• Journal of the Korean Society of Visualization
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• v.9 no.2
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• pp.21-26
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• 2011

Hydrodynamic focusing technique to generate focused flow has been used for flow cytometry in microfluidic devices. However, devices with circular capillary tubes made of glass are not suitable for flow visualization or optical signal detection because the rays of light are distorted at the curved interface. We devised a new acrylic chamber assembled with a pulled micropipette and a rectangular microchannel made of glass. This new channel geometry enabled us to visualize the three-dimensional (3D) flow characteristics with confocal imaging technique. We analyzed the 3D hydrodynamic focusing in a circular capillary tube and a rectangular microchannel over a practical range of flow rates, viscosities and pressure drops.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.910-917
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• 2000

Because the random early detection(RED) algorithm deals all flows with the same best-effort traffic characteristic, it can not correctly control the output link bandwidth for the flows with different traffic characteristics. To remedy this problem, several per-flow algorithms have been proposed. In this paper, we propose a new per-flow type Fair Droptail algorithm which can fairly allocate bandwidth among flows over a shared output link. By evenly allocating buffers per flow, the Fair Droptail can restrict a flow not to use more bandwidth than others. In addition, it can be simply implemented even if it employs the per-flow state mechanism, because the Fair Droptail only keeps each information of flow in active state.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.563-570
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• 2022

This study was objected to show the complexity of groundwater flow system in a site-scale area as a design parameter of the groundwater monitoring network for early detection of pollutant leakage from a potential source of groundwater contamination (e.g., storage tank). Around the tanks, three monitoring wells were installed at about 22~25 m deep and groundwater level and temperature had been monitored for 22 months by 2-minute interval, and then compared with precipitation and temperature data from nearby weather station. Annual variation of groundwater level and its response to precipitation event, variation of groundwater temperature and delayed response to that of atmospheric temperature indicate the complexity of groundwater flow and flow paths even in the relatively small area. Thus, groundwater monitoring network for early detection of contaminant leakage should be designed with full consideration of the complexity of groundwater flow system, identified from the detailed hydrogeological investigation of the site.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.19-19
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• 2005

This paper reports a novel magnetic force-based microfluidic immunoassay using microbeads and magnetic nanoparticles. The magnetic force-based immunoassay was devised first and successfully applied to detect the rabbit IgG as the model analyte of microfluidic sandwich immunoassay. The microchannels were fabricated by poly(dimethysiloxane) (PDMS) molding processes and bonded on a slide glass by plasma treatment. At the part of the inlet, sample solution was hydrodynamically focused. The focused microbeads of sample solution were flowed through the 150 ${\mu}m$ width channel of outlet. However, when the microbeads are conjugated with the superparamagnetic nanoparticles under the applied magnetic fields, they will switch their flow path and flow through the 95 ${\mu}m$ width channel of outlet. The movements of microbeads conjugated with magnetic nanoparticles were demonstrated by magnetic field $gradients.^{1)}$ High magnetic field gradients using micro electromagnets could be applied to this detection method for high sensitivity and lower detection limit. In addition, the multiplexed $immunoassay^{2)}$ using an encoded microbead which is immobilized with a certain antibody could be possible using this detection principle.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.234-239
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• 2017

A real-time violence detection algorithm based on a new descriptor using the magnitude and direction changes of movement in images is proposed. The descriptor was developed from the observation that the changes of violent actions are much larger than those of normal movements. Descriptor feature vectors consisting of descriptor values during several frames are obtained and these are inputs to SVM(Support Vector Machine) classifier for discriminating violence actions from and non-violence actions. Comparison experiments between the ViF(Violent Flow) and the proposed algorithm were conducted with three different types of datasets. The experimental results show that the proposed algorithm outperforms the ViF in every case.

• Journal of Mechanical Science and Technology
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• v.20 no.3
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• pp.426-434
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• 2006

The impact of leakage was incorporated into the transfer functions of the complex head and discharge. The impedance transfer functions for the various leaking pipeline systems were also derived. Hydraulic transients could be efficiently analyzed by the developed method. The simulation of normalized pressure variation using the method of characteristics and the impulse response method shows good agreement to the condition of turbulent flow. The leak calibration could be performed by incorporation of the impulse response method with Genetic Algorithm (GA) and Harmony Search (HS). The objective functions for the leakage detection can be made using the pressure-head response at the valve, or the pressure-head or the flow response at a certain point of the pipeline located upstream from the valve. The proposed method is not constrained by the Courant number to control the numerical dissipation of the method of characteristics. The limitations associated with the discreteness of the pipeline system in the inverse transient analysis can be neglected in the proposed method.

• Smart Media Journal
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• v.9 no.3
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• pp.98-106
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• 2020

Currently, as Internet users increase, the use of swearword is indiscriminately increasing. As a result, cyber violence among teenagers is increasing very seriously, and among them, cyber-language violence is the most serious. In order to eradicate cyber-language violence, research on detection of swearword has been conducted, but the method of detecting swearword by looking at the meaning of words and the flow of context is insufficient. Therefore,in this paper,we propose a method of detecting swearword using FastText model and LSTM model so that deliberately modified swearword and standard language can be accurately detected by looking at the flow of context.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.473-474
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• 2008

This paper proposes that the relative transmittance and emission intensity measured via optical emission spectroscopy (OES) is a useful for fault detection of reactive ion etch process. With the increased requests for non-invasive as well as real-time plasma process monitoring for fault detection and classification (FDC), OES is suggested as a useful diagnostic tool that satisfies both of the requirements. Relative optical transmittance and emission intensity of oxygen plasma acquired from various process conditions are directly compared with the process variables, such as RF power, oxygen flow and chamber pressure. The changes of RF power and Pressure are linearly proportional to the emission intensity while the change of gas flow can be detected with the relative transmittance.

• IE interfaces
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• v.23 no.4
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• pp.349-356
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• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.