• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.29-38
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• 2015

The Energy Storage System stores electricity for later use. This system can store electricity from legacy electric power systems or renewable energy systems into a battery device when demand is low. When there is high electricity demand, it uses the electricity previously stored and enables efficient energy usage and stable operation of the electric power system. It increases the energy usage efficiency, stabilizes the power supply system, and increases the utilization of renewable energy. The recent increase in the global interest for efficient energy consumption has increased the need for an energy storage system that can satisfy both the consumers' demand for stable power supply and the suppliers' demand for power demand normalization. In general, an energy storage system consists of a Power Conditioning System, a Battery Management System, a battery cell and peripheral devices. The specifications of the subsystems that form the energy storage system are manufacturer dependent. Since the core component interfaces are not standardized, there are difficulties in forming and operating the energy storage system. In this paper, the design of the profile structure for energy storage system and realization of private profiling system for energy storage system is presented. The profiling system accommodates diverse component settings that are manufacturer dependent and information needed for effective operation. The settings and operation information of various PCSs, BMSs, battery cells, and other peripheral device are analyzed to define profile specification and structure. A profile adapter software that can be applied to energy storage system is designed and implemented. The profiles for energy storage system generated by the profile authoring tool consist of a settings profile and operation profile. Setting profile consists of configuration information for energy device what composes energy saving system. To be more specific, setting profile has three parts of category as information for electric control module, sub system, and interface for communication between electric devices. Operation profile includes information in relation to the method in which controls Energy Storage system. The profiles are based on standard XML specification to accommodate future extensions. The profile system has been verified by applying it to an energy storage system and testing charge and discharge operations.

• Journal of agriculture & life science
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• v.46 no.5
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• pp.143-152
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• 2012

This study was performed to reduce the operating cost of a greenhouse by securing electric energy required for greenhouse operation. Therefore, it experimentally reviewed the performance analysis of photovoltaic system in terms of maximum amount of generated electric power based on the amount of horizontal solar radiation during daytime. That is to say, the maximum solar radiation at 300, 400, 500, 600, 700, 800 and 900 W. $m^{-2}$, respectively. The amount of momentary electric power of the photovoltaic system at any was about 970 W and we found that the momentary efficiency of the photovoltaic system that was used for this experiment was 97%. In the case of this system, we found that electric power will be generated when amount of horizontal solar radiation is more than 200 W. $m^{-2}$, at minimum. If the amount of horizontal solar radiation is increased, the maximum power generation is also increased. At that time, the maximum efficiencies were 30, 78, 86 and 90%, respectively. However, when the amount of insolation was about 800 W. $m^{-2}$, the maximum power generation tended to be lower than 700 W. $m^{-2}$. The efficiency which caused the maximum electric power was decreased to less than 97% of the momentary generated electric power. When the total amounts of horizontal solar radiation per day were 3.24, 8.10, 10, 90, 12.70, 14.33, 19.53 and $21.48MJ{\cdot}m^{-2}$ respectively, the total amounts of power energy were 0.03, 0.40, 3.60, 4.37, 4.71, 4.70 and 4.91 kWh. And it represented that the total amounts of power energy were either decreased or increased a bit on the border between some solar radiations. The temperature at the back of the array tended to be higher than the temperature at the front but it demonstrated an increased when the amount of solar radiation increased. In the case of this system, the performance of the module in terms of degradation has not been shown yet.

• 대한공업교육학회지
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• v.44 no.1
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• pp.52-71
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• 2019

The quality of school education is a key element for national education development. An important factor that determines the quality of school education is qualities of teachers who are in responsible for school education in the field. Therefore, it is necessary to hire competent teachers in the teacher appointment exam for the secondary school. This necessity is evident especially for vocational high schools and Meister high schools with the introduction of 2015-revised curriculum based on NCS that separates each three subjects, "Electrical, Electronics Communication" resulting in the change of question mechanism, which requires new designing of assessment and content area. So, this study analyzes curriculum in college of education for "Electrical", "Electronics", "Communication", 2015-revised curriculum based on NCS and the development of standards for teacher qualifications and assessment area and evaluation of teaching ability in the subjects of the teacher appointment exam, "Electrical, Electronics Communication" Engineering" in 2009. The assessment area and content elements of "Electrical", "Electronics", "Communication are extracted from the analyzed results and they are verified by experts' consultation and presented as follows; First, the assessment area and content elements of the "Electrical" subject were designed to evaluate the NCS - based 2015 revised curriculum by presenting the NCS learning module to the evaluation area and content element in the basic subject "Electrical and Electronics Practice". Second, the section of "Electronics" presented the assessment area and content elements applying the Electronic Circuit, basic subject of the NCS and it also added "Electromagnetics", which is the basic part of Electronics in the Application of Electromagnetic waves that could be applied to the assessment. Third, the assessment area and content elements of "Communication" consist of the communication-related practice that is based on "Electrical" and "Electronic", considering the characteristics of "Communication Engineering". In particular, "Electrical and Electronics practice" which adds network construction practice and communication-related practice makes it to be able to evaluate the communication-related practical education.

• Journal of Astronomy and Space Sciences
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• v.36 no.1
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• pp.21-33
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• 2019

This paper focuses on the interpretation of radiation fluxes from active galactic nuclei. The advantage of positron annihilation spectroscopy over other methods of spectral diagnostics of active galactic nuclei (therefore AGN) is demonstrated. A relationship between regular and random components in both bolometric and spectral composition of fluxes of quanta and particles generated in AGN is found. We consider their diffuse component separately and also detect radiative feedback after the passage of high-velocity cosmic rays and hard quanta through gas-and-dust aggregates surrounding massive black holes in AGN. The motion of relativistic positrons and electrons in such complex systems produces secondary radiation throughout the whole investigated region of active galactic nuclei in form of cylinder with radius R= 400-1000 pc and height H=200-400 pc, thus causing their visible luminescence across all spectral bands. We obtain radiation and electron energy distribution functions depending on the spatial distribution of the investigated bulk of matter in AGN. Radiation luminescence of the non-central part of AGN is a response to the effects of particles and quanta falling from its center created by atoms, molecules and dust of its diffuse component. The cross-sections for the single-photon annihilation of positrons of different energies with atoms in these active galactic nuclei are determined. For the first time we use the data on the change in chemical composition due to spallation reactions induced by high-energy particles. We establish or define more accurately how the energies of the incident positron, emitted ${\gamma}-quantum$ and recoiling nucleus correlate with the atomic number and weight of the target nucleus. For light elements, we provide detailed tables of all indicated parameters. A new criterion is proposed, based on the use of the ratio of the fluxes of ${\gamma}-quanta$ formed in one- and two-photon annihilation of positrons in a diffuse medium. It is concluded that, as is the case in young supernova remnants, the two-photon annihilation tends to occur in solid-state grains as a result of active loss of kinetic energy of positrons due to ionisation down to thermal energy of free electrons. The single-photon annihilation of positrons manifests itself in the gas component of active galactic nuclei. Such annihilation occurs as interaction between positrons and K-shell electrons; hence, it is suitable for identification of the chemical state of substances comprising the gas component of the investigated media. Specific physical media producing high fluxes of positrons are discussed; it allowed a significant reduction in the number of reaction channels generating positrons. We estimate the brightness distribution in the ${\gamma}-ray$ spectra of the gas-and-dust media through which positron fluxes travel with the energy range similar to that recorded by the Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics (PAMELA) research module. Based on the results of our calculations, we analyse the reasons for such a high power of positrons to penetrate through gas-and-dust aggregates. The energy loss of positrons by ionisation is compared to the production of secondary positrons by high-energy cosmic rays in order to determine the depth of their penetration into gas-and-dust aggregations clustered in active galactic nuclei. The relationship between the energy of ${\gamma}-quanta$ emitted upon the single-photon annihilation and the energy of incident electrons is established. The obtained cross sections for positron interactions with bound electrons of the diffuse component of the non-central, peripheral AGN regions allowed us to obtain new spectroscopic characteristics of the atoms involved in single-photon annihilation.

• Journal of IKEEE
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• v.27 no.1
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• pp.122-126
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• 2023

In this paper, a control system for a complex microbial incubator was proposed. The proposed control system consists of a control unit, a communication unit, a power supply unit, and a control system of the complex microbial incubator. The controller of the complex microbial incubator is designed and manufactured to convert analog signals and digital signals, and control signals of sensors such as displays using LCD panels, water level sensors, temperature sensors, and pH concentration sensors. The water level sensor used is designed and manufactured to enable accurate water level measurement by using the IR laser method with excellent linearity in order to solve the problem that existing water level sensors are difficult to measure due to foreign substances such as bubbles. The temperature sensor is designed and used so that it has high accuracy and no cumulative resistance error by measuring using the thermal resistance principle. The communication unit consists of two LAN ports and one RS-232 port, and is designed and manufactured to transmit signals such as LCD panel, PCT panel, and load cell controller used in the complex microbial incubator to the control unit. The power supply unit is designed and manufactured to supply power by configuring it with three voltage supply terminals such as 24V, 12V and 5V so that the control unit and communication unit can operate smoothly. The control system of the complex microbial incubator uses PLC to control sensor values such as pH concentration sensor, temperature sensor, and water level sensor, and the operation of circulation pump, circulation valve, rotary pump, and inverter load cell used for cultivation. In order to evaluate the performance of the control system of the proposed complex microbial incubator, the result of the experiment conducted by the accredited certification body showed that the range of water level measurement sensitivity was -0.41mm~1.59mm, and the range of change in water temperature was ±0.41℃, which is currently commercially available. It was confirmed that the product operates with better performance than the performance of the products. Therefore, the effectiveness of the control system of the complex microbial incubator proposed in this paper was demonstrated.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.80-81
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• 2012

Recently, one of the critical issues in the etching processes of the nanoscale devices is to achieve ultra-high aspect ratio contact (UHARC) profile without anomalous behaviors such as sidewall bowing, and twisting profile. To achieve this goal, the fluorocarbon plasmas with major advantage of the sidewall passivation have been used commonly with numerous additives to obtain the ideal etch profiles. However, they still suffer from formidable challenges such as tight limits of sidewall bowing and controlling the randomly distorted features in nanoscale etching profile. Furthermore, the absence of the available plasma simulation tools has made it difficult to develop revolutionary technologies to overcome these process limitations, including novel plasma chemistries, and plasma sources. As an effort to address these issues, we performed a fluorocarbon surface kinetic modeling based on the experimental plasma diagnostic data for silicon dioxide etching process under inductively coupled C4F6/Ar/O2 plasmas. For this work, the SiO2 etch rates were investigated with bulk plasma diagnostics tools such as Langmuir probe, cutoff probe and Quadruple Mass Spectrometer (QMS). The surface chemistries of the etched samples were measured by X-ray Photoelectron Spectrometer. To measure plasma parameters, the self-cleaned RF Langmuir probe was used for polymer deposition environment on the probe tip and double-checked by the cutoff probe which was known to be a precise plasma diagnostic tool for the electron density measurement. In addition, neutral and ion fluxes from bulk plasma were monitored with appearance methods using QMS signal. Based on these experimental data, we proposed a phenomenological, and realistic two-layer surface reaction model of SiO2 etch process under the overlying polymer passivation layer, considering material balance of deposition and etching through steady-state fluorocarbon layer. The predicted surface reaction modeling results showed good agreement with the experimental data. With the above studies of plasma surface reaction, we have developed a 3D topography simulator using the multi-layer level set algorithm and new memory saving technique, which is suitable in 3D UHARC etch simulation. Ballistic transports of neutral and ion species inside feature profile was considered by deterministic and Monte Carlo methods, respectively. In case of ultra-high aspect ratio contact hole etching, it is already well-known that the huge computational burden is required for realistic consideration of these ballistic transports. To address this issue, the related computational codes were efficiently parallelized for GPU (Graphic Processing Unit) computing, so that the total computation time could be improved more than few hundred times compared to the serial version. Finally, the 3D topography simulator was integrated with ballistic transport module and etch reaction model. Realistic etch-profile simulations with consideration of the sidewall polymer passivation layer were demonstrated.