• 제목/요약/키워드: Data Quality Validation

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Verification Methods of ATE for TICN System (전술정보통신체계 ATE 유효성 검증 방안)

  • Bak, HyeonJeong;Kim, JinSung
    • Journal of Korea Society of Industrial Information Systems
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    • v.25 no.4
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    • pp.17-27
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    • 2020
  • In this paper, we proposed verification methods to prove the effectiveness of automatic test equipment (ATE) for weapon systems. Since the test results from the unproven ATE is not reliable and its use is limited as objective data, it is essential to verify the test equipment in order to guarantee the quality level of the unit under test (UUT). Through the suggested methods, it is applied to the ATE of the tactical information communications network (TICN) system to confirm the verification results and to describe the validation results.

Nondestructive Prediction of Fatty Acid Composition in Sesame Seeds by Near Infrared Reflectance Spectroscopy

  • Kim, Kwan-Su;Park, Si-Hyung;Choung, Myoung-Gun;Kim, Sun-Lim
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.51 no.spc1
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    • pp.304-309
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    • 2006
  • Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

Quality Assessment of Beef Using Computer Vision Technology

  • Rahman, Md. Faizur;Iqbal, Abdullah;Hashem, Md. Abul;Adedeji, Akinbode A.
    • Food Science of Animal Resources
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    • v.40 no.6
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    • pp.896-907
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    • 2020
  • Imaging technique or computer vision (CV) technology has received huge attention as a rapid and non-destructive technique throughout the world for measuring quality attributes of agricultural products including meat and meat products. This study was conducted to test the ability of CV technology to predict the quality attributes of beef. Images were captured from longissimus dorsi muscle in beef at 24 h post-mortem. Traits evaluated were color value (L*, a*, b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, fat, ash, thiobarbituric acid reactive substance (TBARS), peroxide value (POV), free fatty acid (FFA), total coliform count (TCC), total viable count (TVC) and total yeast-mould count (TYMC). Images were analyzed using the Matlab software (R2015a). Different reference values were determined by physicochemical, proximate, biochemical and microbiological test. All determination were done in triplicate and the mean value was reported. Data analysis was carried out using the programme Statgraphics Centurion XVI. Calibration and validation model were fitted using the software Unscrambler X version 9.7. A higher correlation found in a* (r=0.65) and moisture (r=0.56) with 'a*' value obtained from image analysis and the highest calibration and prediction accuracy was found in lightness (r2c=0.73, r2p=0.69) in beef. Results of this work show that CV technology may be a useful tool for predicting meat quality traits in the laboratory and meat processing industries.

Experimental studies of validation and stability of Sweet Bee Venom using HPLC (Sweet BV의 조제물 농도분석 및 안정성 확인을 위한 시험적 연구)

  • Kang, Kye-Sung;Kwon, Ki-Rok
    • Journal of Pharmacopuncture
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    • v.12 no.4
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    • pp.33-50
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    • 2009
  • Objectives : This study was conducted to confirm validation and stability of concentration analysis method of pure melittin (Sweet Bee Venom-Sweet BV) extracted from the bee venom by utilizing protein isolation method of gel filtration. Methods : All experiments were conducted at Biotoxtech, a non-clinical studies authorized institution, under the regulations of Good Laboratory Practice (GLP). Standard solutions of melittin (SIGMA, USA) and test substances were dispensed and were analyzed with HPLC for Sweet BV to secure the validation of analysis. Results : 1. Measurement of system suitability of Sweet BV satisfied criterion of below 3%. 2. Confirming Linearity of Sweet BV in 10-200${\mu}g/m\ell$ solution yielded correlation coefficient (r) of 0.995 and accuracy of 85-115% which satisfy criterion. 3. Measurement of Specificity of Sweet BV didn't yield any substance affecting the peak of test substances, but detected at 21.22min verified as the test substance. 4. Confirming Intra-day of Sweet BV, accuracy and precision of 0.1, 100${\mu}g/m\ell$ were 105.70, 95.81 and 0.66, 0.73, respectively, satisfying both criteria of accuracy (85-115%) and precision (within 10%). 5. To measure Stability in autosampler, all samples used in Intra-day reproducibility sat in the autosampler for five hours and were re-analyzed. Both variability and precision satisfied the criteria. 6. Homogeneity of Sweet BV (0.1, 100${\mu}g/m\ell$) at upper, middle, and lower layers all satisfied the accuracy and precision criteria. 7. Stability of Sweet BV (0.1, 100${\mu}g/m\ell$) at room temperature for four hours and refrigerated for 7 days all satisfied the criterion. 8. For the measurement of Quality control, QC samples measured on the first and eighth day all satisfied accuracy and precision criteria. Conclusion : Above experiment data satisfies validation and stability of concentration analysis method of Sweet BV.

Quantitative Assessment of the Quality of Regional Adaptation Trial Data for Crop Model Improvement (작물 모형 개선을 위한 지역적응시험 자료의 정량적 품질 평가)

  • Hyun, Shinwoo;Seo, Bo Hun;Lee, Sukin;Kim, Kwang Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.22 no.3
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    • pp.194-204
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    • 2020
  • Cultivar parameters, which are key inputs to a crop growth model, have been estimated using observation data in good quality. Observation data with high quality often require considerable labor and cost, which makes it challenging to gather a large quantity of data for calibration of cultivar parameters. Alternatively, data in sufficient quantity can be collected from the reports on the evaluation of cultivars by region although these data are of questionable quality. The objective of our study was to assess the quality of crop and management data available from the reports on the regional adaptation trials for rice cultivars. We also aimed to propose the measures for improvement of the data quality, which would aid reliable estimation of cultivar parameters. DatasetRanker, which is the tool designed for quantitative assessment of the data for parameter calibration, was used to evaluate the quality of the data available from the regional adaptation trials. It was found that these data for rice cultivars were classified into the Silver class, which could be used for validation or calibration of key cultivar parameters. However, those regional adaptation trial data would fall short of the quality for model improvement. Additional information on management, e.g., harvest and irrigation management, can increase the quantitative quality by 10% with the minimum effort and cost. The quality of the data can also be improved through measurements of initial conditions for crop growth simulations such as soil moisture and nutrients. In addition, crop model improvement can be facilitated using crop growth data in time series, which merits further studies on development of approaches for non-destructive methods to monitor the crop growth.

The study on a plan for applying UNeDocs to Maritime Logistics to achieve its paperless logistics (Paperless 해운 물류를 위한 UNeDocs 적용 방안 연구)

  • Ahn, Kyeong Rim
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.5 no.2
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    • pp.199-208
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    • 2009
  • Mosts of export/import cargo has been moving using maritime transport means. Korea had been driven the system automation project using EDI document since the mid-1990s. However, this automation system comes upon about 40-50% against overall maritime business process, manual or paper document processing work is existing as ever. International e-business environment also has changing into electronic form document transaction from paper document-based transaction. International standardization organization, UN/CEFACT proposed UNeDocs for paperless jtransaction. UNeDocs is a specification to define XML data model as well as electronic form. With UNeDocs, it is not necessary to generate the duplexed data, and it can support user convenient and guarantee the flexibility. This paper defines the UNeDocs data model for EDI and Off-Line processing at the current maritime business. Then, it have to check XML syntax and structure for the defined data model through quality of document check system. Also, it explains the applying plan about the defined UNeDocs data model. It is possible to support paperless transaction as defining UNeDocs-based standard data model and converting into paper document, XML and EDI document using UNeDocs data model.

Prelaunch Study of Validation for the Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI) 자료 검정을 위한 사전연구)

  • Ryu, Joo-Hyung;Moon, Jeong-Eon;Son, Young-Baek;Cho, Seong-Ick;Min, Jee-Eun;Yang, Chan-Su;Ahn, Yu-Hwan;Shim, Jae-Seol
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.251-262
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    • 2010
  • In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

Improving the quality of light-field data extracted from a hologram using deep learning

  • Dae-youl Park;Joongki Park
    • ETRI Journal
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    • v.46 no.2
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    • pp.165-174
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    • 2024
  • We propose a method to suppress the speckle noise and blur effects of the light field extracted from a hologram using a deep-learning technique. The light field can be extracted by bandpass filtering in the hologram's frequency domain. The extracted light field has reduced spatial resolution owing to the limited passband size of the bandpass filter and the blurring that occurs when the object is far from the hologram plane and also contains speckle noise caused by the random phase distribution of the three-dimensional object surface. These limitations degrade the reconstruction quality of the hologram resynthesized using the extracted light field. In the proposed method, a deep-learning model based on a generative adversarial network is designed to suppress speckle noise and blurring, resulting in improved quality of the light field extracted from the hologram. The model is trained using pairs of original two-dimensional images and their corresponding light-field data extracted from the complex field generated by the images. Validation of the proposed method is performed using light-field data extracted from holograms of objects with single and multiple depths and mesh-based computer-generated holograms.

A study on the Effectiveness of Urban air temperature Through Citizen Participation (시민참여형 도시온도 모니터링의 실효성에 관한 연구)

  • Kim, Eun-Sub;Lee, Dong-Kun;Won, Ji-Eun;Choi, Sun-Kyung;Kim, Mi-Hwa;Bae, Chae-Young;Park, Sang-Jin
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.23 no.5
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    • pp.87-98
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    • 2020
  • At the point of implementing policies related to urban heat through the overall environmental assessment of the city using national data, citizen science projects that can collect data in a wide range are emerging for effective policy establishment. Although the utility of citizen data is improving, data quality is a primary concern for researchers employing public participation in scientific research. In this study, validation was conducted based on citizen data acquired in the "Suwon City Heat Map Project", and the applicability to temperature monitoring was confirmed based on the results. As a result of analyzing the validity verification of citizen data using three methods, the data result value is 0.843, RMSE: 0.683℃, and a meaningful value was found within 3km of national data. We found that citizen data utilization is high through the results of this study and These projects are expected to be used as basic data for establishing effective policies or can be reflected in the various planning.

A Study on the Factors Influencing the Performance of FinTech Platform (핀테크 플랫폼의 성과에 영향을 미치는 요인 연구)

  • Xian, Feng Si;Um, Hyemi
    • Journal of Information Technology Applications and Management
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    • v.28 no.2
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    • pp.1-16
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    • 2021
  • In recent years, as IT technologies such as cloud computing and mobile payment have evolved and Internet users have increased, the Internet financial market has become intelligent, mobile, and platformed. This study considers the impact of the psychological characteristics of platform systems and users on the performance of fintech platforms. The results of this study are as follows. Information quality affected trust and commitment, service quality affected commitment only, and system quality affected trust and commitment. The perceived risk affected trust and commitment, and the perceived benefit only affected trust and was shown to have an insignificant relationship with immersion. Trust has been shown to have a significant relationship with commitment, and both trust and commitment affected performance. In the validation of mediation effects, trust has shown a partially mediated effect between information quality, system quality, perceived risks, and perceived benefits and performance. There was no mediation effect between service quality and performance. Immersion has been shown to have a partial mediating effect between information quality, service quality, system quality, perceived risk and performance, and there is no mediating effect between perceived benefits and performance. This study showed what are the main factors that affect the performance of the fintech platform and will be used as a useful foundation for increasing the performance of the platform in the future.