• Journal of Korean Society of Water and Wastewater
• /
• v.37 no.6
• /
• pp.347-361
• /
• 2023

Water utilities are making various efforts to reduce water losses from water networks, and an essential part of them is to recognize the moment when a pipe burst occurs during operation quickly. Several physics-based methods and data-driven analysis are applied using real-time flow and pressure data measured through a SCADA system or smart meters, and methodologies based on machining learning are currently widely studied. Water utilities should apply various approaches together to increase pipe burst detection. The most intuitive and explainable water balance method and its procedure were presented in this study, and the applicability and detection performance were evaluated by applying this approach to water supply pipelines. Based on these results, water utilities can establish a mass balance-based pipe burst detection system, give a guideline for installing new flow meters, and set the detection parameters with expected performance. The performance of the water balance analysis method is affected by the water network operation conditions, the characteristics of the installed flow meter, and event data, so there is a limit to the general use of the results in all sites. Therefore, water utilities should accumulate experience by applying the water balance method in more fields.

• Journal of Biomedical Engineering Research
• /
• v.8 no.1
• /
• pp.75-80
• /
• 1987

With the conventional CW Doppler velocity meter, bl-directional velocities cannot be separated. The new CW Doppler system uses quadrature detection and phase rotation to produce simultaneous independent audio and velocity signals for forward and reverse blood flow direction, is fabricated. Specially, this system shows that phase rotation method for flow direction separation provides easy and satisfactory feature. From in vivo blood flow measurement, we can easily differentiate typical artery flow from vein flow, and measure both velocity characteristics qualitatively.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.1 no.4
• /
• pp.239-247
• /
• 2001

The Fluorescence-Activated Cell Sorter (FACS) is a well-established instrument used for identifying, enumerating, classifying and sorting cells by their physical and optical characteristics. For a miniaturized FACS device, a disposable plastic microchip has been developed which has a hydrodynamic focusing chamber using soft lithography. As the characteristics of the spatially confined sample stream have an effect on sample throughput, detection efficiency, and the accuracy of cell sorting, systematic fluid dynamic studies are required. Flow visualization is conducted with a laser scanning confocal microscopy (LSCM), and three-dimensional flow structure of the focused sample stream is reconstructed from 2D slices acquired at $1\mutextrm{m}$ intervals in depth. It was observed that the flow structure in the focusing chamber is skewed by unsymmetrical velocity profile arising from trapezoidal cross section of the microchannel. For a quantitative analysis of a microscopic flow structure, Confocal Micro-PIV system has been developed to evaluate the accelerated flow field in the focusing chamber. This study proposes a method which defines the depth of the measurement volume using a detection pinhole. The trajectories of red blood cells (RBCs) and their interactions with surrounding flow field in the squeezed sample stream are evaluated to find optimal shape of the focusing chamber and fluid manipulation scheme for stable cell transporting, efficient detection, and sorting

• The KIPS Transactions:PartC
• /
• v.13C no.4 s.107
• /
• pp.397-404
• /
• 2006

Successful software attacks require both injecting malicious code into a program's address space and altering the program's flow control to the injected code. Code section can not be changed at program's runtime, so malicious code must be injected into data section. Detoured flow control into data section is a signal of software attack. We propose a new software attack detection method which verify the target address of CALL, JMP, RET instructions, which alter program's flow control, and detect a software attack when the address is not in code section. Proposed method can detect all change of flow control related data, not only program's return address but also function pointer, buffer of longjmp() function and old base pointer, so it can detect the more attacks.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.4
• /
• pp.687-697
• /
• 2023

Botnets, whose attack patterns are becoming more sophisticated and diverse, are recognized as one of the most serious cybersecurity threats today. This paper revisits the experimental results of botnet detection using autoencoder, a semi-supervised deep learning model, for UGR and CTU-13 data sets. To prepare the input vectors of autoencoder, we create data points by grouping the NetFlow records into sliding windows based on source IP address and aggregating them to form features. In particular, we discover a simple power-law; that is the number of data points that have some flow-degree is proportional to the number of NetFlow records aggregated in them. Moreover, we show that our power-law fits the real data very well resulting in correlation coefficients of 97% or higher. We also show that this power-law has an impact on the learning of autoencoder and, as a result, influences the performance of botnet detection. Furthermore, we evaluate the performance of autoencoder using the area under the Receiver Operating Characteristic (ROC) curve.

• Journal of Biomedical Engineering Research
• /
• v.35 no.1
• /
• pp.1-7
• /
• 2014

Among semi-quantitative or fully quantitative lateral flow assay readers, an image sensor-based instrument has been widely used because of its simple setup, cheap sensor price, and compact equipment size. For all previous approaches, monochrome CCD or CMOS cameras were used for lateral flow assay imaging in which the overall intensities of all colors were taken into consideration to estimate the analyte content, although the analyte related color information is only limited to a narrow wavelength range. In the present work, we introduced a color CCD camera as a sensor and a color decomposition method to improve the sensitivity of the quantitative biosensor system which utilizes the lateral flow assay successfully. The proposed setup and image processing method were applied to achieve the quantification of imitatively dispensed particles on the surface of a porous membrane first, and the measurement result was then compared with that using a monochrome CCD. The compensation method was proposed in different illumination conditions. Eventually, the color decomposition method was introduced to the commercially available lateral flow immunochromatographic assay for the diagnosis of myocardial infarction. The measurement sensitivity utilizing the color image sensor is significantly improved since the slopes of the linear curve fit are enhanced from 0.0026 to 0.0040 and from 0.0802 to 0.1141 for myoglobin and creatine kinase (CK)-MB detection, respectively.

• Analytical Science and Technology
• /
• v.7 no.3
• /
• pp.253-260
• /
• 1994

Analytical characteristics of low power-low flow inductively coupled plasma-atomic emission spectometry(ICP-AES) has been studied. Although the net intensity of the low power ICP is lower than the moderate power ICP, the signal to background ratio becomes higher since the background intensity decreases with decreasing the RF power. The detection limit of the low power ICP is comparable with that of the moderate power ICP. The dynamic range of the calibration curve of the low power ICP is $10^4{\sim}10^5$. The ionization interferences by alkali metals increase with increasing the carrier gas flow rate, but the effects are not varied significantly with the RF power.

• Nuclear Engineering and Technology
• /
• v.51 no.4
• /
• pp.1169-1175
• /
• 2019

The minimum detectable activity (MDA) value was derived according to the flow rate of the sample and degree of amplification of the device by sending the sample directly from the collection site to the detection part through a pump. This method can lead to reduction in time and cost compared to the existing measurement method that uses a pre-treatment process. In this study, experiments were conducted on $^3H$ and $^{90}Sr$, which are the major pure beta-emitting radionuclides, by setting the sample flow rate and the amplification gain as factors. The MDA values were derived according to the flow rates, considering that the flow rate can affect the MDA values. There were no change in the MDA under different flow rates of 0, 600, 800, and 1000 mL/min. Therefore, it was confirmed that the flow rate may not be considered when collecting samples for monitoring in actual field. As the degree of amplification of the amplifier increased, the time required to reach the target MDA decreased. When the amplification was quadrupled, the detection efficiency increased by approximately 23.4 times, and the time to reach the MDA decreased to approximately 1/550 times. This method offers the advantage of real-time on-site monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5978-5999
• /
• 2018

Pedestrian detection is a challenging area in the intelligent vehicles domain. During the last years, many works have been proposed to efficiently detect motion in images. However, the problem becomes more complex when it comes to detecting moving areas while the vehicle is also moving. This paper presents a variational optical flow-based method for motion estimation in vehicular traffic scenarios. We introduce a framework for detecting motion areas with small and large displacements by computing optical flow using a multilevel architecture. The flow field is estimated at the shortest level and then successively computed until the largest level. We include a filtering parameter and a warping process using bicubic interpolation to combine the intermediate flow fields computed at each level during optimization to gain better performance. Furthermore, we find that by including a penalization function, our system is able to effectively reduce the presence of outliers and deal with all expected circumstances in real scenes. Experimental results are performed on various image sequences from Daimler Pedestrian Dataset that includes urban traffic scenarios. Our evaluation demonstrates that despite the complexity of the evaluated scenes, the motion areas with both moving and static camera can be effectively identified.

• Convergence Security Journal
• /
• v.18 no.5_1
• /
• pp.19-24
• /
• 2018

For a long time now, general-purpose processors have provided dedicated hardware / software tracing modules to provide developers with tools to fix bugs. A hardware tracer generates its enormous data into a log that is used for both performance analysis and debugging. Processor Trace (PT) is a new hardware-based tracing feature for Intel CPUs that traces branches executing on the CPU, which allows the reconstruction of the control flow of all executed code with minimal labor. Hardware tracer has been integrated into the operating system, which allows tight integration with its profiling and debugging mechanisms. However, in the Windows environment, existing studies related to PT focused on decoding only one flow in sequence. In this paper, we propose an extended PT decoder structure that provides basic data for real-time trace and malicious code detection using the functions provided by PT in Windows environment.