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Design of Client-Server Model For Effective Processing and Utilization of Bigdata (빅데이터의 효과적인 처리 및 활용을 위한 클라이언트-서버 모델 설계)

  • Park, Dae Seo;Kim, Hwa Jong
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.109-122
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    • 2016
  • Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

An Analysis on the Conditions for Successful Economic Sanctions on North Korea : Focusing on the Maritime Aspects of Economic Sanctions (대북경제제재의 효과성과 미래 발전 방향에 대한 고찰: 해상대북제재를 중심으로)

  • Kim, Sang-Hoon
    • Strategy21
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    • s.46
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    • pp.239-276
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    • 2020
  • The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

Development of Intelligent Job Classification System based on Job Posting on Job Sites (구인구직사이트의 구인정보 기반 지능형 직무분류체계의 구축)

  • Lee, Jung Seung
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.123-139
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    • 2019
  • The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

Spatial effect on the diffusion of discount stores (대형할인점 확산에 대한 공간적 영향)

  • Joo, Young-Jin;Kim, Mi-Ae
    • Journal of Distribution Research
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    • v.15 no.4
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    • pp.61-85
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    • 2010
  • Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown

    . In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(${\gamma}$). From spatial coefficient(${\gamma}$) we can infer that when the diffusion in the vicinity of the diffusing center occurs, the diffusion is influenced by one in the diffusing center. The difference between the Bass model(II) and the spatial diffusion model(IV) is statistically significant with the ${\chi}^2$-distributed likelihood ratio statistic is 16.598(p=0.0023). Which implies that the spatial diffusion model is more effective than the Bass model to describe diffusion of discount stores. So the research question (1) is supported. In addition, we found that there are statistically significant relationship between similarity of retail environment and spatial effect by using correlation analysis. So the research question (2) is also supported.

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  • Development of New Variables Affecting Movie Success and Prediction of Weekly Box Office Using Them Based on Machine Learning (영화 흥행에 영향을 미치는 새로운 변수 개발과 이를 이용한 머신러닝 기반의 주간 박스오피스 예측)

    • Song, Junga;Choi, Keunho;Kim, Gunwoo
      • Journal of Intelligence and Information Systems
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      • v.24 no.4
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      • pp.67-83
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      • 2018
    • The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

    A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)

    • Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
      • 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.

    A Study on Forestation for Landscaping around the Lakes in the Upper Watersheds of North Han River (북한강상류수계(北漢江上流水系)의 호수단지주변삼림(湖水団地周辺森林)의 풍경적시업(風景的施業)에 관(関)한 연구(硏究))

    • Ho, Ul Yeong
      • Journal of Korean Society of Forest Science
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      • v.54 no.1
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      • pp.1-24
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      • 1981
    • Kangweon-Do is rich in sightseeing resources. There are three sightseeing areas;first, mountain area including Seolak and Ohdae National Parks, and chiak Provincial Park; second eastern coastal area; third lake area including the watersheds of North Han River. In this paper, several methods of forestation were studied for landscaping the North Han River watersheds centering around Chounchon. In Chunchon lake complex, there are four lakes; Uiam, Chunchon, Soyang and Paro from down to upper stream. The total surface area of the above four lakes is $14.4km^2$ the total pondage of them 4,155 million $m^3$, the total generation of electric power of them 410 thousand Kw, and the total forest area bordering on them $1,208km^2$. The bordering forest consists of planned management forest ($745km^2$) and non-planned management forest ($463km^2$). The latter is divided into green belt zone, natural conservation area, and protection forest. The forest in green belt amounts to $177km^2$ and centers around the 10km radios from Chunchon. The forest in natural conservation area amounts to $165km^2$, which is established within 2km sight range from the Soyang-lake sides. Protection forest surrounding the lakes is $121km^2$ There are many scenic places, recreation gardens, cultural goods and ruins in this lake complex, which are the same good tourist resources as lakes and forest. The forest encirelng the lakes has the poor average growing stock of $15m^3/ha$, because 70% of the forest consists of the young plantation of 1 to 2 age class. The ration of the needle-leaved forest, the broad-leaved forest and the mixed forest in 35:37:28. From the standpoint of ownership, the forest consists of national forest (36%), provincial forest (14%), Gun forest (5%) and private forest(45%). The greater part of the forest soil, originated from granite and gneiss, is much liable to weathering. Because the surface soil is mostly sterile, the fertilization for improving the soil quality is strongly urged. Considering the above-mentioned, the forestation methods for improving landscape of the North Han River Watersheds are suggested as follows: 1) The mature-stage forest should be induced by means of fertilizing and tendering, as the forest in this area is the young plantation with poor soil. 2) The bare land should be afforested by planting the rapid growing species, such as rigida pine, alder, and etc. 3) The bare land in the canyon with moderate moist and comparatively rich soil should be planted with Korean-pine, larch, ro fir. 4) Japaness-pine stand should be changed into Korean-pine, fir, spruce or hemlock stand from ravine to top gradually, because the Japanese-pine has poor capacity of water conservation and great liability to pine gall midge. 5) Present hard-wood forest, consisting of miscellaneous trees comparatively less valuable from the point of wood quality and scenerity, should be change into oak, maple, fraxinus-rhynchophylla, birch or juglan stand which is comparatively more valuable. 6) In the mountain foot within the sight-range, stands should be established with such species as cherry, weeping willow, white poplar, machilus, maiden-hair tree, juniper, chestnut or apricot. 7) The regeneration of some broad-leaved forests should be induced to the middle forest type, leading to the harmonious arrangement of the two storied forest and the coppice. 8) For the preservation of scenery, the reproduction of the soft-wood forest should be done under the selection method or the shelter-wood system. 9) Mixed forest should be regenerated under the middle forest system with upper needle-leaved forest and lower broad-leaved forest. In brief, the nature's mysteriousness should be conserved by combining the womanly elegance of the lakes and the manly grandeur of the forest.

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    Combined Effect of Ganciclovir and Vidarabine on the Replication, DNA Synthesis, and Gene Expression of Acyclovir-resistant Herpes Simplex Virus (Acyclovir저항성 Herpes Simplex Virus의 복제, DNA합성 및 형질 발현에 미치는 Ganciclovir 및 Vidarabine의 병용효과에 관한 연구)

    • Yang, Young-Tai;Cheong, Dong-Kyun;Mori, Masakazu
      • The Korean Journal of Pharmacology
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      • v.25 no.1
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      • pp.115-134
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      • 1989
    • Combined effects of ganciclovir (GCV) and vidarabine (ara-A) on the replication, DNA synthesis, and gene expression of wild type-1 herpes simplex virus (HSV-1) and three acyclovir (ACV)-resistant HSV-1 mutants were studied. These mutants include a virus expressing no thymidine kinase $(ACV^r)$, a virus expressing thymidine kinase with altered substrate specificity $(IUdR^r)$, and a mutant expressing altered DNA polymerase $(PAA^r5)$. GCV, an agent activated by herpesvirus specific thymidine kinase, showed potent antiviral activity against the wild type HSV-1(KOS) and DNA polymerase mutant $(PAA^r5)$. The ACV-resistant mutants with thymidine kinase gene $(ACV^r\;and\;IUdR^r)$ were resistant to GCV. All tested wild type HSV-1 or ACV-resistant HSV-1 mutants did not display resistance to vidarabine (are-A). Combined GCV and ara-A showed potentiating synergistic antiviral activity against wild type KOS and $PAA^r5$, and showed subadditive combnined ativiral activity against thymidine kinase mutants. Combined GCV and ara-A more significantly inhibited the viral DNA synthesis in wild type KOS and $PAA^r5-infected$ cells to a greater extent than either agent alone, but the synergism was not determined in $ACV^r$ or $IUdR^r-infected$ cells. These data clearly indicate that combined GCV and ara-A therapy might be useful for the treatment of infections caused by wild type HSV-1 or ACV-resistant HSV-1 with DNA polymerase mutation. ACV-resistant viruses with the mutation in thymidine kinase gene are also, resistant to GCV, but susecptible to ara-A, indicating that ara-A would the drug of choice for the treatment of ACV-resistant HSV-1 which does not express thymidine kinase or expresses thymidine kinase with altered substrate specificity. While the synthesis of viral ${\alpha}-proteins$ of wild type HSV-1 was not affected by ACV, GCV, ara-A, or combined GCV and ara-A, the synthesis of ${\beta}-proteins$ was slightly but significantly increased at the later stage of viral infection by the antiviral agents. The synthesis of ${\gamma}-proteins$ of wild type HSV- 1 was significantly inhibited by ACV, GCV, ara-A, and combined GCV and ara-A. Combined GCV $(5-{\mu}M)$ and ara-A $(100-{\mu}M)$ also significantly altered the expression of viral ${\beta}-and$ ${\gamma}-proteins$, of which efffct was similar to that of GCV $(10-{\mu}M)$ alone. Although ACV at the concentration of $10-{\mu}M$ did not alter the expression of ${\alpha}-$, ${\beta}-$, and ${\gamma}-proteins$ of ACV-resistant $PAA^r5$, GCV and ara-A significantly alter the epression of ${\beta}-and$ ${\gamma}-proteins$, not ${\alpha}-protein$, as same manner as they altered the expression of those proteins in cells inffcted with wild type HSV-1. Combined GCV $(5-{\mu}M)$ and ara-A $(100-{\mu}M)$ altered the expression ${\beta}-and$ ${\gamma}-proteins$ in $PAA^r5$ infected cells, and the effect of combined regimen was comparable of that of GCV $(10-{\mu}M)$. These data indicate that the alteration in the expression of ${\beta}-and$ ${\gamma}-proteins$ in wild type HSV-1 or $PAA^r5$ infected cells could be more significantly affected by combined GCV and are-A than individual GCV or ara-A. In view of the fact that (a) viral ${\alpha}-$, ${\beta}-$, and ${\gamma}-proteins$ are synthesized in a cascade manner; (b) ${\beta}-proteins$ are essential for the synthesis of viral DNA; (c) the synthesis of ${\beta}-proteins$ are inhibited by ${\gamma}-proteins$; and (d) most ${\gamma}-proteins$ are made from the newly synthesized progeny virus, it is suggested that GCV and ara-A, alone or in combination, primarily inhibit the synthesis of viral DNA, and by doing so might exhibit their antiherpetic activity. The alteration in viral protein synthesis in the presence of tested antiviral agents could result from the alteration in viral DNA synthesis. From the present study, it can be concluded that (a) combined GCV and ara-A therapy would be beneficial for the control of inffctions caused by wild type HSV-1 or ACV-resistant DNA polymerase mutants; (b) the combined synergistic activity of GCV and ara-A is due to further decrease in the viral DNA by the combined regimen; (c) ara-A is the drug of choice for the infection caused by ACV-resistant HSV-1 with thymidine kinase mutation; and (d) the alteration in viral protein synthesis by GCV and ars-A, alone or in combination, is mostly due to the decreased synthesis of viral DAN.

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    A Study on Intelligent Value Chain Network System based on Firms' Information (기업정보 기반 지능형 밸류체인 네트워크 시스템에 관한 연구)

    • Sung, Tae-Eung;Kim, Kang-Hoe;Moon, Young-Su;Lee, Ho-Shin
      • Journal of Intelligence and Information Systems
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      • v.24 no.3
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      • pp.67-88
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      • 2018
    • Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

    The Effects of Proinflammatory Cytokines and TGF-beta, on The Fibroblast Proliferation (Proinflammatory Cytokines과 TGF-beta가 섬유모세포의 증식에 미치는 영향)

    • Kim, Chul;Park, Choon-Sik;Kim, Mi-Ho;Chang, Hun-Soo;Chung, Il-Yup;Ki, Shin-Young;Uh, Soo-Taek;Moon, Seung-Hyuk;Kim, Yong-Hoon;Lee, Hi-Bal
      • Tuberculosis and Respiratory Diseases
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      • v.45 no.4
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      • pp.861-869
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      • 1998
    • Backgrounds: The injury of a tissue results in the infalmmation, and the imflammed tissue is replaced by the normal parenchymal cells during the process of repair. But, constitutional or repetitive damage of a tissue causes the deposition of collagen resulting in the loss of its function. These lesions are found in the lung of patients with idiopathic pulmonary fibrosis, complicated fibrosis after diffuse alveolar damage (DAD) and inorganic dust-induced lung fibrosis. The tissue from lungs of patients undergoing episodes of active and/or end-stage pulmonary fibrosis shows the accumulation of inflammatory cells, such as mononuclear cells, neutrophils, mast cells and eosinophils, and fibroblast hyperplasia. In this regard, it appears that the inflammation triggers fibroblast activation and proliferation with enhanced matrix synthesis, stimulated by inflammatory mediators such as interleukin-1 (IL-1) and/or tumor necrosis factor (TNF). It has been well known that TGF-$\beta$ enhance the proliferation of fibroblasts and the production of collagen and fibronectin, and inhibit the degradation of collagen. In this regard, It is likely that TGF-$\beta$ undergoes important roles in the pathogenesis of pulmonary fibrosis. Nevertheless, this single cytokine is not the sole regulator of the pulmonary fibrotic response. It is likely that the balance of many cytokines including TGF-$\beta$, IL-1, IL-6 and TNF-$\alpha$ regulates the pathogenesis of pulmonary fibrosis. In this study, we investigate the interaction of TGF-$\beta$, IL-1$\beta$, IL-6 and TNF-$\alpha$ and their effect on the proliferation of fibroblasts. Methods: We used a human fibroblast cell line, MRC-5 (ATCC). The culture of MRC-5 was confirmed by immunofluorecent staining. First, we determined the concentration of serum in cuture medium, in which the proliferation of MRC-5 is supressed but the survival of MRC-5 is retained. Second, we measured optical density after staining the cytokine-stimulated cells with 0.5% naphthol blue black in order to detect the effect of cytokines on the proliferation of MRC-5. Result: In the medium containing 0.5% fetal calf serum, the proliferation of MRC-5 increased by 50%, and it was maintained for 6 days. IL-1$\beta$, TNF-$\alpha$ and IL-6 induced the proliferation of MRC-5 by 45%, 160% and 120%, respectively. IL-1$\beta$ and TNF-$\alpha$ enhanced TGF-$\beta$-induced proliferation of MRC-5 by 64% and 159%, but IL-6 did not affect the TGF-$\beta$-induced proliferation. And lNF-$\alpha$-induced proliferation of MRC-5 was reduced by IL-1$\beta$ in 50%. TGF-$\beta$, TNF-$\alpha$ and both induced the proliferation of MRC-5 to 89%, 135% and 222%, respectively. Conclusions: TNF-$\alpha$, TGF-$\beta$ and IL-1$\beta$, in the order of the effectiveness, showed the induction of MRC-5 proliferation of MRC-5. TNF-$\alpha$ and IL-1$\beta$ enhance the TGF-$\beta$-induced proliferation of MRC-5, but IL-6 did not have any effect TNF-$\alpha$-induced proliferation of MRC-5 is diminished by IL-1, and TNF-$\alpha$ and TGF-$\beta$ showed a additive effect.

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