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- 저자 : ( Yusun Chang ) (검색결과 2 건)
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( Myeung-su Lee ),( Chang Hoon Lee ),( Hye Soon Lee ),( Yoon-kyoung Sung ),( Jung Ran Choi ),( Kyungsu Park ),( Mi-kyoung Lim ),( Byoong Yong Choi ),( Hyoun-ah Kim ),( Seung Won Choi ),( Yusun Lee ),( 대한류마티스학회 2021 대한류마티스학회지 Vol.28 No.2
Objective. Rheumatoid arthritis (RA) is a chronic, progressive, autoimmune disorder that impairs patients’ overall health-related quality of life (HRQOL). In this study, we evaluated the effect of adalimumab in Korean patients with active RA on HRQOL. Methods. Patients included in the study had moderate to severe active RA that did not respond to conventional drugs with a Disease Activity Score of 28 joints >3.2 and were biologics-naïve. All patients received adalimumab 40 mg subcutaneously every other week and were followed for 24 weeks. The primary endpoint was the change in baseline Health Assessment Questionnaire Disability Index (HAQ-DI) score at week 24. Secondary endpoints were changes in the EuroQol 5-dimension 3-Level (EQ-5D-3L) baseline score and Short Form 36-Item Health Survey (SF-36) domain scores at weeks 12 and 24 and change in baseline HAQ-DI score at week 12. Results. In total, 91 Korean patients were included. Ninety-three percent of patients were in high disease activity with a baseline mean DAS28 value of 6.1 within all patients. The mean change from baseline in HAQ-DI scores were -0.46 at week 12 and∼0.67 at week 24 (p<0.0001). Additionally, EQ-5D-3L score at weeks 12 and 24 had significantly improved (p<0.0001) compared to baseline. SF-36 at weeks 12 and 24 had significantly improved (p<0.0001, p=0.0001) compared to baseline. Conclusion. Treatment with adalimumab resulted in significant improvement in HAQ-DI, EQ-5D-3L, and SF-36 scores at 12 and 24 weeks in Korean RA patient. (J Rheum Dis 2021;28:68-75)
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A Reactive Cross Collision Exclusionary Backoff Algorithm in IEEE 802.11 Network
( Subodh Pudasaini ),( Yusun Chang ),( Seokjoo Shin ) 한국인터넷정보학회 2010 KSII Transactions on Internet and Information Syst Vol.4 No.6
An inseparable challenge associated with every random access network is the design of an efficient Collision Resolution Algorithm (CRA), since collisions cannot be completely avoided in such network. To maximize the collision resolution efficiency of a popular CRA, namely Binary Exponential Backoff (BEB), we propose a reactive backoff algorithm. The proposed backoff algorithm is reactive in the sense that it updates the contention window based on the previously selected backoff value in the failed contention stage to avoid a typical type of collision, referred as cross-collision. Cross-collision would occur if the contention slot pointed by the currently selected backoff value appeared to be present in the overlapped portion of the adjacent (the previous and the current) windows. The proposed reactive algorithm contributes to significant performance improvements in the network since it offers a supplementary feature of Cross Collision Exclusion (XCE) and also retains the legacy collision mitigation features. We formulate a Markovian model to emulate the characteristics of the proposed algorithm. Based on the solution of the model, we then estimate the throughput and delay performances of WLAN following the signaling mechanisms of the Distributed Coordination Function (DCF) considering IEEE 802.11b system parameters. We validate the accuracy of the analytical performance estimation framework by comparing the analytically obtained results with the results that we obtain from the simulation experiments performed in ns-2. Through the rigorous analysis, based on the validated model, we show that the proposed reactive cross collision exclusionary backoff algorithm significantly enhances the throughput and reduces the average packet delay in the network.
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