• Korean Chemical Engineering Research
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• v.56 no.6
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• pp.871-877
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• 2018

Storing the surplus energy from renewable energy resource is one of the challenges related to intermittent and fluctuating nature of renewable energy electricity production. $CO_2$ methanation is well known reaction that as a renewable energy storage system. $CO_2$ methanation requires a catalyst to be active at relatively low temperatures ($250-500^{\circ}C$) and selectivity towards methane. In this study, the catalytic performance test was conducted using a pressurized bubbling fluidized bed reactor (Diameter: 0.025 m and Height: 0.35 m) with $Ni/{\gamma}-Al_2O_3$ (Ni70%, and ${\gamma}-Al_2O_3$30%) catalyst. The range of the reaction conditions were $H_2/CO_2$ mole ratio range of 4.0-6.0, temperature of $300-420^{\circ}C$, pressure of 1-9 bar, and gas velocity ($U_0/U_{mf}$) of 1-5. As the $H_2/CO_2$ mole ratio, temperature and pressure increased, $CO_2$ conversion increases at the experimental temperature range. However, $CO_2$ conversion decreases with increasing gas velocity due to poor mixing characteristics in the fluidized bed. The maximum $CO_2$ conversion of 99.6% was obtained with the operating condition as follows; $H_2/CO_2$ ratio of 5, temperature of $400^{\circ}C$, pressure of 9 bar, and $U_0/U_{mf}$ of 1.4-3.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1456-1471
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• 2018

This article discusses the nutritional requirements, reviews senior or geriatric dog nutritional evaluation, and then addresses some common nutrition-related problems in older dogs. The purpose of this study was to investigate the Physiologic change associated with aging, essential nutrients and their diseases in senior or geriatric dog subjects. According to a 2002 market research, 30% to 40% of dogs raisedin the United States are 7 years of age. In Europe the number of dogs considered to be "senior or geriatric" (>7 years of age) increased by approximately 50% between 1983 and 1995. A 2012 e-mail survey of 50,347 respondents revealed that 33.2% of dogs were 6 to 10 years of age and 14.7% were older than 11 years in the United States. The average life expectancy of dogs raised in the home is affected by health care, aging and nutrition.And, the aging process is influenced by breed size, genetics, nutrition, environment, and other factors. Although many pets remain active and youthful well into their teens, most dogs start to slow down and may show signs of aging beginning as early as 5 or 6 years of age. Improvements in the control of various diseases and in the nutrition of dogs have resulted in a gradual increase in the average lifespan of companion dogs. Nutritional goals for aging dogs include supporting health and vitality, preventing the onset or slowing the progression of age-related health disorders, and enhancing the dog's quality of life and, if possible, life expectancy. Aging brings with its physiologicchanges. Some changes are obvious, such as whitening of hair, a general decline in body and coat condition, and failing senses including sight and hearing. Other changes are less obvious, however, and these include alterations in the physiology of the digestive tract, immune system, kidneys, and other organs. Nutritional requirements can change with age. In addition, many diseases common in older dogs may be nutrient-sensitive, meaning that diet can play an important role in the management of the condition.

• Korean Journal of Food Science and Technology
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• v.51 no.4
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• pp.379-392
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• 2019

The current study investigated the effect of Gabjubaekmok (Diospyros kaki) ethanolic extract (GEE) on $H_2O_2$-induced human neuroblastoma MC-IXC cells and amyloid beta $(A{\beta})_{1-42}$-induced ICR (Institute of Cancer Research) mice. GEE showed significant antioxidant activity that was evaluated based on ABTS, DPPH scavenging activity, and inhibition of malondialdehyde (MDA) and acetylcholinesterase activity. Further, GEE inhibited ROS production and increased cell viability in $H_2O_2$-induced MC-IXC cells. Administration of GEE ameliorated the cognitive dysfunction on $A{\beta}$-induced ICR mice as evaluated using Y-maze, passive avoidance, and Morris water maze tests. Results of ex vivo test using brain tissues showed that, GEE protected the cholinergic system and mitochondrial functions by increasing the levels of antioxidants such as ROS, mitochondrial membrane potential (MMP), and adenosine triphosphate (ATP) against $A{\beta}$-induced cognitive dysfunction. Moreover, GEE decreasd the expression levels of apoptosis-related proteins such as $TNF-{\alpha}$, p-JNK, p-tau, BAX and caspase 3. While, expression levels of p-Akt and $p-GSK3{\beta}$ increased than $A{\beta}$ group. Finally, gallic acid was identified as the main compound of GEE using high performance liquid chromatography.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.261-268
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• 2021

Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

• Food Science and Industry
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• v.50 no.4
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• pp.82-91
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• 2017

The purpose of this study was to investigate development and nutrient analysis of traditional food in the Sunchang area. A total 6 kinds of set tables was excavated from storytelling. Among set tables, taste and season food were the best in Sunchang gochujang hanjeongsik and Sunchang arirang season table. Shape color, smell, and commercialization possibility and differentiation were best in Sunchang arirang season table. Mole Ratio of sodium and potassium was 1:1 in Sunchang gochujang hanjeongsik and Sunchang arirang season table. The calcium contents in Sunchang gochujang hanjeongsik and Sunchang arirang season table were higher than other traditional foods. This result indicated that Sunchang gochujang hanjeongsik and Sunchang arirang season table are useful for traditional functional food. Also, it is highly suggested to make a database system about local food and standardization of traditional foods cookery.

• Clean Technology
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• v.27 no.1
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• pp.9-16
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• 2021

Since the active matrix organic light-emitting diode (AMOLED) encapsulation process is very vulnerable to moisture and oxygen, high-purity nitrogen with minimal moisture and oxygen must be used. In this study, a copper-based catalyst used to remove oxygen from nitrogen in the AMOLED encapsulation process was optimized. Two-component and three-component catalysts composed of CuO, Al2O3, or ZnO were prepared through a co-precipitation method. The prepared catalysts were characterized by using BET, XRD, TPR, and XRF analysis. In order to verify the oxygen removal performance of the catalyst, several catalytic reactions were conducted in a fixed bed reactor, and the corresponding oxygen contents were measured through an oxygen analyzer. In addition, reusability of the catalysts was proven through repetitive regeneration. The properties and oxygen removal capacity of the catalysts prepared with CuO and Al2O3 ratios of 6 : 4, 7 : 3, and 8 : 2 were compared. The number of active sites of the catalyst with a ratio of CuO and Al2O3 of 8 : 2 was the highest among the 2-component catalysts. Moreover, the reducibility of the catalyst with a ratio of CuO and Al2O3 of 8 : 2 was the best as it had the highest CuO dispersion. As a result, the oxygen removal ability of the catalyst with a ratio of CuO and Al2O3 of 8 : 2 was the best among the 2-component catalysts. The best oxygen removal capacity was obtained when 2wt% of ZnO was added to the sub-optimized catalyst (i.e., CuO : Al2O3 = 8 : 2) probably due to its outstanding reducibility. Furthermore, the optimized catalyst kept its performance during a couple of regeneration tests.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.318-331
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• 2021

This study was conducted on the assumption that bone age would be more effective when it comes to physique and physical fitness assessment for adolescents, and the purpose of this study was to identify the differences in physique and physical fitness for students in their adolescence through bone age and chronological age in order to contribute to the well-balanced physique and physical fitness development in adolescents and the health improvement in students. Total 874 adolescents(483 males, 391 females) aged 11~16 were selected as subjects out of the total population of 1100 adolescents aged 6~16 based on the PAPS(Physical Activity Promotion System) and age standards of the TW3 method; and skeletal maturation, which symbolize the indicators of biological maturation, were evaluated by using the TW3(Tanner-Whitehouse 3) method after hand-wrist radiographs, and birth date was used for chronological age. A stadiometer and InBody 270 (Biospace, Korea) were used to measure 2 components in physique. A total of 7 components in physical fitness, which included muscular strength, muscular endurance, flexibility, power, cardiovascular endurance, balance, agility, were measured as well. A independent samples t-test was conducted for data processing using SPSS 25.0, and the significance level was set at p< .05. The study results are as follows. First, bone age and chronological age used for physique comparison in males aged 11 and 12, height and weight showed significant difference; in males aged 13, weight showed signicant difference. Weight and height in females aged 11, and height in females aged 12 showed significant difference. Second, bone age and chronological age used for physical fitness comparison in males aged 11, muscular strength, power, flexibility, cardiovascular endurance showed significant difference; in males aged 12, muscular strength. power, cardiovascular endurance; in males aged 13, flexibility showed significant difference. Muscular strength, power, flexibility, muscular endurance, cardiovascular endurance in females aged 11, and flexibility in females aged 14 showed significant difference. As a result, this study concluded that in a period of rapid skeletal growth, evaluating physique and physical fitness based on bone age is more accurate than evaluating based on chronological age.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.