• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Research in Community and Public Health Nursing
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• v.7 no.2
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• pp.294-312
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• 1996

Relatively young widows, who are left with young children by a sudden death of their husbands, will be faced with not only psychological troubles such as individual anxiety and frustration but also the dual burden of playing both father and mother roles in a family, Also, family members have difficulty in adapting themselves to new circumstances of the family system, the training and raising of family members, and management of the family economy. In this study, the realistic resources on the experience of middle-aged women who are bereaved of their husbands by accidents were explored. The purpose of this study is to help widows adapt to life in society and live a more positive life by setting a new goals and recovering from a lost and twisted life. 11 women, who have experienced the loss their husbands and live in the Seoul metropolitan area were studied. The research took 116 days from December 15, 1995 to April 8, 1996. The method of research was direct interviews. While having interviews with them, the contents were recorded with their consent. The ground theory was that used by Strauss & Corbin(1990) in the analysis of the data. 81 concepts were analyzed and they were subdirided into 22 subordinate categories through the course of the analysis. These were then classified into 9 general categories. In the course of being categorized, 'absurdity' was showed as a core category. The subordinate categories 'surprise', 'gloom', 'grudge', 'helplessness', 'emptiness', and 'loss' were united in the core category 'absurdity'. Ominous presentiment, belated notice, death, surprise, gloom, grudge, helplessness, emptiness, loss, the situation of the children, lack of support from neighbors, support from neighbors, mulling over ways to live, choosing a job, strengthening, reinforcement, burden, sadness, smoldering, yearning, overcoming these 22 subordinate categories were re-composed into 9 general ones the husband's death, absurdity, presence of children, existence of support, self-support ability, preparation of countermeasures, self-reinforcement, toilsomeness, and overcoming. 'Absurdity' widows experience was shown in the results of 'toilsomeness' and 'overcoming' through reaction, confrontation, and adaptation. According to the analysis the central phenomenon was absurdity, the causal condition of the death of a husband, the presence of children and the existence of support, and the meditated situation of self-support. To solve absurdity, the preparation of countermeasures and self-reinforcements were shown resulting in toilsomeness and overcoming. Through the contrast in the data, the following statements were deduced: (1) If the death of the husband is expected, the more a widow will feel absurdity. (2) The more children she has and the younger she is, the more a widow will feel absurdity. (3) The lower support she is given, the more a widow will feel absurdity. (4) The larger self-ability she has, the more actively she will prepare countermeasures. (5) The smaller self-ability she has, the more passively she will prepare countermeasures. (6) The larger self-ability she has, the weaker self-reinforcement she will preform. (7) The smaller self-ability she has, the stronger self-reinforcement she will perform. (8) The more actively she prepares countermeasures for absurdity, the better she will overcome. (9) The more passively she prepares counter measure for absurdity, the worse she will overcome. (10) The stronger self-reinforcement for absurdity she performs, the better she will overcome. (11) The weaker self-reinforcement for absurdity she performs, the worse she will overcome. Through the results in this study, the following suggested: 1) A study whose object is all family members, and a comparative study on the case of a husband who has lost his wife should be done. These studies can be expected to develop a more refined theory. 2) Because of the collapse of the extended family system and the changes of family culture in Korea, a widow's status and position are apt to be ambiguous between her husband's home and her parent's. Therefore a new study on family culture should be made. 3) A continuous study on growing social Self Help Groups should be requested for the widows of this study to re-establish and recover from their twisted and scattered lives.

• Journal of Distribution Science
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• v.7 no.4
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• pp.15-26
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• 2009

The internet has dramatically changed a way of business management and competition in the business environment. Especially, it stimulated not only to evolve online floral distribution service but also to change a phase of competition among floral retail stores in industry. And that also led to keen competition among IT service providers as well. This study is to examine how floral retail stores have been evolved and competed with the radical situation of the floral distribution industry through IT service in the aspect of business and information technology. In addition, the Typhoon Positioning Strategy(TPS), a strategy for the IT service positioning, is introduced from IT service provider's perspective. For IT service providers to create high business value and continuous service providing, IT service should be positioned on the customers' "core business" and developed to the level of "solution." The Typhoon Positioning Strategy(TPS) is a strategy for the IT service positioning, indicating that IT service should be positioned according to a Business Process-Service model with the consideration of business development direction, IT service trend, and user's IT capability. That is, IT service providers should find out customers' "core business" area first to provide a right IT service to the company, and the IT service provided should meet to the level of business solution. The capability of the IT solution users is also an important factor to be considered for the advanced IT service. There are four principles of the Typhoon Positioning Strategy(TPS). Principle 1) IT service provided should be an IT solution Map suitable for customer business processes. Principle 2) IT service provided should be able to support customer core business. Principle 3) IT service provided should be a business solution. Principle. 4) IT service provided should be applied differently according to the level of customer's IT capability.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.6
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• pp.1-15
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• 2021

This study considered Forest Specialists, who are nurtured by the legal system through the analysis of laws and regulations under the jurisdiction of the Korea Forest Service. In particular, the transition process of forest-related laws and laws to train forest specialists were identified. In addition, changes and characteristics regarding the cultivation of professional forestry talents according to forestry policy were investigated. As a result, it was found that Forest Specialist on policy dealt with forestry success for forestry promotion, and forestry engineers dealt with technical skills for forestry industry development. In addition, according to the revision of the laws for the sustainable use of timber, wood-structural engineers, timber grade evaluators, and timber education specialists are trained separately. Forest Specialists concerned with forest welfare policies were found to train forest experts and complete specialized training courses to provide various services for forest cultural and recreation facilities, healing forests, and forest leisure sports facilities. There is an instructor for forest leisure sports. Forest welfare experts are divided into forest education experts and forest healing instructors; forest education specialists are further divided into forest interpreters, forest guides for children, and forest trekking guides. Forest Specialists on forest protection policy were found to train arboretum and garden experts for the efficient management and exhibition of arboretums. Gardens and tree doctors and tree treatment technicians for arboretums wer also trained. A tree doctor and a tree treatment technician were found to have the necessary qualifications to run a tree hospital business, diagnosing and treating tree damage. Therefore, it is thought that the Korea Forest Service is nurturing Forest Specialists with technical capabilities for forestry promotion, forest industry development, and tree treatment; and the Forest Specialists can provide education and welfare services at culture, recreation, treatment, and conservation sites in forests.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Journal of agricultural medicine and community health
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• v.1 no.1
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• pp.5-9
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• 1976

The categories of national health problems may be mainly divided into health promotion, problems of diseases, and population-economic problems which are indirectly related to health. Of them, the problems of diseases will be exclusively dealt with this speech. Rurality and Disease Problems There are many differences between rural and urban areas. In general, indicators of rurality are small size of towns, dispersion of the population, remoteness from urban centers, inadequacy of public transportation, poor communication, inadequate sanitation, poor housing, poverty, little education lack of health personnels and facilities, and in-accessibility to health services. The influence of such conditions creates, directly or indirectly, many problems of diseases in the rural areas. Those art the occurrence of preventable diseases, deterioration and prolongation of illness due to loss of chance to get early treatment, decreased or prolonged labour force loss, unnecessary death, doubling of medical cost, and economic loss. Some Considerations of Innovative Approach The followings art some considerations of innovative approaches to the problems of diseases in the rural Korea. 1. It would be essential goal of the innovative approaches that the damage and economic loss due to diseases will be maintained to minimum level by minimizing the absolute amount of the diseases, and by moderating the fee for medical cares. The goal of the minimization of the disease amount may be achieved by preventive services and early treatment, and the goal of moderating the medical fee may be achieved by lowering the prime cost and by adjusting the medical fees to reasonable level. 2. Community health service or community medicine will be adopted as a innovative means to disease problems. In this case, a community is defined as an unit area where supply and utilization of primary service activities can be accomplished within a day. The essential nature o the community health service should be such activities as health promotion, preventive measures, medical care, and rehabilitation performing efficiently through the organized efforts of the residents in a community. Each service activity should cover all members of the residents in a community in its plan and performance. The cooperation of the community peoples in one of the essential elements for success of the service program, The motivations of their cooperative mood may be activated through several ways: when the participation of the residents in service program of especially the direct participation of organized cooperation of the area leaders art achieved through a means of health education: when the residents get actual experience of having received the benefit of good quality services; and when the health personnels being armed with an idealism that they art working in the areas to help health problems of the residents, maintain good human relationships with them. For the success of a community health service program, a personnel who is in charge of leadership and has an able, a sincere and a steady characters seems to be required in a community. The government should lead and support the community health service programs of the nation under the basis of results appeared in the demonstrative programs so as to be carried out the programs efficiently. Moss of the health problems may be treated properly in the community levels through suitable community health service programs but there might be some problems which art beyond their abilities to be dealt with. To solve such problems each community health service program should be under the referral systems which are connected with health centers, hospitals, and so forth. 3. An approach should be intensively groped to have a physician in each community. The shortage of physicians in rural areas is world-wide problem and so is the Korean situation. In the past the government has initiated a system of area-limited physician, coercion, and a small scale of scholarship program with unsatisfactory results. But there might be ways of achieving the goal by intervice, broadened, and continuous approaches. There will be several ways of approach to motivate the physicians to be settled in a rural community. They are, for examples, to expos the students to the community health service programs during training, to be run community health service programs by every health or medical schools and other main medical facilities, communication activities and advertisement, desire of community peoples to invite a physician, scholarship program, payment of satisfactory level, fulfilment of military obligation in case of a future draft, economic growth and development of rural communities, sufficiency of health and medical facilities, provision of proper medical care system, coercion, and so forth. And, hopefully, more useful reference data on the motivations may be available when a survey be conducted to the physicians who are presently engaging in the rural community levels. 4. In communities where the availability of a physician is difficult, a trial to use physician extenders, under certain conditions, may be considered. The reason is that it would be beneficial for the health of the residents to give them the remedies of primary medical care through the extenders rather than to leave their medical problems out of management. The followings are the conditions to be considered when the physician extenders are used: their positions will be prescribed as a temporary one instead of permanent one so as to allow easy replacement of the position with a physician applicant; the extender will be under periodic direction and supervision of a physician, and also referral channel will be provided: legal constraints will be placed upon the extenders primary care practice, and the physician extenders will used only under the public medical care system. 5. For the balanced health care delivery, a greater investment to the rural areas is needed to compensate weak points of a rurality. The characteristics of a rurality has been already mentioned. The objective of balanced service for rural communities to level up that of urban areas will be hard to achieve without greater efforts and supports. For example, rural communities need mobile powers more than urban areas, communication network is extremely necessary at health delivery facilities in rural areas as well as the need of urban areas, health and medical facilities in rural areas should be provided more substantially than those of urban areas to minimize, in a sense, the amount of patient consultation and request of laboratory specimens through referral system of which procedures are more troublesome in rural areas, and more intensive control measures against communicable diseases are needed in rural areas where greater numbers of cases are occurred under the poor sanitary conditions.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.221-241
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• 2018

As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.1
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• pp.31-38
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• 2020

The characteristics of ship traffic routes and the long term fluctuation in marine traf ic volume of the incoming and outgoing routes of the Yeosu Gwangyang Port were analyzed using vessel traffic data from the past 22 years and a real-time vessel traffic volume survey performed for 72 hours per year, for three years, between 2015 and 2017. As of 2017, the number of vessels passing through Yeosu Gwangyang Port was about 66,000 and the total tonnage of these ships was about 804,564 thousand tons, which is a 400 % increase from the 189,906 thousand tons shipped in 1996. Specifically, the dangerous cargo volume was 140,000 thousand tons, which is a 250 % increase compared to 1996. According to the real-time vessel traffic volume survey, the average daily number of vessels was 357, and traf ic route utilization rates were 28.1 % in the Nakpo sea area, 43.8 % in the specified sea area, and the coastal area traf ic route, Dolsan coastal area, and Kumhodo sea area showed the same rate of 6.8 %. Many routes meet in the Nakpo sea area and, parallel and cross passing were frequent. Many small work vessels entered the specific sea area from the neighboring coastal area traffic route and frequently intersected the path of larger vessels. The anchorage waiting rate for cargo ships was about 24 %, and the nightly passing rate for dangerous cargo ships such as chemical vessels and tankers was about 20 %. Although the vessel traffic volume of Yeosu Gwangyang Port increases every year, the vessel traffic routes remain the same. Therefore, the risk of accidents is constantly increasing. The route conditions must be improved by dredging and expanding the available routes to reduce the high risk of ship accidents due to overlapping routes, by removing reefs, and by reinforcing navigational aids. In addition, the entry and exit time for dangerous cargo ships at high-risk ports must be strictly regulated. Advancements in the VTS system can help to actively manage the traffic of small vessels using the coastal area traffic route.