• Nutrition Research and Practice
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• v.16 no.6
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• pp.801-812
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• 2022

BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• Journal of the Korean earth science society
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• v.35 no.3
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• pp.203-212
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• 2014

It is important to explore ways that reinforce teachers' curricular expertise at the school level as the school curriculum autonomy expands. This study investigated teachers' curricular expertise that is required for teachers' professionalism, autonomy, and accountability to cope with the increasing school curriculum autonomy. Teachers in the future school are expected to explore and develop school level curriculum within a given school context. Through literature reviews, domestic and foreign case studies, and survey of teachers, this study examined difficulties in science teachers' exercise of their professionalism on curriculum organization and implementation at the school level. Difficulties in exercising teachers' curricular expertise include lack of actual autonomy in curriculum operation at the school level, inadequate infrastructures, demanding accountability based on students' achievement results, lack of time for reflection, and lack of recognition for teachers as independent curriculum designers. In the conclusion section, a couple of ways to solve these difficulties are suggested including expansion of actual autonomy, activation of teachers' participation in policy decision making, reinforcement of qualitative components in school assessment, diversification of the teacher's career ladder, and activation of teachers' participation in professional learning communities.

• Molecules and Cells
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• v.43 no.4
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• pp.360-372
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• 2020

The basal ganglia network has been implicated in the control of adaptive behavior, possibly by integrating motor learning and motivational processes. Both positive and negative reinforcement appear to shape our behavioral adaptation by modulating the function of the basal ganglia. Here, we examined a transgenic mouse line (G2CT) in which synaptic transmissions onto the medium spiny neurons (MSNs) of the basal ganglia are depressed. We found that the level of collaterals from direct pathway MSNs in the external segment of the globus pallidus (GPe) ('bridging collaterals') was decreased in these mice, and this was accompanied by behavioral inhibition under stress. Furthermore, additional manipulations that could further decrease or restore the level of the bridging collaterals resulted in an increase in behavioral inhibition or active behavior in the G2CT mice, respectively. Collectively, our data indicate that the striatum of the basal ganglia network integrates negative emotions and controls appropriate coping responses in which the bridging collateral connections in the GPe play a critical regulatory role.

• Cross-Cultural Studies
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• v.35
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• pp.315-338
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• 2014

The purpose of this study is to propose actual operation condition of Japanese lecture based on social welfare organizations located in Seoul to investigate the current status and problems of Japanese language education in terms of lifelong education. According to the result of this study, the remarkable point was that a majority of Japanese lecture courses are highly focused on the elderly and 86% of the welfare organizations are providing free education. Regarding the effect of specialized business for the aged run by social welfare community center, it says, as Korea changing to aging society at the beginning of 21st century, it has put focus on strengthening personal competences of seniors through opportunities for participation in lifelong education, recreational activity programs and culture classes. It means foreign language classes are operating as one of the lifelong education programs for reinforcement of individual capability. Considering this tendency, it is expected that the lifelong education participation rate of the elder in Seoul will be raised. So, systematic improvements will be needed for this. First, it is required to recognize the existence of Educational and Cultural Industry and work hard to make it public so it could be invigorated and utilized by people usefully at the same time. Second, Japanese language training that mostly 55-year-old or more than 60-year-old people receive at the welfare center needs to be systematized for preparations on proper studying environment which provides the older with appropriate education method and content as well. Third, stable and systematic operation should be available through the link with experts in the field of Japanese language education and elderly education. Fourth, education program development is needed, which is able to satisfy one's desires for learning. Hence, targeting Japanese learners at each welfare center, we need to know the estimation of satisfaction degree and consciousness on learning Japanese. Finally, it has not been studied sufficiently regarding the instructors on teaching Japanese language in this paper, but it has been reported that most of social welfare centers, where Japanese language lectures are provided, are run by volunteers who can teach Japanese. Thus, the study on actual condition for Japanese language instructors will be conducted as well later on.

• Tunnel and Underground Space
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• v.13 no.1
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• pp.6-19
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• 2003

This study has for its object to increase an objectivity of the observation result in the face mapping of tunnel and to suggest the reasonable support and reinforcement methods to be considered the rock properties. It was developed in this study to the tunnel stability evaluation system(Prototype NFEST) to be used fuzzy set theory and neuro-fuzzy techniques, and this system was verified according to the reliability evaluation between the 36 learning data and the inferred results. When it summarized the results; (1) 12 evaluation items and ranges were proposed to be modified basis on the RMR which are well known to the domestic workers. (2) It was shown that correlation coefficient(│R│) between $RMR_{inf}$ inferred by 12 items and $RMR_{org}$ due to arithmetic total, $RMR_{chk}$ due to subjective judgement of observer are relatively high relationship with each 0.83 and 0.79. (3) Inferred result of the total tunnel safety shows also a good relationship with $RMR_{inf}$ (│R│=0.7) and the rock weathering(│R│=0.84).

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.601-613
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• 2016

The purpose of this study is to present the mental model of young adolescents' media environment and the use and to provide several educational suggestions drawing on the revealed model. For this, the data were collected through 4 activities such as interview, picture drawings, word association experiment, and sentence completion task with ten 4-5th graders in elementary schools; they were qualitatively analyzed by 2 researchers. First, the meaning components driven by sentence completion task, word association experiment were totally 6 components: media device, connection(alienation), competence(provision), entertainment, adverse effects, ambilaterality. Second, the components of media mental model driven by pictures were 4 components: functions/competence, entertainment, conflict with paper books/sharing, harmfulness/ambilaterality. Third, the components from interview consisted of conflict between paper books and electronic media, communication-centeredness, fear(addiction) and users' qualification. Based on those results, careful examination in cyber talk, necessity of addiction prevention, active development of learning media and their balanced utilization with books, and healthful media literacy education and reinforcement of critical thinking were suggested.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09b
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• pp.21-31
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• 2010

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to get it practically on considering various geography and geotechnical condition. So construction management of information concept is required to manage immediately on the field condition because it is very time-consuming to establish the countermeasure of underground reinforcement and the pattern change of Bo. Therefore, when construction is on tunnel area, examination of accurate safety and prediction of behavior is performed to overcomes the limit of predicting behavior by using Artificial Neural Network(ANN) in this study. Firstly, the field data was secured. Secondly, suitable structure was made on multi-layer perceptrons among the ANN. Thirdly, learning algorithm-propagated applies to ANN. The data for the learn of field application using ANN was used by considering impact factors, which influenced the behavior of tunnel, and performing credibility analysis. crown displacement, spring displacement, subsurfacement, and rock bolt axial force are predicted at the tunnel construction and on-site application was confirmed by using ANN from analyzing and comparing with measurement value of on-site. In this study, the data from Seoul Highway $\bigcirc\bigcirc$ tunnel section was applied to the ANN Theory, and the analysis on the investigate value and the reasoning for the value associated with field application was performed.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.70-75
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• 2022

With the spread of various digital devices, devices have become commonplace in modern society. Moreover, due to the increase in device usage and online learning while staying indoors during the COVID-19 pandemic, symptoms such as an increase in myopia in children due to eye fatigue, an increase in young presbyopia, and dry eye syndrome are increasing, and now people are paying attention to eye health. This is different from before. There are various prescriptions for eye health, but in this paper, we would like to propose a training method for enhancing visual function using VR contents. The analog methods of the existing teaching aids for visual function reinforcement training were planned and produced as digital contents, and VR-based training contents were selected from among the various methods carried out with teaching aids at the visual function training center, which can be made into contents. was developed with In the training process for each content, it was proposed to apply eye tracking to the VR device in order to give the user feedback on their participation in the training so that the management and concentration of the training process could be analyzed.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.154-159
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• 2015

Over the past few years, user needs in the smartphone application market have been shifted from diversity toward intelligence. Here, we propose a novel cognitive agent that plans the daily routines of users using the lifelog data collected by the smart phones of individuals. The proposed method first employs DPGMM (Dirichlet Process Gaussian Mixture Model) to automatically extract the users' POI (Point of Interest) from the lifelog data. After extraction, the POI and other meaningful features such as GPS, the user's activity label extracted from the log data is then used to learn the patterns of the user's daily routine by POMDP (Partially Observable Markov Decision Process). To determine the significant patterns within the user's time dependent patterns, collaboration was made with the SNS application Foursquare to record the locations visited by the user and the activities that the user had performed. The method was evaluated by predicting the daily routine of seven users with 3300 feedback data. Experimental results showed that daily routine scheduling can be established after seven days of lifelogged data and feedback data have been collected, demonstrating the potential of the new method of place-time-activity coupled daily routine planning systems in the intelligence application market.