• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• The Journal of Engineering Geology
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• v.24 no.4
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• pp.525-534
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• 2014

Environmental problems typically occurring in abandoned mine lands (AML) include: contaminated and acidic surface water and groundwater; stockpiled waste rock and mill tailings; and ground subsidences due to mining operations. This study examines the effectiveness of various geophysical techniques for mapping potential hazard and contaminated zones. Four AML sites with sedimentation contamination problems, acid mine drainage (AMD) channels, ground subsidence, manmade liner leakage, and buried mine tailings, were selected to examine the applicability of various geophysical methods to the identification of the different types of mine hazards. Geophysical results were correlated to borehole data (core samples, well logs, tomographic profiles, etc.) and water sample data (pH, electrical conductivity (EC), and heavy metal contents). Zones of low electrical resistivity (ER) corresponded to areas contaminated by heavy metals, especially contamination by Cu, Pb, and Zn. The main pathways of AMD leachate were successfully mapped using ER methods (low anomaly peaks), self-potential (SP) curves (negative peaks), and ground penetrating radar (GPR) at shallow penetration depths. Mine cavities were well located based on composite interpretations of ER, seismic tomography, and well-log records; mine cavity locations were also observed in drill core data and using borehole image processing systems (BIPS). Damaged zones in buried manmade liners (used to block descending leachate) were precisely detected by ER mapping, and buried rock waste and tailings piles were characterized by low-velocity zones in seismic refraction data and high-resistivity zones in the ER data.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.313-324
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• 2017

A lava tube is one of the hot issues of lunar science because it is regarded as a good candidate place for setting a lunar base. Recently much effort has been made to find lunar lava tubes. However, preceding works mainly made use of high-resolution lunar surface image data in conjunction with geomorphological consideration to present some lava tube candidates. Yet, those candidates stay no more than indirect indications. We propose a new data analysis technique of High Frequency (HF) radar observation data to find lunar lava tubes of which location depth is smaller than the range resolution of the radar pulse. Such shallow target echoes cannot be resolved from surface echoes, which presents the different location of the lunar surface compared to that of real lunar surface. The proposed technique instead finds the surface range (distance from LRS to the reflector of the most intense signal) anomaly which occurs as a result of the low range resolution of LRS pulse. We applied this technique to the surface range of Kaguya Lunar Radar Sounder (LRS) data. The surface range was deduced to make LRS surface elevation which was compared with the average surface elevation of Kaguya Digital Terrain Model (DTM). An anomalous discrepancy of the surface elevation was found in the Rima Galilaei area, which suggests the existence of a shallow lava tube.

• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.489-499
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• 2018

A series of geological events such as the formation of the Antarctic continental ice sheets, the changes in ocean circulation and a mass extinction after the onset of Oligocene has been studied as major concerns by various researches. However, paleoclimatic and paleoceanographic changes during the most period of Oligocene since the Eocene-Oligocene transition (EOT) still remains unclear. Especially, although the late Oligocene warming (LOW) has been assessed as the largest period in the paleoceanographic changes, the detailed understanding on the changed components is very low. The purpose of this study is the reconstruction of the paleoceanographic history during the late Oligocene using core sediments from IODP Expedition 342 Site U1406 performed in J-Anomaly Ridge in North Atlantic. Because North Atlantic deep water (NADW) has flowed southward through the study area since the early Oligocene, this area has been considered to an important location for studies on the changes of NADW. The core sediment analyzed in this study were deposited from about 26.0 to 26.5 Ma as evidenced by both of onboard and shore-based paleomagnetic data, and this is corresponded to the earliest period of LOW. The sediment profile can be divided into three Units (Unit 1, 2 & 3) based on the changes in both of total number and test size of Oridorsalis umbonatus as well as grain size data of clastic sediments. Unit 2 represents largest values in these three data. Because the total number, test size of O. umbonatus and grain size can be proxy records on the oxygen concentration and circulation intensity of deep water, we interpreted that Unit 2 had been deposited during the period of relatively strengthened NADW. Previous Cibicidoides spp. stable isotope results from the low latitude region of the North Atlantic also support our interpretation that is the intensified formation of NADW during the identical period. In conclusion, our results present a new evidence for the previous ideas that the causes on LOW are directly related to the changes in NADW.

• Ocean and Polar Research
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• v.26 no.2
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• pp.199-205
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• 2004

$SiO_2$ and CaO are added to decrease the smelting temperature in the reduction-smelting method for manganese nodule processing. These elements are components of the manganese nodules and might be very important controlling factors in the processing due to the locally variable content. The 707 chemical data of manganese nodules acquired from 1994 to 2001 in KODOS(Korea Deep Ocean Survey) area were used for the hierarchical cluster analysis. The chemical data were classified by the morphological types, and the averages of the chemical data for each station were classified by the facies groups and the localities. All data are plotted on the $SiO_2-CaO-MnO$ phase diagram at $1773^{\circ}K$ to compare with the best compositional area in the nodule smelting. Variations and distributions of $SiO_2$ and CaO in KODOS nodules were also reviewed. The mineral phases assigned by the cluster analysis are CFA(Carbonate Fluorapatite), Fe-oxide, Al-silicate, and Mn-oxide. MnO contents are generally higher than $SiO_2$ contents in most of the morphological types except for the Is- and It-type. The Dt- and Tt-type show wider range and the E-types show high anomaly in their CaO contents. The stations which belong to facies group A and B show generally higher MnO contents than $SiO_2$ contents, however, the stations of facies group C and D show wide range in their MnO and $SiO_2$ contents. It seems to be very important to control the $SiO_2$ contents in the processing because of the wide range in the northern area. The additions of approximately 10 wt.% CaO and 10 wt.% $SiO_2$ are recommended for the northern area, whereas, the additions of approximately 10 wt.% CaO and 20 wt.% $SiO_2$ are recommended for the southern area.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.134-153
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• 2008

The main purpose of the research is to illustrate the value of the spatial statistical approach to residential differentiation by providing a framework for exploratory spatial data analysis (ESDA) using a local spatial separation measure. ESDA aims, by utilizing a variety of statistical and cartographic visualization techniques, at seeking to detect patterns, to formulate hypotheses, and to assess statistical models for spatial data. The research is driven by a realization that ESDA based on local statistics has a great potential for substantive research. The main results are as follows. First, a local spatial separation measure is correspondingly derived from its global counterpart. Second, a set of significance testing methods based on both total and conditional randomization assumptions is provided for the local measure. Third, two mapping techniques, a 'spatial separation scatterplot map' and a 'spatial separation anomaly map', are devised for ESDA utilizing the local measure and the related significance tests. Fourth, a case study of residential differentiation between the highly educated and the least educated in major Korean metropolitan cities shows that the proposed ESDA techniques are beneficial in identifying bivariate spatial clusters and spatial outliers.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.235-258
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• 2011

The purpose of this study is to investigate climatological variations from the temporal and spatial surface particulate organic carbon (POC) estimates based on SeaWiFS spectral radiance, and to determine the physical mechanisms that affect the distribution of pac in the Gulf of Mexico. 7-year monthly mean values of surface pac concentration (Sept. 1997 - Dec. 2004) were estimated from Maximum Normalized Difference Carbon Index (MNDCI) algorithm using SeaWiFS data. Synchronous 7-year monthly mean values of remote sensing data (sea surface temperature (SST), sea surface wind (SSW), sea surface height anomaly (SSHA), precipitation rate (PR)) and recorded river discharge data were used to determine physical forcing factors. The spatial pattern of POC was related to one or more factors such as river runoff, wind-derived current, and stratification of the water column, the energetic Loop Current/Eddies, and buoyancy forcing. The observed seasonal change in the POC plume's response to wind speed in the western delta region resulted from seasonal changes in the upper ocean stratification. During late spring and summer, the low-density river water is heated rapidly at the surface by incoming solar radiation. This lowers the density of the fresh-water plume and increases the near-surface stratification of the water column. In the absence of significant wind forcing, the plume undergoes buoyant spreading and the sediment is maintained at the surface by the shallow pycnocline. However, when the wind speed increases substantially, wind-wave action increases vertical motion, reducing stratification, and the sediment were mixed downward rather than spreading laterally. Maximum particle concentrations over the outer shelf and the upper slope during lower runoff seasons were related to the Loop Current/eddies and buoyancy forcing. Inter-annual differences of POC concentration were related to ENSO cycles. During the El Nino events (1997-1998 and 2002-2004), the higher pac concentrations existed and were related to high runoffs in the eastern Gulf of Mexico, but the opposite conditions in the western Gulf of Mexico. During La Nina conditions (1999-2001), low Poe concentration was related to normal or low river discharge, and low PM/nutrient waters in the eastern Gulf of Mexico, but the opposite conditions in the western Gulf of Mexico.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.85-92
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• 2008

National Oceanographic Research Institute is carrying out an oceanographic survey for the entire sea areas around Korean Peninsula annually starting with the East Sea from 1996 by establishing a national oceanographic basic map survey plan for the sea areas under the jurisdiction of Korea, so this paper used the oceanographic geomagnetism data measured at the southern area of the Yellow Sea using 'Hae Yang 2000' in 1999, aiming at clarifying the cause of geomagnetic abnormality zone during the course of treating and analyzing the geomagnetic data. For treatment of magnetic data, we obtained electromagnetic force values and geomagnetic abnormality values around the investigated sea area through a process of searching and removal of bad data, correction of sensor positions, correction of magnetic field effects around the hull, correction of diurnal variation, normal correction, correction of cross point errors, etc. The electromagnetic force distribution around the investigated sea area was $49000\;{\sim}\;51600\;nT$, which is judged to be within the normal electromagnetic force intensity distribution range around the Yellow Sea. The isodynamic lines are distributed in Northeast-Southwest direction, and electromagnetic force values are increasing toward the northwest. The result of comparing the magnetic abnormality around the sea area among $124^{\circ}$ 49' 48" E, $35^{\circ}$ 10' 48" N $\sim$ $125^{\circ}$ 7' 48" E, and $35^{\circ}$ 33' 00" N sections with the elastic wave cross section and the result of modeling coincide well with the underground geological structure clarified from the existing elastic wave survey cross section. Therefore, it is judged that the distribution of magnetic force abnormality generally shows the effect pursuant to the distribution of the sedimentary basins in the Tertiary period and the bedrocks in the Cretaceous period which are well developed in the bottom of the sea.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.