• Journal of Food Hygiene and Safety
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• v.26 no.4
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• pp.296-301
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• 2011

This study was to evaluate the growth potential of E. coli O157:H7 in lettuce leaf extracts and on lettuce leaf surface at various temperatures. The pathogen can survive and multiply in the extracts and leaf surface of lettuce. The population of E. coli O157:H7 in the lettuce extracts reached to 4.79 log CFU/mL at $37^{\circ}C$. The multiplication of pathogen in lettuce extracts initiated within 10 hours of inoculation over $15^{\circ}C$ conditions. And it can survive in the lettuce leaf extracts at $4^{\circ}C$ for 100 hours at least. And this pathogen can multiply on lettuce leaf surface and the population of pathogen on the lettuce leaf surface increased to 1.82 log CFU/g at $25^{\circ}C$. At $37^{\circ}C$, the pathogen density increased to 1.53 CFU/g within 3 days after inoculation. At all temperature, irrespective of the inoculation level, similar trends in growth of E. coli O157:H7 were observed. These results emphasize the growth potential of E. coli O157:H7 in lettuce leaf extract and on lettuce leaf surface. To reduce the risk of outbreak, it is important to maintain the cold chain system during storage before the consumption.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.427-442
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• 2011

In fatigue life design of mechanical components, uncertainties arising from materials and manufacturing processes should be taken into account for ensuring reliability. A common practice is to apply a safety factor in conjunction with a physics model for evaluating the lifecycle, which most likely relies on the designer's experience. Due to conservative design, predictions are often in disagreement with field observations, which makes it difficult to schedule maintenance. In this paper, the Bayesian technique, which incorporates the field failure data into prior knowledge, is used to obtain a more dependable prediction of fatigue life. The effects of prior knowledge, noise in data, and bias in measurements on the distribution of fatigue life are discussed in detail. By assuming a distribution type of fatigue life, its parameters are identified first, followed by estimating the distribution of fatigue life, which represents the degree of belief of the fatigue life conditional to the observed data. As more data are provided, the values will be updated to reduce the credible interval. The results can be used in various needs such as a risk analysis, reliability based design optimization, maintenance scheduling, or validation of reliability analysis codes. In order to obtain the posterior distribution, the Markov Chain Monte Carlo technique is employed, which is a modern statistical computational method which effectively draws the samples of the given distribution. Field data of turbine components are exploited to illustrate our approach, which counts as a regular inspection of the number of failed blades in a turbine disk.

• Information Systems Review
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• v.5 no.1
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• pp.1-18
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• 2003

Many organizations experience that the value they gained from IT (information technology) investment is lower than they expected prior to the actual implementation of a system - the value gap between expected value and realized value from IT. Research on the barriers to the expectation and realization is of high importance both in practice and in IS research. This study analyzed such barriers observed in three companies that have adopted such IT systems as Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM) systems each. From analyses of the three companies we specifically identified eight types of barriers: barriers related to industry, organization, knowledge, resource, usage, competence, product, and safety. Common barriers among the three cases were classified into six types, e.g. lack of strategic mind-set, improper organizational structure, lack of human resource, etc. We expect that the results help managers in IS investment to minimize the valuation gap and maximize realized values.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.155-159
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• 2016

Background: Nuclear reactors produce a great number of antielectron neutrinos mainly from beta-decay chains of fission products. Such neutrinos have energies mostly in MeV range. We are interested in neutrinos in a region of keV, since they may take part in special weak interactions. We calculate reactor antineutrino spectra especially in the low energy region. In this work we present neutrino spectrum from a typical pressurized water reactor (PWR) reactor core. Materials and Methods: To calculate neutrino spectra, we need information about all generated nuclides that emit neutrinos. They are mainly fission fragments, reaction products and trans-uranium nuclides that undergo negative beta decay. Information in relation to trans-uranium nuclide compositions and its evolution in time (burn-up process) were provided by a reactor code MVP-BURN. We used typical PWR parameter input for MVP-BURN code and assumed the reactor to be operated continuously for 1 year (12 months) in a steady thermal power (3.4 GWth). The PWR has three fuel compositions of 2.0, 3.5 and 4.1 wt% $^{235}U$ contents. For preliminary calculation we adopted a standard burn-up chain model provided by MVP-BURN. The chain model treated 21 heavy nuclides and 50 fission products. The MVB-BURN code utilized JENDL 3.3 as nuclear data library. Results and Discussion: We confirm that the antielectron neutrino flux in the low energy region increases with burn-up of nuclear fuel. The antielectron-neutrino spectrum in low energy region is influenced by beta emitter nuclides with low Q value in beta decay (e.g. $^{241}Pu$) which is influenced by burp-up level: Low energy antielectron-neutrino spectra or emission rates increase when beta emitters with low Q value in beta decay accumulate Conclusion: Our result shows the flux of low energy reactor neutrinos increases with burn-up of nuclear fuel.

• The Korean Journal of Food And Nutrition
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• v.31 no.5
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• pp.616-630
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• 2018

This study analyzed the current status of registered patents related to food tech in Korea and Japan. Using the patent information search services of Korean and Japanese Patent Offices, patents registered during the past 10 years from January 1, 2005 to December 31, 2015 were searched with the following key words/phrases: "food or meal or diet" and "program or information system". A total of 669 patents (539 for Korea and 130 for Japan) were finally selected and analyzed. Based on Porter's value chain theory, the patents were categorized into three dimensions related to "manufacturing/processing/distribution", "sales & marketing", and "consumer support". The results showed that in Korea, 41.7% of the total patents were related to sales & marketing followed by consumer support (37.3%) and manufacturing/processing/distribution (21.0%). In Japan, patents related to consumer support accounted for 56.2% followed by manufacturing/processing/distribution (32.3%), and sales & marketing (11.5%). In the area of manufacturing/processing/distribution, "food quality management system" in Korea, and "food manufacturing and processing management system" and "food safety control and hazard analysis system" in Japan tended to show a significantly higher proportion of patents registered (p<.05). Under sales & marketing, patents in the categories of "food purchase and delivery service system" in Korea and "restaurant information sharing system" in Japan tended to be more frequently registered (p<.05). Finally, in the area of consumer support, "kitchen facility and cooking device control system" in Korea and "menu and nutrition management system" in Japan tended to account for a significantly higher proportion of patents registered (p<.001). The results are expected to provide useful insights into the development of new patents and markets for food tech in the future.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Food Science and Biotechnology
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• v.17 no.6
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• pp.1240-1245
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• 2008

Kimbab is the most popular ready-to-eat (RTE) food in Korea. A rapid detection method based on multiplex PCR technique was developed for detection of major food-borne pathogens like Salmonella spp., Shigella spp., Bacillus cereus, Listeria monocytongenes, and Staphylococcus aureus. Specific bands were obtained as 108 bp (Sau, S. aureus), 284 bp (Sal, S. enterica, S. enteritids, and S. typhmurium), 404 bp (Lmo, L. monocytogenes), 475 bp (Bce, B. cereus), and 600 bp (Shi, S. flexineri and S. sonnei). Visible cell numbers varied from 4.14-5.03, 3.61-4.47, and 4.10-5.11 log CFU/g in randomly collected June, July, and August samples, respectively. Among the 30 kimbab samples obtained 83.3% samples were contaminated and 16.7% samples were free from contamination. The highest rate of contamination was with S. aureus (56.7%) followed by B. cereus (43.3%), Salmonella spp. (36.7%), Shigella spp. (13.3%), and L. monocytogenes (6.7%). The identification of the pathogenic species could be faster using one polymerase chain reaction (PCR) and the ability to test for food-borne pathogenic species in kimbab will save time and increase the ability to assure its quality.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.75-84
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• 2021

As the weather changes become frequent, weather disasters are increasing, causing more damage to plastic greenhouses. Among the damage caused by various disasters, damage by snow to the greenhouse takes a relatively long time, so if an alarm system is properly prepared, the damage can be reduced. Existing greenhouse design standards and snow warning systems are based on snow depth. However, even in the same depth, the load on the greenhouse varies depending on meteorological characteristics and snow density. Therefore, this study aims to secure the structural safety of greenhouses by developing sensors that can directly measure snow loads, and analysing the warning criteria for load using a stochastic model. Markov chain was applied to estimate the failure probability of various types of greenhouses in various regions, which let users actively cope with heavy snowfall by selecting an appropriate time to respond. Although it was hard to predict the precise snow depth or amounts, it could successfully assess the risk of structures by directly detecting the snow load using the developed sensor.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.17-24
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• 2022

Lora, a non-band network technology of the long-distance wireless standard LPWAN standard, uses ABP and OTTA methods and AES-128-based encryption algorithm (shared key) for internal terminal authentication and integrity verification. Lora's recent firmware tampering vulnerability and shared-key encryption algorithm structure make it difficult to defend against MITM attacks. In this study, the consensus algorithm(PBFT) is applied to the Lora network to enhance safety. It performs authentication and PBFT block chain creation by searching for node groups using the GPS module. As a result of the performance analysis, we established a new Lora trust network and proved that the latency of the consensus algorithm was improved. This study is a 4th industry convergence study and is intended to help improve the security technology of Lora devices in the future.

• Journal of Electrochemical Science and Technology
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• v.14 no.2
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• pp.152-161
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• 2023

Vanadium redox flow batteries (VRFBs) have been considered one of promising power sources for large scale energy storage systems (ESS) because of their excellent cycle performance and good safety. However, VRFBs still have a few challenging issues, such as poor Coulombic efficiency due to vanadium crossover between catholyte and anolyte, although recent efforts have shown promise in electrochemical performance. Herein, the vanadium complexes with various glyme ligands have been examined as active materials to suppress vanadium crossover between catholyte and anolyte, thus improving the Coulombic efficiency of VRFBs. The conventional Nafion membrane has a channel size of ca. 10 Å, whereas vanadium cation species are small compared to the Nafion membrane channel. For this reason, vanadium cations can permeate through the Nafion membrane, resulting in significant vanadium crossover during cycling, although the Nafion membrane is a kind of ion-selective membrane. In this regard, various glyme additives, such as 1,2-dimethoxyethane (monoglyme), diethylene glycol dimethyl ether (diglyme), and tetraethylene glycol dimethyl ether (tetraglyme) have been examined as complexing agents for vanadium cations to increase the size of vanadium-ligand complexes in electrolytes. Since the size of vanadium-glyme complexes is proportional to the chain length of glymes, the vanadium permeability of the Nafion membrane decreases with increasing the chain length of glymes. As a result, the vanadium complexes with tetraglyme shows the excellent electrochemical performance of VRFBs, such as stable capacity retention (90.4% after 100 cycles) and high Coulombic efficiency (98.2% over 100 cycles).