• YAKHAK HOEJI
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• v.26 no.4
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• pp.223-229
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• 1982

Uremia is associated with defective protein binding of weakly acidic drugs, whereas the protein binding of basic drugs tends to be normal. The exact chemical nature of compound(s) and mechanism for these changes as yet is unknown, and has not been defined. Organic solvent extraction of pooled normal human urine following hydrolysis by hydrochloric acid produced an extract, which when added to normal human serum, was capable of inducing binding defects similar to those in uremia. Binding defects were observed with the weakly acidic drugs such as nafcillin, salicylate, sulfamethoxazole and phenytoin while the binding of the basic drugs such as trimethoprim and quinidine were unaffected. The binding defects induced by the hydrolyzed urine extract could readily be corrected by same organic solvent extraction of acidified serum and the defects could be transferred to the normal human serum using the organic solvent layer at the physiologic pH (7.4). Followed by reacidification ind extraction of the binding defects induced serum with the same solvent, separated several fractions were obtained on thin-layer chromatography. One of these fractions could reinduce the binding defects and this factor(s) is apparently weakly acidic compounds and tightly bound to serum at physiologic pH, but extractable at acidic pH, and its molecular weight range is approximately 500 or less similar to those seen in uremia. These findings strongly support the hypothesis that the drug binding defect in uremia is due to the accumulation of endogenous metabolic products which arc normally excreted by the kidneys but accumulate in renal failure.

• Journal of Microbiology
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• v.42 no.2
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• pp.139-142
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• 2004

To identify genes involved in the decolorization of brilliant green, we isolated random mutants generated by transposon insertion in brilliant green-decolorizing bacterium, Citrobacter sp. The resulting mutant bank yielded 19 mutants with a complete defect in terms of the brilliant green color removing ability. Southern hybridization with a Tn5 fragment as a probe showed a single hybridized band in 7 mutants and these mutants appeared to have insertions at different sites of the chromosome. Tn5-inserted genes were isolated and the DNA sequence flanking Tn5 was determined. By comparing these with a sequence database, putative protein products encoded by bg genes were identified as follows: bg 3 as a LysR-type regulatory protein; bg 11 as a MalG protein in the maltose transport system; bg 14 as an oxidoreductase; and bg 17 as an ABC transporter. The sequences deduced from the three bg genes, bg 2, bg 7 and bg 16, showed no significant similarity to any protein with a known function, suggesting that these three bg genes may encode unidentified proteins responsible for the decolorization of brilliant green.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.121-126
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• 2017

EES System support to maximize equipment efficiency by providing real-time information of main equipment which has a significant effect on product quality and productivity, and to prevent equipment failure by detecting equipment abnormality in advance. Smart Equipment Engineering System(S-EES) integrates the activities performed at equipment that are the core of production activities and manages them by system so as to maximize the efficiency of equipment and raise the quality level of products to one level. In other words, when the product is put into the equipment, the recipe is downloaded through the RMS, the recipe is set to the optimal condition through R2R(process control), and the system detects and controls the abnormality of the equipment during operation through the FDC function in real time it means. In this way, we are working with the suitable recipe that matches the lot of product, detecting the abnormality of the equipment during operation, preventing the product from being defective, and establishing a system to maximize the efficiency through real-time equipment management. In this study, we review the present status and problems of equipment management in actual production lines, collect the requirements of the manufacturing line for the PCB line, design and develop the system, The measurement model was studied.

• Steel and Composite Structures
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• v.30 no.6
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• pp.517-534
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• 2019

In this paper, the effects of inevitable out-of-plane defects on the postbuckling behavior of single-layered graphene sheets (SLGSs) under in-plane loadings are investigated based on nonlocal first order shear deformation theory (FSDT) and von-Karman nonlinear model. A generic imperfection function, which takes the form of the products of hyperbolic and trigonometric functions, is employed to model out-of-plane defects as initial geometrical imperfections of SLGSs. Nonlinear equilibrium equations are derived from the principle of virtual work and variational formulation. The postbuckling equilibrium paths of imperfect graphene sheets (GSs) are presented by solving the governing equations via isogeometric analysis (IGA) and Newton-Raphson iterative method. Finally, the sensitivity of the postbuckling behavior of GS to shape, amplitude, extension on the surface, and location of initial imperfection is studied. Results showed that the small scale and initial imperfection effects on the postbuckling behavior of defective SLGS are important and cannot be ignored.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.11
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• pp.115-120
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• 2021

In this study, cigarettes, which are an essential element in the production of tobacco, are generally not cylindrical. The main materials used for cigarettes are generally hemp and pulp. For the production of cylindrical cigarettes, the cigarettes or cylinders are mounted via gluing. This adhesive is a vinyl acetate emulsion, a high-temperature melt adhesive, and is adhered in a cylindrical shape immediately after being linearly applied to the inner surface of the paper roll or a local part. These adhesives are greatly affected by the atmospheric temperature of the manufacturing space in summer and winter. In the summer, even if the adhesive is temporarily adhered, the coagulation time of the adhesive is long, and problems such as deterioration of the adhesive state occur. in the winter, there is a problem that the temperature of the manufacturing space is low and the adhesive force of the adhesive is poor, resulting in defective adhesive products. In order to solve these problems, another heat transfer device is utilized to cure the remaining adhesive to ensure higher adhesiveness.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.551-559
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images, 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc., so that a total of seven images, that is, one color image from the top side of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filter image and the other is 970nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results to the Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defective and shape were 95.3%, 86% and 91%, respectively. Grading time was 0.35 sec per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.623-625
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• 2021

Rubber o-rings are produced by conventional injection molding methods. In this case, products that are not normally molded are determined to be defective. However, if images acquired during image-based reading are read as original, there is a problem of poor accuracy. We have thus learned from convolutional neural networks using adaptive binarization and Convex Hull algorithms by extracting only rubber oring parts from the original images through pre-processing. During the test process, it was confirmed that the defect detection performance of the learning method applied pre-processing was better than the standard suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.447-449
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• 2022

This study was based on Android, one of the representative mobile platforms with the characteristics of connecting to the network anytime, anywhere and flexible mobility. In addition, using a demand prediction algorithm that can know the data of defective products based on AI, we will study the real-time monitoring UI design method based on Android studio with demand prediction data and company time series data.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.21-28
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• 2023

In manufacturing companies that focus on small-scale production of multiple product varieties, defective products are manually selected by workers rather than relying on automated inspection. Consequently, there is a higher risk of incorrect sorting due to variations in selection criteria based on the workers' experience and expertise, without consistent standards. Moreover, for non-standardized flexible objects with varying sizes and shapes, there can be even greater deviations in the selection criteria. To address these issues, this paper designs a quality inspection system using artificial intelligence-based unsupervised learning methods and conducts research by experimenting with accuracy using a dataset obtained from real manufacturing environments.