• Journal of IKEEE
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• v.23 no.2
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• pp.727-734
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• 2019

This paper confirms whether the movement or specific operation of the muscles in the process of transferring a person from the brain can find a signal showing an essential feature of a certain part of the brain. As a rule, the occurrence of EEG(Electroencephalogram) changes when a signal is received from a specific action or from an induced action. These signals are very vague and difficult to distinguish from the naked eye. Therefore, it is necessary to define a signal for analysis before classification. The EEG form can be divided into the alpha, beta, delta, theta and gamma regions in the frequency ranges. The specific size of these signals does not reflect the exact behavior or intention, since the band or energy difference of the activated frequencies varies depending on the EEG measurement domain. However, if different actions are performed in a specific method, it is possible to classify the movement based on EEG activity and to determine the EEG tendency affecting the movement. Therefore, in this article, we first study the EEG expression pattern based on the activation of the left and right biceps EMG, and then we determine whether there is a significant difference between the EEG due to the activation of the left and right muscles through EEG. If we can find the EEG classification criteria in accordance with the EMG activation, it can help to understand the form of the transmitted signal in the process of transmitting signals from the brain to each muscle. In addition, we can use a lot of unknown EEG information through more complex types of brain signal generation in the future.

• Korean Journal of Applied Biomechanics
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• v.29 no.3
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• pp.157-166
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• 2019

Objective: This study examined the effects of stimulating fingertip temperature on the patterns of force sharing and stability properties during multi-finger force production tasks. Method: 9 adult subjects (male: 3, female: 6, age: $26.11{\pm}4.01yrs$, height: $169.22{\pm}5.97cm$, weight: $61.44{\pm}11.27kg$) participated in this study. The experiment consisted of three blocks: 1) maximal voluntary contraction (MVC) task, 2) single-finger ramp task to quantify enslaving (i.e., unintended force production by non-task fingers), and 3) 12 trials of multi-finger steady-state force production task at 20% MVC. There were three temperature conditions including body-temperature (i.e., control condition), $40^{\circ}C$, and $43^{\circ}C$, and the stimulation was given to the index finger only for all experimental conditions. Results: There were no significant differences in the MVC forces, enslaving, and the accuracy of performance during the steady-state task between the conditions. However, the share of stimulated index finger force increased with the index fingertip temperature, while the share of middle finger force decreased. Also, the coefficient of variation of both index and middle finger forces over repetitive trials increased with the index fingertip temperature. Under the framework of the uncontrolled manifold (UCM) hypothesis used to quantify indices of multi-finger synergies (i.e., stability property) stabilizing total force during the steady-state task, the two variance components within the UCM analysis increased together with the fingertip temperature, while no changes in the synergy indices between the conditions. Conclusion: The current results showed that fingertip temperature stimulation only to index finger does not affect to muscle force production capability of multi-finger, independence of individual fingers, and force production accuracy by the involvement of all four fingers. The effect of fingertip temperature on the sharing pattern and force variation may be due to diffuse reflex effects of the induced afferent activity on alpha-motoneuronal pools. However, the unchanged stability properties may be the reflection of the active error compensation strategies by non-stimulated finger actions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.575-584
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• 2021

The critical low temperature and response of the behavioral tolerance of red sea bream Pagrus major fingerlings were determined using the continuous behavior monitoring system (CBMS). The behavior of the experimental organisms was observed by decreasing the water temperature by 2.0℃ and 4.0℃ every 12 hours and 24 hours in the range of 8.0-20.0℃. An unstable behavior pattern was observed in red seabream fingerlings exposed to water temperatures below 12.0℃, in which the swimming activity decreased and repeatedly stopped, regardless of the exposure time and water temperature fluctuation. The swimming ability of the organisms exposed to 8.0-10.0℃ decreased sharply, and the behavior of staying at the bottom of the test tank was observed. Only 50 % of the organisms survived due to the low-temperature stress, and all individuals died within six hours after the cold shock. In addition, the behavior index (BI) decreased rapidly, and the amplitude change of the coefficient of variation (CV) was found to have a greater variation than the other water temperatures (p<0.05). Low-temperature stress of red sea bream is promoted at 12.0℃, and it is interpreted as the tolerance limit, which can induce a sublethal response of the organisms exposed to cold shock of 8.0-10.0℃.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.515-520
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• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.59-65
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• 2022

Background: Since people move through microenvironments rather than staying in one place, they may be exposed to both indoor and outdoor PM_2.5 concentrations. Objectives: The aim of this study was to assess the exposure level of each sub-population group and evaluate the contribution rate of the major microenvironments. Methods: Exposure scenarios for sub-population groups were constructed on the basis of a 2019 Time-Use survey and the previous literature. A total of five population groups were classified and researchers wearing MicroPEM simulated monitoring PM_2.5 exposure concentrations in real-time over three days. The exposure contribution for each microenvironment were evaluated by multiplying the inhalation rate and the PM_2.5 exposure concentration levels. Results: Mean PM_2.5 concentrations were 33.0 ㎍/m³ and 22.5 ㎍/m³ in Guro-gu and Wonju, respectively. When the exposure was calculated considering each inhalation rate and concentration, the home showed the highest exposure contribution rate for PM_2.5. As for preschool children, it was 90.8% in Guro-gu, 94.1% in Wonju. For students it was 65.3% and 67.3%. For housewives it was 98.2% and 95.8%, and 59.5% and 91.7% for office workers. Both regions had higher exposure to PM_2.5 among the elderly compared to other populations, and their PM_2.5 exposure contribution rates were 98.3% and 94.1% at home for Guro-gu and Wonju, respectively. Conclusions: The exposure contribution rate could be dependent on time spent in microenvironments. Notably, the contribution rate of exposure to PM_2.5 at home was the highest because most people spend the longest time at home. Therefore, microenvironments such as home with a higher contribution rate of exposure to PM_2.5 could be managed to upgrade public health.

• Journal of Science Education
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• v.45 no.1
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• pp.23-41
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• 2021

This study is to investigate the characteristics of problem-finding and problem-solving abilities demonstrated by the secondary gifted students in the context of STEAM convergent problems. For this, using the STEAM convergence problem solving ability test, we qualitatively and quantitatively compared and analyzed the workbook outputs written in the process of finding and solving problems for each student in the gifted class. The results are as follows: First, we found that the speciality of the major of the proposed activity paper influenced the preference for questions and pattern of finding problems. Second, it was found that the difference in the ability to find and solve problems for a specific task was not by the major of the gifted class, but by the composition of the group. Third, in finding and solving the STEAM convergent problem, the individual creativity and the cooperative creativity of the group were more significant than the major. These results suggest that it is necessary to include the affective factors of gifted students and the concept of cooperation in problem-finding and problem-solving ability evaluation, and there is a need to develop a teaching and learning strategy that can improve cooperative problem-solving skills so that group creativity can be exhibited well.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.199-209
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• 2020

"Positive Influence(PI)" of popular star has recently emerged as a social concern, but the lack of prior research has led to confusion over its concept and range of activity. On this point, this study carried out to lay the groundwork for discussions on the systematization of related theories, focused on identifying the current situations by analyzing articles for 15 months from January 2019 to March 2020 when related reports were in full swing. As a result of the analysis of the remarks from the entertainers mentioned in the articles, they were not clearly aware of the concept while doing good deeds under the name of PI in light of the study outcome by Aegean and Singer(2013). The motivations for good deed were classified into six types, including difficulty empathy, fandom reward, participation urge, nidana emphasis, experience subjugation, and memory evocation in the order of frequency of cases. Specific behaviors of PI were followed by donations of money and valuables for 54.4 percent, participation of social agendas for 14.0 percent, volunteering for 13.2 percent, joining campaign for 11.4 percent, other good deeds for 4.0 percent, and philanthropy for 3.0 percent. In occupational analysis, the concentration of donations was also evident. Their activities in the fields of human rights sensitivity, environmental protection and self-management, which are expected to have great effects with their influence, have been extremely poor. The results of the study first require academia to establish a interdisciplinary concept for PI. It also suggests that entertainers and their agencies should take far more strategic approach to evolve the PI event in a way that utilizes the advantages of each job group, such as actors, singers and comedians, and expands the diversity of areas.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.39-48
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• 2022

The main purpose of the work is to analyze modern innovative educational practices in the field of culture and art and their effectiveness in the context of the spread of digitalization trends. The study used general scientific theoretical methods of analysis, synthesis, analogy, comparative, induction, deduction, reductionism, and a number of others, allowing you to fully understand the pattern of modern modernization processes in a long historical development and demonstrate how the rejection of the negativity of progress allows talented artists to realize their own potential. The study established the advantages and disadvantages of involving innovative technologies in the educational process on the example of European experience and outlined possible ways of implementing digitalization processes in Ukrainian institutions of higher education, formulated the main difficulties encountered by teachers and students in the use of technological innovation in the pandemic. The rapid development of digital technologies has had a great impact on the sphere of culture and art, both visual, scenic, and musical in all processes: creation, reproduction, perception, learning, etc. In the field of art education, there is a synthesis of creative practices with digital technologies. In terms of music education, these processes at the present stage are provided with digital tools of specially developed software (music programs for composition and typing of musical text, recording, and correction of sound, for quality listening to the whole work or its fragments) for training programs used in institutional education and non-institutional learning as a means of independent mastering of the theory and practice of music-making, as well as other programs and technical tools without which contemporary art cannot be imagined. In modern stage education, the involvement of video technologies, means of remote communication, allowing realtime adjustment of the educational process, is actualized. In the sphere of fine arts, there is a transformation of communicative forms of interaction between the teacher and students, which in the conditions of the pandemic are of two-way communication with the help of information and communication technologies. At this stage, there is an intensification of transformation processes in the educational industry in the areas of culture and art.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.222-235
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• 2022

The purpose of this study is to investigate the effect of emotional labor and job stress on patient safety management activities in emergency room nurse. Data were collected using self-report questionnaires from 143 nurses working in the emergency room of small and medium-sized hospitals. As factors influencing patient safety management activities, emotional labor, job stress, demographic characteristics, and work characteristics were investigated. Stepwise multiple regression analysis were used for factors affecting patient safety management activities. There were significant differences in patient safety management activities by age, experience in emergency room, position, work pattern, and intention to move to another department. In the regression analysis, the factors that had a significant effect on patient safety management activities were job stress and choice to work in the emergency room, and the explanatory power of these variables was 27%. It was found that the higher the job stress, the lower the patient safety management activity. In conclusion, it is necessary to manage job stress arrange departments according to individual needs to improve patient safety management activities of nurses in the emergency room of small and medium-sized hospitals.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.39-48
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• 2022

Cyberattacks around the world continue to increase, and their damage extends beyond government facilities and affects civilians. These issues emphasized the importance of developing a system that can identify and detect cyber anomalies early. As above, in order to effectively identify cyber anomalies, several studies have been conducted to learn BGP (Border Gateway Protocol) data through a machine learning model and identify them as anomalies. However, BGP data is unbalanced data in which abnormal data is less than normal data. This causes the model to have a learning biased result, reducing the reliability of the result. In addition, there is a limit in that security personnel cannot recognize the cyber situation as a typical result of machine learning in an actual cyber situation. Therefore, in this paper, we investigate BGP (Border Gateway Protocol) that keeps network records around the world and solve the problem of unbalanced data by using SMOTE. After that, assuming a cyber range situation, an autoencoder classifies cyber anomalies and visualizes the classified data. By learning the pattern of normal data, the performance of classifying abnormal data with 92.4% accuracy was derived, and the auxiliary index also showed 90% performance, ensuring reliability of the results. In addition, it is expected to be able to effectively defend against cyber attacks because it is possible to effectively recognize the situation by visualizing the congested cyber space.