• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.11-20
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• 2022

The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.1
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• pp.13-20
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• 1991

This paper describes the fish-density dependence of the mean backscattering strength with aggregations of encaged, free-swimming fish of known density in relation to the experimental verification of echo-integration technique for estimating the density of fish shoals. In this experiment, various numbers of gold crussian, Carassius burgeri burgeri, with a mean length of 18.5cm and a mean weight of 205.9g, were introduced into a net cage of approximately 0.76m super(3). During the backscattering measurements. the cage was suspended on the sound axis of the 50kHz transducer having a beam width of 33 degrees at -3dB downpoints. The volume backscattering strengths from fish aggregations were measured as a function of fish density. Data acquisition, processing and analysis were performed by means of the microcomputer-based sonar-echo processor including a FFT analyzer. The calibration of echo-sounder system was carried out at field with a steel ball bearing of 38mm in diameter having the target strength of -40.8dB. The dorsal-aspect target strengths on anesthetized specimens of gold crussian used in the cage experiment were measured and compared with the target strength predicted by the fish density-echo energy relationship for aggregations of free-swimming gold crussian in the cage. The results obtained can be summarized as follows: 1. The target strengths in the dorsal aspect on anesthetized specimens of gold crussian, with the mean length of 19.1cm and the mean weight of 210.5g, varied from -40.9dB to -44.8dB with a mean of -42.6dB. This mean target strength did not differ significantly from that predicted by the regression of echo energy on fish density of free-swimming gold crussian in the cage. It suggests that the target-strength measurements on anesthetized fish was valid and can be representative for live, free-swimming fish. 2. The relationship between mean backscattering strength(, dB) and distribution density of gold $crussian(\rho, $ fish/m super(3)) was expressed by the following equation; =-41.9+11 $Log(\rho)$ with a correlation coefficient of 0.97. This result support the existence of a linear relationship between fish density and echo energy, but suggest that this line has steeper slope than the regression by the theory of estimating the density of fish schools.

• Journal of Food Hygiene and Safety
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• v.25 no.3
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• pp.238-244
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• 2010

Currently, in vitro suspension tests using tubes are used as a authorized test method for sanitizers and disinfectants. However, the methods could not accurately assess the efficacy of sanitizers and disinfectant on the food-contacted surfaces in the field. This study evaluated the effectiveness of 5 kinds of representative sanitizers and disinfectants against E. coli and S. aureus to compare three quantitative surface testing methods that have been internationally standardized. As a result, the ASTM E2111-05 (ASTM(1)) test method obtained 5.18 $\pm$ 0.03 and 5.27 $\pm$ 0.04 log cfu/carrier reduction in dealing with E. coli and S. aureus, respectively, the ASTM E2197-02 (ASTM(2)) test method obtained 4.63 $\pm$ 0.04 and 3.97 $\pm$ 0.03 log cfu/carrier reduction and the CEN EN 13697 test method should 6.14 $\pm$ 0.05 and 5.31 $\pm$ 0.10 log cfu/carrier reduction in clean condition (CEN(1)) but 4.37 $\pm$ 0.02 and 4.06 $\pm$ 0.01 log cfu/carrier reduction in dirty condition (CEN(2)). Among them, CEN(1) showed the highest bactericidal effects, whereas ASTM(2) and CEN(2) revealed low performance (p < 0.05). In conclusion, the bactericidal effects of the ASTM(2) method and the CEN EN 13697 method adopting stainless steel were lower than the ASTM(1) method, which uses glass. The effectiveness assessment results among nationally accredited test methods were different each other. This implies that they could not fit for in the accurate evaluation of sanitization and disinfection on food-contact surfaces in practical food-processing fields. These results could be used as a basic data for establishment of an official surface test methods applicable in the field.

• The korean journal of orthodontics
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• v.40 no.5
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• pp.294-303
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• 2010

Objective: This study was designed to measure the surface roughness at the slot floor of various ceramic brackets. Methods: One kind of stainless steel bracket ($Succes^{(R)}$), two kinds of monocrystalline brackets (Inspire $Ice^{(R)}$, $Perfect^{(R)}$) and two kinds of polycrystalline brackets (Crystalline $V^{(R)}$, $Invu^{(R)}$) were examined. Atomic force microscopy (AFM) was used to measure the surface roughness of each bracket. Data acquisition and processing were performed using $SPIP^{TM}$. Results: The differences in values of Sa, Sq, and Sz in $Invu^{(R)}$ and Inspire $Ice^{(R)}$ were not statistically different from the control group $Succes^{(R)}$. The values of Sa, Sq, and Sz of $Perfect^{(R)}$ and Crystalline $V^{(R)}$ were greater than those of $Succes^{(R)}$. Differences of all the Sa, Sq, and Sz values between $Perfect^{(R)}$ and Crystalline $V^{(R)}$ were not statistically significant. Conclusions: It is concluded that the slot surfaces of $Succes^{(R)}$, Inspire $Ice^{(R)}$, and $Invu^{(R)}$ were smooth compared to those of Crystalline $V^{(R)}$ and $Perfect^{(R)}$.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2000.11a
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• pp.3-4
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• 2000

Many researchers are interested in the synthesis and characterization of carbon nitride and diamond-like carbon (DLq because they show excellent mechanical properties such as low friction and high wear resistance and excellent electrical properties such as controllable electical resistivity and good field electron emission. We have deposited amorphous carbon nitride (a-C:N) thin films and DLC thin films by shielded arc ion plating (SAIP) and evaluated the structural and tribological properties. The application of appropriate negative bias on substrates is effective to increase the film hardness and wear resistance. This paper reports on the deposition and tribological OLC films in relation to the substrate bias voltage (Vs). films are compared with those of the OLC films. A high purity sintered graphite target was mounted on a cathode as a carbon source. Nitrogen or argon was introduced into a deposition chamber through each mass flow controller. After the initiation of an arc plasma at 60 A and 1 Pa, the target surface was heated and evaporated by the plasma. Carbon atoms and clusters evaporated from the target were ionized partially and reacted with activated nitrogen species, and a carbon nitride film was deposited onto a Si (100) substrate when we used nitrogen as a reactant gas. The surface of the growing film also reacted with activated nitrogen species. Carbon macropartic1es (0.1 -100 maicro-m) evaporated from the target at the same time were not ionized and did not react fully with nitrogen species. These macroparticles interfered with the formation of the carbon nitride film. Therefore we set a shielding plate made of stainless steel between the target and the substrate to trap the macropartic1es. This shielding method is very effective to prepare smooth a-CN films. We, therefore, call this method "shielded arc ion plating (SAIP)". For the deposition of DLC films we used argon instead of nitrogen. Films of about 150 nm in thickness were deposited onto Si substrates. Their structures, chemical compositions and chemical bonding states were analyzed by using X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy and infrared spectroscopy. Hardness of the films was measured with a nanointender interfaced with an atomic force microscope (AFM). A Berkovich-type diamond tip whose radius was less than 100 nm was used for the measurement. A force-displacement curve of each film was measured at a peak load force of 250 maicro-N. Load, hold and unload times for each indentation were 2.5, 0 and 2.5 s, respectively. Hardness of each film was determined from five force-displacement curves. Wear resistance of the films was analyzed as follows. First, each film surface was scanned with the diamond tip at a constant load force of 20 maicro-N. The tip scanning was repeated 30 times in a 1 urn-square region with 512 lines at a scanning rate of 2 um/ s. After this tip-scanning, the film surface was observed in the AFM mode at a constant force of 5 maicro-N with the same Berkovich-type tip. The hardness of a-CN films was less dependent on Vs. The hardness of the film deposited at Vs=O V in a nitrogen plasma was about 10 GPa and almost similar to that of Si. It slightly increased to 12 - 15 GPa when a bias voltage of -100 - -500 V was applied to the substrate with showing its maximum at Vs=-300 V. The film deposited at Vs=O V was least wear resistant which was consistent with its lowest hardness. The biased films became more wear resistant. Particularly the film deposited at Vs=-300 V showed remarkable wear resistance. Its wear depth was too shallow to be measured with AFM. On the other hand, the DLC film, deposited at Vs=-l00 V in an argon plasma, whose hardness was 35 GPa was obviously worn under the same wear test conditions. The a-C:N films show higher wear resistance than DLC films and are useful for wear resistant coatings on various mechanical and electronic parts.nic parts.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.