• 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.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2017.05a
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• pp.165-165
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• 2017

지난 수 십 년 동안, 전 세계적으로 자원의 소비가 급격히 증가하게 되면서 최근 자원 고갈은 물론 환경오염이 커다란 이슈로 문제가 되고 있다. 이에 따라 재료 관련 분야에 있어서는 보다 효율적이고 친환경적인 방법으로 자원을 활용해야 된다는 필요성이 대두되었고 이와 같은 관점에서 목적하는 성분이 우수하고 환경 친화적인 표면처리 재료 개발연구가 활발하게 진행되고 있는 실정이다. 그 중 플라즈마 전해 산화(Plasma Electrolytic Oxidation, PEO)는 알루미늄, 마그네슘 등의 경금속의 경도를 향상시키고 높은 내마모성, 내식성을 갖게 하는 표면처리로써 그 관심이 증가하고 있다. 이 플라즈마 전해 산화는 일반적으로 공정비용 대비 효과적이고 환경 친화적이며 코팅 성능 면에서 우수하다고 알려져 있다. 이러한 고유한 특성으로 인해 플라즈마 전해 산화 코팅은 최근 몇 년 동안 기계, 자동차, 우주항공, 의학 및 전기 산업 등의 분야에서 그 적용이 점차 증가하고 있는 상황이다. 한편, 플라즈마 전해 산화 코팅을 하는 모재들의 경우 부동태 산화피막을 용이하게 형성할 수 있는 특성의 모재에 한정되고 있어서 그 응용확대에 한계가 있는 것이 사실이다. 따라서 본 연구에서는 플라즈마 전해 산화법을 사용하여 용융알루미늄도금 강판 상에 산화피막 형성을 시도하였다. 전원공급 장치의 양극은 전해질 속에 잠겨있는 작동전극에 연결하고 음극은 대전극 역할을 하는 스테인레스강 전해질 용기에 연결되었다. 전해질은 Sodium Aluminate 및 기타 첨가제를 함유한 것을 사용하였고 온도는 열교환기를 사용하여 $30^{\circ}C$ 이하로 유지되었다. 또한 여기서 전류밀도는 $5{\sim}10A/dm^2$, 실험 주파수는 700Hz, Duty cycle은 30 및 90%의 각 조건에서 공정처리 시간을 각각 30분 및 60분 동안 진행하였다. 이와 같은 조건에서 형성한 막들에 대해서는 주사형전자현미경(SEM)을 이용하여 코팅 막의 표면 및 단면의 모폴로지를 관찰하였음은 물론 EDS 및 XRD 측정을 통하여 원소조성분포 및 결정구조를 각각 분석하였다. 또한 이 코팅 막들에 대한 내식성은 5% 염수분무 환경 중 노출시험(Salt spray test), 3% NaCl 용액에서의 침지 시험 및 전기화학적 동전위 양극분극(Potentiodynamic Polarization) 시험을 진행하여 평가하였다. 이상의 실험결과에 의하면, 제작조건별 플라즈마 전해 산화 코팅 막의 모폴로지 및 결정구조가 상이하게 나타나는 것을 알 수 있었다. 코팅 막의 모폴로지 관찰 결과, 공정 시간에 비례하여 표면에 존재하는 원형 기공의 수는 감소하였으나 그 크기가 커지고 크레이터의 직경 또한 커진 것이 확인되었다. 이 기공은 마이크로 방전에 의해 형성된다고 알려져 있는데 공정 시간이 증가함에 따라 코팅 두께가 점차 증가하여 마이크로 방전의 빈도수가 줄어들고 그 강도는 증가하게 되어 기공 크기가 증가한 것으로 사료된다. 또한 공정시간이 긴 시편에서 표면에 크랙이 다수 존재하는 것으로 확인되었다. 이것은 방전에 의해 고온이 된 소재가 차가운 전해질과 만나게 되어 생긴 큰 온도구배로 인해 강한 열응력이 발생하여 균열을 초래한 것으로 보인다. 조성원소 분석 결과 원형 기공 주변의 크레이터 영역에는 알루미늄이 풍부하였으며 그 주변에 결절상을 갖는 구조에서는 전해질 성분의 원소가 포함되어 있는 것이 확인되었다. 이러한 코팅 막의 표면 특성은 내식성에 영향을 주게 된 원인으로 사료된다. 동전위 분극측정 결과에 의하면 플라즈마 전해 산화 공정 시간이 길어질수록 부식전류밀도가 증가하였다. 이것은 공정시간이 길어짐에 따라 강한 방전이 발생하여 기공의 크기가 증가하고 크랙이 발생하게 되면서 내식성이 저하된 것으로 판단된다. 종합적으로 재료특성 분석 및 내식성 평가를 분석한 결과, 플라즈마 전해 산화의 공정 시간이 너무 길게 되면 오히려 내식성은 저하되는 것이 확인되었다. 이상의 연구를 통하여 고내식 특성을 갖는 플라즈마 전해 산화 막의 유효성을 확인하였으며 용융알루미늄강판 상에 실시한 플라즈마 전해 산화 처리에 대한 기초적인 응용 지침을 제시할 수 있을 것으로 사료된다.

• The Korean Journal of Air & Space Law and Policy
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• v.25 no.2
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• pp.139-162
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• 2010

In terms of the international air transport, the open skies policy implies freedom in the sky or opening the sky. In the normative respect, the open skies policy is a kind of open-door policy which gives various forms of traffic right to other countries, but on the other hand it is a policy of free competition in the international air transport. Since the Airline Deregulation Act of 1978, the United States has signed an open skies agreement with many countries, starting with the Netherlands, so that competitive large airlines can compete in the international air transport market where there exist a lot of business opportunities. South Korea now has an open skies agreement with more than 20 countries. The frequent flyer program (FFP) is part of a broad-based marketing alliance which has been used as an airfare strategy since the U.S. government's airline deregulation. The membership-based program is an incentive plan that provides mileage points to customers for using airline services and rewards customer loyalty in tangible forms based on their accumulated points. In its early stages, the frequent flyer program was focused on marketing efforts to attract customers, but now in the environment of intense competition among airlines, the program is used as an important strategic marketing tool for enhancing business performance. Therefore, airline companies agree that they need to identify customer needs in order to secure loyal customers more effectively. The outcomes from an airline's frequent flyer program can have a variety of effects on international competition. First, the airline can obtain a more dominant position in the air flight market by expanding its air route networks. Second, the availability of flight products for customers can be improved with an increase in flight frequency. Third, the airline can preferentially expand into new markets and thus gain advantages over its competitors. However, there are few empirical studies on the airline frequent flyer program. Accordingly, this study aims to explore the effects of the program on international competition, after reviewing the types of strategic alliance between airlines. Making strategic airline alliances is a worldwide trend resulting from the open skies policy. South Korea also needs to be making open skies agreements more realistic to promote the growth and competition of domestic airlines. The present study is about the performance of the airline frequent flyer program and international competition under the open skies policy. With a sample of five global alliance groups (Star, Oneworld, Wings, Qualiflyer and Skyteam), the study was attempted as an empirical study of the effects that the resource structures and levels of information technology held by airlines in each group have on the type of alliance, and one-way analysis of variance and regression analysis were used to test hypotheses. The findings of this study suggest that both large airline companies and small/medium-size airlines in an alliance group with global networks and organizations are able to achieve high performance and secure international competitiveness. Airline passengers earn mileage points by using non-flight services through an alliance network with hotels, car-rental services, duty-free shops, travel agents and more and show high interests in and preferences for related service benefits. Therefore, Korean airline companies should develop more aggressive marketing programs based on multilateral alliances with other services including hotels, as well as with other airlines.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.3
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• pp.15-25
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• 2023

In this study, silicon sludge from semiconductor dicing process is recycled to fabricate silica nanoparticles, which are applied as dispersing materials for electro-responsive (ER) smart fluid. In specific, metal impurities are removed from silicon sludge by acid washing to obtain the high-purity silicon powder. And then, silica nanoparticles are synthesized by facile hydrothermal method employing the silicon powder as reactant material. To control the size of silica nanoparticles, the reaction time of hydrothermal method is varied as 8, 15, 20, and 30 hours are applied to control the size of silica nanoparticles. Sizes of silica nanoparticles are increased proportionally to the reaction time owing to the increased numbers of hydrolysis and condensation reactions. As-synthesized silica nanoparticles are prepared as electro-responsive smart fluids by dispersing into silicon oil. Silica nanoparticles synthesized by 30 hours of hydrothermal reaction (SiO₂-H30) exhibit the highest shear stress of 21.4 Pa under an applied electric field strength of 3.0kV mm^-1. Such enhancement in ER performance of SiO₂-H30 among various silica nanoparticles are attribute to the reinforcing effect originated from the mixed particle size, which allowing the formation of rigid chain-like structures. Accordingly, this study successfully propose a recycling method of silicon sludge to synthesize silica nanoparticles and their derived ER fluids, which may suggest new possibility to ESG management emphasizing the eco-friendliness.