evaluation gave scores of 89.3, 22.2, and 27.8 to the Geumjang mine tailings dam, the Gupoong mine tailings dam, and the Hwachun mine tailings dam, respectively. The advanced method can provide quantitative evaluation and perform detailed monitoring of the dams. This quantitative evaluation can be used to decide on maintenance priorities, select the main management items, and establish schedules of maintenance.

• Journal of Korean Critical Care Nursing
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• v.13 no.2
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• pp.24-35
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• 2020

Purpose : This study aimed to determine whether the Korean Patient Classification System for Neonatal Care Nurses (KPCSN) properly measures neonatal intensive care needs and to compare the scale's results with those of the Workload Management System for Critical Care Nurses (WMSCN). Methods : Data were collected from the medical records of 157 patients who were admitted to the NICU of a university hospital, in D city. Two types of patient classification systems were applied to investigate the total points and distributions to investigate the total points and distributions by categories and compare relationships and classification groups between two scales. Finally, the score distribution among the classification groups was analyzed when the KPCSN was applied. Results : Scores on the KPCSN for the feeding, monitoring, and measure categories were 19.16±15.40, 16.88±3.52, and 9.13±4.78, respectively. Classification group distribution of the KPCSN was as follows : 1.9% for the first group, 24.2% for the second group, 58% for the third group, and 15.9% for the fourth group. The classification group distribution of the WMSCN was as follows: 35.7% for the third group, 61.1% for the fourth group, and 3.2% for the fifth group. Finally, the scores by categories were analyzed according to KPCSN classification group, and the characteristics of the patients' nursing needs were identified for each classification group. Conclusion : Results of this study indicate that the KPCSN effectively measures feeding needs, which account for many nursing activities in neonatal intensive care. Comparisons between the KPCSN and WMSCN classification group scores and distribution ratios verified the correlation and significance of nursing requirements.

• Korean journal of food and cookery science
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• v.21 no.5
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• pp.616-628
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• 2005

The purpose of this study was to monitor the current nutrition labeling practice on the packaging of the processed foods providing consumers with reliable nutrition information, which has been considered as a useful aid for food selection and a potent educational tool for nutrition in a daily life. The 2,214 processed foods purchased at the a wholesale market in July, 2003, were divided by food categories issued from the 2003 food codes and assessed in the terms of the nutrition composition labeling and nutrition claims. Nutrition composition labeling was found on 533 out of the 2,214 processed foods items. The findings of this study were as follows : Milk and dairy products had 66.4% of nutrition composition labeling, which was the largest percentage among the food categories. Tables format (71.3%) is the most widely used type of nutrition labeling. The title of nutrition composition labeling used the most widely was nutrition composition (71.3%). Nutrition composition included many different ways of expression, such as a table of nutrition composition, and indication of nutrition composition, etc. The expression unit of the nutrition composition labeling was use per 100g or 100mL (40.5%). The processed foods with nutrition claims were 18.0% (399 items). Nutrition claims were divided into two categories: nutrient content claims and nutrient comparative claims. The most frequently used nutrient content claims were contained (43.9%) and more or plus in the nutrient comparative claims (16.0%). Ca was the most popular item as a nutrition claim nutrient (33.6%).