• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1714-1728
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• 2016

This paper presents improved harmonics extraction based on Adaptive Linear Neuron (ADALINE) algorithm for single phase photovoltaic (PV) shunt active power filter (SAPF). The proposed algorithm, named later as Improved ADALINE, contributes to better performance by removing cosine factor and sum of element that are considered as unnecessary features inside the existing algorithm, known as Modified Widrow-Hoff (W-H) ADALINE. A new updating technique, named as Fundamental Active Current, is introduced to replace the role of the weight factor inside the previous updating technique. For evaluation and comparison purposes, both proposed and existing algorithms have been developed. The PV SAPF with both algorithms was simulated in MATLAB-Simulink respectively, with and without operation or connection of PV. For hardware implementation, laboratory prototype has been developed and the proposed algorithm was programmed in TMS320F28335 DSP board. Steady state operation and three critical dynamic operations, which involve change of nonlinear loads, off-on operation between PV and SAPF, and change of irradiances, were carried out for performance evaluation. From the results and analysis, the Improved ADALINE algorithm shows the best performances with low total harmonic distortion, fast response time and high source power reduction. It performs well in both steady state and dynamic operations as compared to the Modified W-H ADALINE algorithm.

• Communications of Mathematical Education
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• v.32 no.2
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• pp.113-129
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• 2018

The importance of mathematics is increasing as human beings are entering the 4th industrial revolution era from the information society. In response to this trend, the government is also paying a lot of attention to math education by addressing 2012 mathematics education as 'the year of mathematics education.' However, many students are still suffering from mathematics and they feel math is difficult and even give up math. For this cause, students who give up math are showing up a lot in middle and high schools. For these math low achievers, the government, educational institutions, research institutes, and schools are creating and implementing a lot of programs. Among these programs, there is also a program called Math Clinic counseling. However, most of these math clinic counseling end up in a one-time events or are not linked to class because counselors and math teachers are different. So, this research focuses on this fact : gap between math clinical counseling and real mathematics class. The study analyze the reasons of the cause of low level of self-confidence in math and high level of math anxiety from the students. And it suggests some strategies for the individual students base on their difficulties. Applying these strategies to the students, the study mainly focused on how the strategies are presented in real class by observing practical classes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4115-4120
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• 2015

To ensure the transient stability of power system connected to a wind farm, wind power plant must be able to supply reactive power at the point of the common coupling(PCC). The reactive power capability of each individual wind turbine may not sufficient to maintain stability. Also, there are large reactive power losses in connection cables between wind farm and PCC. The static synchronous compensator(STATCOM) is considered for transient stability enhancement, because it provides many advantages such as the fast response time and superior reactive power support capability. In this paper, the effectiveness of a STATCOM in enhancing transient stability of power system connected to a wind farm is presented. The results of dynamic simulations show that STATCOM installed at the PCC can enhance transient stability.

• Advances in Energy Research
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• v.4 no.3
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• pp.189-202
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• 2016

This work emphasized optimum production of biodiesel using non-edible Prunus armeniaca (Bitter Apricot) oil via transesterification collected from the high altitude areas of Himachal Pradesh, India. In this study the author produced biodiesel through the process of transesterification by using an alkali catalyst with alcohol (methanol and ethanol), under the varying molar ratio (1:6, 1:9, 1:12), variable catalyst percentage (1% and 2%) and temperature ($70^{\circ}C$, $75^{\circ}C$, $80^{\circ}C$, $85^{\circ}C$). Furthermore, a few strong base catalysts were used that includes sodium hydroxide, potassium hydroxide, sodium metal and freshly prepared sodium methoxide. After screening the catalyst, response surface methodology (RSM) in connection with the central composite design (CCD) was used to statistically evaluate and optimize the biodiesel production operation using NaOH as catalyst. It was found that the production of biodiesel achieved an optimum level biodiesel yield with 97.30% FAME conversion under the following reaction conditions: 1) Methanol/oil molar ratio: 1:6, 2) Reaction time: 3h, 3) Catalyst amount: NaOH 2 wt. %, and 4) Reaction temperature: $85^{\circ}C$. The experimental results showed that the optimum production and conversion of biodiesel through the process of transesterification could be achieved under an optimal set of reaction conditions. The biodiesel obtained showed appropriate fuel properties as specified in ASTM, BIS and En- standards.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1071-1082
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• 2021

COVID-19 has changed a lot in our daily lives, where school classes and remote classes have been combined or converted to remote classes. Many students spent more time online, and cyberbullying, such as indiscriminate disclosure of their personal information, bullying of their classmates online, increased. In this paper, we propose an online education program as a countermeasure against cyberbullying. This program is designed for elementary, middle, and high school students and can also be used for informatics or ethics classes in the 2015 curriculum. The proposed program is divided into four major themes: 'Cyberbullying,' 'Information Security,' 'Cyber Crime,' and 'Language Violence,' and is divided into a total of ten topics according to its connection. It was organized to teach the topics evenly by grade. Also, the program's feasibility was verified by experts on the selection of educational contents and organizing of contents. In the future, it will be necessary to apply for this program and conduct an effectiveness analysis to measure whether it has effectively contributed to the decrease in cyberbullying rates among students and the improvement of coping skills.

• Journal of Elementary Mathematics Education in Korea
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• v.22 no.4
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• pp.331-368
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• 2018

This study is derived from a student who can add without knowing the addition principle. To understand where the student's response come from, we came to analyse the curriculum contents of natural numbers, decimals and fractions addition principle. At the same time, we surveyed two different school of forty six sixth grade participants with questionnaires to determine whether it is a problem of the student or an universal one. As a result, we found that there is a room for improvement in the addition and connections of addition. We propose appropriate instructional method regarding connections of addition and addition principle of natural numbers, decimals and fractions. The conclude there is a close relation and differences among the principles of natural numbers, decimals and fractions in the proposed instructional method. Therefore, we need to consider and instruct the differences of the number expansion.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.69-78
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• 1999

In this paper, a neural network approach to forecast Korean regional precipitation is presented. We first analyze the characteristics of the conventional models for time series prediction, and then propose a new model and its learning method for the precipitation forecast. The proposed model is a layered network in which the outputs of a layer are buffered within a given period time and then fed fully connected to the upper layer. This study adopted the dual connections between two layers for the model. The network behavior and learning algorithm for the model are also described. The dual connection structure plays the role of the bias of the ordinary Multi-Layer Perceptron(MLP), and reflects the relationships among the features effectively. From these advantageous features, the model provides the learning efficiency in comparison with the FIR network, which is the most popular model for time series prediction. We have applied the model to the monthly and seasonal forecast of precipitation. The precipitation data and SST(Sea Surface Temperature) data for several decades are used as the learning pattern for the neural network predictor. The experimental results have shown the validity of the proposed model.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.9-15
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• 2021

With the recent development of 5G and artificial intelligence technologies, it is interested in AIOT technology to collect, process, and analyze information in cloud edge environments. AIIoT technology is being applied to various smart environments, but research is needed to perform fast response processing through accurate analysis of collected information. In this paper, we propose a technique to minimize bandwidth and processing time by blocking the connection processing between AIOT information through fast processing and accurate analysis/forecasting of information collected in the smart environment. The proposed technique generates seeds for data indexes on AIOT devices by multipointing information collected by blockchain, and blocks them along with collection information to deliver them to the data center. At this time, we deploy Deep Neural Network (DNN) models between cloud and AIOT devices to reduce network overhead. Furthermore, server/data centers have improved the accuracy of inaccurate AIIoT information through the analysis and predicted results delivered to minimize latency. Furthermore, the proposed technique minimizes data latency by allowing it to be partitioned into a layered multilayer network because it groups it into blockchain by applying weights to AIOT information.

• Journal of Korean Medical Ki-Gong Academy
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• v.10 no.1
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• pp.130-157
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• 2007

The purpose of this research is to seek for efficient health maintenance device and to suggest desirable daily habit, based on the inquiry on interrelationship between workers' daily lives and their heartbeat change level. The paper survey about general features, case history and daily habits was conducted on workers during medical examination in Jeollabukdo, and examined their change of heartbeat as well. The results of research deducted from data analysis are as follows; 1. There found very positive interrelations between time-domain analysis and frequency-domain analysis, and MHR and LF/HF ratio had negative connection with other analyses. 2. The recipient showed high time-domain analysis when they are younger, have worked shorter or have spouse, and it contributes to stable sympathetic nerve and parasympathetic nerve as it stimulates autonomic nervous system. 3. According to the result of frequency-domain analysis, recipients showed higher TP and LF when they are younger, and the highest HF when they are under 34.The level of VLF was higher for university graduates than the ones who finished high school. The recipients showed higher TP and HF when they don't have spouse, and lower TP, LF and HF when they have worked longer. 4. The level of RMSSD and TSRD was high for the people who don't have case history, and HF was high when they don't have any disease in progress. 5. According to the result concerning correlation of daily habits with time-domain analysis and frequency-domain analysis, cigarette, alcohol and sleeping hours don't affect heartbeat change, but the ones who regularly workout showed higher result in every analysis. It shows that the autonomic nervous system of recipients who regularly exercise response more actively. The result mentioned above suggests that the change of heartbeat is a direct index which shows the change of autonomic nervous system, and it depends on the exercise the most. Thus, workout is proved to be the best method in order for workers to take care of their health.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.276-284
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• 2005

In the mobile computing environment, caching data at the client's side is a useful technique for improving the performance. For caching to be effective, the cache contents must be consistent with those stored in the server. That is, unfortunately, difficult to enforce due to the frequent disconnection and mobility of clients. In the literature, the basic approach adopted is for the sever to periodically broadcast invalidation reports(IRs) that contain information about objects that have been updated recently. However IR-based cache maintenance scheme has a main drawback. Any client who has been disconnected longer than w seconds has to discard all cached items even some of them may still be valid. In this paper, we propose two main schemes which can adapt clients' losing IR messages by long disconnection. First, the client sends its disconnection time when connection is re-established, and the server uses this information to decide the size of broadcast window w dynamically. Second, the server maintains IR messages for a given period of time and a client who has been disconnected longer than w seconds can verify its cache consistency individually. Compared to previous IR-based schemes, our schemes can significantly reduce cache missing and uplink request and improve the throughput by reducing response time.