• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1089-1096
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• 2010

The relation between the vibration induced from machinery and the radiated sound is complicated. Acoustic intensity method is widely used to obtain the accuracy of noise measurement and noise identification. In this study, as groundwork, the complex acoustic intensity method is performed to identify noise source and transmission path on different free space point source fields. As an industrial application, the complex acoustic intensity method is applied to HVAC to identify sound radiation characteristics in the near field. Experimental complex acoustic intensity method was applied to HVAC, it is possible to identify noise sources in complicated sound field characteristics which noise sources are related with each other, and certificate the validity of complex acoustic intensity. Especially, it can be seen that complex acoustic intensity method using both of active and reactive intensity is vital in devising a strategy for identification of noise. Also, the vector flow of acoustic intensity was investigated to identify sound intensity distributions and energy flow in the near field of HVAC.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.1
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• pp.79-83
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• 2004

This study was how to control the mass flow controller in gas supplying system. The flow controller consists of piezoelectric material and sensor with heating wire. It is difficult to obtain accurate model, because MFC was composed of many parts, and the relationship between input and output of controller is nonlinear. The model for control was obtained by time constant and DC gain Based on this model, PID controller was applied to flow controller using DSP board. Also, the results were compared to controller using system identification.

• ETRI Journal
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• v.30 no.2
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• pp.183-193
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• 2008

In this paper, we propose quality of service mechanisms for flow-based routers which have to handle several million flows at wire speed in high-speed networks. Traffic management mechanisms are proposed for guaranteed traffic and non-guaranteed traffic separately, and then the effective harmonization of the two mechanisms is introduced for real networks in which both traffic types are mixed together. A simple non-work-conserving fair queuing algorithm is proposed for guaranteed traffic, and an adaptive flow-based random early drop algorithm is proposed for non-guaranteed traffic. Based on that basic architecture, we propose a dynamic traffic identification method to dynamically prioritize traffic according to the traffic characteristics of applications. In a high-speed router system, the dynamic traffic identification method could be a good alternative to deep packet inspection, which requires handling of the IP packet header and payload. Through numerical analysis, simulation, and a real system experiment, we demonstrate the performance of the proposed mechanisms.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4751-4758
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• 2022

Two-phase flow may almost exist in every branch of the energy industry. For the corresponding engineering design, it is very essential and crucial to monitor flow patterns and their transitions accurately. With the high-speed development and success of deep learning based on convolutional neural network (CNN), the study of flow pattern identification recently almost focused on this methodology. Additionally, the photographing technique has attractive implementation features as well, since it is normally considerably less expensive than other techniques. The development of such a two-phase flow pattern online monitoring system is the objective of this work, which seldom studied before. The ongoing preliminary engineering design (including hardware and software) of the system are introduced. The flow pattern identification method based on CNNs and transfer learning was discussed in detail. Several potential CNN candidates such as ALexNet, VggNet16 and ResNets were introduced and compared with each other based on a flow pattern dataset. According to the results, ResNet50 is the most promising CNN network for the system owing to its high precision, fast classification and strong robustness. This work can be a reference for the online monitoring system design in the energy system.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.3
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• pp.34-42
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• 1994

The present study is aimed to improve the PIV performance by suggesting a two-frame particle identification technique and by introducing estimation method of wall pressure distribution from the velocity data. Adopted image processing system consists of one commercial image board slit into a personal computer, 2-D sheet light generator, flow picture recording apparatus and related particle identification software. A revised particle tracking method essential to PIV performance is obtained by particle centroid correlation pairing (CCP) and its effectiveness is ascertained by comparison with multi-frame identification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.108-108
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• 2004

• Journal of Digital Convergence
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• v.10 no.11
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• pp.243-251
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• 2012

Digital items, considered as virtual assets, include avatars, accessories for the avatars, digital wallpapers, and game items, etc. The objective of this study is to examine the factors influencing the purchase of digital items. Factors, based upon Uses and Gratifications theory, including image making, self-expression, social awareness and fun-seeking, are introduced as salient variables for purchasing digital items. In addition, social identification and flow are also considered as key motivators. Statistical results indicates that social identification affects both flows and the intension to purchase digital items, and then flow next influences intension to purchase. It was also found that motives based upon Uses and Gratifications theory influences social identification, but have no impact on flow. As a conclusion, the academic and practical implications of these findings are also discussed.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.155-165
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• 2004

It is needed to develop on-line real time management and RFID-PPS(Radio Frequency Identification-Pallet Pool System) by putting information technology. Additionally, it is possible to figure out the flow of all the materials loaded on the RFID pallet; product, material, raw material immediately, so that epoch-making management is possible and it contributes to the reduction of logistics cost because there are little loss or outflow of pallet. The materials flow is getting speedy and inventory is decreasing in the logistics process, and also bad inventory and loss problems are prevented. As a result, not only logistics cost of company but also national logistics cost is decreased. Thus it contributes to the strength of national competitiveness.

• Journal of Information Technology Services
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• v.6 no.1
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• pp.83-99
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• 2007

The purpose of this research is to identify the determinants of loyalty in online games. This study developed a research model to analyze the factors explaining the loyalty level from gamers, employing social identification, flow, and positive anticipated emotion as major research variables, and collected 1308 survey responses from gamers. Within the context of arguing that the exploration of age range issues with respect to online games is important, this research also examines the age differences in path coefficients. To this end, the structural model was tested with the data from entire data sample (i.e., the age of 10s, 20s, and 30s pooled together) and each of the subsamples (i.e., teens taken separately, twenties taken separately, and thirties taken separately). Properties of the causal paths, including standardized path coefficients, the significance of difference, in the hypothesized model, are also presented, so that we can investigate the relative influences of different dominants, demonstrating how teens, twenties, and thirties differ in their decision-making processes regarding the flow, social identification and loyalty from online games.