• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.502-513
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• 2016

In this study, heavy metal distributions in the tissues of feral pigeon (Columba livia) were characterized using samples collected from bio-monitoring sites (Hangang Park and Hampyeong Park) of the NESB (National Environmental Specimen Bank), Korea, in order to evaluate the feasibility of feral pigeons as an indicator for the environmental monitoring. Cadmium (Cd) was analyzed to be accumulated in kidneys at higher concentration than in the other tissues. Such trend can also be found in the reviews on the Cd accumulations of the 34 cases including 17 avian species which showed that 31 cases had the highest Cd concentrations in the kidney among tissues. However, lead (Pb) was found to be richest in the bones in this study. 17 cases out of 30 reviewed cases had the highest Pb concentration in bones, whereas other 10 cases showed the highest concentration in kidneys, and 3 cases in livers. Therefore, kidneys together with bones can be a main target organ to test cadmium exposure to different habitat environments depending on physiological traits of birds. Zinc (Zn) was found to be the highest concentration in the pigeon livers of Hangang Park, but not in the bones. In contrast, the 13 cases of 16 reviewed cases had the highest Zn concentration in bones, and the 3 cases in livers. In addition, the heavy metal distribution patterns in relations to the metal accumulation mechanisms (a competition between Pb and Ca, a function of methallothionein protein, and etc.) were discussed.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Women's Health Nursing
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• v.6 no.2
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• pp.234-257
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• 2000

At present in the medical care, the study and effort for producing health service to consider efficiency, effectiveness, and quality are urgently called for because of the difficulty in the keen competition according to the inter- nationalization and opening, the operation in the medical institution service testing system, the change in the medical policy of KDRGs, and the lack of the health care cost increasing rate. As an alternative, the case management for the new management system is introduced in the U.S., and the Critical Pathway that is the method designing the contents of activity and its result has been developed and applied in order to anticipate and manage the patient-outcome for the realization of the cost-effective case-management. Thus, this study intended to analyze the effectiveness to obtain by developing the Critical Pathway presented as the method to improve the quality-betterment and cost effectiveness through the continuous and consistent patient management for the hysterectomy patient and applying it to the real practice. As a study method, this author formed a conceptual framework through considering five Critical Pathway used in the current U.S. and three Critical Pathway presented in the literature to develop the Critical Pathway for the hysterectomy patient, and made out the preliminary Critical Pathway through reviewing the old chart. This author made the verified the validity of the expert group about the developed Critical Pathway, and to confirm the possibility of practice application, completed and settled the final Critical Pathway after using the Critical Pathway to the hysterectomy patient from March 1st to 15th, 1997. Finally, to analyze the application-effect of the developed Critical Pathway, this author offered health care service applying the Critical Pathway to the hysterectomy patient from April 15th to August 31th, 1997. The guide for the Critical Pathway was carried out in advance by outpatient setting nurse for outpatient setting visit before the operation, and after hospitalization the primary nurse monitored the execution degree on the every duty. After discharge this author surveyed the complication through phone visiting, and one month after discharge surveyed the patient's reaction about the offered service when outpatient setting visit and analyzed the result. The source for health care cost was obtained by the statistics about the hospital charge which was offered by the General Business Department. The results were as follows. 1. It was decided that the vertical line of the Critical Pathway was made up of eight items such as monitoring/assessment, treatment, line/drains, activity, medication, lab test, diet, patient teaching, and the horizontal line of the Critical Pathway was made up of from hospitalization to discharge. 2. After the analysis of service contents through reviewing the old chart, it was decided that the horizontal line of the preliminary Critical Pathway was made up of from hopitalization to fourth postoperative day, and the vertical line of it was divided into eight items which were the contents to occur with the time frame of the horizontal line. 3. After the verifying the validity of the expert group about the preliminary Critical Pathway, the horizontal line was amended from hopitalization to third postoperative day, and taking their consensus, some contents of the horizontal line was amended and deleted. 4. From March 1st to 15th, 1997, to confirm the clinical suitability, this author offered eight hysterectomy patients the medical service through the Critical Pathway. The result was that three of them could be discharged at the expected discharge day, and the others later than that day. Supplementing the preliminary Critical Pathway through analyzing the cause of that delay- case, this author developed the final Critical Pathway. 5. There were no significant differences between the experimental and the control group in the incidence of complication(P > 0.05). 6. The 92.4% of experimental group was satisfied with the Critical Pathway service. 7. The length of hospital stay of the experimental group offered with the Critical Pathway service was 4.6 days and there was a significant difference that it was 1.3 days shorter than that of the control group(t=-29.514, P=0.000). 8. There wsa a significant difference that the mean medical charge per one patient of the experimental group offered the Critical Pathway service was cheaper \124,150 than that of the control group(t=-9.826, P=0.000). 9. The result that the author assumed and analyzed hospital income with the rate of turning bed was assumed that the increase of hospital income was \63,245,072 for that study, and the income increase was expected with \68,704,864 for a year. The result that this author applied the Critical Pathway to the hysterectomy patient have no differences in the incidence of complication, high satisfaction with that service, and the length of hospital stay decreased in the experimental group, and the mean hospital charge per one patient decreased, but hospital income increased. Suggestions for further study and nursing practice are as follows. 1. The study to apply the Critical Pathway for a year, verify the validity, and measure the effect repeatedly is needed. 2. To apply and manage the Critical Pathway effectively, the study to computerize it is needed. 3. The study to develop hospital-based Critical Pathway about other diseases or procedure, and measure the effect is needed.

• KDI Journal of Economic Policy
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• v.13 no.2
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• pp.97-127
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• 1991

This paper investigates the roles and the limitations of the Korean antitrust agencies-the Office of Fair Trade (OFT) and the Fair Trade Commission (FTC) during the making of the major industrial policies of the 1980's. The Korean antitrust agencies played only a minimal role in three major industrial policy-making issues in the 1980's- the enactment of the Industrial Development Act (IDA), the Industrial Rationalization Measures according to the IDA, and the Industrial Readjustment Measures on Consolidation of Large Insolvent Enterprises based on the revised Tax Exemption and Reduction Control Act. As causes for this performance bias in the Korean antitrust system, this paper considers five factors according to the current literature on implementation failure: ambiguous and insufficient statutory provisions of the Monopoly Regulation and Fair Trade Act (MRFTA); lack of resources; biased attitudes and motivations of the staff of the OFT and the FTC; bureaucratic incapability; and widespread misunderstanding about the roles and functions of the antitrust system in Korea. Among these five factors, bureaucratic incompetence and lack of understanding in various policy implementation environments about the roles and functions of the antitrust system have been regarded as the most important ones. Most staff members did not have enough educational training during their school years to engage in antitrust and fair trade policy-making. Furthermore, the high rate of staff turnover due to a mandatory personnel transfer system has prohibited the accumulation of knowledge and skills required for pursuing complicated structural antitrust enforcement. The limited capability of the OFT has put the agency in a disadvantaged position in negotiating with other economic ministries. The OFT has not provided plausible counter-arguments based on sound economic theories against other economic ministries' intensive market interventions in the name of rationalization and readjustment of industries. If the staff members of antitrust agencies have lacked substantive understanding of the antitrust and fair trade policy, the rest of government agencies must have had serious problems in understanding the correst roles and functions of the antitrust system. The policy environment of the Korean antitrust system, including other economic ministries, the Deputy Prime Minister, and President Chun, have tended to conceptualize the OFT more as an agency aiming only at fair trade policy and less as an agency that should enforce structural monopoly regulation as well. Based on this assessment of the performance of the Korean antitrust system, this paper evaluate current reform proposals for the MRFT A. The inclusion of the regulation of conglomerate mergers and of business divestiture orders may be a desirable revision, giving the MRFTA more complete provisions. However, given deficient staff experties and the unfavorable policy environments, it would be too optimistic and naive to expect that the inclusion of these provisions alone could improve the performance of the Korean antitrust system. In its conclusion, this paper suggests several policy recommendations for the Korean antitrust system, which would secure the stable development and accumulation of antitrust expertise for its staff members and enough understanding and conformity from its environments about its antitrust goals and functions.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.43-65
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• 2010

Facing a complex environment driven by a decade, many companies are adopting new strategic frameworks such as Customer Relationship Management system to achieve sustainable profitability as well as overcome serious competition for survival. In many business areas, CRM system advanced a great deal in a matter of continuous compensating the defect and overall integration. However, pharmaceutical companies in Korea were slow to accept them for usesince they still have a tendency of holding fast to traditional way of sales and marketing based on individual networks of sales representatives. In the circumstance, this article tried to empirically address current status of CRM system as well as the effects of the system on the performance of pharmaceutical companies by applying BSC method's four perspectives, from financial, customer, learning and growth and internal process. Survey by e-mail and post to employers and employees who were working in pharma firms were undergone for the purpose. Total 113 cases among collected 140 ones were used for the statistical analysis by SPSS ver. 15 package. Reliability, Factor analysis, regression were done. This study revealed that CRM system had a significant effect on improving financial and non-financial performance of pharmaceutical companies as expected. Proposed regression model fits well and among them, CRM marketing information system shed the light on substantial impact on companies' outcome given profitability, growth and investment. Useful analytical information by CRM marketing information system appears to enable pharmaceutical firms to set up effective marketing and sales strategies, these result in favorable financial performance by enhancing values for stakeholderseventually, not to mention short-term profit and/or mid-term potential to growth. CRM system depicted its influence on not only financial performance, but also non-financial fruit of pharmaceutical companies. Further analysis for each component showed that CRM marketing information system were able to demonstrate statistically significant effect on the performance like the result of financial outcome. CRM system is believed to provide the companies with efficient way of customers managing by valuable standardized business process prompt coping with specific customers' needs. It consequently induces customer satisfaction and retentionto improve performance for long period. That is, there is a virtuous circle for creating value as the cornerstone for sustainable growth. However, the research failed to put forward to evidence to support hypothesis regarding favorable influence of CRM sales representative's records assessment system and CRM customer analysis system on the management performance. The analysis is regarded to reflect the lack of understanding of sales people and respondents between actual work duties and far-sighted goal in strategic analysis framework. Ordinary salesmen seem to dedicate short-term goal for the purpose of meeting sales target, receiving incentive bonus in a manner-of-fact style, as such, they tend to avail themselves of personal network and sales and promotional expense rather than CRM system. The study finding proposed a link between CRM information system and performance. It empirically indicated that pharmaceutical companies had been implementing CRM system as an effective strategic business framework in order for more balanced achievements based on the grounded understanding of both CRM system and integrated performance. It suggests a positive impact of supportive CRM system on firm performance, especially for pharmaceutical industry through the initial empirical evidence. Also, it brings out unmet needs for more practical system design, improvement of employees' awareness, increase of system utilization in the field. On the basis of the insight from this exploratory study, confirmatory research by more appropriate measurement tool and increased sample size should be further examined.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.307-316
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• 2010

Complex terrain refers to irregular surface properties of the earth that influence gradients in climate, lateral transfer of materials, landscape distribution in soils properties, habitat selection of organisms, and via human preferences, the patterning in development of land use. Complex terrain of mountainous areas represents ca. 20% of the Earth's terrestrial surface; and such regions provide fresh water to at least half of humankind. Most major river systems originate in such terrain, and their resources are often associated with socio-economic competition and political disputes. The goals of the TERRECO-IRTG focus on building a bridge between ecosystem understanding in complex terrain and spatial assessments of ecosystem performance with respect to derived ecosystem services. More specifically, a coordinated assessment framework will be developed from landscape to regional scale applications to quantify trade-offs and will be applied to determine how shifts in climate and land use in complex terrain influence naturally derived ecosystem services. Within the scope of TERRECO, the abiotic and biotic studies of water yield and quality, production and biodiversity, soil processing of materials and trace gas emissions in complex terrain are merged. There is a need to quantitatively understand 1) the ecosystem services derived in regions of complex terrain, 2) the process regulation occurred to maintain those services, and 3) the sensitivities defining thresholds critical in stability of these systems. The TERRECO-IRTG is dedicated to joint study of ecosystems in complex terrain from landscape to regional scales. Our objectives are to reveal the spatial patterns in driving variables of essential ecosystem processes involved in ecosystem services of complex terrain region and hence, to evaluate the resulting ecosystem services, and further to provide new tools for understanding and managing such areas.

• Journal of Wetlands Research
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• v.24 no.3
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• pp.185-195
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• 2022

This study conducted a survey over spring and autumn from 2014 to 2020 to confirm the ecological characteristics of the size of streams and habitats, centering on the ecological landscape conservation area, and a total 256 species of benthic macroinvertebrates in 105 families, 25 orders, 8 classes, and 5 phyla appeared. In terms of appearance species, by region, the rate of appearance of Ephemeroptera and Trichoptera was high in regions consisting of lotic area and the rate of appearance of Coleoptera and Odonata was high in regions consisting of lentic areas. When comparing the population of Ephemeroptera-Plecoptera-Trichoptera (EPT) groups by region, they were classified into three groups: upstream area, mainstream area, and lentic areas, and it was confirmed that the population ratio of EPT changed as it moved from upstream to downstream. As the stream order increased, the number of species and populations increased. The Shredder group (SH) tended to decrease as the size of stream increased(r=0.9925), and the Collector-Filtering (CF) tended to increase as the size of stream increased(r=0.9319). It was confirmed that the Scraper (SC) replaced each other between species with the same ecological status as it went downstream from upstream, and it is thought that the SC did not differ significantly by stream order. In order to maintain a healthy ecosystem in the designation and management of ecological landscape conservation areas, it is necessary to consider ecological factors such as competition and physico-chemistry factors such as water quality and substrate conditions. Therefore, if the competent authority designated survey areas including buffer areas that include streams and physical habitats of various sizes, it will be advantageous to the conservative area and securing more biological resources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.161-178
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• 2017

Whereas the demand for development of forested areas covering more than 60% of Korean territory, permission on the forest development has been still given from the perspective of effective land utilization rather than conservation. As the assessment of large forested areas usually focuses more on forest structure, it has its limitation of observing and analyzing the interior change in forest in this way. This study was aimed at computing landscape metrics using a presence vegetation map and FRAGTSTATS 4.2 and analyzing vegetation mosaics. Colonies in native vegetation were classified into a series of major groups and sub-groups based on the native species within the colonies. The colonies were investigated by analyzing a suite of landscape metrics - Core Area, Percentage of Landscape, Number of Patches, Patch Density, Largest Patch Index, Total Edge, Edge Density, Landscape Shape Index, Mean Patch Area, Euclidean Nearest Neighbor. In the Chungnam province major groups and sub-groups of colonies classified based on the proportion of pine and oak species, and pine species was the principal one in terms of distribution area. As for the competition between pines and oaks, while the coverage of pine-centered colonies were three times larger than those of oak-centered ones, pine colonies showed the greater number of patches and therefore higher fragmentation than oaks at the major group level. For the sub-groups, the largest coverage colonies were not only indicated by Pinus densiflora-Quesrcus mongolica colonies among P. densiflora-centered colonies, Q. accutissima colonies among Q. accutissima-centered ones, Q. accutissima-P. densiflora colonies among Q. accutissima-centered ones, Q. mongolica colonies among Q. mongolica-centered ones, P. thumbergii colonies among P. thumbergii-centered ones, and Q. serrata-Q. acutissima colonies among Q. serrata-centered ones, but also revealed more severely mosaicked than other smaller colonies. The overall mosaicking degree estimated by landscape metrics was considered useful for monitoring and investigating vegetation. However, in order to develop management strategy based on analyzing the reason for the mosaicking process and anticipating a trend in vegetation succession, it is essential to further study about ecological characteristics of each colony in the vegetation.