• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.2
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• pp.145-152
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• 2001

This study was performed to evaluate the coke oven emissions (COE) and polynuclear aromatic hydrocarbon levels in coke manu-facturing industry, secondary lead smelting industry and glass bottle manufacturing industry. 1. There were no significant difference between the means of personal samples and area samples by the types of industry(p>0.05). The levels of airborne total particulates of the secondary lead smelting industry was the highest($2.30mg/m^3$), and those of the coke manu-facturing industry and glass bottle manu facturing industry were $1.95mg/m^3$ and $1.37mg/m^3$. The concentration of COE was the highest in the glass bottle manufacturing industry($0.79mg/m^3$), and in order of $0.19mg/m^3$ in the coke manufacturing industry and $0.06mg/m^3$ in the secondary lead smelting industry. COE/total particulates(%) was highest in the glass bottle manufacturing industry(58.1%) and in order of 10.3% in the coke manufacturing industry and 3.1% in secondary lead smelting industry. There were significant differences in the total particle concentration and COE by the types of industry(p<0.05). 2. The levels of airborne total particulates was the highest at the smelting process of secondary lead smelting industry($2.30{\pm}0.72mg/m^3$), and the lowest at the smelting process of glass bottle manufacturing industry ($0.99{\pm}1.22mg/m^3$) Concentration of COE was the highest at the casting process of glass bottle manufacturing industry ($1.09{\pm}1.15mg/m^3$), the lowest at the smelting process of secondary lead smelting industry ($0.06{\pm}0.03mg/m^3$). The COE/total particulates(%) was the highest at the casting process of glass bottle manufacturing industry($65.9{\pm}20.5%$), and the lowest at the smelting process of secondary lead smelting indusry($3.1{\pm}2.7%$). 3. There were positive correlations between level of The airborne total particulates and concentration of COE in coke manufacturing industry and glass bottle manufacturing industry (p<0.05), but negative correlation in secondary lead smelting industry. 4. The numbers of case and rates that over the Threshold Limit Values(TLVs) were 24 (77.4%)cases in glass bottle manufacture, 14(23.7%) cases in the coke manufacturing industry and no one case in secondary lead smelting industry. Total numbers of case and rates that over TLVs were 38( 35.5%) cases. 5. The limit of detection(LOD) for PAH was $10{\mu}g/ml$ in standard sample. All PAH levels of the cokes manufacturing industry and the secondary lead smelting industry and the glass bottle manufacturing industry were trace or not to detect.

• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.1-30
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• 2019

The advent of digitalisation has transformed economies into more integrated, but increasingly complex systems. This new trend has brought dynamic changes in the manufacturing sector through advanced ICT infrastructure, smart factories, digitally-controlled logistics, and skilled ICT-labour. The impacts of the digital economy on manufacturing could be best illustrated through "Industry 4.0." With this wave of technological advancement, countries aim to establish an industrial ecosystem where every manufacturing process and function is connected and interacts through digital networks. Industry 4.0 presents opportunities for Emerging Asia, as the region has emerged as a fast-growing manufacturing hub and particularly a production base for ICT goods. However, growing production capacity, increased exports, and increases in FDI in the field of ICT goods manufacturing have so far contributed little to the development and diffusion of ICT. A huge gap exists in the ICT uptake amongst countries and between small and large firms. This paper highlights the level of Industry 4.0 readiness of Emerging Asia and key factors that determine its enhancement.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.649-664
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• 2017

Purpose: This paper introduces the technology of prognostics for Industry 4.0 and presents its application procedure for fitness-for-service assessment of natural gas pipelines according to ISO 13374 framework. Methods: Combining data-driven approach with pipe failure models, we present a hybrid scheme for the gas pipeline prognostics. The probability of pipe failure is obtained by using the PCORRC burst pressure model and First Order Second Moment (FOSM) method. A fuzzy inference system is also employed to accommodate uncertainty due to corrosion growth and defect occurrence. Results: With a modified field dataset, the probability of failure on the pipeline is calculated. Then, its residual useful life (RUL) is predicted according to ISO 16708 standard. As a result, the fitness-for-service of the test pipeline is well-confirmed. Conclusion: The framework described in ISO 13374 is applicable to the RUL prediction and the fitness-for-service assessment for gas pipelines. Therefore, the technology of prognostics is helpful for safe and efficient management of gas pipelines in Industry 4.0.

• Fourth Industrial Review
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• v.3 no.2
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• pp.1-10
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• 2023

Purpose - The main purpose of the paper is to examine the variables affecting carbon emissions in different nations around the world. Research design, data, and methodology - To measure its impact on carbon emissions, secondary data has data of the top 50 Countries have been taken. The stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model have been used to quantify the factors that affect carbon emissions. A modified version using Industry 4.0 and region in fundamental STIRPAT model has been applied with the ordinary least square approach. The outcome has been measured using both the basic and extended STIRPAT models. Result - Technology found a positive determinant as well as statistically significant at the alpha level of 0.001models indicating that technological innovation helps reduce carbon emissions. In total, 4 models have been derived to test the best fit and find the highest explaining capacity of variance. Model 3 is found best fit in explanatory power with the highest adjusted R2 (97.95%). Conclusion - It can be concluded that the selected explanatory variables population and Industry 4.0 are found important indicators and causal factors for carbon emission and found constant with all four models for total CO2 and Co2 per capita.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.2
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• pp.160-171
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• 1995

The size characteristics of lead particle which is one of the important factors associated with absorption of lead were ignored in establishing lead standard. This study was conducted to investigate distribution of lead particles by operation of industry. Aerodynamic Mass Median Diameters (MMD) of airborne lead particles in the battery and litharge manufacturing industry were $14.1{\mu}m$ and $15.1{\mu}m$, respectively. There was no significant difference between those two values(p>0.05). However, the diameters in radiator manufacturing and secondary smelting industry were $1.3{\mu}m$, $4.9{\mu}m$, respectively. Those were significantly smaller than the particle sizes in other industries(p<0.05). Total lead concentrations in the secondary smelting industry were higher than those in the battery and litharge manufacturing industry. Total lead concentrations in other industries except radiator manufacturing industry exceeded the standard of $50{\mu}g/m^3$. Only radiator manufacturing industry indicated lead concentrations significantly lower than those in other industries(p<0.05). Concentrations of lead particles smaller than $1{\mu}m$ defined as respirable fraction by OSHA's CPA model assumption were $72.4{\mu}g/m^3$ in the secondary smelting industry, exceeding $50{\mu}g/m^3$. The relationship of concentrations between total lead and lead of particles smaller than $1{\mu}m$ was log Y = 0.46 logX + 0.06(n=119, $r^2=0.44$, p=0.0001). Relationship of respirable lead concentrations between OSHA and ACGIH was significantly detected in the litharge and battery manufacturing industry(p=0.0001), but was not significant in the radiator(p=0.2720) and secondary smelting manufacturing industry(p=0.2394). As MMDs of lead particles generated in industry were small, difference of respirable lead concentration between OSHA and ACGIH became smaller. There was a significant difference between concentrations respirable lead defined by two organizations such as OSHA and ACGIH in the battery and litharge manufacturing industry. Average concentration of respirable lead by ACGIH definition was 43.3 % of total lead in secondary smelting and 48.9 % in radiator manufacturing industry, and lower fractions were indicated in battery and litharge manufacturing industry. Relationships of total lead with IPM, TPM, and RPM were significant respectively(p=0.0001) and lead concentrations by particle size could be estimated using this relationship. Linear regression equation between total lead concentration(X) and ACGIH-RPM concentration(Y) was log Y = 0.76 log X - 0.40($r^2=0.89$, p=0.0001).

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.447-466
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• 2021

Purpose: This article aims 1) to propose Quality 4.0 concept through surveying related literature, 2) to suggest key elements of Quality 4.0 by arranging the elements of Quality 4.0 that appeared in the literature, 3) to determine the levels of Quality 4.0, and 4) to suggest ideas for effective deployment of Quality 4.0. Methods: Eleven papers or documents are reviewed for Quality 4.0 concept; two papers and one document are investigated for key element extraction of Quality 4.0; and smart factory roadmap and industry 4.0 maturity model are studied to determine the levels of Quality 4.0. Results: 1) Quality 4.0 definition is proposed. 2) Three key elements are determined: data acquisition and analytics, connection and integration, and leadership and culture. 3) Six Quality 4.0 levels are determined. 4) Some suggestions are addressed for effective deployment of Quality 4.0. Conclusion: 1) Definition, key elements, levels, and some suggestions on effective deployment of Quality 4.0 are addressed. 2) Specific contents of Quality 4.0 education and training courses should be provided in the future. 3) Two future research directions are proposed.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.623-633
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• 2016

A total of 6,973 steer growth records of Hanwoo breeding bull's progeny test data collected from 1989 to 2015 were analyzed to identify the most appropriate growth curve among three growth curve models (Gompertz, Logistic and von Bertalanffy). The Gompertz growth curve model equation was $W_t=990.5e^{{-2.7479e}^{-0.00241t}}$, the Logistic growth curve model equation was $W_t=772(1+8.3314e^{-0.00475t})^{-1}$, and the von Bertalanffy growth curve model equation was $W_t=1,196.4(1-0.646e^{-0.00162t})^3$. The Gompertz model parameters A, b, and k were estimated to be $990.5{\pm}10.27$, $2.7479{\pm}0.0068$, and $0.00241{\pm}0.000028$, respectively. The inflection point age was estimated to be 421 days and the weight of inflection point was 365.3 kg. The Logistic model parameters A, b, and k were estimated to be $772.0{\pm}4.12$, $8.3314{\pm}0.0453$, and $0.00475{\pm}0.000033$, respectively. The inflection point age was estimated to be 445 days and the weight of inflection point was 385.0 kg. The von Bertalanffy model parameters A, b, and k were estimated to be $1196.4{\pm}18.39$, $0.646{\pm}0.0010$, and $0.00162{\pm}0.000027$, respectively. The inflection point age was estimated to be 405 days and the weight of inflection point was 352.0 kg. Mature body weight of the von Bertalanffy model was 1196.4 kg, the Gompertz model was 990.5 kg, and the Logistic model was 772.0 kg. The difference between actual and estimated weights was similar in the Logistic model and the von Bertalanffy model. The difference between market weight and estimated market weight was the lowest in the Gompertz model. The growth curve using the von Bertalanffy model showed the lowest mean square error.

• Journal of Animal Science and Technology
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• v.64 no.4
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• pp.727-739
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• 2022

Mycotoxin contamination in pig feeds has a negative impact on growth performance, the immune system, and major body organs. Arginine (Arg) plays an important role in animals' body biochemistry and physiology. This study aimed to determine the effect of dietary Arg supplementation on mitigating the negative effects of mycotoxins in growing pigs. A total of 72 growing pigs (Landrace × Large white) with initial mean body weight (BW) = 55 ± 2.5 kg were allotted to four treatment groups with three replicates per group of six pigs per replicate in a completely randomized design. The treatments included a non-toxin diet with 1.2% Arg (NT1.2) and mycotoxin-challenged treatments supplemented with 1.2% Arg (TX1.2), 1.3% Arg (TX1.3), and 1.4% Arg (TX1.4). Statistical analysis of data included the effects of dietary level of Arg. The results indicated a significantly higher BW (p < 0.05), average daily gain (p < 0.05), and gain-to-feed ratio (p < 0.05) in the NT1.2 group than in the TX1.2, TX1.3, and TX1.4 groups. The relative weight of the liver was higher (p < 0.05) in the TX1.2 compared to that of the NT1.2 group, although it was not different from that of TX1.3 and TX1.4. The level of tumor necrosis factor-alpha was significantly up-regulated (p < 0.05) in the liver tissue of the TX1.2 group compared to that of the other treatments. Overall, dietary Arg supplementation remedied liver injury and alleviated the compromised immune system caused by mycotoxin toxicity.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.235-240
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• 2018

ICT converged smart factory started from German Industry 4.0 has been the driving force for the $4^{th}$ Industrial Revolution and the center of manufacturing innovation for major industrial countries. It will be developed according to industry characteristics of each country. Korea is relatively later than other competing countries in the smart factory area. So, the government is establishing related policy and tendering all sorts of supports for smart factory mainly to the small and medium-sized enterprises to spread over the manufacturing industry. It is necessary for government to categorize among similar manufacturing industry and make them share digitalized production information mutually. It will be more effective method for securing global competitiveness than the uniform support. Also, large companies need to establish cloud based production forecasting system over similar industry and share it with other companies rather than expansion of individual smart factory. Mutual development in the manufacturing industry will be realized when the small and medium-sized enterprises and large companies take part in the cooperating ground of smart factory.

• Journal of Mushroom
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• v.18 no.4
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• pp.380-386
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• 2020

The study was conducted for the safety evaluation of 320 pesticide residues in 768 Lentinula edodes fruit body samples and 143 L. edodes media samples, which are distributed nationwide in South Korea. The monitoring method was the second of the multi-residue methods in the Korean Food Code. GC-ECD, GC-NPD, and GC-MSD were used as evaluation equipment for analysis. Single-analysis of the target pesticides was performed for mepiquat chloride. Through the analysis of collected L. edodes samples, pesticide residues were detected in total seven cases, including four L. edodes fruit body samples and three L. edodes media samples. The detected pesticide residues were carbendazim, diflubenzuron, fluopyram, and dinotefuran. In this study, carbendazim was detected in three L. edodes fruit body samples and one L. edodes media sample. The detected amount of carbendazim was 0.056, 0.17, 0.043, and 0.09 mg/kg, respectively. The amount of carbendazim in the collected L. edodes samples was detected below the MRLs (maximum residue level). The detected amounts of fluopyram and dinotefuran were 0.068 mg/kg and 0.06 mg/kg, respectively. Two pesticide residues were detected in the medium in one case. Mepiquat chloride was not detected in this study. These results suggested that residual pesticides were detected in a small number of collected L. edodes. However, the PLS for unregistered pesticides MRL was 0.01 ppm; therefore, we have to conduct research on preparing safety standards for mushrooms, including L. edodes.