• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1225-1234
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• 2013

According to the importance of greenhouse gas emissions, it grows day by day, the goverment is promoting to prepare the specific policy implementation to enhance building energy-saving design standars as the development agenda. In this study, the statistical analysis was performed by Descriptive statistics, Regression analysis, and Hypothesis testing to collect to generate and storage energy usage data in real time to settle parameter setting to affect energy consumption under energy-guzzling apartment not single building. This study is expected to be utilized as the basis for the optimum energy-saving design of the future of the building or facility energy costs rise and the demand for energy-efficient and stable management.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.42-47
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• 2007

To reduce the chattering errors of reed switch sensors in the automatic remote measurement of water meter a reed switch sensor was analyzed and improved. The operation of reed switch sensors can be described as a mechanical contact switch by approximation of permanent magnet piece to generate an electrical pulse. The reed switch sensors are used mostly in measurement application to detect the rotational or translational displacement. To apply for water flow measurement devices, the reed switch sensors should keep high reliability. They are applied for the electronic digital type of water flow meters. The reed switch sensor is just mounted simply on the conventional mechanical type flow meter. A small magnet is attached on a pointer of the water meter counter rotor. Inside the reed sensor two steel leaf springs make mechanical contact and apart repeatedly as rotation of flow meter counter. The counting electrical contact pulses can be converted as the water flow amount. The MCU sends the digital flow rate data to the server using the wireless communication network. But the digital data is occurred difference or won by chattering noise. The reed switch sensor contains chattering error by it self at the force equivalent position. The vibrations such as passing vehicle near to the switch sensor installed location causes chattering. In order to reduce chattering error, most system uses just software methods, for example using filter algorithm and also statistical calibration methods. The chattering errors were reduced by changing leaf spring structure using mechanical characteristics.

• Journal of Advanced Navigation Technology
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• v.21 no.3
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• pp.294-299
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• 2017

Home network service is evolving into a service that can receive contents such as remote education, home automation, remote meter reading and various entertainment anytime and anywhere by connecting all household appliances in home with wired and wireless network. In this paper, an intelligent home gateway installed at home is connected to the mobile communication terminal from the outside to solve the problems of the existing home network and configure and maintain a more efficient and comfortable home network environment for the user, In the window, the login page is activated to confirm the user access authority, and the user proceeds the authentication procedure through own login information. When the normal authentication procedure is performed, the intelligent home gateway maintains only the network connection with the user, and the user presents the intelligent home network system using the RFID which is accessed by the intelligent home network system.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• Journal of Chest Surgery
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• v.36 no.10
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• pp.748-753
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• 2003

Background: The pulmonary nodules (PN), when indicated, need thoracoscopic resection, especially in cases of non-diagnostic or technically infeasible PCNA (percutaneous needle aspiration). In the difficult situations of small or deeply seated PN, several techniques facilitating thoracoscopy have been used for detecting them. Our new protocol for managing PN was developed and prospectively reviewed. Material and Method: In the procedure of PCNA, we firstly placed the tip of the needle in the center of, or just in contact with PN under CT guidance, and loaded one or two segments of platinum radiomarker inside the needle after removing the stylet. Then, we forced the radiomarker to move to the tip of the needle by pushing the stylet. Finally, if the tip of the needle was not within PN, it was reoriented to the their center to obtain the sample for PCNA. Result: Between May 1999 and May 2000, radiomarkers were successfully placed in 28 PN of 26 patients, with the exception of one. In 18 (85%) of 21 nodules needing throacoscopy, intraoperative fluoroscopy was used to detect them or guide stapling resection during thoracoscopy. Conclusion: The advantages of this technique are that there is that there is no need for further localization for thoracoscopy even in cases of unsuccessful PCNA, and it was more effective in respect to both cost and time. Therefore, this strategy for PN expecting thoracoscopy will be helpful to patients and medical staff alike.