• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.45-47
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• 2022

Mobile edge computing (MEC), which enables mobile terminals to offload computational tasks to a server located at the user's edge, is considered an effective way to reduce the heavy computational burden and achieve efficient computational offloading. In this paper, we study a multi-user MEC system in which multiple user devices (UEs) can offload computation to the MEC server via a wireless channel. To solve the resource allocation and task offloading problem, we take the total cost of latency and energy consumption of all UEs as our optimization objective. To minimize the total cost of the considered MEC system, we propose an DRL-based method to solve the resource allocation problem in wireless MEC. Specifically, we propose a Asynchronous Advantage Actor-Critic (A3C)-based scheme. Asynchronous Advantage Actor-Critic (A3C) is applied to this framework and compared with DQN, and Double Q-Learning simulation results show that this scheme significantly reduces the total cost compared to other resource allocation schemes

• Biomedical Science Letters
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• v.5 no.1
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• pp.131-133
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• 1999

In order to the investigate epidemiological characteristics of methicillin-resistant Staphylococcus aureus (MRSA), 31 strains of Staphylococcus aureus were isolated from the equipments of two hospitals in Chonbuk. And their antimicrobial resistance patterns against 7 kinds of antimicrobial agents and the identification of MRSA by polymerase chain reaction (PCR) were studied. Seven strains among 10 strains of methicillin resistant Staphylococcus aureus showed 554 bp DNA which was a part of mecA gene in PCR analysis.

• Journal of IKEEE
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• v.25 no.4
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• pp.598-606
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• 2021

In this paper, we presents a new service binding and resource management model for context based services in mobile edge computing (MEC) networks. The proposed control is composed of two layers: MEC service bindng control layer (MCL) and user context control layer (UCL). The MCL manages service binding construction, resource allocation, and service policy construction from a system point of view; and the UCL manages real-time service adaptation using meta-objects. Through simulations, we confirmed that the proposed control offers enhanced throughput and content transfer time when it is compared to the legacy computing and control models. The proposed control model can be employed as a key component for the context based various internet-of-things (IoT) services in MEC environments.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.291-296
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• 2021

The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile Edge Computing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically close to the devices. Task offloading to MEC servers is efficient for devices with limited battery life and computational capability. In this paper, we assumed an industrial IoT environment requiring high reliability. The complexity of optimization problem in industrial IoT environment with many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting the MEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability and energy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms of energy consumption and reliability.

• Journal of Microbiology and Biotechnology
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• v.33 no.12
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• pp.1692-1697
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• 2023

Staphylococcus aureus integrated with mecA gene, which codes for penicillin-binding protein 2a, is resistant to all penicillins and other beta-lactam antibiotics, resulting in poor treatment expectations in skin and soft tissue infections. The development of a simple, sensitive and portable biosensor for mecA gene analysis in S. aureus is urgently needed. Herein, we propose a dual-toehold-probe (sensing probe)-mediated exonuclease-III (Exo-III)-assisted signal recycling for portable detection of the mecA gene in S. aureus. When the target mecA gene is present, it hybridizes with the sensing probe, initiating Exo III-assisted dual signal recycles, which in turn release numerous "3" sequences. The released "3" sequences initiate catalytic hairpin amplification, resulting in the fixation of a sucrase-labeled H2 probe on the surface of magnetic beads (MBs). After magnet-based enrichment of an MB-H1-H2-sucrase complex and removal of a liquid supernatant containing free sucrase, the complex is then used to catalyze sucrose to glucose, which can be quantitatively detected by a personal glucose meter. With a limit of detection of 4.36 fM for mecA gene, the developed strategy exhibits high sensitivity. In addition, good selectivity and anti-interference capability were also attained with this method, making it promising for antibiotic tolerance analysis at the point-of-care.

• Journal of Microbiology and Biotechnology
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• v.30 no.3
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• pp.469-475
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• 2020

During meiosis I, programmed DNA double-strand breaks (DSBs) occur to promote chromosome pairing and recombination between homologs. In Saccharomyces cerevisiae, Mec1 and Tel1, the orthologs of human ATR and ATM, respectively, regulate events upstream of the cell cycle checkpoint to initiate DNA repair. Tel1^ATM and Mec1^ATR are required for phosphorylating various meiotic proteins during recombination. This study aimed to investigate the role of Tel1^ATM and Mec1^ATR in meiotic prophase via physical analysis of recombination. Tel1^ATM cooperated with Mec1^ATR to mediate DSB-to-single end invasion transition, but negatively regulated DSB formation. Furthermore, Mec1^ATR was required for the formation of interhomolog joint molecules from early prophase, thus establishing a recombination partner choice. Moreover, Mec1^ATR specifically promoted crossover-fated DSB repair. Together, these results suggest that Tel1^ATM and Mec1^ATR function redundantly or independently in all post-DSB stages.

• Journal of Yeungnam Medical Science
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• v.38 no.2
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• pp.169-174
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• 2021

Mucoepidermoid carcinoma (MEC) is the most common malignant neoplasm of the salivary gland, but primary thyroid MEC has rarely been reported and usually has a good prognosis. Herein, I report a case of thyroidal MEC with a poor prognosis in an 82-year-old woman with an anterior neck mass. Ultrasonography and computed tomography revealed a thyroid mass. The patient initially underwent fine-needle aspiration, was diagnosed with malignancy, and underwent a right lobectomy. On gross examination, a 4.0×3.6×2.6 cm-sized ill-defined, unencapsulated, and infiltrative tan to whitish mass with necrosis was identified. Microscopically, epidermoid tumor cell nests or solid sheets were identified. Mucous cells that were positive for periodic acid-Schiff and mucicarmine stains were also identified within epidermoid cell nests. Frequent mitosis and necrosis were observed. Immunohistochemical staining for p40 and p63 was positive, and that for thyroid transcription factor-1 and paired box gene 8 was focally positive. According to the Armed Forces Institute of Pathology grading system for salivary gland MEC, the current case was classified as high-grade MEC. After surgery, the patient suffered from dyspnea due to a remnant neck mass that compressed and obstructed the trachea; therefore, the patient refused further treatment. Thyroidal MECs are considered low-grade with a favorable prognosis, but there are several reported cases of thyroidal MEC with poor prognosis. The current case is a rare presentation of high-grade thyroidal MEC with a poor prognosis.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.46-59
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• 2022

The 5G MEC (Multi-access Edge Computing) technology offers network and computing functionalities that allow application services to improve in terms of network delay, bandwidth, and security, by locating the application servers closer to the users at the edge nodes within the 5G network. To offer its interoperability within various networks and user equipment, standardization of the 5G MEC technology has been advanced in ETSI, 3GPP, and ITU-T, primarily for the MEC platform, transport support, and MEC federation. This article offers a brief review of the standardization activities for 5G MEC technology and the details about the system architecture and functionalities developed accordingly.

• Biomedical Science Letters
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• v.5 no.2
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• pp.135-145
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• 1999

A total of 45 Staphylococcus aureus strains from clinical samples were tested for the biochemical test and antibiotic susceptibility test. Forty-five S. aureus strains were subjected to the molecular epidemiological study by susceptiblity test, antibiogram, bacteriophage typing, polymerase chain reaction and mec-associated hypervariable region gene in order to detect of mecA gene which was one of the structural gene related to antibiotic resistant expression factors. Three of 15 mecA-negative S. aureus isolates were classified as oxacillin resistant despite borderline minimal inhibitory concentration values. Methicillin susceptiblities were completely consistent with PCR results for these strains. On the other hand, 4 of 30 mecA-positive isolates yielded results in the oxacillin and methicillin susceptibility tests which were discrepant from those of PCR analysis. Except for SA6, the methicillin resistant S. aureus strains tested were highly resistant to penicillin, oxacillin, gentamicin, and chloramphenicol. In the phage typing, 27 strains were typable. The Iytic group III was as many as 12 strains, and 7 of 12 were 75/83A/84 type. In the PCR of specific mecA gene probe with chromosomal DNA of 30 methicillin resistant S. aureus, the amplified DNA band of 533 bp was confirmed in 30 strains and not in methicillin sensitive S. aureus. The single amplified band of hypervariable region related to mec was investigated in all of 30 methicillin resistant S. aureus, but in methicillin sensitive S. aureus it was amplified. The size of PCR products was between 200 bp and 600 Up. Four units was directly repeated.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.74-77
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• 2022

최근 사물 인터넷(IoT)의 발전으로 계산 집약적이거나 지연시간에 민감한 태스크가 증가하면서, 모바일 엣지 컴퓨팅 기술이 주목받고 있지만 지상에 고정되어 있는 MEC 서버는 사용자의 요구사항 변화에 따라 서버의 위치를 변경하거나 유연하게 대처할 수 없다. 이 문제를 해결하기 위해 UAV(Unmanned Aerial Vehicle)를 추가로 이용해 엣지 서비스를 제공하는 기법이 연구되고 있다. 그러나 UAV는 지상 MEC와는 달리 배터리 용량이 제한되어 있어 태스크 마이그레이션을 통해 에너지 사용량을 최소화하는 것이 필요하다. 본 논문에서는 MEC 서버들 사이의 로드 밸런싱과 UAV MEC 서버의 에너지 효율성을 최적화하기 위해 강화학습 기법인 Q-learning을 이용한 태스크 마이그레이션 기법을 제안한다. 제안 시스템의 성능을 평가하기 위해 UAV의 개수에 따라 실험을 진행하여 잔여 에너지와 로드 밸런싱 측면에서 성능을 분석한다.