• Korean Journal of Food Science and Technology
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• v.23 no.3
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• pp.366-369
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• 1991

In order to elucidate texturization mechanism of extrudated protein, egg white lysozyme was heated under high pressure conditions, and its solubility and changes of molecular weight were investigated. Under high pressure conditions of $100,\;300\;and\;600\;kg/cm^2$, solubility decreased gradually with increasing temperature in the samples heated at $70,\;120\;and\;150^{\circ}C$ and decreased notably with increasing pressure at $200^{\circ}C$. Polymerization was found in the samples heated at $150\;and\;200^{\circ}C$ while a band which located below monomer(low-molecular) could be recognized. Molecular weight of the low-molecular was estimated to be about $6,000{\sim}9,000$ and no smaller peptide was recognized. The polymerization may have occured by disulfide crosslinking in the samples heated at $120^{\circ}C$ but other crosslinking may have played a role in those at $150\;and\;200^{\circ}C$.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.53-63
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• 2008

In this paper, we propose the regional travel time measurement algorithm using the sequence pattern matching to the type of vehicles between the origin of the region and the end of the region, that could be able to overcome the limit of conventional method such as Probe Car Method or AVI Method by License Plate Recognition. This algorithm recognizes the vehicles as a sequence group with a definite length, and measures the regional travel time by searching the sequence of the origin which is the most highly similar to the sequence of the end. According to the assumption of similarity cost function, there are proposed three types of algorithm, and it will be able to estimate the average travel time that is the most adequate to the information providing period by eliminating the abnormal value caused by inflow and outflow of vehicles. In the result of computer simulation by the length of region, the number of passing cars, the length of sequence, and the average maximum error rate are measured within 3.46%, which means that this algorithm is verified for its superior performance.

• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.594-599
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• 2003

By using the spectroscopic ellipsometry, we have measured and analyzed the optical characteristics of P $r^3$$^{+}$-doped selenide glasses of Ge-Sb-Se system, a strong candidate material for U band fiber amplifiers. The ellipsometric spectra measured in the transparent wavelengths range of the material were all fitted to a model consisting of ambient/roughness/thin fil $m_strate structures to obtain simultaneously the optical properties such as refractive index, in terms of Sellmeier parameters and film structure of P $r^3$$^{+}$-doped selenide glasses. Repeated measurements on different positions in both polished faces rendered to verify positional dependence of measured spectre-ellipsometric data. Hence, the model made possible the analysis of the optical characteristics of the glasses. Even though surface roughness was mainly responsible for the position dependencies, the averaged refractive indexes were as precise as to reflect the minute compositional change tantamount to 1 mol%. The measured refractive indexes are useful for design of core and clad compositions of single-mode selenide optical fibers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.1-9
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• 2018

In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.117-126
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• 2019

Legacy study for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods are complex to process and manipulate data and have difficulties in classifying various arrhythmias. Therefore it is necessary to classify various arrhythmia based on short-term data. In this study, we propose a feature extraction based on auto regressive modeling and an premature contraction arrhythmia classification method using SVM., For this purpose, the R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. Also, we classified Normal, PVC, PAC through SVM in realtime by extracting four optimal segment length and AR order. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 99.23%, 97.28%, 96.62% in Normal, PVC, PAC classification.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Explosives and Blasting
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• v.39 no.1
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• pp.1-9
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• 2021

As the national economic growth and the rapid increase in industrial structures are aging, the demand for removing steel structures is increasing, and research on improving the penetration performance of the linear shape charge explosives. In the study, numerical analyses were performed on the effect of the type of explosive used in the self-made shape charging container and the initiation method on the cutting performance of the steel plate and the effect on the shaped explosive installed close to it. ANSYS LS-DYNA, which can analyze the large deformation problem of materials due to explosion, was used, and an ALE(Arbitrary-Lagrange-Eulerian) model was applied that enables interlocking analysis of gases, liquids, and solid.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.471-480
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• 2022

In this study, a integrated platform applied with various analysis and evaluation models and data collection modules was developed for urban river management. Modules applied to the integrated platform are data collection and provision module, flood analysis module, river evaluation module, and levee breach simulation module, which were selected and applied for efficient urban river management. The integrated platform collects data for application to analysis and evaluation modules from various institutions. The collected data is refined through pre-processing and stored. The stored data is used as input data for each module and is also provided as an Open API through the platform. The flood analysis module is provided to analyze and prepare for floods occurring in cities and rivers. The river evaluation module is used for river planning and management by evaluating rivers in various ways. Finally, the levee breach simulation module can be used to establish countermeasures by deriving a possible damage area due to levee breach through analysis of a virtual breach situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1670-1675
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• 2021

The adoption of smart construction technology in the construction industry is progressing rapidly. By utilizing smart construction technologies such as BIM (Building Information Modeling), drones, artificial intelligence, big data, and Internet of Things technology, it has the effect of lowering the accident rate at the construction site and shortening the construction period. In order to introduce a digital twin platform for construction site management, real-time construction site management is possible in real time by constructing the same virtual space. The digital twin virtual space construction method collects and processes data from the entire construction cycle and visualizes it using a 3D model file. In this paper, we introduce a modeling automation technique that constructs an efficient digital twin space by automatically generating 3D modeling that composes a digital twin space based on 3D spatial data.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.815-821
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• 2021

The advantage of big data is to collect a large amount of data on the Internet and refine and use valuable data. That is, the unstructured data is processed so that the user can analyze and utilize it from a necessary point of view. This paper is a relatively small project and is based on unstructured data that can be closely applied to real life and used for marketing. The subjects of the experiment were modeled on lodging companies in the Seoul metropolitan area an hour away from Seoul, and analyzed for the increase in lodging rates before and after marketing using big data. As an experiment that shows the effects of increasing sales, reducing costs, and increasing returns by users, we propose a system to determine and filter whether data input in the process of analyzing big data such as social networks can be used as accommodation-related information.