• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.197-205
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• 2022

The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.10
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• pp.983-988
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• 2016

Internet of Things Iranian people and things, things and things are connected through the Cloud. It can significantly save energy through a combination of LED lighting as a new ICT technologies and industry-to provide a human-centric, eco-friendly, and the content is embedded multifunction solutions that meet your needs, environment, implementation time according to user requirements, technology It can be systematized as converged next-generation lighting. In this paper, we have developed regarding whether the building in relation to the LED lighting control system using smart devices and Cloud-based user as a human connection through the board to the Arduino Yun lit LED lighting, wireless smart device or to the Cloud or off. After the Arduino Yun is connected to the Internet, taking the current date and time information from the Linux shell command used the way coming across the bridge (BRIDGE) its value.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.331-337
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• 2014

Paradigm shift to cloud computing has increased the importance of security. Even though public cloud computing providers such as Amazon, already provides security related service like firewall and identity management services, it is not suitable to protect data in cloud environments. Because in public cloud computing environments do not allow to use client's own security solution nor equipments. In this environments, user are supposed to do something to enhance security by their hands, so the needs of visualized security management arises. To implement visualized security management, developing near realtime data handling & packet classification mechanisms are crucial. The key technical challenges in packet classification is how to classify packet in the manner of unsupervised way without human interactions. To achieve the goal, this paper presents automated packet classification mechanism based on naive-bayesian and packet Chunking techniques, which can identify signature and does machine learning by itself without human intervention.

• Journal of the Korean Institute of Gas
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• v.14 no.2
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• pp.15-21
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• 2010

The demand of gas as an eco-friendly energy source has being increased. With increasing the LPG demand, the number of LPG filling station. In this work, the influence on over-pressure caused by Vapor Cloud Explosion in gas station was calculated by using the Hopkinson's scaling law and injury effect by the accident to a human body was estimated by applying the probit model. As a result of the injury estimation conducted by using the probit model for leakage 10% of 20ton storage tank. The distances from LPG station for death and tympanum rupture are 36.5 and 290 meters, respectively.

• Food Science and Biotechnology
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• v.15 no.1
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• pp.13-18
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• 2006

Mandarin juice was processed using a continuous high pressure $CO_2$ system. Response surface methodology was used to investigate the effects of the processing parameters such as temperature, pressure, residence time, and %(w/w) ratio of $CO_2$ to juice on total aerobic count (TAC), pectinesterase (PE) activity, cloud level, $^{\circ}Brix$, pH, and titratable acidity (TA) of the juices. Maximum log reduction (3.47) of TAC was observed at $35^{\circ}C$, 41.1 MPa, 9 min residence time, and 7% $CO_2$. PE was inactivated by 7-51%. The cloud was not only retained but was also enhanced by 38%. Lightness and yellowness increased, and redness decreased. The processing temperature and % $CO_2$/juice ratio significantly affected high pressure $CO_2$ processing of the juice in terms of pasteurization, PE inactivation, cloud increase, and color change. The $^{\circ}Brix$, pH, and TA before and after treatment remained unchanged.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2585-2598
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• 2015

Hand posture recognition has played a very important role in Human Computer Interaction (HCI) and Computer Vision (CV) for many years. The challenge arises mainly due to self-occlusions caused by the limited view of the camera. In this paper, a robust hand posture recognition approach based on 3D point cloud from two RGB-D sensors (Kinect) is proposed to make maximum use of 3D information from depth map. Through noise reduction and registering two point sets obtained satisfactory from two views as we designed, a multi-viewed hand posture point cloud with most 3D information can be acquired. Moreover, we utilize the accurate reconstruction and classify each point cloud by directly matching the normalized point set with the templates of different classes from dataset, which can reduce the training time and calculation. Experimental results based on posture dataset captured by Kinect sensors (from digit 1 to 10) demonstrate the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2575-2580
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• 2012

The aim of this paper is to analyze factors for site selection of the cloud data center and to develop spatial data model considering disasters information based on the GIS. In this paper, historical areas of the natural and human disaster are considered to analyze location of the cloud center. The model is developed using ArcGIS S/W tool. The model is applied on Busan city using disaster data from storm and flood, and small administrative district located Kang-Seo-Gu is selected as site selection of the cloud data center of Busan.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.536-539
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• 2002

The reverse engineering (RE) technology can quickly generate 3D point cloud data of an object by capturing the surface of a model using a 3D scanner. In the rapid prototyping (RP) technology, prototypes are rapidly produced from 3D CAD models in a layer-by-layer additive basis. In this paper, a physical human head shape is duplicated using a new RP process, the Transfer-type Variable Lamination Manufacturing process using expandable polystyrene foam sheet (VLM-ST), after the point cloud data of a human head shape measured from 3D SNX scanner are converted to STL file. From the duplicated human head shape, it has been shown that the VLM-ST process in connection with the 3D scanner is a fast and efficient process in that shapes with free surface, such as the human head shape, can be duplicated with ease. Considering the measurement time and the shape duplication time, the use of 3D SNX scanner and the VLM-ST process is expected to reduce the lead-time fur the development of new products in comparison with the other existing RE-RP connected manufacturing systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.7-12
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• 2019

Clouds in the atmosphere are important variables that affect the temperature change by reflecting the radiant energy of the earth surface as well as changing the amount of sunshine by reflecting the sun's radiation energy. Especially, the amount of sunshine on the surface is very important It is essential information. Therefore, eye-observations of the sky on the surface of the earth have been enhanced by satellite photographs or relatively narrowed observation equipments. Therefore, cloud automatic observing systems have been developed in order to replace the human observers, but depending on the seasons, the reliability of observations is not high enough to be applied in the field due to pollutants or fog in the atmosphere. Therefore, we have developed a cloud observation algorithm that is robust against smog and fog. It is based on the calculation of the degree of aerosol from the all-sky image, and is added to the developed cloud reader to develop season- and climate-insensitive algorithms to improve reliability. The result compared to existing cloud readers and the result of cloud cover is improved.