• Genomics & Informatics
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• v.20 no.2
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• pp.22.1-22.9
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• 2022

The rise of newer coronavirus disease 2019 (COVID-19) variants has brought a challenge to ending the spread of COVID-19. The variants have a different fatality, morbidity, and transmission rates and affect vaccine efficacy differently. Therefore, the impact of each new variant on the spread of COVID-19 is of interest to governments and scientists. Here, we proposed mathematical SEIQRDVP and SEIQRDV3P models to predict the impact of the Omicron variant on the spread of the COVID-19 situation in South Korea. SEIQEDVP considers one vaccine level at a time while SEIQRDV3P considers three vaccination levels (only one dose received, full doses received, and full doses + booster shots received) simultaneously. The omicron variant's effect was contemplated as a weighted sum of the delta and omicron variants' transmission rate and tuned using a hyperparameter k. Our models' performances were compared with common models like SEIR, SEIQR, and SEIQRDVUP using the root mean square error (RMSE). SEIQRDV3P performed better than the SEIQRDVP model. Without consideration of the variant effect, we don't see a rapid rise in COVID-19 cases and high RMSE values. But, with consideration of the omicron variant, we predicted a continuous rapid rise in COVID-19 cases until maybe herd immunity is developed in the population. Also, the RMSE value for the SEIQRDV3P model decreased by 27.4%. Therefore, modeling the impact of any new risen variant is crucial in determining the trajectory of the spread of COVID-19 and determining policies to be implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.581-586
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• 2010

MC-DS-CDMA is technique where a single data symbol is transmitted at multiple subcarriers which are orthogonal to each other. With this technique, frequency diversity can be achieved. Time variant channels lead to interchannel interference which increases the bit error rate for MC-DS-CDMA systems. The performance of PSAM MC-DS-CDMA system over time variant channels is analyzed. The BER performance of this system over multipath fading environment is evaluated, considering the channel estimation error, carrier frequency offset.

• Korean Journal of Hydrosciences
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• v.8
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• pp.69-83
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• 1997

The Parameters of the storage function model (SFM) are taken as constants, while they have different values during every rainfall period and the duration of the runoff. Therefore, the results of the SFM generally show remarkably large errors. In this study, the modified storage function model (MSFM), in which the time variant parameters are introduced, is proposed to improve the SFM which is a conceptual rainfall-runoff model. The fuzzy reasoning method is applied as a real-time control one of the time variant parameters of the proposed model. The applicability of the MSFM was examined in the Bochung river, at a tributary of the Geum River, Korea. The pattern of the predicted runoff hydrograph and the peak discharge by the MSFM with fuzzy control are very similar to the measured values, compared with the results produced by the SFM.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.2
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• pp.35-44
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• 2003

A system reliability method is proposed to decide reliable serviceability of agricultural irrigation system. Even though reliability method is applied to real engineering situations involving actual life environments and maintaining costs, a number of Issues arise as a modeling and analysis level. This article use concepts that can be described the probability of failure with time variant and series-parallel system reliability analysis model. A proposed method use survivor function that can simulate a time-variant performance function for a lifetime before it is required essential maintenance or replacement to define a target probability of failure in agricultural irrigation canal. In the further study, it is required a relationship between a state of probability of failure and current serviceability to make the optimum repair strategy to maintain appropriate serviceability of an irrigation system.

• Korean Journal of Head & Neck Oncology
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• v.20 no.2
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• pp.123-127
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• 2004

Objectives: The tall cell variant is an uncommon variant and has been known as more aggressive form of papillary thyroid carcinoma (PTC). Owing to the rarity of these thyroid cancers, their clinical behavior remains incompletely understood. To elucidate the clinicopathologic characteristics of tall cell variant, we retrospectively reviewed our surgical experience of patients with tall cell variant. Methods: Between August 1993 and July 2004, a total of 11 consecutive patients who were pathologically diagnosed with tall cell variant of papillary thyroid carcinoma were enrolled in this study. All patients underwent total (8 cases) or subtotal thyroidectomy (3 cases) with central compartment node dissections. The lateral neck dissection was added in 6 patients. After the operation, neck ultrasound and serum thyroglobulin were checked regularly during the follow-up period. Results: The mean age of the patients was 56.6years (range, 30-74years) at the time of diagnosis. 3 patients were men, and 8 were women. The mean diameter of tumor was 3.7cm(range, 1.5-6.0cm), and 6 patients had lateral neck node metastasis. Extrathyroidal extension was seen in 5 patients (45%). Loco-regional recurrence was found in 2 patients (18%), and distant metastasis in 1 patient (9%). The 5-year disease free survival rate was 68%. Conclusion: The tall cell variant of papillary thyroid carcinoma is an uncommon disease. Clinicopathologic feature and prognosis of this disease show more aggressive behaviors than ordinary papillary thyroid carcinoma. More aggressive treatment and close follow-up should be undertaken in the tall cell variant of papillary thyroid carcinoma.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.923-926
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• 2000

In this paper we address the problem of detecting and estimating an unknown narrow band signal in a noise interference environment A new practical band estimation method, yielding good performance even in case of finite-length data, is presented. More specifically, wavelet packet transform is utilized to detect the more accurate time-variant band, then we estimate the power from wavelet filter-coefficients of the respective band. Also, third-order cumulants, and projection cross-correlation (PCC) criterion are utilized to achieve an effective SNR improvement for the time-variant band estimation. In case of time variant band estimation, the PCC method yields better performance than the correlation method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.435-439
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• 2007

This paper deals with RLS algorithm using Newton-Raphson method based adaptive forgetting factor for a passive telemetry RF sensor system in order to estimate the time variant parameter to be included in RF sensor model. For this estimation with RLS algorithm, phasor typed RF sensor system modelled with inductive coupling principle is used. Instead of applying constant forgetting factor to estimate time variant parameter, the adaptive forgetting factor based on Newton-Raphson method is applied to RLS algorithm without constant forgetting factor to be determined intuitively. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1098-1102
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• 1990

We consider a method for enhancement of speech signal degraded by additive random noise with time-variant and/or colored natures. For enhancement of speech signal with such noise, it is effective to utilize the natures of speech and noise. The objective of enhancement of speech is to improve the overall quality and the articulation of speech degraded by the time-variant and/or colored random noise. In the proposed method the distribution model of speech spectrum is given as information to noise reduction system. The proposed system can improve about lOdB in SNR when the input SNR is 0 dB.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.410-413
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• 2008

Existing Outlier detections have been widely studied in geosensor networks. Recently, machine learning and data mining have been applied the outlier detection method to build a model that distinguishes outliers based on anchored criterion. However, it is difficult for the existing methods to detect outliers against incoming time-variant data, because outlier detection needs to monitor incoming data and classify irregular attacks. Therefore, in order to solve the problem, we propose a time-variant outlier detection using 2-dimensional grid method based on unanchored criterion. In the paper, outliers using geosensor data was performed to classify efficiently. The proposed method can be utilized applications such as network intrusion detection, stock market analysis, and error data detection in bank account.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1948-1951
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• 2002

In this paper, we propose a chip timing recovery algorithm that is robust to frequency offset and time variant fading environments for DS/CDMA. The proposed structure is a modified non-coherent Delay Locked Loop (DLL) that employs a decimator. Analytical expression for the proposed non-coherent DLL S-curve and steady-state timing jitter is derived and confirmed by computer simulation. The results show that the proposed structure can reduce a steady-state timing jitter of the regenerated spreading code replica to frequency offset and time-variant fading in mobile radio channel, especially in very low SNR.