• Molecules and Cells
• /
• v.46 no.1
• /
• pp.41-47
• /
• 2023

The rapid development of mRNA vaccines has contributed to the management of the current coronavirus disease 2019 (COVID-19) pandemic, suggesting that this technology may be used to manage future outbreaks of infectious diseases. Because the antigens targeted by mRNA vaccines can be easily altered by simply changing the sequence present in the coding region of mRNA structures, it is more appropriate to develop vaccines, especially during rapidly developing outbreaks of infectious diseases. In addition to allowing rapid development, mRNA vaccines have great potential in inducing successful antigen-specific immunity by expressing target antigens in cells and simultaneously triggering immune responses. Indeed, the two COVID-19 mRNA vaccines approved by the U.S. Food and Drug Administration have shown significant efficacy in preventing infections. The ability of mRNAs to produce target proteins that are defective in specific diseases has enabled the development of options to treat intractable diseases. Clinical applications of mRNA vaccines/therapeutics require strategies to safely deliver the RNA molecules into targeted cells. The present review summarizes current knowledge about mRNA vaccines/ therapeutics, their clinical applications, and their delivery strategies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.6
• /
• pp.178-186
• /
• 2020

In the domain of Korean weapon system development, issues about software reliability have become crucial factors when developing a weapon system. There is a process required for weapon system software development and management that includes certain activities required to improve the reliability of software. However, these activities are biased toward static and dynamic analyses of source code and do not include activities necessarily required by the international standard. IEEE std. 1633-2016 defines a process for software reliability engineering and describes software reliability estimation as an essential activity in the process. Software reliability estimation means that collecting defective data during the test and estimating software reliability by using the statistical model. Based on the estimated model, developers could estimate the failure rate and make comparisons with the objective failure rate to determine termination of the test. In this study, we collected defective data and applied reliability estimation models to analyze software reliability in the development of a weapon system. To achieve objective software reliability, we continuously tested our software and quantitatively calculated software reliability. Through the research, we hope that efforts to include activities described by the international standard will be carried out in the domain of Korean weapon system development.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.125-140
• /
• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Smart Structures and Systems
• /
• v.21 no.5
• /
• pp.687-694
• /
• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• Information Systems Review
• /
• v.20 no.1
• /
• pp.61-80
• /
• 2018

Individuals often receive smishing campaigns (mobile phishing messages), which they treat as spam. Thus, firms should understand how their customers distinguish their promotion messages from smishing. However, only a few studies examined this important issue. The present study employs the elaboration likelihood model to develop research hypotheses on the relationship between message cue and message credibility. The message cue in this study is classified as content cue, which is found in the content of promotion messages, and as leakage cue, which is found in peripheral information in the message. Leakage cue includes orthography (inclusion of special characters)and an abbreviated link sent by a faithless sender. We also propose that contextualization has a moderating effect on the relationship between content cue and credibility. We conducted a survey experiment to examine the effect of message cues on message credibility in the context of respondents receiving discount coupons through mobile messages. The result of data analysis based on 166 responses suggests that leakage cue had a negative effect on message credibility. A message with defective content cue has a marginally negative effect on message credibility. In particular, defective content cue in a high-contextual message has a strong negative impact on message credibility. This effect was not observed in low-contextual messages. Moreover, message credibility is significantly low regardless of the degree of contextualization if there is a leakage cue in the message. Our findings suggest that mobile promotion messages should be customized for message receivers and should have no leakage cues.

• Journal of the Korea Organic Resources Recycling Association
• /
• v.28 no.2
• /
• pp.31-40
• /
• 2020

As private sewage treatment facilities in Korea are constantly concerned about the distribution and poor construction of defective products, minimum standards for each unit process applicable to the planning and design of sewage treatment facilities are deemed necessary. The problems and requirements of the analysis results of the operation status discussed in this study are as follows. 1) Strengthening education of supervisor of private sewage treatment facility. 2) Poor operation and management of Sewage treatment facilities. 3) A mandatory review of sewage treatment facilities for less than 2 ㎥/day of facilities other than sewage treatment zones. 4) Necessity of management of sewage treatment facility in feedstocks. 5) As a result of the technical review, Improvement plans for Ineligible facility are needed. It is also necessary to prepare a guidebook for design construction and maintenance by investigating and analyzing guidelines and data related to domestic and foreign private sewage treatment facilities.

• Korean Journal of Construction Engineering and Management
• /
• v.16 no.2
• /
• pp.21-28
• /
• 2015

Construction defects are major components that result in cost overruns and schedule delays in construction projects. There have been extensive research efforts to investigate the cause of defects. However, little effort has been devoted to analyze correlation among various reasons of construction defects while a defect is not usually an outcome of a single cause, but rather occurs when several interrelated causes combine. Based on this recognition, this paper analyzes 831 nonconformity reports collected from 30 construction projects in Korea from 2011 to 2014. The correlation analysis revealed that a significant portion of construction defects occurred in the procurement and construction phase and as the pattern of function defect and installation defect. Triggered by human error, defective material and faulty method, these defects are treated by conccession, repair, rework that can significantly lower the cost and schedule performance. This paper is significant in terms of providing a theoretical basis for analyzing correlation among various reasons of construction defects and quantitative measures for establishing effective defect prevention strategies.

• Korean Journal of Construction Engineering and Management
• /
• v.9 no.5
• /
• pp.214-226
• /
• 2008

Construction delay caused considerable losses to project parties. Avoiding construction delays is important to save costs for project stakeholders. The main objective of this paper is to identify major causes of construction delays of apartment construction projects in Vietnam. Sixteen causes of delay were identified through a questionnaire survey of 166 professionals. Factor analysis was employed to categorize these causes. The results of the survey revealed the main causes of delay of apartment projects in Vietnam are: (1) owner's and contractor'S financial difficulties; (2) lack of experienced contractors; (3) late delivery of materials; (4) late construction site handover; (5) owner's late payments for completed works; (6) low bid prices; (7) inappropriate construction method; and (8) defective works and unnecessary reworks. Factor analysis uncovered that causes of delay can be grouped under five categories labeled the five INs: incompetence, ineffectiveness, inadequateness, inapplicableness and inconceivableness. Comparative analysis between the Vietnam construction industry (VCI) and the Korea construction industry (KCI) has been performed to infer valuable lessons for researchers and practitioners in the VCI and the KCI. Comparative analysis indicated that main causes of delay in the VCI somewhat differ from main causes of delay in the KCI. However, "contractor'S financial difficulties", "late construction site handover", "unnecessary rework", "incapable designers", "site clearance difficulties" are common causes of delay in the VCI as well as the KCI. The findings of this research can be used as a guideline to overcome problems in the VCI as well as in other construction industries. Since Korea has emerged as the first largest foreign investor in Vietnam, the results of this study may be useful not only to practitioners and researchers in Vietnam but also to participants in Korea.

• Journal of the Korea Safety Management & Science
• /
• v.6 no.4
• /
• pp.61-81
• /
• 2004

What is the most important in articles of food is hygienic safety. Because food Is the most common thing in our everyday life, however, the importance of its hygienic safety and other many problems caused by food may be easily neglected. What is more, food is can be dangerous as much as it is directly related to human life and accidents from the same cause may have different effects on the victims according to physical and environmental differences of individuals. Thus PL action for food requires more thorough prevention and measure. Korea has been enforcing 'the Product Liability Act' since the 1/sup 1st/ of July 2002. Product Liability (PL) is liability of the manufacturer or the seller of a product to compensate for the death or injury of consumers or the loss of properties caused by the defect of the product. This study surveyed consumers' response to and the effects of the enforcement of the Product Liability Act, investigated how consumers perceived the importance of food safety and the risk of defective food based on PL standards and their experience in damage by food through a questionnaire survey, and analyzed collected data through empirical analyses (reliability analysis, factorial analysis, regression analysis and ANOVA t-test) using SPSS 10.0. Based on the results of analysis, the researcher proposed strategies for coping with the Product Liability Act in the food industry.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.2
• /
• pp.129-136
• /
• 2017

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.