• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.7 no.1
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• pp.20-31
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• 2002

This study was carried out to investigate the composition and the distribution of the benthic polychaetous communities in Deugryang Bay, semi-enclosed bays, on the southern coast of Korea and to deduce temporal changes in community with the comparison of the past studies. In Deugryang Bay, benthic polychaetous community structure was investigated on the base of the samples from 98 stations in 1996 and 1997. The main facies of surface sediment was clayey silt. The overall benthic macrofaunal density was 871 ind./m$^{2}$. The density was highest in the middle part of the bay because Musculus senhousia (Bivalvia) and cumaceans (Crustacea) had their highest densities in some stations. Benthic polychaetes were comprised of 100 species with a mean density of 138 ind./m$^{2}$. Their abundances were higher in the inner bay, in the middle bay, and in the mouth of bay, but poor community structures were established in the whole bay. The dominant species over 1.0 percentage were composed of the total 21 species, and they occupied 78.3% of the total abundance of the benthic polychaetes. The most dominant species was Lumbrineris longifolia (9.3%), followed by Eteone longa (7.3%), Heteromastus filifomis (7.1%), Sternaspis scutata (6.1%). From the cluster analysis, the study area could be divided into three station groups. Station group AI was located in the inner bay and in the shallow coastal region, and its most dominant species was Heteromastus filiformis. At the station group AII in the mouth of bay and in some channel region, its most dominant species were Lumbrineris longifolia and Eteone longa. And at the station group B located in middle part of the bay, the most dominant specis was Sternaspis scutata. In comparison with previous studies, the benthic polychaetous community experienced great change in the view of species number, density and dominant species. The dominant species were Sternaspis scutata and Eteone longa, but their densities declined greatly. Instead of these species, Lumbrineris longifolia and Heteromastus filiformis, known as the potential organic enrichment indicator species, appeared to the new dominant species even if their low densities. These facts mean that Deugryang Bay was maintained yet as little organic enriched area compared to other bays on the coast of Korea, but needed some caution of marine environmental management.

• 한국해양학회지
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• v.24 no.3
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• pp.157-164
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• 1989

Quantitative species distribution and primary productivity of phytoplankton were studied monthly from August, 1987 to July, 1988 along with the quantitative distribution of total heterotrophic bacterioplankton and three groups of physiologically chracteristic bacterioplankton in the intertidal and subtidal waters off Kum River Estuary, Yellow Sea. A total of 121 phytoplankton taxa including 102 diatoms occurred, and cell concentration ranged from 15 to 5451 (cells/ml). The great spatio-temporal variations of the number of phytoplankton species and cell concentration well reflected the environmental differences between the intertidal and subtidal waters. Primary productivity (in Piopt, mgC/$m^3$/hr) ranged from 0.6 to 27.3. Just after the phytoplankton bloom (March) Piopt was very low in April at station 1, where amylolytic bacterioplankton also showed quite low population density. The peaks of primary productivity were not always coincided with those of phytoplankton standing crop. The ratio of Piopt's between samples well indicated the environmental differences between the intertidal and subtidal waters. Little characteristic trend was found in the scatter diagrams of phytoplankton standing crop along the population densities of total heterotrophic bacterioplankton and the three groups of physiologically characteristic bacterioplankton. In summer the phytoplankton standing crop was minimum in contrast with the high population density of bacterioplankton, which implies the influx of much allochthonous orgainc matter from Kum River. The scatter diagrams of Piopt along bacterioplankton population density revealed some phenomena there. Piopt had highly positive correlation with the population density of amylolytie bacterioplankton($R^2$=0.84) and that of lipolytic bacterioplankton($R^2$=0.70) while total heterotrophic bacterioplankton and proteolytic bacterioplankton had lesser correlations with Piopt. From the regression lines the increase of unit Piopt (mgC/$m^3$/hr) in the study area was calculated to mean the increase of $9.0{\times}10$ cells/ml and $8.0{\times}10$ cells/ml of amylolytic bacterioplankton and lipolytic bacterioplankton, respectively.

• Land and Housing Review
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• v.12 no.3
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• pp.11-26
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• 2021

With the increasing demand for office space, there have been questions on how office rent distribution produces a change in the urban spatial structure in Seoul. The purpose of this paper is to investigate a relative price gradient and to present a time-series model that can quantitatively explain the dynamic changes in the urban spatial structure. The analysis was dealt with office rent above 3,306 m² for the past 10 years from 1Q 2010 to 4Q 2019 within Seoul. A modified repeat sales model was employed. The main findings are briefly summarized as follows. First, according to the estimates of the office price gradient in the three major urban centers of Seoul, the CBD remained at a certain level with little change, while those in the GBD and the YBD continued to increase. This result reveals that the urban form of Seoul has shifted from monocentric to polycentric. This shows that the spatial distribution of companies has gradually accelerated decentralized concentration implying that the business networks have become significant. Second, contrary to small and medium-sized office buildings that have undertaken no change in the gradient, large office buildings have seen an increase in the gradient. The relative price gradients in small and medium-sized buildings were inversely proportional among the CBD, the GBD, and the YBD, implying their heterogeneous submarkets by office rent movements. Presumably, those differences in the submarkets were attributed to investment attraction, industrial competition, and the credit and preference of tenants. The findings are consistent with the hierarchical system identified in the Seoul 2030 Plan as well as the literature about Seoul's urban form. This research claims that the proposed method, based on the modified repeat sales model, is useful in understanding temporal dynamic changes. Moreover, the findings can provide implications for urban growth strategies under rapidly changing market conditions.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.4
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• pp.409-421
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• 2022

Achieving a highly resolved spatial distribution of Mn-bearing minerals and elements in the natural ferromanganese nodules can provide detailed knowledge of the temporal variations of geochemical conditions affecting the formation processes of nodules. While a recent study utilizing Raman spectroscopy has reported the changes in the manganate mineral phases with growth for spherical nodules from the Arctic Sea, the distributions of minerals and elements in the nodules from the shallow Arctic Sea with non-spherical forms have not yet fully elucidated. Here, we reported the micro-laser Raman spectra with varying data acquisition points along three different profiles from the center to the outermost rim of the non-spherical ferromanganese nodules collected from the East Siberian Sea (~73 m). The elemental distributions in the nodule (such as Mn, Fe, etc.) were also investigated by energy dispersive X-ray spectroscopy (EDS) analysis to observe the internal structure and mineralogical details. Based on the microscopic observation, the internal structures of a non-spherical nodule can be divided into three different regions, which are sediment-rich core, iron-rich substrate, and Mn-Fe layers. The Raman results show that the Mn-bearing mineral phases vary with the data acquisition points in the Mn-Fe layer, suggesting the changes in the geochemical conditions during nodule formation. In addition, we also observe that the mineral composition and structural characteristics depend on the profile direction from the core to the rim. Particularly, the Raman spectra obtained along one profile show the lack of Fe-(oxy)hydroxides and the noticeably high crystallinity of Mn-bearing minerals such as birnessite and todorokite. On the other hand, the spectra obtained along the other two profiles present the presence of significant amount of amorphous or poorly-ordered Fe-bearing minerals and the low crystallinity of Mn-bearing minerals. These results suggest that the diagenetic conditions varied with the different growth directions. We also observed the presence of halite in several layers in the nodule, which can be evidence of the alteration of seawater after nodule formation. The current results can provide the opportunity to obtain detailed knowledge of the formation process and geochemical environments recorded in the natural non-spherical ferromanganese nodule.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1635-1650
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• 2023

Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m^-3, and primary production of 580.96-1574.13 mg C m^-2 day^-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.4
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• pp.292-302
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• 2012

This paper reviews comparison analysis of current and latest application for stock identification methods of Todarodes pacificus, and the pros and cons of each method and consideration of how to compensate for each other. Todarodes pacificus which migrates wide areas in western North Pacific is important fishery resource ecologically and commercially. Todarodes pacificus is also considered as 'biological indicator' of ocean environmental changes. And changes in its short and long term catch and distribution area occur along with environmental changes. For example, while the catch of pollack, a cold water fish, has dramatically decreased until today after the climate regime shift in 1987/1988, the catch of Todarodes pacificus has been dramatically increased. Regarding the decrease in pollack catch, overfishing and climate changes were considered as the main causes, but there has been no definite reason until today. One of the reasons why there is no definite answer is related with no proper analysis about ecological and environmental aspects based on stock identification. Subpopulation is a group sharing the same gene pool through sexual reproduction process within limited boundaries having similar ecological characteristics. Each individual with same stock might be affected by different environment in temporal and spatial during the process of spawning, recruitment and then reproduction. Thereby, accurate stock analysis about the species can play an efficient alternative to comply with effective resource management and rapid changes. Four main stock analysis were applied to Todarodes pacificus: Morphologic Method, Ecological Method, Tagging Method, Genetic Method. Ecological method is studies for analysis of differences in spawning grounds by analysing the individual ecological change, distribution, migration status, parasitic state of parasite, kinds of parasite and parasite infection rate etc. Currently the method has been studying lively can identify the group in the similar environment. However It is difficult to know to identify the same genetic group in each other. Tagging Method is direct method. It can analyse cohort's migration, distribution and location of spawning, but it is very difficult to recapture tagged squids and hard to tag juveniles. Genetic method, which is for useful fishery resource stock analysis has provided the basic information regarding resource management study. Genetic method for stock analysis is determined according to markers' sensitivity and need to select high multiform of genetic markers. For stock identification, isozyme multiform has been used for genetic markers. Recently there is increase in use of makers with high range variability among DNA sequencing like mitochondria, microsatellite. Even the current morphologic method, tagging method and ecological method played important rolls through finding Todarodes pacificus' life cycle, migration route and changes in spawning grounds, it is still difficult to analyze the stock of Todarodes pacificus as those are distributed in difference seas. Lately, by taking advantages of each stock analysis method, more complicated method is being applied. If based on such analysis and genetic method for improvement are played, there will be much advance in management system for the resource fluctuation of Todarodes pacificus.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.1
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• pp.37-46
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• 2000

We investigated the temporal and spatial variations in heterotrophic dinoflagellates (hereafter HTD) and ciliates from June to September 1997 in the waters off Kohung, Korea where red tides dominated by harmful dinoflagellates had occurred from August to October since 1995. We took water samples five times from 5-7 depths at 3 stations in this study period. A total of 17 HTD species were present and of these species in the genus Protoperidinium were 11. The species number of tintinnids (hereafter TIN) present totalled 15 and several naked ciliate (hereafter NC) species were observed. The species numbers of HTD and TIN rapidly increased between August 1st and 21st and then reached to the maximum numbers of 13 and 10, respectively, on August 27 when red tides dominated by Gyrodinium impudicum were first observed in the study area. However the species numbers drastically decreased on September 22. The maximum densities of HTD, TIN, and NC were 45, 39, 57 cells $ml^{-1}$, respectively. ADAS, calculated by averaging the densities of a certain species in the all samples collected from all depths and stations at a sampling period, most increased between August 1st and 21st and then reached to the maximum density of f cells $ml^{-1}$ on August 27 for HTD, while did between August 21st and 27th and up to 7 cells $ml^{-1}$ for TIN. Unlike ADAS of HTD and TIN, that of NC did not change much with the maximum of 8 cells $ml^{-1}$ on August 27th. The pattern of the temperal variation in the species number and ADAS of HTD was similar to that of diatoms and the distributions of Protoperidinium spp. and diatoms had a strong positive correlation. This evidence suggests that HTD, in particular Protoperidinium spp. be a grazer on diatom. In general, the densities of HTD, TIN, and NC decreased with going to stations located in the outer bay. Therefore, the availability of suitable prey and distance from the coastal line might be responsible for the distribution of HTD, TIN, and NC. The results of the present study provide a basis for further experiments for the feeding by dominant HTD, TIN, and NC on dominant phytoplankton including red tide species and for understanding food webs in the planktonic community before, during, and after the red tide outbreak.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.