• The Journal of Industrial Distribution & Business
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• v.2 no.2
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• pp.5-14
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• 2011

Opening agricultural market expansion, reduced purchases through wholesale markets, expanding the influence large retailers of consumer's market such as changes in the distribution system to the farmer's market conditions are changing rapidly. Because of this, retailers of the scaled and chain-store operations was centered on distribution environmental changes of the consumer market place. In producing area due to changes in market conditions in the agricultural production of in producing area distribution organization and the size distribution can not be put off no longer challenge is imminent. If it do not raise forces banded together, the producer is bound to remain as the weak. To support the distribution of this production was introduced in 2000 enable the Activation Project of in producing area distribution. Recent in producing area Changes of Agricultural conditions in order to cope with the Small-scale farmers and small individual farmers are becoming Scaled and specialized. Also, is specific to each item and regional is showing aspects. Government support for Activation Project of in producing area distribution is greatly improved, but in terms of competitiveness on the market still is showing the limitations. The most common of these problems, the market response if in producing area producer's organization and scale of the problem. Equipped for the purpose of consumer market place responsiveness unreasonable propelled outward from the Painter-sized weakens the organizational power. also, Difficult to succeed organizational size is a dissolution or anything within a few years, farmers around the best producer organizations, such as deviation occurs is exposed to a variety of issues. In this study, previous studies refer to the recent changes in agricultural retail environment, background and needs of organization·scaled, Determine the status of the domestic in producing area organizations and derived Problems, look into Domestic and overseas of in producing area organization with best practices for enhancing the competitiveness of the proposed improvement are intended to. In the future, in producing area distribution policy would like to provide direction to the development. The results of the study showed the follwing : 1) enhance utilization and orrganized through the diversification of the agricultural Collection systems. 2) Scaled to achieve through Items of specialized a wide area marketing. 3) Management operating units, such as installation and operating that overseas the best practices " Comite Economique Agricole Regional 'Fruits et Legumes' de Bretagne". 4) To establish a support system that in producing area distribution organization model development for appropriate domestic. In particular, in case of domestic in producing area distribution organization, through the analysis of various case study that a successful organization and scaled. The process of the various challenges arising in organizational scaled and generalization, and by the way he goes about trying to overcome is required. At the end of the study's limitations and future research directions suggested.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.97-116
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• 2012

Conceptual modeling is an important step for successful system development. It helps system designers and business practitioners share the same view on domain knowledge. If the work is successful, a result of conceptual modeling can be beneficial in increasing productivity and reducing failures. However, the value of conceptual modeling is unlikely to be evaluated uniformly because we are lack of agreement on how to elicit concepts and how to represent those with conceptual modeling constructs. Especially, designing relationships between components, also known as part-whole relationships, have been regarded as complicated work. The recent study, "Representing Part-Whole Relations in Conceptual Modeling : An Empirical Evaluation" (Shanks et al., 2008), published in MIS Quarterly, can be regarded as one of positive efforts. Not only the study is one of few attempts of trying to clarify how to select modeling alternatives in part-whole design, but also it shows results based on an empirical experiment. Shanks et al. argue that there are two modeling alternatives to represent part-whole relationships : an implicit representation and an explicit one. By conducting an experiment, they insist that the explicit representation increases the value of a conceptual model. Moreover, Shanks et al. justify their findings by citing the BWW ontology. Recently, the study from Shanks et al. faces criticism. Allen and March (2012) argue that Shanks et al.'s experiment is lack of validity and reliability since the experimental setting suffers from error-prone and self-defensive design. They point out that the experiment is intentionally fabricated to support the idea, as such that using concrete UML concepts results in positive results in understanding models. Additionally, Allen and March add that the experiment failed to consider boundary conditions; thus reducing credibility. Shanks and Weber (2012) contradict flatly the argument suggested by Allen and March (2012). To defend, they posit the BWW ontology is righteously applied in supporting the research. Moreover, the experiment, they insist, can be fairly acceptable. Therefore, Shanks and Weber argue that Allen and March distort the true value of Shanks et al. by pointing out minor limitations. In this study, we try to investigate the dispute around Shanks et al. in order to answer to the following question : "What is the proper value of the study conducted by Shanks et al.?" More profoundly, we question whether or not using the BWW ontology can be the only viable option of exploring better conceptual modeling methods and procedures. To understand key issues around the dispute, first we reviewed previous studies relating to the BWW ontology. We critically reviewed both of Shanks and Weber and Allen and March. With those findings, we further discuss theories on part-whole (or part-of) relationships that are rarely treated in the dispute. As a result, we found three additional evidences that are not sufficiently covered by the dispute. The main focus of the dispute is on the errors of experimental methods: Shanks et al. did not use Bunge's Ontology properly; the refutation of a paradigm shift is lack of concrete, logical rationale; the conceptualization on part-whole relations should be reformed. Conclusively, Allen and March indicate properly issues that weaken the value of Shanks et al. In general, their criticism is reasonable; however, they do not provide sufficient answers how to anchor future studies on part-whole relationships. We argue that the use of the BWW ontology should be rigorously evaluated by its original philosophical rationales surrounding part-whole existence. Moreover, conceptual modeling on the part-whole phenomena should be investigated with more plentiful lens of alternative theories. The criticism on Shanks et al. should not be regarded as a contradiction on evaluating modeling methods of alternative part-whole representations. To the contrary, it should be viewed as a call for research on usable and useful approaches to increase value of conceptual modeling.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.278-283
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• 2000

As information communication technology developed we could check our blood pressure, pulsation electrocardiogram, SpO2 and blood test easily at home. To check our health at ordinary times is able though interlocking the house medical instrument with the wireless public data network This service will help the inconvenience to visit the hospital everytime and will save the individual's time and cost. In each house an organism data which is detected from the human body will be transmitted to the distance hospital and will be essentially applied through wireless public data network The medical information transmit system is utilized by wireless close range network It would transmit the obtained organism signal wirelessly from the personal device to the main center system in the hospital. Remote telemetry system is embodied by utilizing wireless media access protocol. The protocol is embodied by grafting CSMA/CA(Carrier Sense Multiple Access with Collision Avoidance) protocol falling mode which is standards from IEEE 802.11. Among the house care telemetry system which could measure blood pressure, pulsation, electrocardiogram, SpO2 the study embodies the ECC(electrocardiograph) measure part. It within the ECC function into the movable device and add 900㎒ band wireless public data interface. Then the aged, the patients even anyone in the house could obtain ECG and keep, record the data. It would be essential to control those who had a health-examination heart diseases or more complicated heart diseases and to observe the latent heart disease patient continuously. To embody the medical information transmit system which is based on wireless network. It would transmit the ECG data among the organism signal data which would be utilized by wireless network modem and NCL(Native Control Language) protocol to contact through wireless network Through the SCR(Standard Context Routing) protocol in the network it will be connected to the wired host computer. The computer will check the recorded individual information and the obtained ECC data then send the correspond examination to the movable device. The study suggests the medical transmit system model utilized by the wireless public data network.

• Journal of Korean Academy of Nursing
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• v.28 no.4
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• pp.1047-1059
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• 1998

Senile Dementia is one of the dispositional mental disorder which has been known to the world since Hippocratic age. It has become a wide-spread social problem all over the world because of chronic disease processes and the demands of dependent care for several years as well as improbability of treatment of it at the causal level. Essentially, life styles of the older generation differ from those of the younger generation. While the fomer is used to the patriarchal system and the spirit of filial piet and respect, the latter is pragmatized and individualized under the effects of the Western material civilization. These differences between the two generations cause conflict between family members. In particular, the pain and conflict of care-givers who take care of a totally dependent dementia patient not only is inciting to the collapse of the family union, but is expanding into a serious social problem. According to this practical difficulty, this study has tried to compare dementia care-givers' experiences inter-culturally and to help set up more proper nursing interventions, describing and explaining them through ethnographies by participant observation and in-depth interviews that enable seeing them in a more close, honest and certain way. It also tries to provide a theoetical model of nusing care for dementia patients which is proper to Korean culture. This study is composed of 12 participants (4 males, 8 females) whose ages range from 37-71 years. The relations of patients are 5 spouses(3 husbands, 2 wives), 4 daughters-in-law, 2 daughters, and 1 son-in-law. The following are the care-givers' meaning of experiences that results of the study shows. The first is "psychological conflict". It contains the minds of getting angry, reproaching, being driven to dispair, blaming oneself, giving up lives, and being afraid, hopeless, and resigned. The second is "physical, social and psychological pressure" . At this stage, care-givers are shown to be under stress of both body and soul for the lack of freedom and tiredness. They also feel constraint because they hardly cope with the care and live through others' eyes. The third is "isolation". It makes the relationship of patient care-giver to be estranged, without understanding each other. They, also, experience indifference such as being upset and left alone. The forth is "acceptance" They gradually have compassion, bear up and then adapt themselves to the circumstances they are in. The fifth is "love". Now they learn to reward the other with love. It is also shown that this stage contains the process of winning others' recognition. The final is "hope". In this stage they really want situations to go smoothly and hope everything will be O.K. These consequences enable us to summarize the principles of cue experience such as, in the early stage, negative response such as physical·psychological confusion, pain and conflict are primary. Then the stage of acceptance emerges. It is an initial positive response phase when care-givers may admit their situations. As time passes by a positive response stage emerges. At last they have love and hope. Three stages we noted above : however, there are never consistent situations. Rather it gradually comes into the stage of acceptance, repeating continuous conflict, pressure and isolation. If any interest and understanding of families or the support of surrounding society lack, it will again be converted to negative responses sooner or later. Otherwise, positive responses like hope and love can be encouraged if the family and the surroundings give active aids and understanding. After all, the principles of dementia care experiences neither stay at any stage, nor develop from negative stages to positive stages steadily. They are cycling systems in which negative responses and positive responses are constantly being converted. I would like to suggest the following based on the above conclusions : First, the systematic and planned education of dementia should be performed in order to enhance public relations. Second, a special medical treatment center which deals with dementia, under government's charge, should be managed. Third, the various studies approaching dementia care experiences result in the development of more reasonable and useful nursing guidelines.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.4
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• pp.23-34
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• 2017

This study focused on a planned site located in Gosangol Village in Daegu Metropolitan City that aims to build an urban agricultural park combining urban agriculture and urban park for the sustainable realization of urban agriculture. Accordingly, this study has significance in two perspectives: firstly, suggesting development strategies to be considered when building an urban agricultural park as a theme park, and secondly, presenting guidelines for spatial programs and facilities to be introduced for actual applications. The results are as follows. Firstly, building an urban agricultural park fills a role as a local community space prompted by the demand-oriented evolution of urban parks, and agricultural behaviors to be incorporated in the theme. In this context, 'building an urban agricultural space focusing on sustainability', 'constructing green space systems focusing on agricultural landscape', and 'structuring leisure spaces for communications in the community' are presented as development strategies. Secondly, key functions that an urban agricultural park should have include production and trade of agricultural products on the production side, soil preservation, resource cycling and green space provision on the environmental side, leisure and experience, community vitalization, education, and social security on the social and cultural side, and entertainment functions, ecological functions, and protective functions as urban park functionality. Thirdly, key facilities needed when building an urban agricultural park include urban agricultural facilities other than park management facilities, landscape facilities, recreational facilities, sports facilities, educational facilities, and convenient facilities, and family gardens as the key facility of the urban agricultural park should be scaled in consideration of various purposes and behaviors of their use. This study has a limitation that the subject site was limited to a specific area but has significance in that it presented a planning model for the spatial structuring of park-type urban agriculture.

• KDI Journal of Economic Policy
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• v.13 no.2
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• pp.41-67
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• 1991

Local autonomy of Korea's lower-level local council has been reinstated following elections last March for the first time in thirty years. Last June, we had elections for the upper-level local council. Mayors, governors, and administrative chiefs of cities, provinces and other local government bodies are slated for elections in the first half of next year. The impacts of local autonomy are taking effect in not only the political sphere, but also the administrative and economic spheres. In fact, it seems that some modification of all economic policy making and administration is inevitable. Since the initiation of local autonomy, in order to make the economy work more efficiently, it has become quite important to examine the impact of local autonomy on the national economy. The areas of local autonomy include independent legislative power, administrative power, organizational power, and most important of all, the independent public financial power of the local governments. The purpose of this paper is to examine the effects of local autonomy on the national economy and ways of enhancing the role of local public finance to facilitate settlement and development of the local autonomy system. Local autonomy will contribute to the continuous growth of our economy, allow balanced development, and generate greater efficiency. However, local autonomy can also incur economic costs causing at times short-term price instability, inefficient resource allocation, through tax competition and tax exporting, and insolvency of local government due to abusive fiscal operation. To reduce these side effects, different alternatives must be considered. Local autonomy systems generally provide more efficient resource allocation than centralization. But in the model used in Chapter 3 of this paper, the relative efficiencies of both local autonomy and centralization are determined by comparing the elasticity of substitution between national public goods and local public goods. If the elasticity of substitution is bigger than one, centralization provides a more efficient resource allocation. The development of local autonomy could be attained through democratization of the local public finance system including the following three propositions. I) The independence of public financial power of local governments should be established over central government. Furthermore, a democratically operated scheme of intergovernmental fiscal coordination is especially necessary. 2) In the operation of local finance, direct democracy is needed to induce the voluntary participation of local residents. The residents can take part in planning both the local budget and the development of the community. To attain this goal, all the results of local finance operations should be made public. 3) Among economic ill-effects of the local autonomy system, the most serious one is the possibility of insolvency of local governments. Therefore, measures to limit abusive spending by the local governments should be introduced, such as the fiscal restraints system adopted in the United States.

• Journal of the Korean earth science society
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• v.24 no.5
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• pp.378-392
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• 2003

The purpose of this study is to investigate the depth of earth science teachers' concern over the 7th Science Curriculum and levels of their use of it in reality, using the tools "Concern" and "Levels of use" which are two important tools use in CBAM. The results of the study are as follows. How much concern do the earth science teachers have over the 7th Science Curriculum? There are seven stages (from 0 stage to 6 stage) of teachers' concern over the curriculum. o stage represents teachers' indifference to the curriculum and 98% teachers are placed in this stage. According to the study on teachers' teaching experience, teachers having from 10 to 14 years of teaching experience are the most indifferent to the 7th Science Curriculum, compared to other teachers. Which levels of use of the 7th science curriculum do earth science teachers choose in reality? There are five levels of use (from 1 to 5) of the 7th curriculum. 43.97% of teachers are placed in the 3rd level called "Mechanical level", which represents a teacher-concerned learning method with consideration of learners' response. According to the study on teachers' frequency of level of use in the fields of "Instruction objects, Instruction contents, Instruction methods, Instruction materials and Evaluation.", teachers chose high levels of use in the fields of "Instruction objects and Instruction contents" and low levels of use in the other three fields. What factors are barriers for earth science teachers to perform the 7th Science Curriculum in reality? 80.9% of teachers have trouble performing the 7th Science Curriculum in reality because of too much routine work, official papers, and lack of instructional materials, laboratories, training systems and workshops. The two biggest barriers among the above are routine work and of official papers. According to the study on teachers' teaching experience, teachers having from 0 to years of teaching experience have the most trouble in performing the curriculum in reality, compared to other teachers.