• ETRI Journal
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• 제42권6호
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• pp.872-885
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• 2020

Distributed consensus requires the consent of more than half of the congress to produce irreversible results, and the performance of the consensus algorithm deteriorates with the increase in the number of nodes. This problem can be addressed by delegating the agreement to a few selected nodes. Since the selected nodes must comply with the Byzantine node ratio criteria required by the algorithm, the result selected by any decentralized node cannot be trusted. However, some trusted nodes monopolize the consensus node selection process, thereby breaking decentralization and causing a trilemma. Therefore, a consensus node selection algorithm is required that can construct a congress that can withstand Byzantine faults with the decentralized method. In this paper, an algorithm based on the Byzantine agreement among decentralized agents to facilitate agreement between decentralization nodes is proposed. It selects a group of random consensus nodes per block by applying the proposed proof of nonce algorithm. By controlling the percentage of Byzantine included in the selected nodes, it solves the trilemma when an arbitrary node selects the consensus nodes.

• 대한수학회논문집
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• 제20권3호
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• pp.611-621
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• 2005

This paper introduces an ID based authenticated two pass key agreement protocol of Smart[4] which used the Weil pairing. We propose other an ID based authenticated two pass key agreement protocol which using the Tate Pairing. We will compare protocol of Smart with this protocol.

• Korean Journal of Radiology
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• 제23권12호
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• pp.1251-1259
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• 2022

Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

• Annals of Laboratory Medicine
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• 제38권6호
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• pp.585-590
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• 2018

Background: Although testing to detect weak D antigens using the antihuman globulin reagent is not required for D- patients in many countries, it is routinely performed in Korea. However, weak D testing can be omitted in D- patients with a C-E- phenotype as this indicates complete deletion of the RHD gene, except in rare cases. We designed a new algorithm for weak D testing, which consisted of RhCE phenotyping followed by weak D testing in C+ or E+ samples, and compared it with the current algorithm with respect to time and cost-effectiveness. Methods: In this retrospective study, 74,889 test results from January to July 2017 in a tertiary hospital in Korea were analyzed. Agreement between the current and proposed algorithms was evaluated, and total number of tests, time required for testing, and test costs were compared. With both algorithms, RHD genotyping was conducted for samples that were C+ or E+ and negative for weak D testing. Results: The algorithms showed perfect agreement (agreement=100%; ${\kappa}=1.00$). By applying the proposed algorithm, 29.56% (115/389 tests/yr) of tests could be omitted, time required for testing could be reduced by 36% (8,672/24,084 min/yr), and the test cost could be reduced by 16.53% (536.11/3,241.08 USD/yr). Conclusions: Our algorithm omitting weak D testing in D- patients with C-E- phenotype may be a cost-effective testing strategy in Korea.

• Journal of Korean Medical Science
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• 제33권43호
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• pp.239.1-239.12
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• 2018

Background: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system. Methods: A 5-step retinal fundus image reading tool was developed that rates image quality, presence of abnormality, findings with location information, diagnoses, and clinical significance. Each image was evaluated by 3 different graders. Agreements among graders for each decision were evaluated. Results: The 234,242 readings of 79,458 images were collected from 55 licensed ophthalmologists during 6 months. The 34,364 images were graded as abnormal by at-least one rater. Of these, all three raters agreed in 46.6% in abnormality, while 69.9% of the images were rated as abnormal by two or more raters. Agreement rate of at-least two raters on a certain finding was 26.7%-65.2%, and complete agreement rate of all-three raters was 5.7%-43.3%. As for diagnoses, agreement of at-least two raters was 35.6%-65.6%, and complete agreement rate was 11.0%-40.0%. Agreement of findings and diagnoses were higher when restricted to images with prior complete agreement on abnormality. Retinal/glaucoma specialists showed higher agreements on findings and diagnoses of their corresponding subspecialties. Conclusion: This novel reading tool for retinal fundus images generated a large-scale dataset with high level of information, which can be utilized in future development of machine learning-based algorithms for automated identification of abnormal conditions and clinical decision supporting system. These results emphasize the importance of addressing grader variability in algorithm developments.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.104-108
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• 2003

Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

• 설비공학논문집
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• 제23권1호
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• pp.32-37
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• 2011

The present study has been conducted to propose an algorithm regarding real-time load estimation of a gas engine-driven heat pump. In the study, thermal load of an indoor unit is estimated in terms of air-side and refrigerant-side. The air-side estimation is based on a typical heat exchanger model and is found to be in good agreement with experimental data. When it comes to the refrigerant-side load, a pressure difference across a valve must be estimated. For the estimation, it is assumed to be proportional to a bigger pressure difference that is available either by measurement or by estimation. Relative good agreement between the air- and refrigerant-sides suggests that the assumption may be plausible for the load estimation. The summed flow rate of all of indoor units is in good agreement with the throughput of the compressor which are calculated from the manufacturer's software. Accordingly, estimated thermal loads are also in good agreement. The proposed algorithm may be further developed for improved control algorithm and fault diagnosis.

• ETRI Journal
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• 제43권2호
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• pp.371-371
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• 2021

• 컴퓨터교육학회논문지
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• 제7권1호
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• pp.45-53
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• 2004

Ad-Hoc네트워크에서는 기존의 인프라를 사용하지 않기 때문에 공개 키 기반 구조 또는 제삼자 키 관리 서비스를 지원하지 않는다. 따라서 여러 유형의 보안문제가 발생할 수 있다. 그래서 보안 문제를 해결하기 위한 방법인 키 협정(key agreement)에 대하여 많은 프로토콜들이 제안되어 왔다. 가장 대표적인 것이 디피 헬만(Diffie-Hellman)이 제안한 프로토콜이다. 그러나 이 방법은 두명의 사용자간에서만 사용될 수 있다. 이 논문에서는 디피 헬만 방법을 확장하여 다자간에도 사용될 수 있는, 그룹 키 협정에 대하여 알아보고, 그룹 키 협정 진행 중에 링크 장애가 발생했을 때 그룹 키 협정을 성공적으로 수행하기 위한 효율적인 방법을 제안하였다.

• Korean Journal of Radiology
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• 제22권11호
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• pp.1777-1785
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• 2021

Objective: To investigate the accuracy of the Agatston score obtained with the ultra-high-pitch (UHP) acquisition mode using tin-filter spectral shaping (Sn150 kVp) and a kVp-independent reconstruction algorithm to reduce the radiation dose. Materials and Methods: This prospective study included 114 patients (mean ± standard deviation, 60.3 ± 9.8 years; 74 male) who underwent a standard 120 kVp scan and an additional UHP Sn150 kVp scan for coronary artery calcification scoring (CACS). These two datasets were reconstructed using a standard reconstruction algorithm (120 kVp + Qr36d, protocol A; Sn150 kVp + Qr36d, protocol B). In addition, the Sn150 kVp dataset was reconstructed using a kVp-independent reconstruction algorithm (Sn150 kVp + Sa36d, protocol C). The Agatston scores for protocols A and B, as well as protocols A and C, were compared. The agreement between the scores was assessed using the intraclass correlation coefficient (ICC) and the Bland-Altman plot. The radiation doses for the 120 kVp and UHP Sn150 kVp acquisition modes were also compared. Results: No significant difference was observed in the Agatston score for protocols A (median, 63.05; interquartile range [IQR], 0-232.28) and C (median, 60.25; IQR, 0-195.20) (p = 0.060). The mean difference in the Agatston score for protocols A and C was relatively small (-7.82) and with the limits of agreement from -65.20 to 49.56 (ICC = 0.997). The Agatston score for protocol B (median, 34.85; IQR, 0-120.73) was significantly underestimated compared with that for protocol A (p < 0.001). The UHP Sn150 kVp mode facilitated an effective radiation dose reduction by approximately 30% (0.58 vs. 0.82 mSv, p < 0.001) from that associated with the standard 120 kVp mode. Conclusion: The Agatston scores for CACS with the UHP Sn150 kVp mode with a kVp-independent reconstruction algorithm and the standard 120 kVp demonstrated excellent agreement with a small mean difference and narrow agreement limits. The UHP Sn150 kVp mode allowed a significant reduction in the radiation dose.