• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.12
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• pp.594-602
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• 1986

This paper proposes an effective algorithm for short-term generation scheduling for the purpose of economic and secure operation of thermal power systems. Especially, in the procedure of solution by Dynamic Programming, Linear Programming is introduced to promote the possibility of optimal solution and the security of power systems, and evaluation of security function is improved by the application of seven step approximation of normal distribution. Several necessary considerations, that is, time dependent start-up and constant down cost of generating units, demand and spinning reserve constraints, minimum up and sown time constraints, the number of possible start-up of a generating unit in a d and the number of generating units which can be started up at the same time at the same bus, are also incoporated to elevate the usability and flexibility of the algorithm. Finally, the effectiveness of the proposed algorithm has been demonstrated by applying to the 6-gen. 21-bus model power system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.54-61
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• 2015

This paper presents short-term wind farm power forecasting method using multivariate analysis and time series. Based on factor analysis, the proposed method makes new independent variables which newly composed by raw independent variables such as wind speed, ramp rate, wind power. Newly created variables are used in the time series model for forecasting wind farm power. To demonstrate the improved accuracy, the proposed method is compared with persistence model commonly used as reference in wind power forecasting using data from Jeju Island. The results of case studies are presented to show the effectiveness of the proposed forecasting method.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.230-232
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• 2001

This paper presents a model for short-term load forecasting using multiple time-series. We made one-hour ahead load forecasting without classifying load data according to daily load patterns(e.g. weekday. weekend and holiday) To verify its effectiveness. the results are compared with those of neuro-fuzzy forecasting model(5). The results show that the proposed model has more accurate estimate in forecasting.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.289-291
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• 1998

This paper presents short-term hydro scheduling method for hydrothermal coordination by genetic algorithm. Hydro scheduling problem has many constraints with fixed final reservoir volume. In this paper, the difficult water balance constraints caused by hydraulic coupling satisfied throughout dynamic decoding method. Adaptive penalizing method was also proposed to handle the infeasible solutions that violate various constraints. The effectiveness of proposed method in this paper was examined through the case studies. Further studies for the validation of the hydro scheduling scheme obtained by genetic algorithm will be very appreciated.

• ETRI Journal
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• v.44 no.3
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• pp.438-449
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• 2022

This study proposes a dependency grammar-based self-attention multilayered bidirectional long short-term memory (DG-M-Bi-LSTM) model for subject-predicate-object (SPO) tuple recognition from natural language (NL) sentences. To add recent knowledge to the knowledge base autonomously, it is essential to extract knowledge from numerous NL data. Therefore, this study proposes a high-accuracy SPO tuple recognition model that requires a small amount of learning data to extract knowledge from NL sentences. The accuracy of SPO tuple recognition using DG-M-Bi-LSTM is compared with that using NL-based self-attention multilayered bidirectional LSTM, DG-based bidirectional encoder representations from transformers (BERT), and NL-based BERT to evaluate its effectiveness. The DG-M-Bi-LSTM model achieves the best results in terms of recognition accuracy for extracting SPO tuples from NL sentences even if it has fewer deep neural network (DNN) parameters than BERT. In particular, its accuracy is better than that of BERT when the learning data are limited. Additionally, its pretrained DNN parameters can be applied to other domains because it learns the structural relations in NL sentences.

• Korean Journal of Bronchoesophagology
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• v.19 no.1
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• pp.11-14
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• 2013

Gastro-esophageal reflux disease (GERD) is a recurrent, long-term gastrointestinal condition characterised by the abnormal reflux of stomach contents into the esophagus. Heartburn is the most dominant symptom, which can be life long and can considerably reduce quality of life. The main goals of treatment are to alleviate symptoms and prevent relapses, esophageal stricture and adenocarcinoma. This paper presents a review comparing the effectiveness of omeprazole with Nissen fundoplication surgery for the treatment of GERD. Nissen fundoplication is more effective in controlling heartburn symptoms, healing esophagitis and preventing relapses than omeprazole. Quality of life, in terms of productivity and ability to work, is difficult to assess in the omeprazole group and, as a result, a comparison of this aspect is limited. Although fundoplication is expensive in the short term, it is more cost-effective than omeprazole. Nurses need to be aware of the effectiveness of omeprazole and fundoplication to provide patients with accurate information, which assists patients in decision making regarding treatment options.

• The Korean Journal of Gastroenterology
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• v.72 no.5
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• pp.245-251
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• 2018

Gastric cancer is the most common cancer in Korea and the fifth most common cancer globally. Helicobacter pylori (H. pylori) infection is considered the main etiologic agent for gastric cancer development. Most regional guidelines for H. pylori treatment recommend treating the organism to prevent gastric cancer in the high-risk group. However, evidence that such a strategy can also be applied to the general population, especially in terms of the preventive effect and safety, has not been adequately presented yet. Although a meta-analysis in the general population suggested effectiveness in decreasing gastric cancer incidence, individual studies should be critically reviewed to evaluate the soundness of the evidence. Recently published, long-term, Korean studies on metachronous gastric cancer prevention ended the controversies from previous short-term studies and confirmed the effectiveness. Currently, further prospective, large, randomized studies are ongoing in the general population and will provide more definitive, high-level evidence on this gastric cancer prevention strategy in the next decade.

• Korean Association of Arts Management
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• no.53
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• pp.207-247
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• 2020

is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

• Computers and Concrete
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• v.30 no.5
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• pp.301-310
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• 2022

Cement-based sensors have been widely used as structural health monitoring systems, however, their long-term sensing performance have not actively investigated. In this study, a deep learning-based methodology is adopted to predict the long-term piezoresistive properties of cement-based sensors. Samples with different multi-walled carbon nanotube contents (0.1, 0.3, and 0.5 wt.%) are fabricated, and piezoresistive tests are conducted over 10,000 loading cycles to obtain the training data. Time-dependent degradation is predicted using a modified long short-term memory (LSTM) model. The effects of different model variables including the amount of training data, number of epochs, and dropout ratio on the accuracy of predictions are analyzed. Finally, the effectiveness of the proposed approach is evaluated by comparing the predictions for long-term piezoresistive sensing performance with untrained experimental data. A sensitivity of 6% is experimentally examined in the sample containing 0.1 wt.% of MWCNTs, and predictions with accuracy up to 98% are found using the proposed LSTM model. Based on the experimental results, the proposed model is expected to be applied in the structural health monitoring systems to predict their long-term piezoresistice sensing performances during their service life.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.311-324
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• 2022

The objective of this study is to examine the influence of fraud investigation on organizational performance of Thai listed companies through mediating effects of internal audit quality, accounting information transparency and financial effectiveness, and moderating effect of corporate governance. In this study, 333 Thai listed companies are the samples of the study. Both the structural equation model and multiple regression analysis are used to examine the research relationships. The results of this study show that fraud investigation has a significant influence on internal audit quality, accounting information transparency, and financial effectiveness. Internal audit quality significantly influences accounting information transparency, financial effectiveness, and organizational performance while financial effectiveness significantly influences organizational performance. Next, both internal audit quality and financial effectiveness potentially mediate the fraud investigation-organizational performance relationships. In addition, corporate governance critically moderates the fraud investigation-internal audit quality relationships and the fraud investigation-financial effectiveness relationships. In summary, fraud investigation functions as an important valuable technique of internal audit practices. As a result, businesses must build and implement a systematic fraud investigation procedure to generate and improve beneficial outcomes in the short, medium, and long term.