• The Korean Journal of Air & Space Law and Policy
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• v.30 no.1
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• pp.207-244
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• 2015

Aviation safety is the stage in which the risk of harm to persons or of property damage is reduced to, and maintained at or below, an acceptable level through a continuing process of hazard identification and risk management. Many accidents and incidents have been taking place since 2014, while there had been relatively safer skies before 2014. International civil aviation community has been exerting great efforts to deal with these emerging issues, thus enhancing and ensuring safety throughout the world over the years. The Preamble of the Chicago Convention emphasizes safety and order of international air transport, and so many Articles in the Convention are related to the safety. Furthermore, most of the Annexes to the Convention are International Standards and Recommended Practices pertaining to the safety. In particular, Annex 19, which was promulgated in Nov. 2013, dealing with safety management system. ICAO, as law-making body, has Air Navigation Commission, Council, Assembly to deliberate and make decisions regarding safety issues. It is also implementing USOAP and USAP to supervise safety functions of member States. After MH 370 disappeared in 2014, ICAO is developing Global Tracking System whereby there should be no loophole in tracking the location of aircraft anywhere in world with the information provided by many stakeholders concerned. MH 17 accident drove ICAO to install web-based repository where information relating to the operation in conflict zones is provided and shared. In addition, ICAO has been initiating various solutions to emerging issues such as ebola outbreak and operation under extreme meteorological conditions. Considering the necessity of protection and sharing of safety data and information to enhance safety level, ICAO is now suggesting enhanced provisions to do so, and getting feedback from member States. It has been observed that ICAO has been approaching issues towards problem-solving from four different dimensions. First regarding time, it analyses past experiences and best practices, and make solutions in short, mid and long terms. Second, from space perspective, ICAO covers States, region and the world as a whole. Third, regarding stakeholders it consults with and hear from as many entities as it could, including airlines, airports, community, consumers, manufacturers, air traffic control centers, air navigation service providers, industry and insurers. Last not but least, in terms of regulatory changes, it identifies best practices, guidance materials and provisions which could become standards and recommended practices.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Teachers' Pension
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• v.3
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• pp.69-105
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• 2018

저출산과 고령화 이슈는 우리사회의 경제적 문제뿐만 아니라 공적연금의 재정지속가능성 여부와도 맞물려 있다. 실제로 우리나라 모든 공적연금은 사회보험역설(social insurance paradox)이 지속되기 힘든 새로운 도전에 직면하였다. 즉, 재정지속가능성은 제도 내적 연금개혁 혹은 제도 외적 재정지원이 없다면 항시적 수지불균형 상태가 누적될 것으로 예측된다. 이에 정부는 직접 고용과 관련된 공무원연금과 군인연금에 대해서만 연금충당부채를 산출하도록 규정하고 있다. 발생주의회계를 채택한 국제회계기준(종업원급여)을 참조하여 연금충당부채 산출을 위한 연금회계준칙(2011.8.3. 제정; 2011.1.1. 시행) 그리고 '연금회계 평가 및 공시 지침(2011.8.3. 고시 : 이하 편의상 연금회계지침이라 함)'을 신설하였다. 사학연금에 적용성 여부 논의에 앞서, 이들의 산출방법상의 문제점을 먼저 살펴보았다. 첫째, 공적연금은 공통적으로 세대 간 합의에 의해 운영되는 사회계약에 해당하므로 제도의 연속성을 전제로 한다. 하지만 연금회계준칙 및 지침은 제도의 청산을 전제로 현재 가입자(연금 미수령자, 연금 수령자)에 대해서 연금충당부채를 산출하는 폐쇄형측정(closed group valuation)을 채택하고 있다. 즉, 폐쇄형은 제도의 연속성 속성을 반영하고 있지 못하고 있어 기본 전제와 모순된다. 둘째, 공무원연금과 군인연금은 이미 기금 소진(최소한의 유동성기금만 보유함)이 되었고 정부의 보전금에 의해 수지 균형이 유지되는 순수부과방식 체계로 전환되었다. 따라서 연금충당부채는 해당 적립기금의 과소 여부를 판정하는 재정상태 기준 값에 해당하므로 기금소진이 진행된 현 상황에서는 산출의 목적, 필요성을 찾기가 힘들다. 부언하면, 제도 외적 재정지원(보전금)에 의한 수지균형방식이라면 발생주의회계보다는 현금주의회계가 회계의 목적적합성이 높다. 마지막으로 연금충당부채 산출에 있어 가장 민감한 할인율 설정 권한을 기재부장관에게 위임한 내용은 산출의 객관성, 일관성을 확보하기 힘들다고 판단된다. 이를 해소하기 위한 방안으로 본 연구에서는 5년마다 실시하고 있는 장기재정계산에서 예측된 명목 기금투자수익률을 연도별로 적용할 것을 권고하고 있다. 현행 정부회계기준을 사학연금제도에 그대로 적용하기에는 상당한 무리가 있다. 그 이유와 공시방안에 대해 살펴본다. 현재 사학연금은 기금소진 이슈로부터 상당부분 벗어나기 위해 2015년 연금개혁을 단행한 바가 있고 이를 통해 상당기간 부분적립방식 체계가 유지될 것이다. 물론 제도 외적 재정지원은 사학연금법 제53조의7에서 정부지원의 가능성만을 열어 놓은 상태이므로 미래기금소진의 가능성은 상존한다고 볼 수 있다. 먼 미래에는 순수부과방식 체계로 전환될 개연성이 높다. 이러한 재정의 양면성을 본 연구에서는 이중재정방식(dual financing system)이라고 한다. 이러한 속성을 고려하여 연금충당부채(연금채무라는 표현이 적합할 것으로 사료됨)를 산출하고 공시하여야 한다. 그 주요 연구 결과는 다음과 같이 요약된다. 먼저 현행 부분적립방식의 재정상태 검증을 위해 연금채무를 산정할 필요성이 있다. 이를 위해 본 연구에서는 기발생주의(예측단위방식 적용)에 근거한 폐쇄형 측정I(제도 종료를 전제로 현 가입자의 잠재연금채무(IPD) 산출에 초점을 둠) 그리고 미래발생주의(가입연령방식 적용)에 근거한 폐쇄형 측정II(추가적으로 현 가입자의 일정기간 급여 및 기여 발생 허용)을 제안하고 있다. 이를 통해 미적립채무의 규모 그리고 이를 해소하기 위한 상각부담률을 산출할 수 있다. 최종적으로 미래 가입자들까지 포함하고 기금소진 가능성까지 고려하는 개방형측정(open group valuation)을 다루고 있다. 단, 본 연구에서는 공무원연금처럼 기금부족분에 대해서 향후 정부보전금이 있다는 가정 하에 공시 방법을 제시하고 있다. 요약하면, 현행 사학연금제도는 현재와 미래의 재정 양면성을 모두 고려하여 연금채무 및 미적립채무를 공시하여야 한다. 부언하면, 현재 부분적립방식 재정상태를 반영하는 연금채무는 발생주의회계를 적용하고 미래에 도래할 순수부과방식 재정상태는 현금주의회계를 적용할 것을 최종 결론으로 도출하고 있다. 마지막으로 본 연구의 한계는 정부보전금의 가능성에 대한 법률적 해석과 병행하여 책임준비금 범위의 안정적 확대를 전제로 한 공시 논의 그리고 보전금의 책임한도 범위에 따른 공시 논의 등은 다루고 있지 않다는 점이다. 이러한 논의 사항은 향후 연구과제로 두고자 한다.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.311-320
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• 2007

This paper presents vision-based 3D facial expression animation technique and system which provide the robust 3D head pose estimation and real-time facial expression control. Many researches of 3D face animation have been done for the facial expression control itself rather than focusing on 3D head motion tracking. However, the head motion tracking is one of critical issues to be solved for developing realistic facial animation. In this research, we developed an integrated animation system that includes 3D head motion tracking and facial expression control at the same time. The proposed system consists of three major phases: face detection, 3D head motion tracking, and facial expression control. For face detection, with the non-parametric HT skin color model and template matching, we can detect the facial region efficiently from video frame. For 3D head motion tracking, we exploit the cylindrical head model that is projected to the initial head motion template. Given an initial reference template of the face image and the corresponding head motion, the cylindrical head model is created and the foil head motion is traced based on the optical flow method. For the facial expression cloning we utilize the feature-based method, The major facial feature points are detected by the geometry of information of the face with template matching and traced by optical flow. Since the locations of varying feature points are composed of head motion and facial expression information, the animation parameters which describe the variation of the facial features are acquired from geometrically transformed frontal head pose image. Finally, the facial expression cloning is done by two fitting process. The control points of the 3D model are varied applying the animation parameters to the face model, and the non-feature points around the control points are changed by use of Radial Basis Function(RBF). From the experiment, we can prove that the developed vision-based animation system can create realistic facial animation with robust head pose estimation and facial variation from input video image.

• Journal of Korean Home Economics Education Association
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• v.32 no.4
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• pp.149-170
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• 2020

The purpose of this study was to develop and evaluate a Smart learning-based middle school home economics education plan to improve the online home economics education classes. The educational plan in this study was completed through the process of analysis, design, development, and evaluation. The results of this study are as follows. First, as a result of analyzing consumer life units in the middle school textbooks based on 2015-revised curriculum, Smart learning activities were presented in only two out of the 12 textbooks analyxed. Second, a Smart learning-based middle school home economics education plan was developed in this study with the following characteristics: the topics and contents are structured so that to help learners actively engage in the teaching and learning activities; the education plan to reflects various media and current issues that learners may be interested in; the lesson plans were structured with the premise of online classes; softwares that enable real-time discussion and collaboration are used; and the evaluation method are composed of online activities. Third, the expert evaluation scores for the educational plan and activity materials developed were 4.52 (5-point Likert scale), when averaged across subject, goal, content, teaching/learning activity, and evaluation, and the overall content validity index(CVI) was 0.95. The adequacy of execution, benefit, attractiveness, usefulness, and feasibility were highly with an average of 4.62. Based on the experts' comments, the education plan and activity materials were revised and completed. This study is meaningful in that it developed teaching and learning activities based on online classes after the COVID-19 outbreak, overcoming the limitations of offline classes. It has implications for face-to-face home economics classes due to COVID-19, as it suggests ways to blend online and offline teaching/learning activities depending on the situation.

• Journal of Korea Entertainment Industry Association
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• v.15 no.6
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• pp.35-54
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• 2021

This study examines the characteristics of CBS's Kim Hyun-Jung's News Show(hearafter News Show) and the change to transmedia. The distinguishing characteristics of News Show compared to radio-based current affairs programs are as follows. First, despite its time limit, it adopts the form of investigative reports or investigative documentaries to uncover the truth of the events through 'Detective Son Su-Ho', etc. Second, News show's interviews have avoided biased stance in the reporting of minority issues by interviewing the affected parties anonymously including people involved in incidents and accidents, bereaved families, and other victims. News Show has been producing a transmedia content called 'That Honey Show' (a show that reads comments as fun as honey) since November 2018. 'That Honey Show' is broadcast in real time on YouTube right after the News Show radio broadcast ends. As a form of spin-off content, 'That Honey Show' breaks down the boundaries among staff, MCs, and guests, as well as shifting roles by using 'vice characters'. The female host, Kim conducts interviews with the main characters related to various issues and extends the fixed identity of current affairs shows to the everyday politics and cultural realms. Thus she draws active participation and responses audience. This paper analyzes two representative broadcast cases of 'That Honey Show'-first, the case of resistance and activity of the BTS fandom ARMY in the US presidential election, and, second, the case of reporting on the Nth room incident. This analysis considers the critical participation of digital citizens and the effect of fostering a sense of community in the current affairs show in the transmedia era.

• Journal of The Korean Association For Science Education
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• v.29 no.2
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• pp.137-155
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• 2009

The purpose of the present study was to analyse the effectiveness of a gifted education program. To analyse the effectiveness of an education program for the gifted affiliated with a university, the study carried out a quasi-experimental design to compare the 153 gifted students who enrolled in an education center for the gifted and the 131 potentially gifted students who were nominated by teachers for their high achievements and interests in science but without any education services for the gifted. These two groups of students were compared in the aspects of problem finding ability in science, motivation, self regulation, science-related attitudes, and science anxiety through the pre- and post-treatment settings. The results indicated that the gifted group showed a significant improvement in originality and elaboration of problem-finding ability, but the potentially gifted group showed significant decrease in most variables of problem finding. Related to motivation and self-regulated learning, gifted students showed an increase in cognitive strategy use and decrease in intrinsic value, but the potentially gifted students showed significant decreases in most variables related to motivation and self-regulation, except intrinsic value. Related to the scientific attitudes and science anxiety, there were no significant changes between pre- and post-tests in the gifted group, but significant decreases in most variables were found in the potentially gifted group. The results of paired t-test and Ancova indicate that significant differences between the gifted and the potentially gifted groups are mainly due to the significantly lowered performance in post tests in the potentially gifted group, rather than a significant increase in gifted group.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.12
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• pp.1956-1964
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• 2009

Understanding ethical fashion consumers in Korea is essential for the expansion of the ethical fashion market. This study analyzed ethical consumers in Korea in an examination of the factors that influence ethical purchase behavior and attitudes. The differences between ethical fashion consumers and non-ethical fashion consumers were investigated using eight variables (perceived consumer effectiveness (PCE), self-direction, benevolence, universalism, social responsibility, perceived behavioral control, face saving, and group conformity). Data were collected by means of a questionnaire through both on-line and off-line surveys from April 20 to June 7, 2009. Only the respondents knowledgeable of ethical products or ethical consumption were asked to complete the questionnaire. A total of 494 samples were used for analyses. Using independent samples t-test, the differences in each variable between two groups were examined. There were significant differences between ethical fashion consumers and non-ethical fashion consumers in attitudes toward ethical consumption behavior, behavioral intention, PCE, self-direction, universalism, social responsibility, and face saving variables. The factors influencing attitude and behavior intention were investigated by step-wise regression analyses. For ethical fashion consumers, the attitudes to ethical consumption behavior were largely influenced by PCE and benevolence. Social responsibility was the most predictable variable in guiding behavioral intention. Behavioral intention was also influenced by benevolence and attitude. Group conformity was found to be negatively correlated with behavioral intention. The findings of this study provide significant guidance for marketers of ethical fashion products. This study is the start of ethical fashion consumer research in Korea and can develop into variable subfields in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.119-134
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• 2018

Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.