• Journal of Legislation Research
• /
• no.53
• /
• pp.593-631
• /
• 2017

Like the technological competition of each country around commercialization of Autonomous Vehicles(the rest is 'AV'), legalizations are also in a competition. However, in the midst of this competition, the Ethik-Kommission Automatisiertes und vernetztes Fahren of Germany has recently introduced 20 guidelines. This guideline is expected to serve as a milestone for future AV legislations. In this paper, I have formulated a new legislative proposal that will incorporate the main content presented by the Ethik-Kommission. The structure is largely divided into general rules of purpose and definition, chapter on types of AV and safety standards, registration and inspection, maintenance, licenses for AV, driver's obligations, insurance and accident responsibilities, roads and facilities, traffic system, and chapter on penalties. The commercialization of AV in Korea seems to be in a distant future, and it is possible to pretend that it is not necessary to prepare legal systems. But considering our reality, leading legislation may be necessary. In this paper, I have prepared individual legislative proposals based on the essential matters based on the criminal responsibility in case of AV car accidents. To assure the safety of AV, AV and mode of operation were defined for more clear interpretation and application of law, and basic safety standards for AV were presented. In addition, the obligation of insurance and the liability for damages were defined, and the possibility of immunity from the criminal responsibility was examined. Furthermore, I have examined the penalties for penalties such as hacking in order to secure the effectiveness of the Act. Based on these discussions, I have attempted the 'Autonomous Vehicles Act', which aims to provide a basis for new discussions to be held on the basis of various academic fields related to the operation of AV and related industries in the future. Although there may be a sense of unurgency in time, the automobile industry needs time to prepare for the regulation of the AV ahead of time. And a process of public debate is also needed for the ecosystem of healthy AV industry.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.4
• /
• pp.228-234
• /
• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• KEPCO Journal on Electric Power and Energy
• /
• v.4 no.2
• /
• pp.115-123
• /
• 2018

Various types of robots running on power transmission lines have been developed for the purpose of line patrol monitoring. They usually have complex mechanism to run and avoid obstacles on the power line, but nevertheless did not show satisfactory performance for going over the obstacles. Moreover, they were so heavy that they could not be easily installed on the lines. To compensate these problems, flying robots have been developed and recently, multi-copter drones with flight stability have been used in the electric power industry. The drones could be remotely controlled by human operators to monitor power distribution lines. In the case of transmission line patrol, however, transmission towers are huge and their spans are very long, and thus, it is very difficult for the pilot to control the patrol drones with the naked eye from a long distance away. This means that the risk of a drone crash onto electric power facilities always resides. In addition, there exists another danger of electromagnetic interference with the drones on autopilot waypoint tracking under ultra-high voltage environments. This paper presents a patrol monitoring plan of autopilot drones for power transmission lines and its field tests. First, the magnetic field effect on an autopilot patrol drone is investigated. Then, how to build the flight path to avoid the magnetic interference is proposed and our autopilot drone system is introduced. Finally, the effectiveness of the proposed patrol plan is confirmed through its field test results in the 154 kV, 345 kV and 765 kV transmission lines in Chungcheongnam-do.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.7
• /
• pp.225-233
• /
• 2021

This study quantitatively compares and analyzes lower extremity muscle activity and motor neurons by performing blood flow-restricting aerobic training in the lower extremities, which is closely related to aerobic capacity for health, in normal people, and provides basic data to suggest the effectiveness of an effective blood-restricting exercise program. would like to provide A group of 10 people who applied aerobic exercise on a treadmill by restricting blood flow to 140 mmHg of pressure was set as Experimental Group I. And 11 people who applied only aerobic exercise on a treadmill were randomly assigned as a control group. The intervention program was implemented on a treadmill for 4 weeks, 3 times a week, once a day, for 30 minutes once. In addition, muscle activity and motor neurons were measured and analyzed using surface electromyography before intervention. As a result of the study, the muscle activity of the rectus femoris, biceps femoris, tibialis anterior and gastrocnemius was significantly increased (p<.001) in the pre-and-poster comparison within the group of experimental group I (p<.001). In the pre-and-poster comparison of the control group, the muscle activity of the rectus femoris, biceps femoris, tibialis anterior and gastrocnemius was significantly increased (p<.001). In comparison of changes between groups, there was a significant difference in the activity of the rectus femoris muscle (p<.05). Combining aerobic exercise in parallel with lower extremity blood flow restriction can be developed into an injury prevention exercise program that can restore functional activity in rehabilitation training for elite athletes and elderly people with weak joints. In addition, based on these results in future research, it is considered that it is necessary to expand the scope of non-normal subjects and conduct various studies according to the pressure intensity.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.39-58
• /
• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Journal of Global Scholars of Marketing Science
• /
• v.20 no.1
• /
• pp.80-88
• /
• 2010

There has been considerable research examining the relationship between stockholders equity and various marketing strategies. These include studies linking stock price performance to advertising, customer service metrics, new product introductions, research and development, celebrity endorsers, brand perception, brand extensions, brand evaluation, company name changes, and sports sponsorships. Another facet of marketing investments which has received heightened scrutiny for its purported influence on stockholder equity is television advertisement embedded within specific sporting events such as the Super Bowl. Research indicates that firms which advertise in Super Bowls experience stock price gains. Given this reported relationship between advertising investment and increased shareholder value, for both general and special events, it is surprising that relatively little research attention has been paid to investigating the relationship between advertising in the Olympic Games and its subsequent impact on stockholder equity. While attention has been directed at examining the effectiveness of sponsoring the Olympic Games, much less focus has been placed on the financial soundness of advertising during the telecasts of these Games. Notable exceptions to this include Peters (2008), Pfanner (2008), Saini (2008), and Keller Fay Group (2009). This paper presents a study of Olympic advertisers who ran TV ads on NBC in the American telecasts of the 2000, 2004, and 2008 Summer Olympic Games. Five hypothesis were tested: H1: The stock prices of firms which advertised on American telecasts of the 2008, 2004 and 2000 Olympics (referred to as O-Stocks), will outperform the S&P 500 during this same period of time (i.e., the Monday before the Games through to the Friday after the Games). H2: O-Stocks will outperform the S&P 500 during the medium term, that is, for the period of the Monday before the Games through to the end of each Olympic calendar year (December 31st of 2000, 2004, and 2008 respectively). H3: O-Stocks will outperform the S&P 500 in the longer term, that is, for the period of the Monday before the Games through to the midpoint of the following years (June 30th of 2001, 2005, and 2009 respectively). H4: There will be no difference in the performance of these O-Stocks vs. the S&P 500 in the Non-Olympic time control periods (i.e. three months earlier for each of the Olympic years). H5: The annual revenue of firms which advertised on American telecasts of the 2008, 2004 and 2000 Olympics will be higher for those years than the revenue for those same firms in the years preceding those three Olympics respectively. In this study, we recorded stock prices of those companies that advertised during the Olympics for the last three Summer Olympic Games (i.e. Beijing in 2008, Athens in 2004, and Sydney in 2000). We identified these advertisers using Google searches as well as with the help of the television network (i.e., NBC) that hosted the Games. NBC held the American broadcast rights to all three Olympic Games studied. We used Internet sources to verify the parent companies of the brands that were advertised each year. Stock prices of these parent companies were found using Yahoo! Finance. Only companies that were publicly held and traded were used in the study. We identified changes in Olympic advertisers' stock prices over the four-week period that included the Monday before through the Friday after the Games. In total, there were 117 advertisers of the Games on telecasts which were broadcast in the U.S. for 2008, 2004, and 2000 Olympics. Figure 1 provides a breakdown of those advertisers, by industry sector. Results indicate the stock of the firms that advertised (O-Stocks) out-performed the S&P 500 during the period of interest and under-performed the S&P 500 during the earlier control periods. These same O-Stocks also outperformed the S&P 500 from the start of these Games through to the end of each Olympic year, and for six months beyond that. Price pressure linkage, signaling theory, high involvement viewers, and corporate activation strategies are believed to contribute to these positive results. Implications for advertisers and researchers are discussed, as are study limitations and future research directions.

• Korean Journal of Soil Science and Fertilizer
• /
• v.8 no.2
• /
• pp.89-96
• /
• 1975

The experiment was carried out to investigate the chemical properties of cement kiln dusts, abundantly produced from cement industry as a byproduct, and their effectiveness on rice yield. The field experiment was conducted on the acid paddy soil developed on basalt at Dongsong-Myon, Chulwon-Kun, Gangwon-Do. Two kinds of cement kiln dusts were used ; By Pass (BP) collected from the suspension preheater and Electric Precipitate (EP) from the cottrell electric precipitator. The levels of cement kiln dust applied were 100kg/10a, 200kg/10a and 300kg/10a, and the recommended variety "Nong Back" was adopted for this experiment. The results obtained are summarized as follows ; 1. The component of cement kiln dusts seems to be quite suitable for liming material. BP has 55% alkalinity, 41.7% of soluble calcium, 9.8% of soluble magnesium and 4.5% of water soluble silicate, while EP has 53.5% alkalinity, 41.7% soluble calcium, 8.3% soluble magnesium and 1% water soluble silicate. 2. The relative effectiveness of cement kiln dust in the soil will be superior due to very fine particle size. EP pass through completely 270 mesh screen, and 95% of BP pass through 150 mesh screen, 68% passing 270 mesh. 3. BP application at the rate of 100kg/10a increased 21% of rice yield as compared with control and EP 15%. It was observed that the affected yield components were increased panicle number per hill, grain number per panicle and 1,000 grains weight. 4. The application of optimum amount (100kg/10a) of cement kiln dusts accelerated the uptake of nutrients by rice plant and increased rice yield. However, the excess amounts (200kg/10a, 300kg/10a) of cement kiln dusts retarded the uptake of nutrients from soil.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.13 no.3
• /
• pp.125-140
• /
• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.47-67
• /
• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Korean Chemical Engineering Research
• /
• v.56 no.1
• /
• pp.6-13
• /
• 2018

Utilizing the heat of cooling water discharge of coal-fired power plant, pipeline investment costs for businesses that supply heat to agricultural facilities near power plants increase in proportion to installation distance. On one hand, the distance from the power plant is a factor that brings difficulties to secure economic efficiency. On the other, if the installation distance is short, there is a problem of securing the heating demands, facility houses, which causes economical efficiency to suffer. In this study, the economic efficiency of 1km length of standard heat pipeline was evaluated. The sensitivity of the heat pipe to the new length variation was analyzed at the level of government subsidy, amount of heating demand and the incremental rate of pipeline with additional government subsidy. As a result of the analysis, it was estimated that NPV 131 million won and IRR 15.73%. The sensitivity analysis showed that NPV was negative when the length of heat pipe facility exceeded 2.6 km. If the government supports 50% of the initial investment, the efficiency is secured within the estimated length of 5.3 km, and if it supports 80%, the length increases within 11.4 km. If the heat demand is reduced to less than 62% at the new length of the standard heat pipe, it is expected economic efficiency is not obtained. If the ratio of government subsidies to initial investment increases, the elasticity of the new bloc will increase, and the fixed investment, which is the cost of capital investment for one unit of heating demand, will decrease. This would result in a reduction in the cost of production per unit, and it would be possible to supply heat at a cheaper price level to the facility farming. Government subsidies will result in the increased economic availability of hot plumbing facilities and additional efficiencies due to increased demand. The greater government subsidies to initial investment, the less farms cost due to the decrease in the price per unit. The results of the study are significant in terms of the economic evaluation of the effectiveness of the government subsidy for the thermal power plant heat utilization project. The implication can be applied to any related pilot to come.