• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 춘계학술대회 논문집
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• pp.314-319
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• 2005

The rubber tire type AGT vehicles had been developed in a few years. And testing are finished on the test track. The extremely differ from heavy train with iron wheels are current collect type and wheel's characteristic. Analysis the current collect gear dynamic with vehicle dynamic and reduce the exchange rate shoes of current collect gear's.

• 대한치과의사협회지
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• 제15권12호
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• pp.1023-1025
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• 1977

In order to collect some necessary data to promote correcting the toothbrushing method, the author had observed and evaluated the cervical abrasion experience rate in 1000 Korea male and female adults from 19 to 52 years in the age. The obtained results were as follows 1. Cervical abrasion experience rate was 26.1% 2. Cervical abrasion experience rate in male adults was higher than that in female adults. 3. Cervical abrasion experience rate was gradually increased by aging. 4. In Korean adults, the further detail investigations into the cervical abrasion were required.

• 대한치과의사협회지
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• 제12권2호
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• pp.107-111
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• 1974

In order to collect some necessary data to promote correcting the toothbrushing technic on the Korean public, the author had examined the number of present teeth on which had cervical abrasion and the most basic home dental care in 2,000 Korean male and female adults from 19 to 52 years in the age. Then, the cervical abrasion experience rate and the cervical abrasion experience teeth rate were calculated and evaluated. The obtained results were as follows: 1. Cervical abrasion experience rate was 32.45% 2. Cervical abrasion experience rate was gradually increased by ageing. 3. Cervical abrasion experience rate in male adults was higher than that in female adults. 4. Cervical abrasion experience rate in the lower jaw was higher than that in the upper jaw. 5. Cervical abrasion experience rate of the teeth at the right side was higher than that of the teeth at the left side. 6. Cervical abrasion experience teeth rate was 3.82%. 7. Cervical abrasion experience rate was highest on the first bicuspid, and followed in the sequence of the second bicuspid, canine, first molar, incisors, and 2nd and 3rd molars.

• 대한간호
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• 제20권4호통권112호
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• pp.77-85
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• 1981

This study was undertaken in an attempt to identify level of birth and infant death in the KHDI demonstration areas. The objectives of this study are to collect available information on birth and infant death in the KHDI demonstration areas, and estimate

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.203-206
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• 1998

Since it has been very difficult to collect Korean rain data for winter season, e.g. from November to March, it would be very useful to design satellite communication links if there is a method to extract annual distribution from rain data collected for a specific month. This paper presents a conversion method to annual rainfall rate distribution from rain data for worst month of a year, and illustrates some analysis of the conversion results.

• 자원환경지질
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• 제32권3호
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• pp.273-280
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• 1999

In order to protect inhabitans' health and to collect data for prediction of the effcts from accidental emission of rasioactive materials from nuclear power plant, exposed dose rate be monitored within the limit dose rate. This research was carried out to investigate the accumulation of environmental radioactivity around Younggwang Nuclear Power Plant, and to infer and in infer and assay the additional exposed dose rate of inhabitants in Younggwang site from the operation of nuclear plant operation. External radiation dose rate, radiation environmental samples, and exposed dose rate of inhabitants in Younggwang site were investigated for estimaing environment activity in the vicinity of the nuclear power plant area. For the external radiation dose rate, the result showed that range of normal variation was found and any artificial radioisotope was not deteted in the analysis of environmental samples. Exposed dose rate of inhabitants was lower than 0.4% of the limit value of ICRP and it may be concluded that there was no effect on inhabitants and environment from the operation of nuclear power plant.

• 산업경영시스템학회지
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• 제43권2호
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• pp.120-125
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• 2020

Supply chain managers seek to achieve global optimization by solving problems in the supply chain's business process. However, companies in the supply chain hide the adverse information and inform only the beneficial information, so the information is distorted and cannot be the information that describes the entire supply chain. In this case, supply chain managers can directly collect and analyze supply chain activity data to find and manage the companies described by the data. Therefore, this study proposes a method to collect the order-inventory information from each company in the supply chain and detect the companies whose data characteristics are explained through deep learning. The supply chain consists of Manufacturer, Distributor, Wholesaler, Retailer, and training and testing data uses 600 weeks of time series inventory information. The purpose of the experiment is to improve the detection accuracy by adjusting the parameter values of the deep learning network, and the parameters for comparison are set by learning rate (lr = 0.001, 0.01, 0.1) and batch size (bs = 1, 5). Experimental results show that the detection accuracy is improved by adjusting the values of the parameters, but the values of the parameters depend on data and model characteristics.

• 한국전기전자재료학회논문지
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• 제35권5호
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.280-286
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• 2022

In order to efficiently collect data, it is essential to locate the facilities and analyze the movement data. The current technology for location collection can collect data using a GPS sensor, but GPS has a strong straightness and low diffraction and reflectance, making it difficult for indoor positioning. In the case of indoor positioning, the location is determined by using wireless network technologies such as Wifi, but there is a problem with low accuracy as the error range reaches 20 to 30 m. In this paper, using BLE 4.2 built in Raspberry Pi, we implement Bluetooth Smart Ready. In detail, a beacon was produced for Advertise, and an experiment was conducted to support the serial port for data transmission/reception. In addition, advertise mode and connection mode were implemented at the same time, and a 3-count gradual algorithm and a quadrangular positioning algorithm were implemented for Bluetooth RSSI error correction. As a result of the experiment, the average error was improved compared to the first correction, and the error rate was also improved compared to before the correction, confirming that the error rate for position measurement was significantly improved.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.43-49
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• 2019

Today, with the development of the internet of things, wearable devices related to personal health care have become widespread. Various global information and communication technology companies are developing various wearable health devices, which can collect personal health information such as heart rate, steps, and calories, using sensors built into the device. However, since individual health data includes sensitive information, the collection of irrelevant health data can lead to personal privacy issue. Therefore, there is a growing need to develop technology for collecting sensitive health data from wearable health devices, while preserving privacy. In recent years, local differential privacy (LDP), which enables sensitive data collection while preserving privacy, has attracted much attention. In this paper, we develop a technology for collecting vast amount of health data from a smartwatch device, which is one of popular wearable health devices, using local difference privacy. Experiment results with real data show that the proposed method is able to effectively collect sensitive health data from smartwatch users, while preserving privacy.