• Journal of dental hygiene science
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• v.8 no.4
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• pp.323-329
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• 2008

The purpose of this study was to compare the oral health education effect and the satisfaction about the method between SDL and CCI on elementary school students. Method: The subjects of this study were 233 elementary school students in fourth grade (male: 56%, female: 44%) who attended two different elementary schools in Wonju Gangwon-do. They are divided into two groups and instructed by different method of the oral health education, SDL (Self-Directed Learning) and CCI (Conventional Classroom Instruction). The survey was conducted three times, preeducation, just after the education and one week after education. Collected data were analyzed into Chi-square test, Independent t-test and Repeated measure ANOVA using SPSS 12.0 K program. Result: 1. Changes of oral health knowledge: After the education, the average score of the oral health knowledge went up significantly in both groups. 2. Changes of oral health behavior: After the education, the average score of the oral health behavior rose up significantly in both groups and especially just after education, SDL group was recorded higher average score than CCI group. 3. Satisfaction: In both groups, the satisfaction rates about the education method were high (SDL: 88.9%, CCI: 99.1%). The main reason of satisfaction in SDL group was that the students were interested in the method of the education and the main reason of dissatisfaction was that they could not ask a question to the educator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.295-302
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• 2019

This study was conducted to investigate the effects of adolescent health behavior on obesity using an online health behavior survey. The subjects of this study were 12,090 middle school students and 14,248 high school students among 26,338 Korean youths that responded to an online survey of youth health behaviors in 2018 (14th). There were significant differences in lifestyle, mental factors, exercise habits, and sitting habits as health behavior factors. The risk of obesity was higher in smokers (p<0.001), drinkers (p<0.001), those who ate breakfast less than four times a week (p<0.001), those who consumed fruit less than four times a week (p<0.001) and those who ate fast food less than two times a week (p<0.001). The obesity rate was higher in people with high-stress (p<0.05). Exercise habit as a factor was higher in the obesity rate than in physical activity by three times as much (p<0.001), whereas students categorized as muscular (p<0.01) had one to two times more physical activity (p<0.001). Students who had less than six hours of learning purpose were found to have higher obesity rates than those with more than six hours of learning purpose (p<0.001). In conclusion, the obesity rate did not increase with prolonged sitting habits, but did increase with longer sitting time except for those who studied purpose folly. Therefore, it is necessary to have a set time for internet use, as well as to educate schools about proper lifestyle, and to promote healthy exercise habits.

• Economic and Environmental Geology
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• v.52 no.2
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• pp.199-212
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• 2019

In the machine learning techniques, the sampling strategy of the training data affects a performance of the prediction model such as generalizing ability as well as prediction accuracy. Especially, in landslide susceptibility analysis, the data sampling procedure is the essential step for setting the training data because the number of non-landslide points is much bigger than the number of landslide points. However, the previous researches did not consider the various sampling methods for the training data. That is, the previous studies selected the training data randomly. Therefore, in this study the authors proposed several different sampling methods and assessed the effect of the sampling strategies of the training data in landslide susceptibility analysis. For that, total six different scenarios were set up based on the sampling strategies of landslide points and non-landslide points. Then Random Forest technique was trained on the basis of six different scenarios and the attribute importance for each input variable was evaluated. Subsequently, the landslide susceptibility maps were produced using the input variables and their attribute importances. In the analysis results, the AUC values of the landslide susceptibility maps, obtained from six different sampling strategies, showed high prediction rates, ranges from 70 % to 80 %. It means that the Random Forest technique shows appropriate predictive performance and the attribute importance for the input variables obtained from Random Forest can be used as the weight of landslide conditioning factors in the susceptibility analysis. In addition, the analysis results obtained using specific sampling strategies for training data show higher prediction accuracy than the analysis results using the previous random sampling method.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.299-308
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• 2023

As the spectrum shortage problem has accelerated by the emergence of various services, New Radio-Unlicensed (NR-U) has appeared, allowing users who communicated in licensed bands to communicate in unlicensed bands. However, NR-U network users reduce the performance of Wi-Fi network users who communicate in the same unlicensed band. In this paper, we aim to simultaneously maximize the fairness and throughput of the unlicensed band, where the NR-U network users and the WiFi network users coexist. First, we propose an optimal power allocation scheme based on Monte Carlo Policy Gradient of reinforcement learning to maximize the sum of rates of NR-U networks utilizing rate-splitting multiple access in unlicensed bands. Then, we propose a channel occupancy time division algorithm based on sequential Raiffa bargaining solution of game theory that can simultaneously maximize system throughput and fairness for the coexistence of NR-U and WiFi networks in the same unlicensed band. Simulation results show that the rate splitting multiple access shows better performance than the conventional multiple access technology by comparing the sum-rate when the result value is finally converged under the same transmission power. In addition, we compare the data transfer amount and fairness of NR-U network users, WiFi network users, and total system, and prove that the channel occupancy time division algorithm based on sequential Raiffa bargaining solution of this paper satisfies throughput and fairness at the same time than other algorithms.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.38.2-38.2
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• 2010

Biomimetc is a new domain of learning that proposes a solution getting clues from nature. There seems to be a sign of this phenomenon in fields of Renewable Energy. Foe example, Wind power was imitate the whale's fin that was improve efficiency of generating energy. This study focused on the photovoltaic generation as the instance of applying biomimetic. Efficiency is the most important factor in field of Photovoltaic generation. When given solar cell taking the sun light, most important fields of the study are absorb more light and increase the quantity of generation. For improving efficiency, the solar cell were builded up textures of taking a pyramid form, such a surface structure taking a role for remaining the light. This effects do the role as increasing absorbing efficiency. Such phenomenon calls Light Trapping, locking up the light on the surface of solar cell for a long time. Light is a vital factor to plants in the nature. Plants grow up through the photosynthesis that absorbing light for growth and propagation. So, plants make a effort how can absorb more the light in poor surroundings. This study set up a goal that imitates the minute surface structure of plants and applies to the existing solar cells's surface structure, so it can improve the efficiency of absorbing light. We used Light Tools software analyzing geometrical optics to analyze efficiency about new designed textures on the computer. We made a comparison between existing textures and new designed textures. Consequently, new designed textures were advanced efficiency, absorbing rates of light increasing about 7 percent. In comparison with existing and new textures, advancing about 20 percent in the efficient aspect.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.176-183
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• 1998

A new recognition technique using neural network coupled with Genetic Algorithms (GAs) was proposed. This technique concentrate on efficient Electromyography signal recognition through out improving neural network's several demerits. GAs paly a role of selecting Multilayer Perceptron's optimized initial connection weights by its typical global search. Electro Myography signal was pre-processed with Hidden Markov Model (HMM) in order to refect its time-varying property into input pattern except other features such as Zero Crossing Number(ZCN) and Integral Absolute Value (IAV). Results for 6 primitive motions show that the suggested technique has better performance in learning time and recognition rates than already established ordinary methods. Moreover, it performed stable recognition without convergence into a local minimum.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.130-134
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• 2008

Touch screen phone which is expected to play a big part of the mobile market for the next few years, has many merits but demerits of inaccurate feedback. It offers audio and tactile feedback to strengthen the weak point. This study aims to see if audio feedback and vibration feedback react upon each other under realistic conditions. We had a qualitative research in perception after using touch screen phone feedback. The result showed that with any feedback users were satisfied more than without any feedback and there was diversity in response. We ran the study again to see the performance level and the projective workload between the kind of feedback and interrupting feedback environment Performance rates were faster with audio feedback and according to the projective workload assessment users felt that task was easier and less annoying with audio-vibration feedback. The results suggest that audio feedback could be more effective than vibration feedback. A future study will figure out the relationship between the factors of qualitative-controlled feedback and learning time and the performance, and the main cause to make people prefer one feedback over another in a realistic world.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.337-340
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• 2004

The exactly reproduced prosody of a TTS system is one of the key factors that affect the naturalness of synthesized speech. In general, rules about prosody had been gathered either from linguistic knowledge or by analyzing the prosodic information from natural speech. But these could not be perfect and some of them could be incorrect. So we proposed artificial neural network(ANN)s that can be trained to team the prosody of natural speech and generate it. In learning phase, let ANNs learn the pitch and energy contour of center phoneme by applying a string of phonemes in a sentence to ANNs and comparing the output pattern with target pattern and making adjustment in weighting values to get the least mean square error between them. In test phase, the estimation rates were computed. We saw that ANNs could generate the prosody of a sentence.

• Korean Management Science Review
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• v.32 no.4
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• pp.155-173
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• 2015

Koreatech has adopted a long-term co-op program called IPP (Industry Professional Practice) to address problems in higher education of Korea since 2012, but it was anticipated to face many difficulties in implementing the program due to lack of relevant experiences in Korea. In this regard, a performance evaluation scheme was urgently required to judge the effectiveness of the Co-op program and improve the operational efficiency at the same time. This study aimed to develop comprehensive performance evaluation criteria for the co-op programs on the basis of Kirkpatrick's four-level performance evaluation model for training programs, and apply it to a real Co-op operation to test its feasibility. For this purpose, thorough review on the training program evaluation literature and in-depth analyses of overseas cases of co-op performance evaluation were conducted. Then, a set of Co-op performance evaluation criteria was developed and applied to the Koreatech's Co-op operation in 2013. Two Co-op student questionnaire surveys were administered before and after Co-op terms to measure students' reactions to the Co-op program (Level 1) and changes in participating students' attitudes and competencies (Level 2). In addition, employment rates of Co-op participating and non-participating students were compared (Level 4). The analysis findings showed that participating students were quite satisfied with their jobs and companies, and the Co-op program was effective to a certain degree at enhancing non-major competencies and attitudes to occupation of students. Together, the employment rate of Co-op participants, particularly in small- and medium-sized companies, grew significantly in comparison with that of non-participants. In the last part, several directions for improving the effectiveness of the Co-op programs were discussed.