• Journal of the Korean Vacuum Society
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• v.10 no.2
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• pp.155-163
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• 2001

A number of screws are inevitably used for tightening flanges in constructing a vacuum system. A theoretical relation between the axial force and the torque exerted on a screw is easily obtained assuming that the friction force generated on the contacting plane is known, however, in practice the friction is influenced strongly by unknown detailed surface condition. It is difficult to tighten optimally and uniformly the flange seals if the screws commercially available have undefined surface conditions and scattered dimensions, and the axial force produced by the screws can not be expected properly. In this paper a scatter of the axial force over screws and the deviation from an expected one, depending on various fastening conditions, are investigated using a variety of M8, the most popular size for vacuum flanges, domestic stainless screws of hexagonal head and standard thread.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.41-55
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• 2005

This research is aimed at investigating the ground characterization of the Cheongju granite area using the geophysical methods. Test site was chosen from the building site in Chungbuk University, Chongju, Chungbuk province. Furthermore, geophysical methods are employed on the outcrops in the east to map the distribution of fault and intrusion and reveal the degree of weathering. The subsurface structure mapped from seismic re-fraction survey mainly consists of two units of weathered soil and rock. Threshold of the units were determined on the basis of seismic velocity of 800 m/s, supported from the standard classification table. From the results of standard penetrating test(SPT), these units are found to show medium-high and high density, respectively. Weathering soil is subdivided in unsaturated layer and saturated layer with thresholds of seismic velocity (500 m/s) and resistivity (200 ohm-m). In particular, unsaturated layer is again classified into dry and wet portions using the GPR section. The boundary between unsaturated and saturated weathering soils corresponds to the groundwater table at depth of approximately 5～6.2 m, which is well correlated with the one from drill-core data. However, bedrock is not delineated by geophysical methods. In the GPR section, fault and intrusion observed on the outcrop are revealed not to extend to the building site. With respect to weathering degree, the outcrop characterized by low resistivity and velocity corresponds to the grade of 'completely weathered' from the geotechnical investigations.

• Journal of Bio-Environment Control
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• v.6 no.1
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• pp.48-54
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• 1997

Among the various vegetables eggplant and gourd family can stand against high temperature environmental condition, about 35$^{\circ}C$. However, most of greenhouse farmers are giving up crop cultivation during hot summer season due to extreme temperature, 4$0^{\circ}C$ or above, condition of greenhouse interior. To improve this inferior crop growth condition, for nozzle system was installed in the pet greenhouse and the effect of fog system was investigated in order to determine fog water amount and the required fog nozzle numbers according to house volumes. MEE fog nozzle was selected for this Investigation which can produce water particle size of 27${\mu}{\textrm}{m}$ with water amount of 100$m\ell$ at pumping pressure of 70kg/$\textrm{cm}^2$. House cooling test was conducted in the pet greenhouse with one minute fogging and one minute air ventilation without stopping. It maintained 32$^{\circ}C$ at the house interior when the atmosphere and the house temperature were 35 and 4$0^{\circ}C$, respectively. And, an experimental equation was developed through calculating the changes of relative humidity and temperature with psychrometric equation which revealed the moisture transfer pattern between the house air and fog system. It showed that the required water fogging amounts to reduce 1$0^{\circ}C$, 40 to 3$0^{\circ}C$, needs 80.7$\ell$ for 1-2W(8,350㎥) and 99.9$\ell$ for 3-2G-3S(10,330㎥) type greenhouse with particle size of 27${\mu}{\textrm}{m}$.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.1-9
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• 2022

Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.351-356
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• 2014

Generally, although securing the condition and location of container freights or normal freights, which load a fresh goods, has been a very important issue in the cold-chain system implementations, it has not gotten out of the traditional methods in the related business world yet. To solve this problem, we propose the designing method and architecture which can be used to implement a smart cold-chain monitoring automation systems. The proposed system architecture is based on the oneM2M standards, and it has 3 layers and entities, which can be implemented to S/W and H/W, network services layer and entity, common services layer and entity, application layer and entity. Based on this architecture, we will not only expect an innovative retrenchment of distribution cost, but also automatically secure the freight condition and location.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1819-1824
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• 2018

This paper proposes a control method of ASMR(autonomous sensory meridian response) contents to relieve user's stress and improve his attention. The proposed method measures EEG(electroencephalography), attention, meditation, and eyeblink data from an EEG device and sends them to an oneM2M-compliant IoT(internet of things) server platform through an Android IoT Application. Then a SVM(support vector machine) model is built to classify user's mental health status by using EEG, attention and meditation data collected in the server platform. The ASMR contents are controlled by the mental health status classified by a SVM model and the eyeblink data. When comparing the SVM models according to types of data used, the SVM model with attention and meditation data showed accuracy of 85.7%. It was verified that the proposed control algorithm of ASMR contents properly worked as the mental health status from the SVM model and the eyeblink data changed.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.472-477
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• 2018

In this paper, we develop interactive content services for preventing depression of users through an intelligent Internet of Things(IoT) mirror system. For interactive content services, an IoT mirror device measures attention and meditation data from an EEG headset device and also measures facial expression data such as "sad", "angery", "disgust", "neutral", " happy", and "surprise" classified by a multi-layer perceptron algorithm through an webcam. Then, it sends the measured data to an oneM2M-compliant IoT server. Based on the collected data in the IoT server, a machine learning model is built to classify three levels of depression (RED, YELLOW, and GREEN) given by a proposed merge labeling method. It was verified that the k-nearest neighbor (k-NN) model could achieve about 93% of accuracy by experimental results. In addition, according to the classified level, a social network service agent sent a corresponding alert message to the family, friends and social workers. Thus, we were able to provide an interactive content service between users and caregivers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.413-415
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• 2019

In this paper, we develop IoT-HiAS(IoT-Human Interactive Advertising Service) for sharing economy. The HiAS device shooting the front of the device via a webcam and recognizes the person in real time through the SSD model using MobileNet. If the number of persons above the set threshold is recognized by counting the recognized person, the advertisement is reproduced on the idle resource through the beam projector. At the same time as the advertisement is reproduced, the captured image of the advertisement start time in the front of the device and the number of recognized persons are sends the IoT server of an oneM2M-compliant HiAS server using the IoT client. When the advertisement is finish, the webcam is shooting the front of the device and the image is sends the IoT server. We implemented the IoT-based human interactive advertising service by transmitting the received data to the advertiser and the advertising producers through the SNS(Social Network Service) agent of the HiAS server.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.90-99
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• 2017

The service structure of the Mobius IoT platform, which has been developed on the basis of the oneM2M standard, connects servers and gateways directly to exchange data using HTTP or MQTT. Such structure may cause problems not to operate IoT services safely. In this paper, we propose an effective structure to manage sessions between gateways (or devices) and server using SIP safely and stably. In addition, we provide the way to implement the proposed method on Mobius IoT platform. To verify the operation of the proposed method, we actually implement the proposed method on Mobius IoT platform, and construct a testbed for a typical IoT application service environment with SIP servers. The results of the experiment show that the proposed method works normally, and it can contribute to the stable operation of IoT services.