• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.653-659
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• 2017

In this study, the complex forging process of an outer support ring was developed and the prototype was manufactured. The current process, hot forging and MCT machining, has a disadvantage of excessive material removal rates and longer machining hours. To overcome this disadvantage, a general shape is given through hot forging and the precision is achieved through cold forging. The complex forging process was developed with the minimal machining process. Forging analysis was carried out to design a forging process using the commercial program, Deform-3D. The hot and cold forging processes were set up based on the analyzed result. The mold and prototype were manufactured. Hardness, surface roughness, internal defect, the grain low line of the prototype were evaluated. The results showed no particular problems, and there were no problems in mass production. Using complex forging, the material was reduced by approximately 27 % compared to the process using hot forging and MCT machining. In addition, the production speed was improved 2.15 fold compared to that of hot forging and MCT machining. Through this study, a cost-effective process and mold design technology were established, which is expected to have positive effects on other related automotive parts production.

• Korean Journal of Dental Materials
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• v.44 no.4
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• pp.329-336
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• 2017

This study evaluates the machining accuracy of the custom abutment design according to the selected convergence angle and radius of curvature value in the CAD program. Ten custom abutments were designed based on dental CAD. And then, the fabricated custom abutment was scanned ten times using a contact scanner. The data of the scanned custom abutment was saved as "Test STL" file. The Geomagic studio software was used to superposition each exported as an "Test STL" file with the CAD-reference-model STL file (CRM) specified by the same name. In the experimental results, the A8 group (convergence angle $8^{\circ}$) showed lower error than the A4 group (convergence angle $4^{\circ}$) . In addition, the higher the radius of curvature, the less error in the top and chamfer regions of the custom abutment (p< 0.05). Overall, the convergence angle and radius of curvature value in the custom abutment design were found to affect the machining accuracy.

• Journal of the Korea Institute of Building Construction
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• v.20 no.2
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• pp.171-181
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• 2020

Recently, free-formed construction technology is becoming a new measure of representing technological superiority and sociocultural ingenuity. However, the CNC processing technology utilizing the existing wood and iron form has limitations in terms of the manufacturing time and material cost. Therefore, in this study, the method and process of manufacturing free-formed EPS form using S-LOM-based 3D printing technology were suggested. Furthermore, through the mock-up test, a comparative analysis of the manufacturing time and precision with CNC milling technology was conducted. The results show that S-LOM-based 3D printing technology has reduced manufacturing time about 57.4% compared to CNC milling technology during the free-formed EPS form manufacturing process. In addition, compared to the design drawings, the maximum error value was 20.5mm, proving the applicability of S-LOM-based 3D printing technology. The results of this study are expected to contribute to the improvement of S-LOM method and the activation of S-LOM method by verifying the applicability of S-LOM-based 3D printing technology.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.469-476
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• 2009

The new laser scanning technology allows to attain 3D information faster with higher accuracy on surface ground, vegetation and buildings of the earth surface. This acquired information can be used in many areas after modifying them appropriately by users. The contour production for accurate landform is an advanced technology that can reveal the mountain area landscapes hidden by the trees in detail. However, if extremely precise LiDAR data is used in constructing the contour, massive-sized data intricates the contour diagram and could amplify the data size inefficiently. This study illustrates the algorithm producing contour that is filtered in stages for more efficient utilization using the LiDAR contour produced by the detailed landscape data. This filtering stages allow to preserve the original landscape shape and to keep the data size small. Point Filtering determines the produced contour diagram shape and could minimize data size. Thus, in this study we compared experimentally filtered contour with the current digital map(1:5,000).

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.3
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• pp.342-351
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• 2016

This study was carried out to develop an optimized analytical method using high-performance liquid chromatography (HPLC) applied to canthaxanthin, which is not yet designated as a food colorant in Korea, as well as to perform validation and uncertainty evaluation of this method. Official methods of AOAC, UK, and Japan with HPLC-UV detection were evaluated for the analysis of canthaxanthin by comparison of linearity, resolution, selectivity, limit of detection (LOD), limit of quantitation (LOQ), accuracy, precision, recovery, inter-laboratory tests, and uncertainty measurement. The calibration curves showed high linearity with an $R_2$ value of over 0.999 for canthaxanthin standard solutions in all three official methods. The official method of Japan exhibited the best results in terms of resolution and selectivity, including the lowest LOD and LOQ. The average coefficients of variation were calculated as less than five of three institutes with a precision value less than 1, accuracy near 100%, and recovery ratio between $100{\pm}10%$. The expanded uncertainty for canthaxanthin was estimated to be $39.5{\pm}5.29mg/kg$ (95% confidence level, k=2), and the uncertainty of measurement was 13.4%. In this study, official methods of canthaxanthin were compared and the validities verified. The results will be further applied to establish an authorized analytical method for canthaxanthin in Korea.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.5
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• pp.771-777
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• 2016

Accurate food composition data are essential for calculation of nutrient intake of a population based on its consumption statistics. In the Korean food composition database, there is a lack of reliable analytical data for tocopherols and tocotrienols. Therefore, this study was conducted to provide information on contents on vitamin E in agricultural processed foods in Korea. Tocopherols and tocotrienols were determined by the saponification extraction method followed by high performance liquid chromatography. Analytical method validation parameters were calculated to ensure the method's validity. Samples were obtained in the years of 2013 and 2014 from the Rural Development Administration. The samples included 34 grains and grain products, 14 snacks, 25 fruits, 5 oils, and 11 sources and spices. All vitamin E isomers were quantitated, and the results were expressed as ${\alpha}$-tocopherol equivalent (${\alpha}-TE$). ${\alpha}-TE$ values of cereal and cereal products, snacks, fruits, oils and sauces and spices ranged from 0.03 to 17.53, 1.01 to 12.84, 0.01 to 1.52, 1.09 to 8.15, and 0.01 to $27.53{\alpha}-TE/100g$, respectively. Accuracy was close to 100% (n=3). Repeatability and reproducibility were 2.04% and 4.69%, respectively. Our study provides reliable data on the tocopherol and tocotrienol contents of agricultural and processed foods in Korea.

• Korean Journal of Optics and Photonics
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• v.19 no.4
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• pp.287-293
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• 2008

The collimator which makes a collimated beam, is an essential instrument for assembly and evaluation of telescopes. Recently, the Cassegrain type collimator has been widely used for its compact size as the focal length of high resolution cameras becomes longer. However, this kind of collimator has a disadvantage in that the secondary mirror is a heat source which can degrade the evaluation accuracy for an IR camera system. In this paper, we present the fabrication and measurement process for an off-axis parabolic mirror with the physical diameter pf 1 m, effective diameter 930 mm, and the focal length 6 m. After four months of works we obtained the final surface wave-front error of 30.4 nm rms ($\lambda$/138, ${\lambda}=4.2\;{\mu}m$), which is capable of evaluation of an IR camera as well as a visible camera.

• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• Korean Journal of Food Science and Technology
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• v.52 no.6
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• pp.580-586
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• 2020

Fishery resources have been widely consumed as protein- and vitamin-rich food sources in the Korean diet. However, information regarding their vitamin levels is extremely limited. In this study, trienzyme-Lactobacillus casei method was validated and used to determine the folate contents in fishery foods. The trienzyme-L. casei method for folate analysis showed excellent accuracy (85.2 to 95.3% recovery) and precision (repeatability 1.4% RSD and reproducibility 2.4% RSD). Folate contents of 20 fish foods (4 fish, 3 crustaceans, 3 sea algae, 3 cephalopods, 4 shellfish, and 3 others) ranged from 1.75 to 97.98 ㎍/100 g. Furthermore, we found that the folate content in seaweed fusiforme was the highest, followed by gulfweed (69.73 ㎍/100 g). Folate analysis using the trienzyme-L. casei method was determined excellent based on the z-score of -0.3 in the Food Analysis Performance Assessment Scheme test. Analytical and method validation data generated in this study could be used to update the national food composition table on vitamin B9 in Korean fishery resources.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.