• KIEE International Transactions on Power Engineering
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• v.2A no.4
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• pp.131-135
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• 2002

This paper describes a new ultra-fast contingency screening algorithm for on-line TSA without time simulation. All machines are represented in a classical model and the stability index is defined as the ratio between acceleration power during a fault and deceleration power after clearing the fault. Critical clustering of machines is done based on the stability index, and the power-angle curve of the critical machines is drawn assuming that the angles of the critical machines increase uniformly, while those of the non-critical ones remain constant. Finally, the critical clearing time (CCT) is computed using the power-angle curve. The proposed algorithm is tested on the KEPCO system comprised of 900-bus and 230-machines. The CCT values computed with the screening algorithm are in good agreement with those computed using the detailed model and the SIME method. The computation time for screening about 270 contingencies is 17 seconds with 1.2 GHz PC.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.5
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• pp.225-233
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• 2001

SIME(SIngle Machine Equivalent) method has been recognized as a useful tool to determine transient stability of power systems. In this paper, SIME method is used to develop the KEPCO transient stability assessment (TSA) tool. A new screening algorithm that can be implemented in SIME method is proposed. The salient feature of the proposed screening algorithm is as follows. First, critical generators are identified by a new index in the early stage of the time domain simulation. Thus, computational time required to find OMIB(One Machine Infinite Bus) can be reduced significantly. Second, clustering critical machines can be performed even in very stable cases. It enables to be avoid extra calculation of time trajectory that is needed in SIME for classifying the stable cases. Finally, using power-angle trajectory and subdividing contingency classification have improved the screening capability. This algorithm is applied to the fast TSA of the KEPCO system.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.16 no.2
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• pp.62-69
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• 2016

Newborn screening of some urea cycle disorders has little benefits because of early severe symptoms before the result, low sensitivity (especially hypocitrullinemia) and poor prognosis. But in case of citrullinemia, citrin deficiency and argininosuccinic aciduria diagnosed as elevated citrulline, newborn screening is helpful for early diagnosis and treatment before the symptom. Distinction between the clinical forms of these diseases is based on clinical findings and biochemical results, however, they may not be clearcut. Treatment is different from each other, so exact diagnosis is essential. Here, the diagnostic algorithm for elevated citrulline after tandem mass screening has been proposed. Minimizing total process time from sampling to report of the results is important in Korea for diagnosis and treatment of these disorders.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3458-3481
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• 2021

Existing methods for blind identification of linear block codes without a candidate set are mainly built on the Gauss elimination process. However, the fault tolerance will fall short when the intercepted bit error rate (BER) is too high. To address this issue, we apply the reverse algebra approach and propose a novel "two-step-screening" algorithm by solving the linear error equations on the binary Galois field, or GF(2). In the first step, a recursive matrix partition is implemented to solve the system linear error equations where the coefficient matrix is constructed by the full codewords which come from the intercepted noisy bitstream. This process is repeated to derive all those possible parity-checks. In the second step, a check matrix constructed by the intercepted codewords is applied to find the correct parity-checks out of all possible parity-checks solutions. This novel "two-step-screening" algorithm can be used in different codes like Hamming codes, BCH codes, LDPC codes, and quasi-cyclic LDPC codes. The simulation results have shown that it can highly improve the fault tolerance ability compared to the existing Gauss elimination process-based algorithms.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.229-239
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• 2018

Purpose: There is a difficulty in Environmental Stress Screening (ESS) test design for weapon system's electrical/electronic components/products in small and medium-sized enterprises. To overcome this difficulty, I propose an easy ESS test design approach algorithm that is optimized with only one environment tolerance design information parameter (${\Delta}T$). Methods: To propose the mass production weapon system ESS test design for cost-effective optimization, I define an optimum cost-effective mathematical model ESS test algorithm model based on modified MIL-HDBK-344, MIL-HDBK-2164 and DTIC Technical Report 2477. Results: I clearly confirmed and obtained the quantitative data of ESS effectiveness and cost optimization along our ESS test design algorithm through the practical case. I will expect that proposed ESS test method is used for ESS process improvement activity and cost cutting of mass production weapon system manufacturing cost in small and medium-sized enterprises. Conclusion: In order to compare the effectiveness of the proposed algorithm, I compared the effectiveness of the existing ESS test and the proposed algorithm ESS test based on the existing weapon system circuit card assembly for signal processing. As a result of the comparison, it was confirmed that the test time was reduced from 573.0 minutes to 517.2minutes (9.74% less than existing test time).

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.142-149
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• 2022

In increasing the safety and usage of lithium-ion battery packs, reducing the parameter deviation between cells, such as voltage and temperature within the battery pack, is important. In this study, we propose a screening method to reduce parameter deviation between cells in battery packs. Screening algorithms are constructed based on Fuzzy logic and quantitatively express the similarities between battery cells. Screening is applied by utilizing series resistance components after experiments of electrical characteristics that consider the operation status of battery packs. After screening, the standard deviation of series resistance components according to the similarity ranking is compared and analyzed, and their conformity are verified with the algorithm parameters.

• Journal of Biomedical Engineering Research
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• v.14 no.2
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• pp.185-193
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• 1993

In this paper, the peak detection algorithm was developed for the purpose of screening of the target compounds. Algorithm is divided into searching the characteristic ion and peak detection. The heuristic knowledge about analytical chemistry was applied for the searching the characteristic ion. Peak detection was accomplished in comparison with the peak identification strings and pattern strings around the retention time. Pattern strings are composed with the number which generated by pattern identification function. The variables of pattern identification function are the codes which represent the difference of two adjacent abundances Some of the free steroids were selected to demonstrate the proposed algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.265-274
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• 2022

This paper proposes a machine learning-based screening algorithm to build the retired battery pack of the energy storage system. The proposed algorithm creates the dataset of various performance parameters of the retired battery, and this dataset is preprocessed through a principal component analysis to reduce the overfitting problem. The retried batteries with a large deviation are excluded in the dataset through a density-based spatial clustering of applications with noise, and the K-means clustering method is formulated to select the group of the retired batteries to satisfy the deviation requirement conditions. The performance of the proposed algorithm is verified based on NASA and Oxford datasets.

• Journal of the Korean Institute of Gas
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• v.7 no.1 s.18
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• pp.1-9
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• 2003

A Multi-distinction Equipment Screening Algorithm (MESA) is proposed. It selectively integrates Dow's F&EI as its process hazard index technique and ESA (Equipment Screening Algorithm) as qualitative hazard classification technique, and retrieves a detailed list of hazardous equipments with the total hazard indices of those equipments. The inherent expert system, which includes the accident scenarios of the equipments and processes and experts' views of them, narrows further down the list of hazardous equipments and recommends only the most notable candidates. Through the case study of distinguishing the hazardous ranking of the equipments of the LPG underground storage process, using the expert system or not, the applicability of MESA has been validated. Taking the characteristics of the process equipments with hazardous ranking in the point of process intrinsic safety, this proposed algorithm would contribute to providing engineers or managers with information on constructing safely devices and mitigation devices and on scheduling emergency response planning.

• Journal of KIEE
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• v.11 no.1
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• pp.55-61
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• 2001

SIME(Single Machine Equivalent) method has been recognized as a useful tool to determine transient stability of power system. In this paper, SIME method is used to develop the KEPCO transient stability assessment (TSA) tool. A new screening algorithm that can be generators are identified by a new index in the early stage of the time domain simulation. Thus, computational time require to find OMIB(One Machine Infinite Bus) can be reduced significantly. Second, clustering critical machines can be performed even in very stable cases. It enables to be avoid extra calculation of time trajectory that is needed in SIME for classifying the stable cases. This algorithm is applied to the fast TSA of the KEPCO system in the year of 2010.