• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.36-42
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• 2019

Europe and North America are paying attention to residential ESS(Energy Storage System) that can manage energy efficiently. The ESS is a system that stores and manages the electric power by charging and discharging the battery. The ESS is generally used in conjunction with photovoltaic systems. The ESS supplies the load of the power generation time and stores the remaining PV power to supply the load at the non-power generation time. However, due to the high price of residential ESS, low electric rates and increasing block rates, there is no market of residential ESS in Korea. This paper reviews the price condition and the capacity for applying PV and residential ESS to household of apartments using HOMER in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.49-55
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• 2019

An open office or a shared office is emerging as the emphasis on the collaborative and communicative work environments is increasing. In the past, the user maintained the space, but the maintenance of indoor space became difficult because there is no fixed user. Indoor space information can be collected using the ICBM framework system. The facility management can achieve this with data. Therefore, this study proposed a framework based on ICBM (Internet of Things, Cloud, Big Data, and Mobile) for verifying the possibility of a smart facility management system for indoor space. IoT (Internet of Things) technology was used to measure the indoor temperature, humidity, occupancy, and brightness continuously, and provided the data to Web API via WiFi. Data acquired automatically via IoT, existing maintenance data, and spatial information were integrated through the Cloud. Big data collected by sensors were processed as meaningful spatial information for maintenance. Indoor space information and maintenance information can be delivered to the manager through the mobile. Based on the collected data, room occupancy recognition is limited due to a range of ultrasonic wave sensors. On the other hand, brightness represents the space conditions. The difference between lighting on/off, weekday and weekend can be shown. The temperature data and the relative humidity data were collected steadily to evaluate the comfort.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.359-367
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• 2019

This study was done to examine the effect of 'Zippy's friends' program based on stress coping model for early child. A nonequivalent control group was designed to conduct a pre-post test for this study. The participants for this study were 148 first grade elementary school students in G city(experimental group=72, control group=76). The experimental group received 'Zippy's friends program for 24 weeks (6 module, 24 hours). The control group did not receive any treatment. From April to December 2017 data were collected using self-report structured questionnaires, and were analyzed using the ${\chi}^2$-test, t-test, and ANCOVA with SPSS/WIN 20.0 Program. After the treatment, significant differences were found between the experimental group and control groups in terms of stress coping ability( F=22.77, p<.001),but not in level of emotional intelligence (t=-.37, p=.715). Results of this study indicate that Zippy's program can be used in school based practice as an effective mental health intervention for early child.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.243-269
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• 2021

Since the early 2010s, the social importance of research and practical projects targeting deep geological disposal of high-level nuclear waste, underground CO₂ storage and characterization of deep subsurface by borehole investigation has been increasing. In this regard, there is also a significant increase in the need for in situ test technology to obtain quantitative and reliable information on the hydraulic characteristics of deep rock mass. Through years of research and development, we have independently set up Deep borehole Hydraulic Test System (DHTS) based on the key apparatuses designed and made with our own technology. Using this system, high precision constant pressure injection tests were successfully completed at the two 1 km boreholes located in Mesozoic granite and sedimentary rock regions, Gyeongju. During the field tests, it was possible to measure very low flow rate below 0.01 l/min with micro flow rate injection/control module. In this paper, the major characteristics of DHTS are introduced and also some results obtained from the high precision field tests under the deep and low permeable rock mass environment are briefly discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.646-654
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• 2020

This paper is to develop an electromagnetic wave-based sensor that can measure the spatial distribution of precipitation, and to a electromagnetic wave rain gauge (hereinafter, "EWRG") capable of simultaneously measuring rainfall, snowfall, and wind field, which are the core of heavy rain observation. Through this study, the LFM transmission and reception signals were theoretically analyzed. In addition, In order to develop a radar transceiver, LFM transceiver design and simulation were conducted. In this paper, we developed a K-BAND pulse-driven 6W SSPA(Solid State Power Amplifiers) transceiver using a small HMIC(Hybrid Microwave Integrated Circuit). It has more than 6W of output power and less than 5dB of receiving NF(Noise Figure) with short duty of 1% in high temperature environment of 65 degrees. The manufactured module emits LFM and Square Pulse waveform with the built-in waveform generator, and the receiver has more than 40dB of gain. The transceiver developed in this paper can be applied to the other small weather radar.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.187-195
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• 2022

Recently, with interest in metaverse, attempts are being made to utilize the metaverse platform in various forms. In this paper, we focused on the educational application potential of metaverse, and developed and applied a metaverse STEAM program to provide an effective learning experience to learners in non-face-to-face educational situations. The developed program utilizes Minecraft and ZEPETO, familiar to students, as metaverse learning platforms, and consists of a total of 16 lessons of 5 modules in the form of modules so that alternative classes can take place in the educational field. Through this, the learner's change in STEAM attitude and learning satisfaction were measured, and through the developed STEAM program, the learner's interest, consideration, communication, usefulness, self-concept, self-efficacy, and career choice areas significantly increased. In addition, positive results were confirmed in all areas of the learner satisfaction test related to satisfaction, interest, and overall class. In the future, considering the characteristics of the metaverse, it is necessary to break free from the constraints of time and space to communicate anew, and various learner-centered educational approaches based on a high degree of freedom and immersion should be implemented.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.127-136
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• 2009

Modeling and Simulation, especially in mobile ad hoc network(MANET), are the most effective way to analyze performance or optimize system parameters without establishing real network environment. Focusing mainly on overall network behaviors in MANET concerns dynamics of network transport operations, which can efficiently be characterized with event based system states rather than execution details of protocols. We thus consider the network as a discrete event system to analyze dynamics of network transport performance. Zeigler's set-theoretic DEVS(Discrete Event Systems Specification) formalism can support specification of a discrete event system in hierarchical, modular manner. The DEVSim++ simulation environment can not only provide a rigorous modeling methodology based on the DEVS formalism but also support modelers to develop discrete event models using the hierarchical composition methodology in object-orientation. This environment however hardly supports to specify connection paths of network nodes, which are continuously altered due to mobility of nodes. This paper proposes a DEVS-based modeling and simulation methodology of enabling node mobility, and develops DEVS models for the mobile ad hoc network. We also simulate developed models with the DEVSim++ engine to verify the proposal.