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.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.7
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pp.520-527
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2019
In this study, the technical level and competence of Chungbuk region manufactures were diagnosed and implications for efficiency improvement of cooperation with local universities were derived. The results are as follow. First, in Chungbuk area, 75% of the skilled workers are medium-skilled and high skilled workers. And the life cycle of production products was found to have entered middle/old age. In addition, the industries were overestimating its technology capabilities, including marketing and sales technology, and management technology. Therefore, local universities should develop differentiated program such as technology transfer and commercialization support so that companies can nurture new industries and it is necessary to improve understanding of reality and future prediction ability through various education and seminars. Second, universities in Chungbuk province have failed to meet the practical demands of industry by providing general educational programs such as lifelong education curriculum, rather than the practical training required by industry. First of all, industries needed the practical training programs such as human resource empowerment, technical education and workers' retraining for local industry development. In addition, industries were expected to provide relevant knowledge and infrastructure such as testing, analysis, participation in technology development such as commissioning and joint research. Therefore, universities should prepare customized Industry-Academia Cooperation Programs through industry demand survey in planning. Also, it is necessary to establish various connection points with industry to ensure that industry-academia cooperation will continue and achieve results. Third, the technology of the industries in Chungbuk province was found to be very unrelated to the next generation regional strategic industries. This is not shared vision between industry and local government, Industry-Academia Cooperation Programs will serve as a platform to organize various community entities. Universities will be able to play a key role in between industries and local governments.
Lee, Seokhyun;Lee, Ra Ham;Kim, Sung-Jo;Lee, Hak-Kyo;Na, Chong-Sam;Song, Ki-Duk
Asian-Australasian Journal of Animal Sciences
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v.32
no.12
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pp.1942-1949
/
2019
Objective: Leukocyte cell-derived chemotaxin 2 (LECT2) is associated with several physiological processes including inflammation, tumorigenesis, and natural killer T cell generation. Chicken LECT2 (chLECT2) gene was originally identified as one of the differentially expressed genes in chicken kidney tissue, where the chickens were fed with different calcium doses. In this study, the molecular characteristics and gene expression of chLECT2 were analyzed under the stimulation of toll-like receptor 3 (TLR3) ligand to understand the involvement of chLECT2 expression in chicken metabolic disorders. Methods: Amino acid sequence of LECT2 proteins from various species including fowl, fish, and mammal were retrieved from the Ensembl database and subjected to Insilco analyses. In addition, the time- and dose-dependent expression of chLECT2 was examined in DF-1 cells which were stimulated with polyinosinic:polycytidylic acid (poly [I:C]), a TLR3 ligand. Further, to explore the transcription factors required for the transcription of chLECT2, DF-1 cells were treated with poly (I:C) in the presence or absence of the nuclear factor ${\kappa}B$ ($NF{\kappa}B$) and activated protein 1 (AP-1) inhibitors. Results: The amino acid sequence prediction of chLECT2 protein revealed that along with duck LECT2 (duLECT2), it has unique signal peptide different from other vertebrate orthologs, and only chLECT2 and duLECT2 have an additional 157 and 161 amino acids on their carboxyl terminus, respectively. Phylogenetic analysis suggested that chLECT2 is evolved from a common ancestor along with the actinopterygii hence, more closely related than to the mammals. Our quantitative polymerase chain reaction results showed that, the expression of chLECT2 was up-regulated significantly in DF-1 cells under the stimulation of poly (I:C) (p<0.05). However, in the presence of $NF{\kappa}B$ or AP-1 inhibitors, the expression of chLECT2 is suppressed suggesting that both $NF{\kappa}B$ and AP-1 transcription factors are required for the induction of chLECT2 expression. Conclusion: The present results suggest that chLECT2 gene might be a target gene of TLR3 signaling. For the future, the expression pattern or molecular mechanism of chLECT2 under stimulation of other innate immune receptors shall be studied. The protein function of chLECT2 will be more clearly understood if further investigation about the mechanism of LECT2 in TLR pathways is conducted.
This study investigate the use of ultraviolet(UV) light with hydrogen peroxide($H_2O_2$) for Methyl Tert Butyl Ether(MTBE) degradation in photolysis reactor. The process in general demands the generation of OH radicals in solution at the presence of UV light. These radicals can then attack the MTBE molecule and it is finally destroyed or converted into a simple harmless compound. The MTBE removal by photolysis were mathematically described as the independent variables such as irradiation intensity, initial concentration of MTBE and $H_2O_2$/MTBE ratio, and these were modeled by the use of response surface methodology(RSM). These experiments were carried out as a Box-Behnken Design(BBD) consisting of 15 experiments. Regression analysis term of Analysis of Variance(ANOVA) shows significantly p-value(p<0.05) and high coefficients for determination values($R^2$=94.60%) that allow satisfactory prediction of second-order regression model. And Canonical analysis yields the stationery point for response, with the estimate ridge of maximum responses and optimal conditions for Y(MTBE removal efficiency, %) are $x_1$=25.75 W of irradiation intensity, $x_2$=7.69 mg/L of MTBE concentration and $x_3$=11.04 of $H_2O_2$/MTBE molecular ratio, respectively. This study clearly shows that RSM is available tool for optimizing the operating conditions to maximize MTBE removal.
IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.
The CANDU element bowing is attributed to actions of both the thermally induced bending moments and the bending moment due to hydraulic drag and mechanical loads, where the bowing is defined as the lateral deflection of an element from the axial centerline. This paper consider only the thermally-induced bending moments which are generated both within the sheath and the fuel and sheath by an asymmetric temperature distribution with respect to the axis of an element The generalized and explicit analytical formula for the thermally-induced bending is presented in con-sideration of 1) bending of an empty tube treated by neglecting the fuel/sheath mechanical interaction and 2) fuel/sheath interaction due to the pellet and sheath temperature variations, where in each case the temperature asymmetries in sheath are modelled to be caused by the combined effects of (i) non-uniform coolant temperature due to imperfect coolant mixing, (ii) variable sheath/coolant heat transfer coefficient, (iii) asymmetric heat generation due to neutron flux gradients across an element and so as to inclusively cover the uniform temperature distributions within the fuel and sheath with respect to the axial centerline. As the results of the sensitivity calculations of the element bowing with the variations of the parameters in the formula, it is found that the element bowing is greatly affected relatively with the variations or changes of element length, sheath inside diameter, average coolant temperature and its variation factor, pellet/sheath mechanical interaction factor, neutron flux depression factor, pellet thermal expansion coefficient, pellet/sheath heat transfer coefficient in comparison with those of other parameters such as sheath thickness, film heat transfer coefficient, sheath thermal expansion coefficient and sheath and pellet thermal conductivities.
In this study, the noise contributions by the duct, stator and rotor, which are the propulsor components, are evaluated to identify the flow noise source in cavitation and non-cavitation conditions on pumpjet propulsion and the noise levels in both conditions are compared. The unsteady incompressible Reynolds averaged Navier-Stokes (RANS) equation based on the homogeneous mixture assumption is applied on the suboff submarine hull and pumpjet propeller in the cavitation tunnel, and the Volume of Fluid (VOF) method and Schnerr-Sauer cavitation model are used to describe the two-phase flow. Based on the flow simulation results, the acoustic analogy formulated by Ffowcs Williams and Hawkings (FW-H) equation is applied to predict the underwater radiated noise. The noise contributions are evaluated by using the three types of impermeable integral surface on the duct, stator and rotor, and the two types of permeable integral surface surrounding the propulsor. As a result of noise prediction, the contribution by the stator is insignificant, but it affects the generation of flow noise source due to flow separation in the duct and rotor, and the noise is predominantly radiated into the upward and right where the flow separations are. Also, the noise is radiated into the thrust direction due to pressure fluctuation between suction and pressure sides on the rotor blades, and the it can be seen that the cavitation effect into the noise can be considered through the permeable integral surface.
Y. S. Jang;Y. R. Jang;J. J. Choi;D. J. Jeon;Y. G. Kim;D. M. Ha
Journal of the Korean Society of Safety
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v.38
no.5
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pp.8-14
/
2023
Lithium ions can induce the thermal runaway phenomenon and lead to reignition due to electrical, mechanical, and environmental factors such as high temperature, smoke generation, explosions, or flames, which is extremely likely to create safety concerns. Therefore, one of the ways to improve the flame retardancy of the electrolyte is to use a flame-retardant additive. Comparing the associated characteristic value of existing substances with the required experimental value, it was found that these values were either considerably different or were not documented. It is vital to know a substance's combustion characteristic values, flash point, explosion limit, and autoignition temperature (AIT) as well as its combustion characteristics before using it. In this research, the flash point and AIT of materials were measured by mixing a highly volatile and flammable substance, diethyl carbonate (DEC), with flame-retardant dimethyl methylphosphonate (DMMP). The flash point of DEC, which is a pure substance, was 29℃, and that for DMMP was 65℃. Further, the lower explosion limit calculated using the measured flash point of DEC was 1.79 Vol.%, while that for DMMP was 0.79 Vol.%. The AIT was 410℃ and 390℃ for DEC and DMMP, respectively. In particular, since the AIT of DMMP has not been discussed in any previous study, it is necessary to ensure safety through experimental values. In this study, the experimental and regression analysis revealed that the average absolute deviation (ADD) for the flash point of the DEC+DMMP DEC+DMMP system is 0.58 sec and that the flash point tends to increase according to changes in the composition employed. It also revealed that the AAD for the AIT of the mixture was 3.17 sec and that the AIT tended to decrease and then increase based on changes in the composition.
This study was conducted to estimate the Genomic Estimated Breeding Value (GEBV) using Genomic Best Linear Unbiased Prediction (GBLUP) method in Hanwoo (Korean native cattle) population. The result is expected to adapt genomic selection onto the national Hanwoo evaluation system. Carcass weight (CW), eye muscle area (EMA), backfat thickness (BT), and marbling score (MS) were investigated in 552 Hanwoo progeny-tested steers at Livestock Improvement Main Center. Animals were genotyped with Illumina BovineHD BeadChip (777K SNPs). For statistical analysis, Genetic Relationship Matrix (GRM) was formulated on the basis of genotypes and the accuracy of GEBV was estimated with 10-fold Cross-validation method. The accuracies estimated with cross-validation method were between 0.915~0.957. In 534 progeny-tested steers, the maximum difference of GEBV accuracy compared to conventional EBV for CW, EMA, BT, and MS traits were 9.56%, 5.78%, 5.78%, and 4.18% respectively. In 3,674 pedigree traced bulls, maximum increased difference of GEBV for CW, EMA, BT, and MS traits were increased as 13.54%, 6.50%, 6.50%, and 4.31% respectively. This showed that the implementation of genomic pre-selection for candidate calves to test on meat production traits could improve the genetic gain by increasing accuracy and reducing generation interval in Hanwoo genetic evaluation system to select proven bulls.
Proceedings of the Korea Society for Industrial Systems Conference
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2002.06a
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pp.148-155
/
2002
Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.
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