• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.959-974
• /
• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1657-1667
• /
• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Journal of Music and Human Behavior
• /
• v.1 no.1
• /
• pp.1-10
• /
• 2004

Being engaged in the musical tasks needs cognitive skills to perceive musical sound, organize them into meaningful unit, store them in the memory and retrieve them when needed. These skills are also required for academic tasks indicating that there is positive correlation between skills for musical and academic tasks. Based on these findings, the study purported to examine whether the developed sessions can enhance cognitive skills which is composed of auditory information skills, which is composed of perceiving sounds, organizing them into groups based on the existing information or organization pattern, and short-term memory skills. Eighteen elementary students in 4, 5, and 6th grades have participated in the study. The study has administered Music Cognitive Skills Test(MCST) before and after implementing music therapy sessions. The MCST consisted of five parts, first one measuring the rhythm imitating skills, second, measuring the melodic imitation skills, third, measuring discriminative skills in identifying higher pitch, fourth, measuring discriminative skills in identifying identical chords, and lastly, measuring the tone retention skills. The results indicated that there was statistical difference between the pre and post test in rhythm and melody imitation skills. Because reproduction of perceived rhythm patterns requires memory skills, imitating patterns are considered cognitive skills. Also melody is defined adding spatial dimension to the rhythm which is temporal concept. Being able to understand melodic pattern and to reproduce the pattern also requires cognitive skills. The subjects have shown significant improvement in these two areas. In other areas, there were definite increase of scores, however, no significant differences. The study also explores interpretation of these results and also observed consistencies among the participants in completing the musical tasks.

• Research in Plant Disease
• /
• v.8 no.2
• /
• pp.84-91
• /
• 2002

Disease forecasting in Korea was first studied in the Department of Fundamental Research, in the Central Agricultural Technology Institute in Suwon in 1947, where the dispersal of air-borne conidia of blast and brown spot pathogens in rice was examined. Disease forecasting system in Korea is operated based on information obtained from 200 main forecasting plots scattered around country (rice 150, economic crops 50) and 1,403 supplementary observational plots (rice 1,050, others 353) maintained by Korean government. Total number of target crops and diseases in both forecasting plots amount to 30 crops and 104 diseases. Disease development in the forecasting plots is examined by two extension agents specialized in disease forecasting, working in the national Agricul-tural Technology Service Center(ATSC) founded in each city and prefecture. The data obtained by the extension agents are transferred to a central organization, Rural Development Administration (RDA) through an internet-web system for analysis in a nation-wide forecasting program, and forwarded far the Central Forecasting Council consisted of 12 members from administration, university, research institution, meteorology station, and mass media to discuss present situation of disease development and subsequent progress. The council issues a forecasting information message, as a result of analysis, that is announced in public via mass media to 245 agencies including ATSC, who informs to local administration, the related agencies and farmers for implementation of disease control activity. However, in future successful performance of plant disease forecasting system is thought to be securing of excellent extension agents specialized in disease forecasting, elevation of their forecasting ability through continuous trainings, and furnishing of prominent forecasting equipments. Researches in plant disease forecasting in Korea have been concentrated on rice blast, where much information is available, but are substan-tially limited in other diseases. Most of the forecasting researches failed to achieve the continuity of researches on specialized topic, ignoring steady improvement towards practical use. Since disease forecasting loses its value without practicality, more efforts are needed to improve the practicality of the forecasting method in both spatial and temporal aspects. Since significance of disease forecasting is directly related to economic profit, further fore-casting researches should be planned and propelled in relation to fungicide spray scheduling or decision-making of control activities.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.141-154
• /
• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Clinical and Experimental Reproductive Medicine
• /
• v.23 no.3
• /
• pp.247-268
• /
• 1996

It has been known for a long time that gonadotropins and steroid hormones play a pivotal role in a series of reproductive biological phenomena including the maturation of ovarian follicles and oocytes, ovulation and implantation, maintenance of pregnancy and fetal growth & development, parturition and mammary development and lactation. Recent investigations, however, have elucidated that in addition to these classic hormones, multiple growth factors also are involved in these phenomena. Most growth factors in reproductive organs mediate the actions of gonadotropins and steroid hormones or synergize with them in an autocrine/paracrine manner. The insulin-like growth factor(IGF) system, which is one of the most actively investigated areas lately in the reproductive organs, has been found to have important roles in a wide gamut of reproductive phenomena. In the present communication, published literature pertaining to the intrauterine IGF system will be reviewed preceded by general information of the IGF system. The IGF family comprises of IGF-I & IGF-II ligands, two types of IGF receptors and six classes of IGF-binding proteins(IGFBPs) that are known to date. IGF-I and IGF-II peptides, which are structurally homologous to proinsulin, possess the insulin-like activity including the stimulatory effect of glucose and amino acid transport. Besides, IGFs as mitogens stimulate cell division, and also play a role in cellular differentiation and functions in a variety of cell lines. IGFs are expressed mainly in the liver and messenchymal cells, and act on almost all types of tissues in an autocrine/paracrine as well as endocrine mode. There are two types of IGF receptors. Type I IGF receptors, which are tyrosine kinase receptors having high-affinity for IGF-I and IGF-II, mediate almost all the IGF actions that are described above. Type II IGF receptors or IGF-II/mannose-6-phosphate receptors have two distinct binding sites; the IGF-II binding site exhibits a high affinity only for IGF-II. The principal role of the type II IGF receptor is to destroy IGF-II by targeting the ligand to the lysosome. IGFs in biological fluids are mostly bound to IGFBP. IGFBPs, in general, are IGF storage/carrier proteins or modulators of IGF actions; however, as for distinct roles for individual IGFBPs, only limited information is available. IGFBPs inhibit IGF actions under most in vitro situations, seemingly because affinities of IGFBPs for IGFs are greater than those of IGF receptors. How IGF is released from IGFBP to reach IGF receptors is not known; however, various IGFBP protease activities that are present in blood and interstitial fluids are believed to play an important role in the process of IGF release from the IGFBP. According to latest reports, there is evidence that under certain in vitro circumstances, IGFBP-1, -3, -5 have their own biological activities independent of the IGF. This may add another dimension of complexity of the already complicated IGF system. Messenger ribonucleic acids and proteins of the IGF family members are expressed in the uterine tissue and conceptus of the primates, rodents and farm animals to play important roles in growth and development of the uterus and fetus. Expression of the uterine IGF system is regulated by gonadal hormones and local regulatory substances with temporal and spatial specificities. Locally expressed IGFs and IGFBPs act on the uterine tissue in an autocrine/paracrine manner, or are secreted into the uterine lumen to participate in conceptus growth and development. Conceptus also expresses the IGF system beginning from the peri-implantation period. When an IGF family member is expressed in the conceptus, however, is determined by the presence or absence of maternally inherited mRNAs, genetic programming of the conceptus itself and an interaction with the maternal tissue. The site of IGF action also follows temporal (physiological status) and spatial specificities. These facts that expression of the IGF system is temporally and spatially regulated support indirectly a hypothesis that IGFs play a role in conceptus growth and development. Uterine and conceptus-derived IGFs stimulate cell division and differentiation, glucose and amino acid transport, general protein synthesis and the biosynthesis of mammotropic hormones including placental lactogen and prolactin, and also play a role in steroidogenesis. The suggested role for IGFs in conceptus growth and development has been proven by the result of IGF-I, IGF-II or IGF receptor gene disruption(targeting) of murine embryos by the homologous recombination technique. Mice carrying a null mutation for IGF-I and/or IGF-II or type I IGF receptor undergo delayed prenatal and postnatal growth and development with 30-60% normal weights at birth. Moreover, mice lacking the type I IGF receptor or IGF-I plus IGF-II die soon after birth. Intrauterine IGFBPs generally are believed to sequester IGF ligands within the uterus or to play a role of negative regulators of IGF actions by inhibiting IGF binding to cognate receptors. However, when it is taken into account that IGFBP-1 is expressed and secreted in primate uteri in amounts assessedly far exceeding those of local IGFs and that IGFBP-1 is one of the major secretory proteins of the primate decidua, the possibility that this IGFBP may have its own biological activity independent of IGF cannot be excluded. Evidently, elucidating the exact role of each IGFBP is an essential step into understanding the whole IGF system. As such, further research in this area is awaited with a lot of anticipation and attention.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.4
• /
• pp.81-99
• /
• 2015

The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

• Progress in Medical Physics
• /
• v.14 no.1
• /
• pp.34-42
• /
• 2003

In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

• Atmosphere
• /
• v.12 no.4
• /
• pp.20-42
• /
• 2002

Based on the "Mid to Long Term Plan for Space Development", a project to launch COMeS (Communication, Oceanography, and Meteorological Satellite) into the geostationary orbit is undergoing. Accordingly, KMA (Korea Meteorological Administration) has defined the meteorological missions and prepared the user requirements to fulfill the missions. To make a realistic user requirements, we prepared a first draft based on the ideal meteorological products derivable from a geostationary platform and sent the RFI (request for information) to the sensor manufacturers. Based on the responses to the RFI and other considerations, we revised the user requirement to be a realistic plan for the 2008 launch of the satellite. This manuscript introduces the revised user requirements briefly. The major mission defined in the revised user requirement is the augmentation of the detection and prediction ability of the severe weather phenomena, especially around the Korean Peninsula. The required payload is an enhanced Imager, which includes the major observation channels of the current geostationary sounder. To derive the required meteorological products from the Imager, at least 12 channels are required with the optimum of 16 channels. The minimum 12 channels are 6 wavelength bands used for current geostationary satellite, and additional channels in two visible bands, a near infrared band, two water vapor bands and one ozone absorption band. From these enhanced channel observation, we are going to derive and utilize the information of water vapor, stability index, wind field, and analysis of special weather phenomena such as the yellow sand event in addition to the standard derived products from the current geostationary Imager data. For a better temporal coverage, the Imager is required to acquire the full disk data within 15 minutes and to have the rapid scan mode for the limited area coverage. The required thresholds of spatial resolutions are 1 km and 2 km for visible and infrared channels, respectively, while the target resolutions are 0.5 km and 1 km.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.5 no.2
• /
• pp.1-15
• /
• 2002

Atmospheric aerosols interact with sunlight and affect the global radiation balance that can cause climate change through direct and indirect radiative forcing. Because of the spatial and temporal uncertainty of aerosols in atmosphere, aerosol characteristics are not considered through GCMs (General Circulation Model). Therefor it is important physical and optical characteristics should be evaluated to assess climate change and radiative effect by atmospheric aerosols. In this study GMS-5 satellite data and surface measurement data were analyzed using a radiative transfer model for the Yellow Sand event of April 7~8, 2000 in order to investigate the atmospheric radiative effects of Yellow Sand aerosols, MODTRAN3 simulation results enable to inform the relation between satellite channel albedo and aerosol optical thickness(AOT). From this relation AOT was retreived from GMS-5 visible channel. The variance observations of satellite images enable remote sensing of the Yellow Sand particles. Back trajectory analysis was performed to track the air mass from the Gobi desert passing through Korean peninsular with high AOT value measured by ground based measurement. The comparison GMS-5 AOT to ground measured RSR aerosol optical depth(AOD) show that for Yellow Sand aerosols, the albedo measured over ocean surfaces can be used to obtain the aerosol optical thickness using appropriate aerosol model within an error of about 10%. In addition, LIDAR network measurements and backward trajectory model showed characteristics and appearance of Yellow Sand during Yellow Sand events. These data will be good supporting for monitoring of Yellow Sand aerosols.