비내시경하 중비도내 검체 채취 시 오염을 줄일 수있는 새로운방법 : Shielded Swab

임종범,전시영,김진평,안성용,손희영,박정제,안성기 대한이비인후과학회 2008 대한이비인후과학회지 두경부외과학 Vol.51 No.6

Endoscopically guided middle meatal culture is recommended to determine organ-specific antibiotic therapy in sinusitis. This study was designed to decrease the chance of contamination in endoscopically guided middle meatal swab through a shielded pathway using a sterile straw to bypass the contaminated area in the nose from the vestibule to the middle meatus. Subjects and Method:Seventeen healthy volunteers underwent endoscopically guided middle meatal culture. With or without the sterilization of the nasal vestibule, endoscopically guided middle meatal culture was performed by using a sterile cotton swab (routine swab) and using a sterile cotton swab through a sterile straw (shielded swab). We compared the contamination rates between the routine swab versus shielded swab. Results:With and without the sterilization of the nasal vestibule, the contamination rates of the routine swab was 11.7% and 64.7%, respectively and the contamination rates of the shielded swab was 5.8% in both. Conclusion:In endoscopically guided middle meatal culture, the contamination rates was significantly decreased by using the shielded swab without sterilization of the nasal vestibule. This study suggests that the shielded swab is a new and reliable swab method that can be used easily and simply at the office. (Korean J Otorhinolaryngol- Head Neck Surg 2008;51:524-7)

역행성 구각하체근 회전피판을 이용한 하구순 재건술

임종범,김진평,전시영,김준식 대한이비인후과학회 2003 대한이비인후과학회지 두경부외과학 Vol.46 No.4

The lips are essential in maintaining oral competence and assist in mastication, deglutition, and articulation. The lips are also important aesthetically, contributing to appearance and facial expression. Defects of up to one third of the lower lip can be closed primarily, but larger defects require more complex techniques. Successful lip reconstruction require careful meticulous planning to achieve the optimum functional and cosmetic result. When planning a reconstruction of a large defect of the lower lip, the following points should be taken into consideration:1) maintain the sphincter function, 2) retain the sensation, 3) acquire a large enough opening for the mouth, 4) strive for an acceptable cosmetic appearance. It is not possible to satisfy all these criteria in every instance, and careful preoperative evaluation is essential. We describe here a successful technique to reconstruct a large lower lip defect using a depressor anguli oris musculocutaneous flap and a mucosal flap for elderly patients. (Korean J Otolaryngol 2003;46:331-3)

말초성 안면신경초종 치험 2예

임종범,김진평,안성기,전시영 대한이비인후과학회 2002 대한이비인후과학회지 두경부외과학 Vol.45 No.10

Neurilemmomas are benign tumors that arise from the nerve sheath. Facial nerve neurilemmomas are uncommon, slow-growing neoplasms that occur anywhere along the course of the facial nerve. The majority of facial nerve neurilemmomas are intratem-poral, with a few cases arising from the intraparotid portion. The clinical presentations are generaly insidious and the nature of the disease depends on the location and extent of the tumor. They are dificult to diagnose preoperatively and are frequently misdiagnosed because of the variety of their clinical manifestations. Therefore, early and correct diagnosis and evaluation are necessary. Recently, we experienced two cases of facial nerve neurilemoma with relatively good surgical result, involving the mastoid segment of the facial nerve and the main trunk of the facial nerve in the parotid gland. We reviewed the diagnosis, pa-thology, and treatement of this case, and report the cases with reviews of literature. (Korean J Otolaryngol 2002;45:10-3 )

정상고막을 가진 전음성 난청 환자에서 이소골의 섬유성 변화 2예

임종범,안성기,전시영,김진평 대한이비인후과학회 2003 대한이비인후과학회지 두경부외과학 Vol.46 No.12

In general, causes of conductive hearing loss with the intact tympanic membrane and external auditory canal are known as congenital anomaly of the ossicular chain, otosclerosis, and head trauma-induced ossicular discontinuity. But it may also occur due to fibrotic change by potential inflammation of the ossicular chain as a result of otitis media in the infancy or childhood. We report two cases of fibrous change of the ossicles by probable middle ear inflammation with a review of the related literature. (Korean J Otolaryngol 2003;46:1077-9)

모바일 엣지 클라우드 환경에서 인공지능 기반 모니터링 기법

임종범,최희석,유헌창 한국정보처리학회 2018 정보처리학회논문지. 컴퓨터 및 통신시스템 Vol.7 No.2

모바일 엣지 클라우드 환경에서 중요하게 다루어야 할 사항 중 하나는 모바일 장치에 대한 모니터링이다. 모바일 장치는 장치의 특성상 불안정한 상태가 발생하여 결함이 발생할 수 있기 때문에 모바일 엣지 클라우드의 SLA (Service Level Agreement)를 만족시키기 위해서는 모바일 장치의 모니터링 기법을 통해 결함을 측정하여 이에 대한 조치를 수행하여야 한다. 이 논문에서는 모바일 엣지 클라우드 환경에서 인공지능 기반 모바일 장치 모니터링 기법을 제안한다. 제안하는 모니터링 기법은 모바일 장치에 대한 이전 모니터링 정보와 현재 모니터링 정보를 기반으로 모바일 장치의 결함 발생을 측정할 수 있도록 설계 되었다. 이를 위해 인공지능 기법 중 하나인 은닉 마르코프 체인 모델을 모바일 장치에 대한 모니터링 기법에 적용하였다. 실험 평가를 통해 제안하는 모니터링 기법에 대한 검증을 수행하였다. 제안하는 기법은 모바일 장치뿐만 아니라 일반적인 클라우드 환경에서의 가상 머신을 모니터링 하는 방법으로도 활용할 수 있도록 설계되었다. One of the crucial issues in mobile edge cloud computing environments is to monitor mobile devices. Due to the inherit properties of mobile devices, they are prone to unstable behavior that leads to failures. In order to satisfy the service level agreement (SLA), the mobile edge cloud administrators should take appropriate measures through a monitoring scheme. In this paper, we propose a monitoring scheme of mobile devices based on artificial intelligence in mobile edge cloud computing environments. The proposed monitoring scheme is able to measure faults of mobile devices based on previous and current monitoring information. To this end, we adapt the hidden markov chain model, one of the artificial intelligence technologies, to monitor mobile devices. We validate our monitoring scheme based on the hidden markov chain model. The proposed monitoring scheme can also be used in general cloud computing environments to monitor virtual machines.

경기지역 실버타운의 서비스 품질 향상에 관한 연구

임종범,김영희,한상민 국제관광학회 2007 국제관광연구 Vol.4 No.1

에지 기반 포그 컴퓨팅 환경에서 이동성 지원을 위한라이브 마이그레이션 기반 자원 관리 기법

임종범 한국정보처리학회 2022 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.11 No.4

As cloud computing and the Internet of things are getting popular, the number of devices in the Internet of things computingenvironments is increasing. In addition, there exist various Internet-based applications, such as home automation and healthcare. In turn,existing studies explored the quality of service, such as downtime and reliability of tasks for Internet of things applications. To enhancethe quality of service of Internet of things applications, cloud-fog computing (combining cloud computing and edge computing) can beused for offloading burdens from the central cloud server to edge servers. However, when devices inherit the mobility property, continuityand the quality of service of Internet of things applications can be reduced. In this paper, we propose a resource management schemebased on live migrations for mobility support in edge-based fog computing environments. The proposed resource management algorithmis based on the mobility direction and pace to predict the expected position, and migrates tasks to the target edge server. The performanceresults show that our proposed resource management algorithm improves the reliability of tasks and reduces downtime of services. 클라우드 컴퓨팅과 사물인터넷의 대중화에 따라 사물인터넷 컴퓨팅 환경에 존재하는 인터넷 연결이 가능한 장치들의 수가 점차 증가하고 있다. 또한 스마트홈, 헬스케어 등 사물인터넷을 이용한 다양한 인터넷 응용이 많아짐에 따라 통신 지연 및 연산의 신뢰성과 같은 지표의 서비스품질과관련된 연구들이 진행되고 있다. 사물인터넷 응용의 서비스품질 향상을 위해 중앙집중형 클라우드 서버에 연결하기 보다 장치와 가까이 존재하고중앙집중형 클라우드 서버와의 오프로드(offload) 협업을 위해 에지 컴퓨팅(edge computing)이 결함된 클라우드-포그 컴퓨팅 환경이 주목을 받고있다. 하지만 클라우드-포그 컴퓨팅 환경에서 장치들이 이동성을 특성을 가질 때 사물인터넷 응용 서비스의 연속성이 떨어지고 서비스품질 수준이저하되는 문제점이 발생하고 있다. 이 논문에서는 에지 기반 포그 컴퓨팅 환경에서 이동성 지원을 위한 라이브 마이그레이션 기반 자원 관리 기법을제안한다. 제안하는 자원 관리 알고리즘은 사용자의 이동성 방향과 속도를 기반으로 일정 시간 뒤의 위치를 예측하고 이를 기반으로 라이브 마이그레이션을 통해 사물인터넷 서비스 이주를 지원한다. 성능 평가를 통해 제안하는 자원 관리 알고리즘의 효용성을 측정하였으며, 성능 실험에서 정지시간(downtime)과 서비스 작업의 신뢰성이 크게 향상됨을 보였다.

An Intelligent Residual Resource Monitoring Scheme in Cloud Computing Environments

임종범,유헌창,길준민 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.6

Recently, computational intelligence has received a lot of attention from researchers due to its potentialapplications to artificial intelligence. In computer science, computational intelligence refers to a machine’sability to learn how to compete various tasks, such as making observations or carrying out experiments. Weadopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, sothat the post migration performance of a virtual machine is as consistent with the pre-migration performanceas possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtualmachine to. The design of the proposed residual resource monitoring scheme helps maintain the quality ofservice and service level agreement during the migration. We carried out a number of experimental evaluationsto demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show thatthe proposed scheme intelligently measures the similarities between virtual machines in cloud computingenvironments without causing performance degradation, whilst preserving the quality of service and servicelevel agreement.

Intelligent Resource Management Schemes for Systems, Services, and Applications of Cloud Computing Based on Artificial Intelligence

임종범,이대원,정광식,유헌창 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.5

Recently, artificial intelligence techniques have been widely used in the computer science field, such as theInternet of Things, big data, cloud computing, and mobile computing. In particular, resource management isof utmost importance for maintaining the quality of services, service-level agreements, and the availability ofthe system. In this paper, we review and analyze various ways to meet the requirements of cloud resourcemanagement based on artificial intelligence. We divide cloud resource management techniques based onartificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloudcomputing systems. The aim of the paper is to propose an intelligent resource management scheme thatmanages mobile resources by monitoring devices' statuses and predicting their future stability based on one ofthe artificial intelligence techniques. We explore how our proposed resource management scheme can beextended to various cloud-based systems.

멀티 에이전트 에지 컴퓨팅 환경에서 확장성을 지원하는딥러닝 기반 동적 스케줄링

임종범 한국정보처리학회 2023 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.12 No.9

클라우드 컴퓨팅은 에지 서버가 동작하는 포그(fog) 레이어가 결합된 에지(edge) 컴퓨팅 아키텍처로 진화하고 있다. 에지 컴퓨팅 아키텍처가관심을 받는 이유는 짧은 통신 지연으로 실시간 IoT 응용을 지원할 수 있기 때문이다. 이와 동시에 인공지능 기술을 도입한 많은 클라우드 작업스케줄링 기법들이 제안되었다. 인공지능 기반의 클라우드 작업 스케줄링 기법은 기존 기법보다 더 좋은 성능을 보이지만 스케줄링 시간이 다소소요된다는 단점이 있다. 이 논문에서는 에지 컴퓨팅 환경에서 분산 딥러닝 학습 기반의 동적 스케줄링 기법을 제안한다. 제안하는 기법은 기존기법보다 스케줄링 시간이 짧은 장점이 있다. 또한 멀티 에이전트를 통한 분산 딥러닝 학습의 효과성을 보이기 위해 확장적인 실험 환경에서 제안기법과 기존 인공지능 기법의 성능일 비교 평가하였다. 성능 실험 결과 기존 인공지능 기반 클라우드 작업 스케줄링 기법보다 짧은 스케줄링 시간을보여 IoT 실시간 응용에 적합함을 보였으며, 확장적인 실험에서도 제안 기법이 완료된 작업의 수에 대하여 우수한 성능을 보임을 증명하였다 Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, variouscloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task schedulingtechniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, wepropose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposedmethod shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of theproposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. Theresults show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms ofthe number of completed cloud tasks in a scalable experimental environment.