• Journal of Legislation Research
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• 제53호
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• pp.269-310
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• 2017

This article aims at the study on Improvement of legal System which is related to automated vehicles in the era of the 4th industrial revolution. Legal aspects of driving automation have two view points. One is to permit a automated vehicle, the other is to regulate the behavior of driver on the road. Signifying elements of the 4th industrial revolution are IoT, AI, big data, cloud computing etc. Automated vehicles are the imbodiment of those new ICT technologies. The vehicle management act(VMA) rules about vehicle registration and approval of vehicle types. VMA defines a automated vehicle as a vehicle which can be self driven without handling of driver or passenger. Vehicle makers can take temporary driving permission for testing and research the driving automation. Current definition of automated vehicle of VMA is not enough for including all levels of SAE driving automation. In the VMA must be made also a new vehicle safty standard for automated vehicle. In the national assembly is curruntly pending three draft bills about legislation of artificial intelligence. Driving automation and AI technologies must be parallel developed. It is highly expected that more proceeding research of driving automation can be realized as soon as possible.

• The Journal of Traditional Korean Medicine
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• 제15권1호
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• pp.128-144
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• 2006

This Study aims at looking into the use of oriental medical services in treating hypertension. The first objective to be explored through this study is the morbidity caused by the disease, classifying them by age, gender, and occupation. The second is to determine the regular use of anti-hypertensive medicine and their efficacy in controlling blood-pressure. The third is to investigate the use-rate and satisfaction of oriental medical service. 838 households across the country, were asked to answer questionnaires for the period of time from Apr. to Jun. 2005. The conclusion from the survey can be summarized as following. The age of which the first medical diagnosis of hypertension were made showed lower in males, those with higher education and income. The study showed females were more active in blood-pressure control, with their frequent monitoring of blood-pressure for the past year. With age, people in under 50 age group proved to be less active. The management of high blood pressure was more effective in group with regular dosage compared to group with irregular use of anti-hypertensive medication, but their difference was minimal. Also, group with no medication showed signs of blood-pressure control. The use of oriental medical service for the past year, were more frequent in groups with lower education, either low or high income, old age, females and occupations in agriculture, forestry and fishing industry. Results were similar in both general population and high blood-pressure patient group. Females, people over 51 years old and with lower education showed more intentions in utilizing oriental medical services in the future. Results were similar in both general population and high blood-pressure patient group. It is necessary to offer a more accurate information on oriental medical treatments. Also, a systematic reform to reduce the patient's share of the treatment cost, as well as, heightening public awareness on the infirmity of present blood-pressure management system is crucial.

• Journal of Korea Trade
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• 제25권7호
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• pp.92-107
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• 2021

Purpose - This paper analyzes the relationship between trade facilitation and agricultural products exports and estimates the effects of trade facilitation in importing countries on Chinese agricultural products exports, which is of great significance for promoting agricultural trade between China,Japan and Korea and the governments of the three countries to formulate targeted trade facilitation policies. Design/methodology - Based on Wilson (2003) theoretical framework, this paper sets up its own trade facilitation level measurement system by involving four primary indicators and fifteen secondary indicators to evaluate the trade facilitation levels of Japan and Korea from 2011 to 2018 respectively. The paper selected the data on China's agricultural exports at the HS4 level from 2011-2018 and used a fixed-effects model to estimate the effect of changes in trade facilitation levels in trading partner countries on China's agricultural trade. Findings - Our main findings can be summarized as follows: the level of trade facilitation in importing countries has a significantly positive effect on China's agricultural exports. The higher the level of trade facilitation in trading partner countries, the more Chinese agricultural exports trade, i.e. for every 1 percentage point increase in the level of trade facilitation, the volume of exports will increase by 2.299%.The sub-sample test shows that China's main agricultural products exported to Japan and Korea, such as aquatic products, vegetables, fruits and other perishable fresh products, are particularly significantly affected by the level of trade facilitation. Originality/value - First, from the innovation of the research perspective, which is different from the analysis of the existing paper on the overall trade facilitation of all traded commodities. This article is based on the close trade relations between China, Japan and Korea, and the particularity of agricultural products, from the perspective of China's agricultural exports to Japan and Korea, discuss the impact of importing countries-Japan and Korea's trade facilitation levels on China's agricultural exports;Secondly, in this paper, the hierarchical data of the HS4 quartile is used to avoid the information loss of the industry, and to analyse the impact of the importing country's trade facilitation level on the export of different types of agricultural products more scientifically.

• Korean Journal of Construction Engineering and Management
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• 제20권2호
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• pp.3-12
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• 2019

Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures.

• Clean Technology
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• 제24권4호
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• pp.269-274
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• 2018

In this study, Life Cycle Assessment (LCA) of wet tissue manufacturing process was performed. The wet tissue manufacturing process consists of preparation of wetting agent (chemical liquid), impregnation of nonwoven fabric into wetting agent and primary and secondary packaging. Data and information were collected on the input and output of the actual process from a certain company and the database of the Korea Ministry of Environment and some foreign countries (when Korean unavailable) were employed to connect the upper and the lower process flow. Based on the above and the potential environmental impacts of the wet tissue manufacturing process were calculated. As a result of the characterization, Ozone Layer Depletion (OD) is 3.46.E-06 kg $CFC_{11}$, Acidification (AD) is 5.11.E-01 kg $SO_2$, Abiotic Resource Depletion (ARD) is $3.52.E+00\;1yr^{-1}$, Global Warming (GW) is 1.04.E+02 kg $CO_2$, Eutrophication (EUT) is 2.31.E-02 kg ${PO_4}^{3-}$, Photochemical Oxide Creation (POC) was 2.22.E-02 kg $C_2H_4$, Human Toxicity (HT) was 1.55.E+00 kg 1,4 DCB and Terrestrial Ecotoxicity (ET) was 5.82.E-04 kg 1,4 DCB. In order to reduce the environmental impact of the manufacturing process, it is necessary to improve the overall process as other general cases and change the raw materials including packaging materials with less environmental impact. Conclusively, the energy consumed in the manufacturing process has emerged as a major issue, and this needs to be reconsidered other options such as alternative energy. Therefore, it is recommended that a process system should be redesigned to improve energy efficiency and to change to an energy source with lower environmental impact. Due to the nature of LCA, the final results of this study can be varied to some extent depending on the type of LCI DB employed and may not represent of all wet tissue manufacturing processes in the current industry.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제18권1호
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• pp.43-55
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• 2019

Smart phone based navigation applications are very useful in everyday life. Cost-effective and user friendly navigation can be provided to the user by many applications available in market. Using the Smart phone these navigation applications provide accurate navigation for outdoor locations. But providing an accurate navigation underground space such as subway station is still a challenge. It is hence more convenient and appropriate for mobility services if the visitors could simply view the guidance of the subway station on their mobile phone, wherever and whenever it is needed. This study develops a algorithm for indoor navigation with the help of Augmented Reality(AR) and QR marker code from the entrance to the train platform for users. This indoor navigation uses AR and QR maker codes for two purposes: to provide the user link to the subway station location and to provide the current guidance details to the user. This Smart phone algorithm that uses a smart phone optical tool to decode the QR marker to determine the location information and provide guidance to the AR without indoor Maps. This algorithm also provides a module to guide mobility vulnerable to the Barrier Free route to destination.

• Journal of Cadastre & Land InformatiX
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• 제49권1호
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• pp.85-101
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• 2019

Recently, thank to the popularization of light-weight drone through the significant developments in computer technologies as well as the advanced automated procedures in photogrammetry, Unmanned Aircraft Systems have led to a growing interest in industry as a whole. Documentation, maintenance, and restoration projects of large scaled cultural property would required accurate 3D phenomenon modeling and efficient visual inspection methods. The object of this study verify on the accuracies achieved of 3D phenomenon reconstruction as well as on the validity of the preservation, maintenance and restoration of large scaled cultural property by UAS photogrammetry. The test object is cltural heritage(treasure 1324) that is the rock-carved standing Bodhisattva in Soraesan Mountain, Siheung, documented in Goryeo Period(918-1392). This standing Bodhisattva has of particular interests since it's size is largest stone Buddha carved in a rock wall and is wearing a lotus shaped crown that is decorated with arabesque patterns. The positioning accuracy of UAS photogrammetry were compared with non-target total station survey results on the check points after creating 3D phenomenal models in real world coordinates system from photos, and also the quantified informations documented by Culture Heritage Administration were compared with UAS on the bodhisattva image of thin lines. Especially, tests the validity of UAS photogrammetry as a alternative method of visual inspection methods. In particular, we examined the effectiveness of the two techniques as well as the relative fluctuation of rock surface for about 2 years through superposition analysis of 3D points cloud models produced by both UAS image analysis and ground laser scanning techniques. Comparison studies and experimental results prove the accuracy and efficient of UAS photogrammetry in 3D phenomenon modeling, maintenance and restoration for various large-sized Cultural Heritage.

• Journal of Korean Society on Water Environment
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• 제35권3호
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• pp.224-233
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• 2019

Nitrogen components in liquid manure can reduce safety and quality of environment harmfully. To minimize the environmental risks of manure, understanding fate of manure in environment is necessary. This study aimed at investigating applicability of a simplified Level III fugacity model for simulating $NH_3-N$ component to analyze environmental fate and transport of $NH_3-N$ in liquid manure and to provide basis for improving management of N in the liquid manure system and for minimizing the environmental impacts of N. The model simulation conducted for four environmental compartments (air, water, soil, and rice plants) during rice-cropping to trace $NH_3-N$ component and provided applicability of the Level III fugacity model in studying the environmental fate of $NH_3-N$ in manure. Most of $NH_3-N$ was found in water body and in rice plants depending upon the physicochemical properties and proper removal processes. For more precise model results, the model is needed to modify with the detailed removal processes in each compartment and to collect proper and accurate information for input parameters. Further study should be about simulations of various N-typed fertilizers to compare with the liquid manure based on a modified and relatively simplified Level III fugacity model.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제22권3호
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• pp.446-452
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• 2021

As a higher standard for food consumption is required, the consumption of chicken meat that can satisfy the subdivided food preferences is increasing. In March 2003, the quality criteria for chicken carcasses notified by the Livestock Quality Assessment Service suggested quality grades according to fecal contamination and the size and weight of blood and bruises. On the other hand, it is too difficult for human inspection to qualify mass products, which is key to maintaining consistency for grading thousands of chicken carcasses. This paper proposed the computer vision algorithm as a non-destructive inspection, which can identify chicken carcass parts according to the detailed standards. To inspect the chicken carcasses conveyed at high speed, the image calibration was involved in providing robustness to the side effect of external lighting interference. The separation between chicken and background was achieved by a series of image processing, such as binarization based on Expectation Maximization, Erosion, and Labeling. In terms of shape analysis of chicken carcasses, the features are presented to reveal geometric information. After applying the algorithm to 78 chicken carcass samples, the algorithm was effective in segmenting chicken carcass against a background and analyzing its geometric features.

• The Journal of the Convergence on Culture Technology
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• 제8권2호
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• pp.385-391
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• 2022

Quality evaluation of beef carcasses is an important issue in the livestock industry. Recently, through the AI monitor system based on artificial intelligence, the quality manager can receive help in making accurate decisions based on the analysis of beef carcass images or result information. This artificial intelligence dataset is an important factor in judging performance. Existing datasets may have different surface orientation or resolution. In this paper, we proposed a two-stage classification model that can efficiently manage the grades of beef carcass image using deep learning. And to overcome the problem of the various conditions of the image, a new dataset of 1,300 images was constructed. The recognition rate of deep network for 5-grade classification using the new dataset was 72.5%. Two-stage evaluation is a method to increase reliability by taking advantage of the large difference between grades 1++, 1+, and grades 1 and 2 and 3. With two experiments using the proposed two stage model, the recognition rates of 73.7% and 77.2% were obtained. As this, The proposed method will be an efficient method if we have a dataset with 100% recognition rate in the first stage.