• The Journal of the Korean dental association
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• v.32 no.6 s.301
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• pp.409-416
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• 1994

이 자료는 이전에 공표 되었던 치과계에서의 감염방지 실무에 관한 CDC 권장사항을 개정한 것으로, 새로운 데이터, 재료, 기술, 및 장비 등이 반영되었다. 이러한 권장사항을 이행하면 치과 환경 내에서, 환자에서 치과의료종사자로, 치과의료종사자에서 환자로, 그리고 환자에서 환자로 질병이 전염될 수 있는 위험성을 감소시켜 줄 것이다. 이 문서에는 감염방지의 원칙에 근거하여 다음과 같은 특정 권장사항들이 서술되어 있다. 즉, 치과의료종사자들의 예방접종; 보호용 치장과 방책 기법; 수세와 손의 보호; 날카로운 기구와 바늘의 사용과 관리; 기구들의 멸균이나 소독; 치과진료대 및 주위 표면들의 세척 및 소독; 소독과 치과기공소; 치과진료대의 공기관과 수관에 연결된 핸드피스; 역류방지용 밸브; 기타 구내용 치과 장비 등의 사용과 관리; 한번 쓰고 버리는 기구; 생검 표본의 취급; 치과교육 현장에서 발치 치아를 사용하는 것; 폐기물의 폐기; 권장사항들의 이행.

• Information Systems Review
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• v.16 no.3
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• pp.49-68
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• 2014

These days, consumers have increasingly preferred to digital real-time streamlining and downloading to listen to music because this is convenient and affordable for the consumers. Accordingly, sales of music in compact disk formats have steadily declined. In this regards, online digital music has become a new communication channel to listen musics, where digital files can be delivered over various online networks to people's computing devices. The majority of online digital music distributors has Music Recommender Systems for sales of digital music on their websites. Music Recommender Systems are parts of information filtering systems that provide the ratings or preferences that users give to music. Korean online digital music distributors have Music Recommender Systems. But those online music distributors didn't provide any rules or clear procedures that recommend music. Therefore, we raise important questions as follows: "Is Music Recommender Systems Fair?", "What is the impact of Music Recommender Systems on online music rankings and sales?" While previous studies have focused on usefulness of Music Recommender Systems, this study investigates not only fairness of Current Music Recommender Systems but also Relationship between Music Recommender Systems and online Music Charts. This study examines these issues based on Bandwagon effect, ranking effect, Slot effect theories. For our empirical analysis, we selected the most famous five online digital music distributors in terms of market shares. We found that all recommended music is exposed to the top of 'daily music charts' in online digital music distributors' websites. We collected music ranking data and recommended music data from 'daily music chart' during a one month. The result shows that online music recommender systems are not fair, since they mainly recommend particular music that supported by a specific music production company. In addition, the recommended music are always exposed to the top of music ranking charts. We also find that recommended music usually appear at the top 20 ranking charts within one or two days. Also, the most music in the top 50 or 100 ranks are the recommended music. Moreover, recommended music usually remain the ranking charts more than one month while non-recommended music often disappear at the ranking charts within two week. Our study provides an important implication to online music industry. Because music recommender systems and music ranking charts are closely related, music distributors may improperly use their recommender systems to boost the sales of music that related to their own companies. Therefore, online digital music distributor must clearly announce the rules and procedures about music recommender systems for the better music industry.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.89-98
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• 2021

The Ministry of National Defense aims to create an environment in which transparent and reasonable defense policies can be implemented in real time by establishing the vision of smart defense innovation based on the Fourth Industrial Revolution and promoting innovation in technology-based defense operation systems. Artificial intelligence (AI) based defense technology is at the level of basic research worldwide, includes no domestic tasks, and involves classified military operation data and command control/decision information. Further, it is needed to secure independent technologies specialized for our military. In the army, military power continues to decline due to aging and declining population. In addition, it is expected that there will be more than 500,000 units should be managed simultaneously, to recognize the battle situation in real time on the future battlefields. Such a complex battlefield, command decisions will be limited by the experience and expertise of individual commanders. Accordingly, the study of AI core technologies supporting real-time combat command is actively pursued at home and abroad. It is necessary to strengthen future defense capabilities by identifying potential threats that commanders are likely to miss, improving the viability of the combat system, ensuring smart commanders always win conflicts and providing reasonable AI digital staff based on data science. This paper describes the recent research trends in AI military staff technology supporting commander decision-making, broken down into five key areas.