• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.133-144
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• 2004

A model and a measure which can evaluate the risk of rear end collision are developed. Most traffic accidents involve multiple causes such as the human factor, the vehicle factor, and the highway element at any given time. Thus, these factors should be considered in analyzing the risk of an accident and in developing safety models. Although most risky situations and accidents on the roads result from the poor response of a driver to various stimuli, many researchers have modeled the risk or accident by analyzing only the stimuli without considering the response of a driver. Hence, the reliabilities of those models turned out to be low. Thus in developing the model behaviors of a driver, such as reaction time and deceleration rate, are considered. In the past, most studies tried to analyze the relationships between a risk and an accident directly but they, due to the difficulty of finding out the directional relationships between these factors, developed a model by considering these factors, developed a model by considering indirect factors such as volume, speed, etc. However, if the relationships between risk and accidents are looked into in detail, it can be seen that they are linked by the behaviors of a driver, and depending on drivers the risk as it is on the road-vehicle system may be ignored or call drivers' attention. Therefore, an accident depends on how a driver handles risk, so that the more related risk to and accident occurrence is not the risk itself but the risk responded by a driver. Thus, in this study, the behaviors of a driver are considered in the model and to reflect these behaviors three concepts related to accidents are introduced. And safe stopping distance and accident occurrence probability were used for better understanding and for more reliable modeling of the risk. The index which can represent the risk is also developed based on measures used in evaluating noise level, and for the risk comparison between various situations, the equivalent risk level, considering the intensity and duration time, is developed by means of the weighted average. Validation is performed with field surveys on the expressway of Seoul, and the test vehicle was made to collect the traffic flow data, such as deceleration rate, speed and spacing. Based on this data, the risk by section, lane and traffic flow conditions are evaluated and compared with the accident data and traffic conditions. The evaluated risk level corresponds closely to the patterns of actual traffic conditions and counts of accident. The model and the method developed in this study can be applied to various fields, such as safety test of traffic flow, establishment of operation & management strategy for reliable traffic flow, and the safety test for the control algorithm in the advanced safety vehicles and many others.

• Korean Journal of Heritage: History & Science
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• v.44 no.1
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• pp.138-161
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• 2011

The 'Jwasuyeongseongji' (Site of naval wall-fortress in Suyeong) in Busan is the subject of this study. It has been desturbed mostly, and is named 'Suyeong historic site'. One of the important aspects of 'Jwasuyeongseongji' is that it was a historic place confronting with the Japanese Invasion of Chosun in 1592. This was the place where the Japanese Invasion of Chosun broke out and a number of people were slaughtered by the Japanese invaders. Now the place is converted to a playground. Although 'Jwasuyeongseongji' is the place of historic interest, the forest area is separated by paths and sidewalks. Further, there are sports facilities and relaxing people. Examples of advanced countries show that the abuse like Jwaisuyeongseongji is thoroughly prohibited. Although the Dangsan forest of jwasuyeongseongji remains in the megalopolis of Busan, it has been damaged and abused in spite of being a historic site. Nevertheless, Jwasuyeongseongji is an invaluable traditional cultural heritage. The objective of this study was to search for solutions of authenticity restoration for the remains of Dangsan forest at Jwasuyeongseongji in Busan. The Dangsan forest at Jwasuyeongseongji is a forest of Pinus thunbergii in an area of $130{\times}230m$. Jwasuyeongseongji is currently named Suyeong historic park, and is registered as monuments No. 8 by Suyeong-gu, Busan. The two Dangsan trees at Jwasuyeongseongji are registered as natural monuments No. 270 and No. 311. The complex management system needs to be designated as 'Dangsan forest of Jwasuyeongseongji in Busan', and managed as a natural monument or national historic site. Dangsan forest has a meaning of divine place. Therefore, the artificial facilities need to be removed from Dangsan forest so that the original features are restored with the spirit of Jwasuyeongseongji. Also, the administration needs to be transfered from Suyeong-gu, Busan to the Cultural Heritage Administration.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• Korean Journal of Weed Science
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• v.12 no.1
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• pp.70-79
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• 1992

From the beginning of the chosun dynasty, an agriculture-first policy was imposed by being written farming books, for instance, Nongsajiksul, matched with real conditions of local agriculture, which provided the grounds of new, intensive farming technologies. This farming book was the collection of good fanning technologies that were experienced in rural farm areas at that time. According to Nongsajiksul, rice culture systems were divided into "Musarmi"(Water-Seeded rice), /"Kunsarmi"(dry-seeded rice), /transplanted rice and mountainous rice (upland rice) culture. The characteristics of these rice cultures with high technologies were based of scientific weeding methods, improved fertilization, and cultivation works using cattle power and manpower tools systematically. Reclamation of coastal swampy and barren land was possible in virtue of fire cultivation farming(火耕) and a weeding tool called "Yoonmok"(輪木). Also, there was an improved hoe to do weeding works as well as thinning and heaping-up of soil at seeding stages of rice. Direct-seeded rice culture in flat paddy fields were expanded by constructing the irrigation reservoirs and ponds, and the valley paddy fields was reclaimed by constructing "Boh(洑)". These were possible due to weed control by irrigation waters, keeping soil fertility by inorganic fertilization during irrigation, and increased productivity of rice fields by supplying good physiological conditions for rice. Also, labor-saving culture of rice was feasible by transplanting but in national-wide, rice should not basically be transplanted because of the restriction of water use. Thus, direct-seeded rice in dry soils was established, in which rice was direct-seeded and grown in dry soils by seedling stages and was grown in flooded fields when rained, as in the book "Nongsajiksul". During the middle of the dynasty(AD 1495-1725), the excellent labor-saving farmings include check-rowing transplanting because of weeding efficiency and availability in rice("Hanjongrok"), and, nurserybed techniques (early transplanting of rice) were emphasized on the basis of rice transplanting ["Nongajibsung"]. The techniques for deep plowing with cattle powers and for putting more fertilizers were to improve the productivity of labor and land, The matters advanced in "Sanlimkyungje" more than in "Nongajibsung" were, development of "drybed of rice nursery stock", like "upland rice nursery" today, transplanting, establishment of "winter barly on drained paddy field, and improvement of labor and land-productivity in rice". This resulted in the community of large-scale farming by changing the pattern of small-farming into the production system of rice management. Woo-hayoung(1741-1812) in his book "Chonilrok" tried to reform from large-scale farmings into intensive farmings, of which as eminent view was to divide the land use into transplanting (paddy) and groove-seeding methods(dry field). Especially as insisted by Seo-yugo ("Sanlimkyungjeji"), the advantages of transplanting were curtailment of weeding labors, good growth of rice because of soil fertility of both nurserybed and paddy field, and newly active growth because rice plants were pulled out and replanted. Of course, there were reestimation of transplanting, limitation of two croppings a year, restriction of "paddy-upland alternation", and a ban for large-scale farming. At that period, Lee-jiyum had written on rice farming technologies in dry upland with consider of the land, water physiology of rice, and convenience for weeding, and it was a creative cropping system to secure the farm income most safely. As a integrated considerations, the followings must be introduced to practice the improved farming methods ; namely, improvement of farming tools, putting more fertilizers, introduction of cultural technologies more rational and efficient, management of labor power, improvement of cropping system to enhance use of irrigation water and land, introduction of new crops and new varieties.

• 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 Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.