• The Journal of Society for e-Business Studies
• /
• v.24 no.4
• /
• pp.119-133
• /
• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.

• Proceedings of the Korean DIstribution Association Conference
• /
• 2007.08a
• /
• pp.27-38
• /
• 2007

본 연구는 갈수록 설 자리를 잃어 가는 지역 상권에 있어서 최근 10년 여 기간 동안 원주시에서 지속적으로 정치${\cdot}$경제적, 사회적 이슈로 제기되어 왔던 문제는 지하상가 상권의 침체와 활성화 문제라 할 수 있다. 원주 지하상가는 정부의 요구에 의하여 민방공 대피시설로 생겼으며, 각종 연구보고서나 학술세미나의 정책주제로 지하상가 도심 활성화 문제가 거론되고 있다. 특히 매번 지방선거에서는 지하상가 상권 활성화를 선거공약으로 제시하지 않은 후보가 없었을 정도였다는 것을 우리는 기억하고 있다. 그만큼 지하상가의 문제가 심각하다는 의미이며, 지하상가의 활성화를 통한 도시개발은 원주시민 공동의 과제라는 점을 이해 할 수 있다. 이와 같은 지역사회의 요청에 따라 그동안 수많은 개선안들이 원주시 차원에서 추진되었다. 지하상가 주변에 특화거리를 지정${\cdot}$조성하는 '특화거리 조성사업'에서부터, 주차문제 해결을 위한 '공영주차장 건설사업', '재래시장 현대화사업', '주거환경개선사업', '하상도로 건설사업', '지하상가 리모델링사업' 등 단기 및 중장기 사업계획이 추진되고 있다. 그럼에도 불구하고 크게 개선되지 못하고 있는 실정이며, 앞으로 계속 우리가 깊은 관심을 갖고 해결해 나가야 할 과제로 남아 있다. 그러나 최근 원일프라자 준공을 전후하여 지하상가는 조금씩 변화의 조짐을 보이고 있으며, 일부에서는 도심이 활성화될 것이라는 성급한 판단을 내리기도 한다. 원주시는 미약하나마 인구가 증가하는 추세이며, 전반적으로 도심이 침체의 늪에서 벗어나고 있는 인상을 주고 있기 때문이다. 그러나 이러한 변화가 과연 도심이 활성화되고 있는 징후로 볼 것인가? 특히 이러한 변화의 조짐이 원일프라자의 준공과 직접적인 관련성을 갖고 있는가? 몇가지 변화의 사례를 가지고 간단하게 판단할 수는 없다. 그러나 원일프라자의 준공은 도심지역의 개발${\cdot}$정비를 예정하고 있으며, 장기적으로는 도심 활성화의 중요한 동인이 될 수 있음을 부인할 수 없다. 따라서 본 발제에서는 이와 같은 상황적 변화를 전제로 하여 지하상가 리모델링을 통한 도심활성화와 선진사례를 받아들임으로 지역상권 활성화 방향으로 전환하는 것이 바람직할 것으로 판단된다.

• KIISE Transactions on Computing Practices
• /
• v.23 no.5
• /
• pp.322-327
• /
• 2017

The classification problem in the field of Natural Language Processing has been studied for a long time. Continuing forward with our previous research, which classifies large-scale text using Convolutional Neural Networks (CNN), we implemented Recurrent Neural Networks (RNN), Long-Short Term Memory (LSTM) and Gated Recurrent Units (GRU). The experiment's result revealed that the performance of classification algorithms was Multinomial Naïve Bayesian Classifier < Support Vector Machine (SVM) < LSTM < CNN < GRU, in order. The result can be interpreted as follows: First, the result of CNN was better than LSTM. Therefore, the text classification problem might be related more to feature extraction problem than to natural language understanding problems. Second, judging from the results the GRU showed better performance in feature extraction than LSTM. Finally, the result that the GRU was better than CNN implies that text classification algorithms should consider feature extraction and sequential information. We presented the results of fine-tuning in deep neural networks to provide some intuition regard natural language processing to future researchers.

• Journal of Korea Water Resources Association
• /
• v.52 no.8
• /
• pp.575-587
• /
• 2019

This study evaluated the effect of a mother wavelet in the wavelet analysis of various times series made by combining white noise and/or sine function. The result derived is also applied to short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). This study, different from previous studies evaluating one or two mother wavelets, considers a total of four generally-used mother wavelets, Bump, Morlet, Paul, and Mexican Hat. Summarizing the results is as follows. First, the Bump mother wavelet is found to have some limitations to represent the unstationary behavior of the periodic components. Its application results are more or less the same as the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the non-stationary behavior of the periodic components. Finally, the Mexican Hat mother wavelet is found to be too complicated to interpret. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelet is most frequently used in the wavelet analysis research.

• Tuberculosis and Respiratory Diseases
• /
• v.62 no.6
• /
• pp.549-553
• /
• 2007

Sarcoidosis is a multi-systemic syndrome of an unknown etiology, and it is characterized by the formation of multiple noncaseating granulomas that disrupt the architecture and function of the tissues in which they reside. The most commonly affected organs are lung, skin and lymph nodes. Overt clinical involvement of the nervous system is uncommon and this occurs in about 5% of all patients during the course of their disease. The most common manifestations are granulomatous leptomeningitis, cranial nerve palsy, electrolyte or other endocrinologic abnormalities, but isolated memory impairment is a rare manifestation. This is a case of 59 years-old male with recent memory impairment, and he was previously diagnosed with pulmonary sarcoidosis by transbronchial lung biopsy. The brain MRI imaging revealed the leptomeningeal and parenchymal involvement of sarcoidosis. He was treated with high dose corticosteroid and his memory function was improved to nearly a normal level. We report here on a case of successful treatment of pulmonary sarcoidosis combined with neurosarcoidosis with using high dose corticosteroid, and the patient presented with recent memory impairment.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.10
• /
• pp.8-15
• /
• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Journal of The Korean Association of Information Education
• /
• v.25 no.5
• /
• pp.733-740
• /
• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.377-383
• /
• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• Korean Security Journal
• /
• no.9
• /
• pp.99-131
• /
• 2005

Terrorism which became today's common phenomena over the world is one of the most serious threats the world confront. Although International society make and operate outstanding anti-terrorism system, terror would never end without solving fundamental problems. The main body of terrorism converts from nation to organization and from organization to cell, which makes it difficult for us to recognize the main body. Since the target of today's new terrorism is many and unspecified persons, terrorists will never hesitate to use mass destruction weapons such as nuclear, biological, chemical weapons, and also use cyber-technique or cyber-terrorism. So, effective counter-terrorism measures should be performed as follows. First, it must be better for international society should make long-time plan of solving fundamental problems of terrorism other than to operate directly on terror organization and its means. Second, preventive method should be made. The most effective method of eradicating terrorism is prevention. For this, it is necessary to remove environmental elements of terrorism and terrorist bases, and to stop inflow of money and mass destruction weapons to terrorists. Third, integrated anti-terror organization should be organized and operated for continuous counter-terrorism operations. Also international alliance for anti-terrorism should be maintained to share informations and measures. Fourth, concerned department in the government should prepare counter-terrorism plans in their own parts as follows and make efforts to integrate the plans. - Ministry of Government Administration and Home Affairs : conventional terror - Ministry of Health and Welfare : bio-terror - Ministry of Science and Technology : nuclear-terror Especially, they should convert their policy and operation from post-terror actions to pre-terror actions, designate terror as national disaster and organize integrated emergency response organization including civil, government, and military elements. In conclusion, pre-terror activities and remedy of fundamental causes is the best way to prevent terror. Also, strengthening of intelligence activities, international cooperations, and preventive and comprehensive counter-measures must not ignored.

• Korean Journal of Food Science and Technology
• /
• v.49 no.6
• /
• pp.649-658
• /
• 2017

The potential of the ethyl acetate fraction from Pteridium aquilinum (EFPA) to improve the cognitive function in high-fat diet (HFD)-induced diabetic mice was investigated. EFPA-treatment resulted in a significant improvement in the spatial, learning, and memory abilities compared to the HFD group in behavioral tests, including the Y-maze, passive avoidance, and Morris water maze. The diabetic symptoms of the EFPA-treated groups, such as fasting glucose and glucose tolerance, were alleviated. The administration of EFPA reduced the acetylcholinesterase (AChE) activity and malondialdehyde (MDA) content in mice brains, but increased the acetylcholine (ACh) and superoxide dismutase (SOD) levels. Finally, kaempferol-3-o-glucoside, a major physiological component of EFPA, was identified by using high-performance liquid chromatography coupled with a hybrid triple quadrupole-linear ion trap mass spectrometer (QTRAP LC-MS/MS).