• ALGAE
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• v.31 no.4
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• pp.373-378
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• 2016

Cochlodinium polykrikoides is a red-tide forming dinoflagellate that causes significant worldwide impacts on aquaculture industries and the marine ecosystem. There have been extensive studies on managing and preventing C. polykrikoides blooms, but it has been difficult to identify an effective method to control the bloom development. There is also limited genome information on the molecular mechanisms involved in its various ecophysiology and metabolism processes. Thus, comprehensive genome information is required to better understand harmful algal blooms caused by C. polykrikoides. We estimated the C. polykrikoides genome size using flow cytometry, with detection of the fluorescence of DNA stained with propidium iodide (PI). The nuclear genome size of C. polykrikoides was 100.97 Gb, as calculated by comparing its mean fluorescence intensity (MFI) to the MFI of Mus musculus, which is 2.8 Gb. The exceptionally large genome size of C. polykrikoides might indicate its complex physiological and metabolic characteristics. Our optimized protocol for estimating the nuclear genome size of a dinoflagellate using flow cytometry with PI can be applied in studies of other marine organisms.

• Applied Chemistry for Engineering
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• v.29 no.1
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• pp.97-102
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• 2018

In this work, the surface of gold nanoparticles (AuNPs) was modified with small molecules including mercaptoundecanoic acid (MUA) and L-lysine for the development of highly sensitive lateral flow (LF) sensors. Uniformly sized AuNps were synthesized by a modified Turkevich-Frens method, showing an average size of $16.7{\pm}2.1nm$. Functionalized AuNPs were then characterized by transmission electron microscopy, UV-vis spectroscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. The stable conjugation of AuNPs and antibodies was obtained at pH 7.07 and the antibody concentration of $10{\mu}g/mL$. The functionalized AuNP-based LF sensor exhibited lower detection limit of 10 ng/mL for hepatitis B surface antigens than that of using the bare AuNP-based LF sensor (100 ng/mL).

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.137-147
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• 2005

This study is to define new road capacity concept, and to develop and propose an estimation method, through the analysis of individual vehicular behaviors in continuum flow. Developments in detection technology enable various and precise traffic data collection. The U.S. HCM (Highway Capacity Manual) method does not require such various and precise traffic data, and outputs only limited results. Alternative capacity concepts, which can be classified into a stochastic model and behavioral or deterministic model, are attempts for modeling some prominent traffic flow features, namely so-called a capacity drop and a traffic hysteresis, using such various and precise traffic data. Yet, no capacity concept up-to-date can describe both features. The analysis of individual vehicular behaviors, including speed-density plot per time lap, traffic flow-speed-density diagram per each sampling interval, time headway distribution, and free flow speed distribution, is performed for overcoming the limits of the previous capacity concepts. A stochastic methods are applied to determine time headway for estimating freeway capacity for traffic control.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.91-98
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• 2008

This work was performed to develop a model possible to predict the influent flow and influent components, which are one of main disturbances causing process problems at the operation of municipal wastewater treatment plant. In this study, artificial neural network (ANN) was used in order to develop a model that was able to predict the influent flow, $COD_{Mn}$, SS, TN 1 day-ahead, 2day-ahead and 3 day ahead. Multi-layer feed-forward back-propagation network was chosen as neural network type, and tanh-sigmoid function was used as activation function to transport signal at the neural network. And Levenberg-Marquart (LM) algorithm was used as learning algorithm to train neural network. Among 420 data sets except missing data, which were collected between 2005 and 2006 at field plant, 210 data sets were used for training, and other 210 data sets were used for validation. As result of it, ANN model for predicting the influent flow and components 1-3day ahead could be developed successfully. It is expected that this developed model can be practically used as follows: Detecting the fault related to effluent concentration that can be happened in the future by combining with other models to predict process performance in advance, and minimization of the process fault through the establishment of various control strategies based on the detection result.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.402-411
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• 2000

It is an important step in video indexing and retrieval to detect shot boundaries on video data. Some approaches are proposed to detect shot changes by computing color histogram differences or the variances of DCT coefficients. However, these approaches do not consider the content or meaningful features in the image data which are useful in high level video processing. In particular, it is desirable to detect these features from compressed video data because this requires less processing overhead. In this paper, we propose a new method to detect shot boundaries from MPEG data using region flow and color information. First, we reconstruct DC images and compute region flow information and color histogram differences from HSV quantized images. Then, we compute the points at which region flow has discontinuities or color histogram differences are high. Finally, we decide those points as shot boundaries according to our proposed algorithm.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.163-182
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• 2019

Analyzing the frequency and correlation of the news keywords in the modern society that are becoming complicated according to the time flow is a very important research to discuss the response and solution to issues. This paper analyzed the relationship between the flow of social keyword and major issues through the analysis of news big data for 10 years (2009~2018). In this study, political issues, education and social culture, gender conflicts and social problems were presented as major issues. And, to study the change and flow of issues, it analyzed the change of the issue by dividing it into five years. Through this, the changes and countermeasures of social issues were studied. As a result, the keywords (economy, police) that are closely related to the people's life were analyzed as keywords that are very important in our society regardless of the flow of time. In addition, keyword such as 'safety' have decreased in increasing rate compared to frequency in recent years. Through this, it can be inferred that it is necessary to improve the awareness of safety in our society.

• Tuberculosis and Respiratory Diseases
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• v.85 no.3
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• pp.264-272
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• 2022

Background: The current conventional drug susceptibility test (DST) for Mycobacterium tuberculosis (Mtb) takes several weeks of incubation to obtain results. As a rapid method, molecular DST requires only a few days to get the results but does not fully cover the phenotypic resistance. A new rapid method based on the ability of viable Mtb bacilli to hydrolyze fluorescein diacetate to free fluorescein with detection of fluorescent mycobacteria by flow cytometric analysis, was recently developed. Methods: To evaluate this cytometric method, we tested 39 clinical isolates which were susceptible or resistant to isoniazid (INH) or rifampin (RIF), or ethambutol (EMB) by phenotypic or molecular DST methods and compared the results. Results: The susceptibility was determined by measuring the viability rate of Mtb and all the isolates which were tested with INH, RIF, and EMB showed susceptibility results concordant with those by the phenotypic solid and liquid media methods. The isolates having no mutations in the molecular DST but resistance in the conventional phenotypic DST were also resistant in this cytometric method. These results suggest that the flow cytometric DST method is faster than conventional agar phenotypic DST and may complement the results of molecular DST. Conclusion: In conclusion, the cytometric method could provide quick and more accurate information that would help clinicians to choose more effective drugs.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.23-29
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• 2021

Recently, a situation in which a specific content service is impossible worldwide has occurred due to a failure of the platform service and a significant social and economic problem has been caused in the global service market. In order to secure the stability of platform services, intelligent platform operation management is required. In this study, big data flow management(BDFM) and implementation method were proposed to quickly detect to abnormal service status in the platform operation environment. As a result of analyzing, BDFM technique improved the characteristics of abnormal failure detection by more than 30% compared to the traditional NMS. The big data flow management method has the advantage of being able to quickly detect platform system failures and abnormal service conditions, and it is expected that when connected with AI-based technology, platform management is performed intelligently and the ability to prevent and preserve failures can be greatly improved.

• Korean Journal of Food Science and Technology
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• v.36 no.4
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• pp.677-682
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• 2004

Debates on safety of genetically modified (GM) crops have led to mandatory-labeling legislation of GM foods in many countries including Korea. Effects of heat, pressure, and acid treatments on degradation of DNAs or proteins in GM soybean at levels below detection limits of qualitative PCR and lateral flow strip test (LFST) methods were examined. Results showed that genomic DNAs and proteins were degraded into fragment sizes no longer possible for detection of inserted gene depending on thermal, or thermal and pressure treatment period. Detectaability of LFST for toasted meal increased in weakly treated soybean. DNA and protein detection methods were barely effective for detection of GM ingredient after $121^{\circ}C$ and 1.5 atmospheric treatment for 20 min. These results will be useful in determining GM labeling requirements of processed foods.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.105-118
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• 2001

Incident detection rate and false alarm rate are the key measures tot estimating the performance of automatic incident detection algorithms. It is, however inherently very difficult to improve the two measures simultaneously. The main purpose of this study is to present some methods for solving the problem. For this, an incident detection algorithm has been designed in this study. The algorithm is consisted of two functions, one for detecting incident and another for detecting congestion. A logic for distinguishing non-recurrent congestion from recurrent congestion was employed in the algorithm. The new algorithm basically requires speed, flow, and occupancy data for defining incident situation, but the algorithm is able to perform this task without one of the three parameters. The performance of the algorithm has been evaluated by using the field data collected from Interstate Highway 880 in Bay Area, California. The empirical analysis results are very promising and thus, the algorithm proposed may be very useful for the analysts. This paper presents some empirical test results for the performance of California incident detection algorithm, only for the reference purpose.