• Journal of Korean Society on Water Environment
• /
• v.27 no.4
• /
• pp.533-541
• /
• 2011

Algal blooms have caused problems for drinking water as well as eutrophication. However it is difficult to control algal blooms by current warning manual in rainy season because the algal blooms happen in a few days. The water quality data, which have high correlations with Chlorophyll-a on Daecheongho station, were analyzed and chosen as input data of Artificial Neural Networks (ANN) for training pattern changes. ANN was applied to early forecasting of algal blooms, and ANN was assessed by forecasting errors. Water temperature, pH and Dissolved oxygen were important factors in the cross correlation analysis. Some water quality items like Total phosphorus and Total nitrogen showed similar pattern to the Chlorophyll-a changes with time lag. ANN model (No. 3), which was calibrated by water temperature, pH and DO data, showed lowest error. The combination of 1 day, 3 days, 7 days forecasting makes outputs more stable. When automatic monitoring data were used for algal bloom forecasting in Daecheong reservoir, ANN model must be trained by just input data which have high correlation with Chlorophyll-a concentration. Modular type model, which is combined with the output of each model, can be effectively used for stable forecasting.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.230-235
• /
• 1992

We propose a method of generating data to train a neural network controller. The data can be prepared directly by an iterative learning technique which repeatedly adjusts the control input to improve the tracking quality of the desired trajectory. Instead of storing control input data in memory as in iterative learning control, the neural network stores the mapping between the control input and the desired output. We apply this concept to the trajectory control of a two link robot manipulator with a feedforward neural network controller and a feedback linear controller. Simulation results show good generalization of the neural network controller.

• Clinical and Experimental Reproductive Medicine
• /
• v.18 no.1
• /
• pp.49-53
• /
• 1991

The development of 2-cell mouse embryos to the blastocyst stage in vitro has been used as a quality control for the media empolyed for human in vitro fertilization. There was a comparison between the quality control data of the culture medium as ascertained by 2-cell mouse embryos development and sperm motility and the data from fertilization and cleavage of human oocytes. However, there was no obvious association between fertilization and cleavage of human oocytes and the quality of the medium ascertained by mouse embryo development and sperm motility.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2004.11a
• /
• pp.65-71
• /
• 2004

The Development of GPS practical using and systematic fixing for GPS Quality Control System on On-Line. Developed the program that can prove GPS quality about GPS permanent observation stations or user GPS data in server client system environment of Web-Based objectively Developed Save-module of graph display of analysis result data and reporter form. Developed the program for making an estimate of GPS satellite information in server client system environment of Web-Based. Designed that the Display can be possible and store estimate result can expresses the form such as Sky Plot, DOPs, Satellite Elevation, satellite number cf predict-time and then the result can be preserved for report form.

• The Korean Journal of Applied Statistics
• /
• v.25 no.6
• /
• pp.977-985
• /
• 2012

Data quality and climate forecasting performance deteriorates because of long climate data contaminated by non-climatic factors such as the station relocation or new instrument replacement. For a trusted climate forecast, it is necessary to implement data quality control and test inhomogeneous data. Before the inhomogeneity test, a reference series was created by $d$ index to measure the temperature series relationship between the candidate and surrounding stations. In this study, a inhomogeneity test to each season and climatological station was performed on the daily mean temperatures, daily minimum temperatures and daily maximum temperatures. After comparing two inhomogeneity tests, the traditional and the adjusted SNHT method, we found the adjusted SNHT method was slightly superior to the traditional one.

• Ocean and Polar Research
• /
• v.43 no.4
• /
• pp.321-334
• /
• 2021

'Marine mammals-based observations' refers to data acquisition activities from marine mammals by instrumenting CTD (Conductivity-Temperature-Depth) sensors on them for recording vertical profiles of ocean variables such as temperature and salinity during animal diving. It is a novel data collecting platform that significantly improves our abilities in observing extreme environments such as the Southern Ocean with low cost compared to the other conventional methods. Furthermore, the system continues to create valuable information until sensors are detached, expanding data coverage in both space and time. Owing to these practical advantages, the marine mammals-based observations become popular to investigate ocean circulation changes in the Southern Ocean. Although these merits may bring us more opportunities to understand ocean changes, the data should be carefully qualified before we interpret it incorporating shipboard/autonomous vehicles/moored CTD data. In particular, we need to pay more attention to salinity correction due to the usage of an unpumped-CTD sensor tagged on marine mammals. In this article, we introduce quality control methods for the marine mammals-based CTD profiles that have been developed in recent studies. In addition, we discuss strategies of quality control specifically for the seal-tagging CTD profiles, successfully having been obtained near Terra Nova Bay, Ross Sea, Antarctica since February 2021. It is the Korea Polar Research Institute's research initiative of animal-borne instruments monitoring in the region. We anticipate that this initiative would facilitate collaborative efforts among Polar physical oceanographers and even marine mammal behavior researchers to understand better rapid changes in marine environments in the warming world.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.5
• /
• pp.2519-2525
• /
• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• Journal of the Korean earth science society
• /
• v.41 no.4
• /
• pp.323-343
• /
• 2020

Observation data measured at Ieodo Ocean Research Station (IORS) have been utilized in oceanographic and atmospheric studies since 2003. Sea level data observed at the IORS have not been paid attention as compared with many other variables such as aerosol, radiation, turbulent flux, wind, wave, fog, temperature, and salinity. Total sea level rises at the IORS (5.6 mm yr^-1) from both satellite and tide-gauge observations were higher than those in the northeast Asian marginal seas (5.4 mm yr^-1) and the world (4.6 mm yr^-1) from satellite observation from 2009 to 2018. The rates of thermosteric, halosteric, and steric sea level rises were 2.7-4.8, -0.7-2.6, 2.3-7.4 mm yr^-1 from four different calculating methods using observations. The rising rate of the steric sea level was higher than that of the total sea level in the case with additional data quality control. Calculating the non-steric sea level was not found to yield meaningful results, despite the ability to calculate non-steric sea level by simply subtracting the steric sea level from total sea level. This uncertainty did not arise from the data analysis but from a lack of good data, even though tide, temperature, and salinity data were quality controlled two times by Korea Hydrographic and Oceanography Agency. The status of the IORS data suggests that the maintenance management of observation systems, equipment, and data quality control should be improved to facilitate data use from the IORS.

• Journal of Environmental Impact Assessment
• /
• v.18 no.2
• /
• pp.59-67
• /
• 2009

Water quality of the Lake Youngrang in the Sokcho City is eutrophic. Jangcheon is the largest inflow source to the lake. Major pollutant sources are stormwater runoff from resort areas and various land uses in the Jangcheon watershed. A storm sewer on the southern end of the lake is also an important pollution source. In this study, water quality modelling for Lake Youngrang was carried out considering the rainfall-runoff pollution loads from the watershed. The rainfall-runoff curves and the rainfall-runoff pollutant load curves were derived from the rainfall-runoff survey data during the recent 4 years. The rainfall-runoff pollution loads and flow from the Jangcheon watershed and the storm sewer were estimated using the two kinds of curves, and they were used as the flow and the boundary data of the WASP model. With the measured water quality data of the year 2005 and 2006, WASP model was calibrated. Non-point pollution control measures such as wet pond and infiltration trench were considered as the alternative for water quality management of the lake. The predicted water quality were compared with those under the present condition, and the improvement effect of the lake water quality were analyzed.

• The Journal of Bigdata
• /
• v.2 no.2
• /
• pp.87-93
• /
• 2017

The research on data quality has been performed for a long time. However, the research focused on structured data. With the recent digital revolution or the fourth industrial revolution, quality control of big data is becoming more important. In this paper, we analyze and classify big data quality types through previous research. The types of big data quality can be classified into value, data structure, process, value chain, and maturity model. Based on these comparative studies, this paper proposes a new standard, service quality of big data.