• Food Science and Industry
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• v.49 no.2
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• pp.78-82
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• 2016

DB Integration website(tentatively named Food Processing Aptitude Information Center, FPAIC) has been designed through a "high-value products development project(2013)". Basically, the project aims to secure connections between food raw materials and processing industry, a variety of information sources, and users's convenience. It also aims to build the industry-university-based mutual growth in the food industry through sharing of processing suitability and material research on food raw materials. FPAIC consists of raw material story, information of sample characteristics, food processing study, preceding research data, food industry trends, and understanding of food processing. The major database of research on Food Processing is provided on information of sample characteristics, and food processing study. Currently the web site has 36 raw material stories, 380 information on sample characteristics and food processing studies, 1,600 preceding research data about 31 food raw materials. The web site also provides information on 70 useful web sites, as well as 77 food industry trends, 27 basic information about food processing.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.29 no.2 s.43
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• pp.233-250
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• 2003

We often use the KCID(Korean Cosmetic Ingredient Dictionary) and ICID(International Cosmetic Ingredient Dictionary) within cosmetics research and within their export and import. so far, we do not have a database of a cosmetics' raw materials. Because of this, we consume a lot of time to find the raw material data that is needed. This study constructs a cosmetics' raw material database and develops the program to retrieve it. We used a Linux machine as the equipment for this study and we used Apache web server, MySQL database server and PHP as the tools of this study. 11,817 kinds of raw materials data were registered as ICID, 866 kinds of raw materials data were registered as KCID and 28,008 kinds of raw materials data with registered trade name into the database. Also, The database was composed of the database of the association form. The database of the online form could ultimately reduce the task time as soon as it did its purpose. The product of this study can become a good basis of data to reconfigure. In the future, it can become a good database in relation with different databases.

• Journal of Environmental Health Sciences
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• v.43 no.4
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• pp.298-306
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• 2017

Objectives: Since 1998, the Korea National Health and Nutrition Examination Survey (KNHANES) has been conducted in order to investigate the health and nutritional status of Koreans. The food intake data of individuals in the KNHANES has also been utilized as source dataset for risk assessment of chemicals via food. To improve the reliability of intake estimation and prevent missing data for less-responded foods, the structure of integrated long-standing datasets is significant. However, it is difficult to merge multi-year survey datasets due to ineffective cleaning processes for handling extensive numbers of codes for each food item along with changes in dietary habits over time. Therefore, this study aims at 1) cleaning the process of abnormal data 2) generation of integrated long-standing raw data, and 3) contributing to the production of consistent dietary exposure factors. Methods: Codebooks, the guideline book, and raw intake data from KNHANES V and VI were used for analysis. The violation of the primary key constraint and the $1^{st}-3rd$ normal form in relational database theory were tested for the codebook and the structure of the raw data, respectively. Afterwards, the cleaning process was executed for the raw data by using these integrated codes. Results: Duplication of key records and abnormality in table structures were observed. However, after adjusting according to the suggested method above, the codes were corrected and integrated codes were newly created. Finally, we were able to clean the raw data provided by respondents to the KNHANES survey. Conclusion: The results of this study will contribute to the integration of the multi-year datasets and help improve the data production system by clarifying, testing, and verifying the primary key, integrity of the code, and primitive data structure according to the database normalization theory in the national health data.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.74-79
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• 2017

The Geostationary Ocean Color Imager (GOCI), the world's first ocean color sensor operated in a geostationary orbit, can be utilized to mitigate damages by monitoring marine disasters in real time such as red tides, green algae, sargassum, cold pools, typhoons, and so on. In this paper, we described a methodology and procedure for processing GOCI data in order to maximize its utilization potential. The GOCI data processing procedure is divided into data reception, data processing, and data distribution. The kinds of GOCI data are classified as raw, level 1, and level 2. "Raw" refers to an unstructured data type immediately generated after reception by satellite communications. Level 1 is defined as a radiance data type of two dimensions, generated after radiometric and geometric corrections for raw data. Level 2 indicates an ocean color data type from level-1 data using ocean color algorithms.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.05a
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• pp.166-171
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• 2001

A digital seismic data acquisition and processing system using a PC has been developed in order to replace the analog data acquisition system of shallow marine seismic survey. An A/D converter that has 12bits of resolution and 225KHz of conversion rate was ued to acquire data, and a data acquisition software was developed as a Windows program which provides convenience of use. Raw data acquired at field has been saved to the hard-disk simultaneously. The signal to noise ratio, vertical and horizontal resolution could be improved by a digital data processing of the raw data. The digital processing of the raw data includss gain recovery, filtering, deconvolution, and muting. With the prediction deconvolution algorithm multiple reflections appearing on the shallow marine seismic section could be removed successfully.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.530-533
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• 2005

A raw signal simulator for synthetic aperture radar (SAR) is a useful tool for the design and implementation of SAR system. Also, in order to analyze and verify the developed SAR processor, the raw signal simulator is required. Moreover, there is the need for a test system to help designing new SAR sensors and mission of SAR system. The derived parameters of the SAR simulator also help to generate accurate SAR processing algorithms. Although the ultimate purpose of this research is to presents a general purpose SAR simulator, this paper presents a SAR simulator in frequency domain at the first step. The proposed simulator generates the raw signal by changing various simulation parameters such as antenna parameters, modulation parameters, and sampling parameters. It also uses the statistics from an actual SAR image to imitate actual physical scattering. This paper introduces the procedures and parameters of the simulator, and presents the simulation results. Experiments have been conducted by comparing the simulated raw data with original raw SAR image. In addition, the simulated raw data have been verified through commercial SAR processing software.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.265-275
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• 2015

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.1
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• pp.13-18
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• 2008

Purpose: The image processing method due to the algorism which is various portion nuclear medical image decision is important it makes holds. The purpose of this study is it applies hereupon new image processing method SIEMENS (made by Pixon co.) Onco. flash processing reconstruction and the comparison which use the image control technique of existing the clinical usefulness it analyzes with it evaluates. Materials & Methods: 1. Whole body bone scan-scan speed 20 cm/min, 30 cm/min & 40 cm/min blinding test 2. Bone static spot scan-regional view 200 kcts, 400 kcts for chest, pelvis, foot blinding test 3. 4 quadrant-bar phantom-20000 kcts visual evaluation 4. LSF-FWHM resolution comparison ananysis. Results: 1. Raw data (20 cm/min) & processing data (30 cm/min)-similar level image quality 2. Low count static image-image quality clearly improved at visual evaluation result. 3. Visual evaluation by quadrant bar phantom-rising image quality level 4. Resolution comparison evaluation (FWHM)-same difference from resolution comparison evaluation Conclusion: The study which applies a new method Onco. flash processing reconstruction, it will be able to confirm the image quality improvement which until high level is clearer the case which applies the method of existing better than. The new reconstruction improves the resolution & reduces the noise. This enhances the diagnostic capabilities of such imagery for radiologists and physicians and allows a reduction in radiation dosage for the same image quality. Like this fact, rising of equipment availability & shortening the patient waiting move & from viewpoint of the active defense against radiation currently becomes feed with the fact that it will be the useful result propriety which is sufficient in clinical NM.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.66-73
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• 2023

The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.

• Fisheries and Aquatic Sciences
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• v.24 no.6
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• pp.207-218
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• 2021

This study evaluated the risk of foodborne illness from highly pathogenic Vibrio spp. (Vibrio vulnificus and V. cholerae) by raw whip-arm octopus (Octopus minor) consumption. In total 180 samples of raw whip-arm octopus were collected from markets and examined for the prevalence of V. vulnificus and V. cholerae. Predictive models describing the kinetic behavior of Vibrio spp. in raw whip-arm octopus were developed, and the data on amounts and frequency of raw whip-arm octopus consumption were collected. Using the collected data, a risk assessment simulation was conducted to estimate the probability of foodborne illness raw whip-arm octopus consumption using @RISK. Initial contamination levels of Vibrio spp. in raw whip-arm octopus were -3.9 Log colony-forming unit/g, as estimated by beta distribution fitting. The developed predictive models were appropriate to describe Vibrio spp. in raw whip-arm octopus during distribution and storage with R² values of 0.946-0.964. The consumption frequency and daily consumption amounts of raw whip-arm octopus per person were 0.47% and 57.65 g, respectively. The probability of foodborne illness from raw whip-arm octopus consumption was estimated to be 8.71 × 10^-15 for V. vulnificus and 7.08 × 10^-13 for V. cholerae. These results suggest that the risk of Vibrio spp. infection from raw whip-arm octopus consumption is low in South Korea.