Based on the previous reports that majority of teachers have negative perceptions on food additives, a teacher training program called 'Let's teach food additives correctly' was developed and applied to improve teachers' unbalanced perception on food additives and let them teach students with sound scientific background. The 15-hours training program consisted of understanding of food safety and food additives, education materials on food additives, development of teaching-learning plan, meeting with professionals from Ministry of Food and Drug Safety (MFDS), visiting MFDS labs, application to school class, and evaluation. A total of 63 teachers participated in the training through 2 sessions conducted in August 2016. As a result, teachers showed high satisfaction rates (4.2~4.5 in 5.0-Likert scale) and 91.5% answered the training helpful for the school class. Although their initial intention to participate the training was to know the details of negative intake effects of food additives, their such perception was totally changed in addition, they suggested a continuous training for teachers and immediate correction of incorrect information in school textbooks. Also, post-training education for 1,172 students by these teachers appeared to improve the understanding of and the native perceptions on food additives significantly (p < 0.001). Above results showed that the training program could solve the problem of transmitting unbalanced information on food additives to students by training teachers, and such channel could be used to facilitate food-related risk communication.
Journal of the Institute of Electronics and Information Engineers
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v.53
no.3
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pp.114-123
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2016
The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.
Journal of the Korean BIBLIA Society for library and Information Science
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v.21
no.3
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pp.17-27
/
2010
This study aimed to identify the problems of college students in reading the literature and on the basis of the identified problems, to suggest the approaches to solve the problems. To this end, time required for reading passages, reading patterns, understanding, memory and reading habits and attitudes were analyzed with the freshmen in A university. In accordance with the analysis results, 58% of subjects was good and 42% was not sufficient on the basis of the averages in Scholastic Aptitude Test. Second, 77% of subjects had the good patterns but 23% showed certain problems in reading patterns. Third, 69% and 67% of subjects illustrated good results in the analysis on understanding and memory, respectively. However, 31% and 33% were evaluated as being on the general level or requiring efforts in the analysis on understanding and memory, respectively. Next, according to the analysis on reading habits and attitudes, 77% had no problems but 23% required improvement. For solving the problems identified through the analysis, it is recommended to develop the scientific and standardized evaluation tools for evaluating the reading ability of college students. Second, it is necessary to evaluate the reading ability, habit and attitude during the screening process for admission or after admission. Finally, it is required to operate the Fundamental Academic Ability Learning Center(tentative name) to improve the ability of students who show the insufficient results in evaluation.
This study was performed to investigate the effect of essential oils and ethanolic extracts of approximately 650 plant species on acetylcholine esterase (AChE) enzyme activity using Ellman's colorimetric method in 96-well microplates. The results showed that the ethanolic extracts from twig of Sophora subprostrata, twig of Phellodendron amurense, seed of Corylopsis coreana, and essential oil (EO) from Citrus paradisi, Cupressus sempervirens, Ocimum basilicum, Pinus sylvestris and Rosmarinus officinalis inhibited more than 80% of AChE activity. Among these, EO from Pinus sylvestris, C. sempervirens and C paradisi exhibited higher values of AChE inhibitory activity, which were 75, 84 and 99% at a concentration of 50 ug/ml, respectively. Finally, EO from C paradisi (grapefruit, GEO) showed the highest inhibitory activity towards AChE, which showed 91% of inhibition at a concentration of 20 ug/ml. We also examined the anti-dementia effects of GEO in mouse by passive avoidance test and Morris water maze test. The model mouse (male, ICR) of dementia (negative control) was induced by administration of scopolamine (1 mg/kg body weight). The latency time of sample group administrated with GEO (100 mg/kg, p.o.) increased significantly as compared with negative control on passive avoidance test. There were significant recovery from the scopolamine-induced deficits on learning and memory in water maze test through daily administrations with GEO (100 mg/kg, p.o.). From these results, we conclude that GEO treatment might enhance the cognitive function, suggesting that the EO of C. paradis may be a potential candidate for improvement of perceptive ability and dementia.
Objectives: The aim of this study was to explore perceived meanings of dating and marriage among well-educated Korean couples who were in optimal marriageable ages. Particularly, an emphasis was placed on finding out where the traditional gender norms and post-modern contexts intersect on the couples' course of dating and marriage. Method: We undertook a qualitative analysis of 8 couples (age: 26-34) dating. Participants were limited to university graduates of upper-middle rank universities in Seoul, South Korea. The rationale for choosing such sample was based on the idea that characteristics of class is inherent in the act of dating and marriage, and that such characteristics lead to different contextual experiences in dating and marriage. This study was based on interviews conducted over a three-month time span. The interviews were first transcribed into research text and then subjects and key categories were drawn from the transcripts for analysis. Results: Participants sought meanings of joy, learning, and self-improvement in dating, and they were free from traditional gender norms in their romantic relationships. They viewed marriage as having a permanent companionship with their partner, becoming independent from their parents, and/or a social norm to be followed. Participants reported mixed perceptions about marriage in such fashion that they described their parents' relationship in terms of a gendered leader-supporter relationship, while viewing their own relationship as being genderless partners. In transition to parenthood, however, they regressed to traditional gender norms dichotomized as women being a homemaker and men being a breadwinner. In sum, participants displayed expectations that were inconsistent with regard to dating and marriage over the study period. That is, during the course of dating and early marriage, they did not hold separated gender norms; however, when transitioning from being a newly married couple to giving their first childbirth, expectations shifted to traditional gender norms and values. Conclusion: This suggests that it is not marriage, but the experience of childbirth and motherhood, which strengthen traditional gendered norms, engendering regeneration of the gender norms in families. The results indicate that there is a need to promote co-parenting behavior among the newly-married couples and to educate gender equality about parent roles or for parents in South Korea so that they can overcome traditional gendered norms in family.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.29
no.3
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pp.298-309
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2019
Objectives: This study aimed to investigate stages of safety and health culture change through a reflection on 40 years of hearing conservation history at a multinational company. Methods: The target workplaces were multinational companies with more than 1,000 employees. The research used the clinical case study and system analysis methods based on direct observation of the research from 1994 to 2009. The latter method performed an analysis of the equilibrium state of the cross-section in the given period and the longitudinal profile of the change during the given period. Results: The stages of cultural change are divided into five stages and summarized as follows. In the first stage, workplace noise was not widely recognized as a hazard, while in the second stage, the measurement of noise levels and audiometric testing were conducted under the Korean Occupational Safety and Health Act (KOSHA). The driving force for change in the second stage was the amendment of the KOSHA. In the third stage, noise came to be recognized as a hazard factor through awareness training. The driving force of change during the third stage was the strong executive power exerted by the audit of the industrial hygiene program from the US head office. In the fourth step, there was a change to actually reduce noise. The driving force in this stage was a change in company executives' risk perception resulting from lawsuits over noise-induced hearing loss and the task force team activities for culture change based on the action learning protocol. At the fifth stage, a 'buy quiet policy' was institutionalized. The management's experience that noise reduction was difficult was the motivation to manage noise from the time of purchase of equipment. Conclusions: The activities of a hearing conservation program are determined by the improvement of the legal system and by the way it is enforced. Noise control activities to reduce noise areas may be possible through the shared risk perception of noise-induced hearing loss and by a change agent role as a facilitator to implement noise control.
Proceedings of the Korea Water Resources Association Conference
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2019.05a
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pp.164-175
/
2019
The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.
Journal of the Korea Society of Computer and Information
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v.25
no.4
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pp.165-172
/
2020
In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.
The purpose of this study was to propose a model which is suitable for the actual delivery system by designing a fetal delivery hospital operation management and fetal health classification model. The number of deaths during childbirth is similar to the number of maternal mortality rate of 295,000 as of 2017. Among those numbers, 94% of deaths are preventable in most cases. Therefore, in this paper, we proposed a model that predicts the health condition of the fetus using data like heart rate of fetuses, fetal movements, uterine contractions, etc. that are extracted from the Cardiotocograms(CTG) test using a random forest. If the redundancy of the data is unbalanced, This proposed model guarantees a stable management of the fetal delivery health management system. To secure the accuracy of the fetal delivery health management system, we remove the outlier which embedded in the system, by setting thresholds for the upper and lower standard deviations. In addition, as the proportion of the sequence class uses the health status of fetus, a small number of classes were replicated by data-resampling to balance the classes. We had the 4~5% improvement and as the result we reached the accuracy of 97.75%. It is expected that the developed model will contribute to prevent death and effective fetal health management, also disease prevention by predicting and managing the fetus'deaths and diseases accurately in advance.
In this paper, we analyzed the misconceptions and errors incurred during factorization learning. We also examined whether online individualization classes had a positive effect on students' mathematical achievement. The experiment was conducted for 4 weeks (16 times in total) on middle school juniors in rural areas of Gyeonggi Province, where the influence of private extra education was small. In the class, the 'Google Classroom' was used as a LMS, the video lecture was uploaded to YouTube, and the teacher interacted with the students through "Zoom" and "Facetalk". In the online class situation, students' assignments and test answers were checked in real time through 'Google Classroom', and immediate feedback was provided to the experimental class group's students. However, for the control group students, feedback was provided only to those who desired. A total of 7 achievement evaluations were conducted in the order of pre-test, formative evaluation (5 times), and post-test to confirm the change in students' ability improvement and achievement. Through the formative evaluation analysis, it was possible to grasp the types of errors and misconceptions that occured during the factorization process. Students' errors were divided into four types: theorem or definition distortion error, functional errors such as calculation, operation, and manipulation, errors that do not verify the solution, and no response. As a result of ANCOVA, the two groups did not show any difference from the 1st to 4th formative assessment. However, the 5th formative assessment and post-test showed statistically significant differences, confirming that online individualization classes contributed to improvemed achievement.
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