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2022, Vol.27, No.8

  • 1.

    Applying a Novel Neuroscience Mining (NSM) Method to fNIRS Dataset for Predicting the Business Problem Solving Creativity: Emphasis on Combining CNN, BiLSTM, and Attention Network

    Kyu Sung Kim , Min Gyeong Kim , Kun Chang Lee | 2022, 27(8) | pp.1~7 | number of Cited : 0
    Abstract PDF
    With the development of artificial intelligence, efforts to incorporate neuroscience mining with AI have increased. Neuroscience mining, also known as NSM, expands on this concept by combining computational neuroscience and business analytics. Using fNIRS (functional near-infrared spectroscopy)-based experiment dataset, we have investigated the potential of NSM in the context of the BPSC (business problem-solving creativity) prediction. Although BPSC is regarded as an essential business differentiator and a difficult cognitive resource to imitate, measuring it is a challenging task. In the context of NSM, appropriate methods for assessing and predicting BPSC are still in their infancy. In this sense, we propose a novel NSM method that systematically combines CNN, BiLSTM, and attention network for the sake of enhancing the BPSC prediction performance significantly. We utilized a dataset containing over 150 thousand fNIRS-measured data points to evaluate the validity of our proposed NSM method. Empirical evidence demonstrates that the proposed NSM method reveals the most robust performance when compared to benchmarking methods.
  • 2.

    Development of a parking control system that improves the accuracy and reliability of vehicle entry and exit based on LIDAR sensing detection

    Jeong-In Park | 2022, 27(8) | pp.9~21 | number of Cited : 0
    Abstract PDF
    In this paper, we developed a 100% detection system for entering and leaving vehicles by improving the detection rate of existing detection cameras based on the LiDAR sensor, which is one of the core technologies of the 4th industrial revolution. Since the currently operating parking lot depends only on the recognition rate of the license plate number of about 98%, there are various problems such as inconsistency in the entry/exit count, inability to make a reservation in advance due to inaccurate information provision, and inconsistency in real-time parking information. Parking status information should be managed with 100% accuracy, and for this, we built a parking lot entrance/exit detection system using LIDAR. When a parking system is developed by applying the LIDAR sensor, which is mainly used to detect vehicles and objects in autonomous vehicles, it is possible to improve the accuracy of vehicle entry/exit information and the reliability of the entry/exit count with the detected sensing information. The resolution of LIDAR was guaranteed to be 100%, and it was possible to implement so that the sum of entering (+) and exiting (-) vehicles in the parking lot was 0. As a result of testing with 3,000 actual parking lot entrances and exits, the accuracy of entering and exiting parking vehicles was 100%.
  • 3.

    Prediction of Solar Photovoltaic Power Generation by Weather Using LSTM

    Saem-Mi Lee , Kyu-Cheol Cho | 2022, 27(8) | pp.23~30 | number of Cited : 0
    Abstract PDF
    Deep learning analyzes data to discover a series of rules and anticipates the future, helping us in various ways in our lives. For example, prediction of stock prices and agricultural prices. In this research, the results of solar photovoltaic power generation accompanied by weather are analyzed through deep learning in situations where the importance of solar energy use increases, and the amount of power generation is predicted. In this research, we propose a model using LSTM(Long Short Term Memory network) that stand out in time series data prediction. And we compare LSTM’s performance with CNN(Convolutional Neural Network), which is used to analyze various dimensions of data, including images, and CNN-LSTM, which combines the two models. The performance of the three models was compared by calculating the MSE, RMSE, R-Squared with the actual value of the solar photovoltaic power generation performance and the predicted value. As a result, it was found that the performance of the LSTM model was the best. Therefor, this research proposes predicting solar photovoltaic power generation using LSTM.
  • 4.

    A study on Deep Learning-based Stock Price Prediction using News Sentiment Analysis

    Doo-Won Kang , So-Yeop Yoo , Ha-Young Lee and 1 other persons | 2022, 27(8) | pp.31~39 | number of Cited : 0
    Abstract PDF
    Stock prices are influenced by a number of external factors, such as laws and trends, as well as number-based internal factors such as trading volume and closing prices. Since many factors affect stock prices, it is very difficult to accurately predict stock prices using only fragmentary stock data. In particular, since the value of a company is greatly affected by the perception of people who actually trade stocks, emotional information about a specific company is considered an important factor. In this paper, we propose a deep learning-based stock price prediction model using sentiment analysis with news data considering temporal characteristics. Stock and news data, two heterogeneous data with different characteristics, are integrated according to time scale and used as input to the model, and the effect of time scale and sentiment index on stock price prediction is finally compared and analyzed. Also, we verify that the accuracy of the proposed model is improved through comparative experiments with existing models.
  • 5.

    Text summarization of dialogue based on BERT

    Wongyung Nam , Jisoo Lee , BEAKCHEOL JANG | 2022, 27(8) | pp.41~47 | number of Cited : 0
    Abstract PDF
    In this paper, we propose how to implement text summaries for colloquial data that are not clearly organized. For this study, SAMSum data, which is colloquial data, was used, and the BERTSumExtAbs model proposed in the previous study of the automatic summary model was applied. More than 70% of the SAMSum dataset consists of conversations between two people, and the remaining 30% consists of conversations between three or more people. As a result, by applying the automatic text summarization model to colloquial data, a result of 42.43 or higher was derived in the ROUGE Score R-1. In addition, a high score of 45.81 was derived by fine-tuning the BERTSum model, which was previously proposed as a text summarization model. Through this study, the performance of colloquial generation summary has been proven, and it is hoped that the computer will understand human natural language as it is and be used as basic data to solve various tasks.
  • 6.

    Small CNN-RNN Engraft Model Study for Sequence Pattern Extraction in Protein Function Prediction Problems

    Jeung Min Lee , Hyun Lee | 2022, 27(8) | pp.49~59 | number of Cited : 0
    Abstract PDF
    In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.
  • 7.

    Pedestrian GPS Trajectory Prediction Deep Learning Model and Method

    Seung-Won Yoon , Won-Hee Lee , Kyu-Chul Lee | 2022, 27(8) | pp.61~68 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a system to predict the GPS trajectory of a pedestrian based on a deep learning model. Pedestrian trajectory prediction is a study that can prevent pedestrian danger and collision situations through notifications, and has an impact on business such as various marketing. In addition, it can be used not only for pedestrians but also for path prediction of unmanned transportation, which is receiving a lot of spotlight. Among various trajectory prediction methods, this paper is a study of trajectory prediction using GPS data. It is a deep learning model-based study that predicts the next route by learning the GPS trajectory of pedestrians, which is time series data. In this paper, we presented a data set construction method that allows the deep learning model to learn the GPS route of pedestrians, and proposes a trajectory prediction deep learning model that does not have large restrictions on the prediction range. The parameters suitable for the trajectory prediction deep learning model of this study are presented, and the model’s test performance are presented.
  • 8.

    Predicting lane speeds from link speeds by using neural networks

    Dong hyun Pyun , Changwoo Pyo | 2022, 27(8) | pp.69~75 | number of Cited : 0
    Abstract PDF
    In this paper, a method for predicting the speed for each lane from the link speed using an artificial neural network is presented to increase the accuracy of predicting the required time of a driving route. The time required for passing through a link is observed differently depending on the direction of going straight, turning right, or turning left at the intersection of the end of the link. Therefore, it is necessary to predict the speed according to the vehicle’s traveling direction. Data required for learning and verification were constructed by refining the data measured at the Gongpyeong intersection of Gukchaebosang-ro in Daegu Metropolitan City and four adjacent intersections around it. Five neural network models were used. In addition, error analysis of the prediction was performed to select a neural network experimentally suitable for the research purpose. Experimental results showed that the error in the estimation of the time required for each lane decreased by 17.4% for the straight lane, 4.4% for the right-turn lane, and 3.9% for the left-turn lane. This experiment is the result of analyzing only one link. If the entire pathway is tested, the effect is expected to be greater.
  • 9.

    Implementation of Air Pollutant Monitoring System using UAV with Automatic Navigation Flight

    Sang-Hoon Shin , Myeong-Chul Park | 2022, 27(8) | pp.77~84 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.
  • 10.

    A Study on Implementation of Motion Graphics Virtual Camera with AR Core

    Jin-Bum Jung , Jae-Soo Lee , Seung-hyun Lee | 2022, 27(8) | pp.85~90 | number of Cited : 0
    Abstract PDF
    In this study, to reduce the time and cost disadvantages of the traditional motion graphic production method in order to realize the movement of a virtual camera identical to that of the real camera, motion graphics virtualization using AR Core-based mobile device real-time tracking data A method for creating a camera is proposed. The proposed method is a method that simplifies the tracking operation in the video file stored after shooting, and simultaneously proceeds with shooting on an AR Core-based mobile device to determine whether or not tracking is successful in the shooting stage. As a result of the experiment, there was no difference in the motion graphic result image compared to the conventional method, but the time of 6 minutes and 10 seconds was consumed based on the 300frame image, whereas the proposed method has very high time efficiency because this step can be omitted. At a time when interest in image production using virtual augmented reality and various studies are underway, this study will be utilized in virtual camera creation and match moving.
  • 11.

    A Media Archaeological Analysis on the Origins of Korean Broadcasting

    Sangkil Yoon | 2022, 27(8) | pp.91~101 | number of Cited : 0
    Abstract PDF
    This study started with the awareness that the review of the historical origins of Korean broadcasting will be of great significance in exploring the future of Korean broadcasting, and examined the various "origins" of Korean broadcasting - colonial, Cold War, totalitarian, neoliberal. Based on the theoretical background of "media archaeology", the historical 'origin' of Korean broadcasting was applied to track the origin of Hallyu(the Korean Wave) in the 21st century by comprehensively examining the political and economic motives of the time, the state's situational awareness of problems, major broadcasting policies and broadcasting realities. As a result of the study, it came to the tentative conclusion that the historical origin of the Hallyu, which began to be formed in the 1980s, originated from the three origins of Korean broadcasting and the "synthetic mixture" in the subsequent development process.
  • 12.

    A study on cognition about long-take shot in films

    Yong-Whan Lee | 2022, 27(8) | pp.103~110 | number of Cited : 0
    Abstract PDF
    This study is a paper on the recognition of college students about the long-take shot technique which is often used to give a sense of reality and realism to films. 13 surveys were conducted on 92 students, including their perception of long-take films, their feelings after watching the film, satisfaction, and future prospects. Participants in the surveys consisted of 23 students in the health field, 16 students in the natural field, 41 students in the arts and sports field, and 13 students in the engineering field. As a result of the surveys, 68.8% of students answered “I know” about long-take film, and the feeling after watching the long-take film was found in the order of reality (realism) 68.8%, tension 16.1%, and boredom 15.1%. After watching the long-take film, 16.1% of students chose "Very satisfied" and 31.2% chose "Satisfied". Future prospects for long-take film showed high with 17.2% for "It will be developed very much" and 48.4% for "It will be developed". Preference for long-take film and general film was 67.7% for "long-take film" and 32.3% for "general film", showing high preference for long-take film. As a further research project, more in-depth surveys will be conducted targeting broadcasting & media contents majors in their 20s, and the long-take films used according to the story development process in domestic films will be analyzed.
  • 13.

    A Study on the Korea-U.S. Negotiation Process for AFKN-TV Color Broadcasting in 1977

    Sangkil Yoon | 2022, 27(8) | pp.111~121 | number of Cited : 0
    Abstract PDF
    The purpose of this study is to examine the historical facts about the negotiation process between Korea and the U.S. over the launch of AFKN-TV's color broadcasting in 1977, which can be evaluated as the first time that the government raised the issue of broadcasting sovereignty against the U.S. government. More specifically, through literature research on archive documents stored in the Korean National Archives and Diplomatic Archive of Korea National Diplomatic Academy, this study examined the arguments, perceptions, and actions of the two governments by dividing three phases of the negotiation process. As a result of the study, the negotiations with the U.S. government over the unilateral color broadcasting of AFKN-TV in early 1977 and the conflict between the two countries led to a new perspective of broadcasting sovereignty. The Korean government's commitment to broadcasting sovereignty targeted the U.S. government in the 1980s once again.
  • 14.

    NCS based Leveled Micro-Degree Certification Model for Training Practical Cyber Security Experts

    Jeong-Sham Kim , Kyu-Chang Lee , Sang-Yong Choi | 2022, 27(8) | pp.123~133 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a Leveled Micro-Degree Job Competency Certification Model that considers the level of the job based on the job defined in the NCS. There is a mismatch of manpower due to the problem of university education that cannot keep up with the rapidly changing technological environment caused by the 4th Industrial Revolution. The Nano-Degree and Micro-Degree systems designed to solve this problem are used for job competency certification of cyber security personnel. NCS sub-categorized job field is defined as Micro-Degree and detailed job by ability unit is defined as Nano-Degree, the level of the ability unit defined by level is equally applied to the Micro-Degree. And it is a system that certifies the job competency corresponding to the degree-based university academic background. By applying this system to the curriculum of Cyber Security School, Yeungnam University College, we proposed a method to configure the Nano-Degree course based on NCS duties. The method proposed in this paper can be used as a method for verifying job competency of Nano-Degree and Micro-Degree, which are recently introduced by many universities.
  • 15.

    Efficient Graph Construction and User Movement Path for Fast Inspection of Virus and Stable Management System

    Jong-Hyun Kim | 2022, 27(8) | pp.135~142 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a graph-based user route control for rapidly conducting virus inspections in emergency situations (eg, COVID-19) and a framework that can simulate this on a city map. A* and navigation mesh data structures, which are widely used pathfinding algorithms in virtual environments, are effective when applied to CS(Computer science) problems that control Agents in virtual environments because they guide only a fixed static movement path. However, it is not enough to solve the problem by applying it to the real COVID-19 environment. In particular, there are many situations to consider, such as the actual road traffic situation, the size of the hospital, the number of patients moved, and the patient processing time, rather than using only a short distance to receive a fast virus inspection.
  • 16.

    Patent Keyword Analysis using Gamma Regression Model and Visualization

    Sung-Hae Jun | 2022, 27(8) | pp.143~149 | number of Cited : 0
    Abstract PDF
    Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.
  • 17.

    Route matching delivery recommendation system using text similarity

    Jeongeun Song , Yoon-Ah Song | 2022, 27(8) | pp.151~160 | number of Cited : 0
    Abstract PDF
    In this paper, we propose an algorithm that enables near-field delivery at a faster and lowest cost to meet the growing demand for delivery services. The algorithm proposed in this study involves subway passengers (shipper) in logistics movement as delivery sources. At this time, the passenger may select a delivery logistics matching subway route. And from the perspective of the service user, it is possible to select a delivery man whose route matches . At this time, the delivery source recommendation is carried out in a text similarity measurement method that combines TF-IDF&N-gram and BERT. Therefore, unlike the existing delivery system, two-way selection is supported in a man-to-man method between consumers and delivery man. Both cost minimization and delivery period reduction can be guaranteed in that passengers on board are involved in logistics movement. In addition, since special skills are not required in terms of transportation, it is also meaningful in that it can provide opportunities for economic participation to workers whose job positions have been reduced.
  • 18.

    A Study on the Wearing Satisfaction of Men's Upper Body Correction Underwear

    Hyun-Sook Han | 2022, 27(8) | pp.161~168 | number of Cited : 0
    Abstract PDF
    In this study, a survey on the wearing satisfaction of commercial men's upper body correction underwear was conducted targeting mildly obese men in their twenties, and it was intended to suggest improvement points for the correction underwear. The product used for the study was Adapt's 95 PROBLEM, and 15 subjects were selected as males in their 20s with a BMI of 25-30 (mild obesity). As a result, men's awareness and interest in corrective underwear were low. In the wearing satisfaction survey, 74% of those who answered negatively that it was uncomfortable to wear and take off. In terms of pressure relief, 60% of those who felt the pressure was strong at the beginning, but as time passed, they got used to it and answered that there was no major inconvenience. However, with regard to digestion after a meal, 40% of the subjects felt that the pressure interfered with digestion. There were many deficiencies in terms of functionality, with more than half of those who responded negatively with regard to stuffiness and heat, and many negative opinions regarding sweat absorption and discharge. In the visual section, positive reaction was shown in chest, side waist and front waist correction, and among them, the front waist had the highest score. In conclusion, it seems that functional parts related to heat and sweat must be improved in consideration of the stuffiness and indigestion brought about by excessive pressure for men's upper body correction underwear.
  • 19.

    BSM framework using Event-Sourcing and CQRS pattern in V2X environment

    Sangkon Han , EunHee Goo , Jung-in Choi | 2022, 27(8) | pp.169~176 | number of Cited : 0
    Abstract PDF
    With the continuous development of technologies related to 5G, artificial intelligence, and autonomous vehicle systems, standards and services for V2X and C-ITS environments are being studied a lot. BSM (basic safety message) was adopted as a standard for exchanging data between vehicles based on data collected and generated by vehicle systems in a V2V environment. In this paper, we propose a framework that can safely store BSM messages and effectively check the stored messages using Event-Sourcing and CQRS patterns. The proposed framework can securely store and manage BSM messages using hash functions. And it has the advantage of being able to check the stored BSM data in real time based on the time series and to reproduce the state.
  • 20.

    A Study on the Analysis and Improvement of the Welfare Ordinance for the Elderly in Gwangju and Jeonnam

    Kyung-Sook Kim | 2022, 27(8) | pp.177~183 | number of Cited : 0
    Abstract PDF
    The purpose of this study is to examine the current status of the elderly welfare ordinances currently enacted and operated by local governments, analyze the actual conditions and problems of the contents, and suggest the direction of enactment and revision of the elderly welfare ordinances for actively responding to the demand for various welfare services for the elderly. To this end, the scope of the study was specified by ordinances in Gwangju Metropolitan City, five autonomous districts, Jeollanam-do, and 22 cities and counties, and the criteria for content analysis of the elderly welfare ordinance of these local governments were selected and compared and analyzed in the four major areas of elderly welfare: income and jobs, care, health, leisure activities, and social participation. According to the analysis results, the direction of enacting the ordinance is to secure financial resources for the elderly welfare budget, develop differentiated welfare policies for the elderly that reflect the characteristics of each local government, expand ordinances related to infectious diseases, enact ordinances for medical support for non-infectious diseases, and enact customized ordinances for the elderly living alone. Finally, the limitations on the research subject and analysis scope of this study and future research directions were presented.
  • 21.

    Effects of Long-distance Horseback Riding on Blood Lipid, Adipokine, Inflammatory Marker in Obese Middle Aged Women

    Jin-Wook Lee , PARK JONG HWA | 2022, 27(8) | pp.185~194 | number of Cited : 0
    Abstract PDF
    The purpose of this study was to verify the effects of long-distance horseback riding on blood lipid, adipokines and inflammatory markers in obese middle-aged women. The subjects of this study were 9 obese meddle aged women and the data analysed using the paired t-test. The result of this study were as follows: First, TC(p<.01), LDL-C(p<.01), and HDL-C(p<.001) were significantly increased after long-distance horseback riding(LDHR). Second, adiponectin was significantly increased(p<.01) and also PAI-1 was significantly decreased(p<.01) after LDHR. Third, IL-6 was significantly increased(p<.01) after LDHR. These results suggest that long-distance horseback riding has positive effect on changes blood lipid, adipokines, and inflammatory markers in obese middle-aged women. Therefore we consider that effects of long-distance horseback riding has partial examine on prevention and therapy of obesity in middle-aged obese women who undergo physical and emotional big changed.
  • 22.

    Effects of 60 Minutes Cardiopulmonary Resuscitation on Blood Lactic Acid Concentration, Heart Rate, and Rating of Perceived Exertion in Rescuers

    HANSEUNGEUN , Ahn, Hee-Jeong , Gyu-Sik Shim and 2 other persons | 2022, 27(8) | pp.195~202 | number of Cited : 0
    Abstract PDF
    In this study, when cardiopulmonary resuscitation continued for a long time, the rescuer's blood lactic acid concentration, heart rate, and rating of perceived exertion were measured to identify the change in the rescuer's fatigue. Data collection was conducted from July 5 to July 9, 2021, with a total of 24 students, 12 students department of special warfare medical non-commissioned officer, and 12 students department of emergency medical technology at D University, undergoing a two-person alternative chest compression resuscitation for 60 minutes. As a result of the study, the rescuer's blood lactic acid concentration, heart rate, rating of perceived exertion, and chest compression speed were significantly changed according to the duration of CPR (p<.001, p<.001, p<.001, p<.001). blood lactic acid concentrations at every measurement cycle (30 minutes, 40 minutes, 50 minutes, 60 minutes) showed a significant positive correlation with heart rate (r=.696, p<.001, r=.672, p<.001, r=.709, p<.001, r=.782, p<.001), there was also a significant positive correlation with the rating of perceived exertion (r=.476, p<).05, r=.426, p<.05, r=.470, p<.05, r=.470, p<.05). Therefore, monitoring the fatigue of rescuers using heart rate and rating of perceived exertion will be useful for maintaining high-quality chest compression in situations where cardiopulmonary resuscitation is required for a long time.
  • 23.

    A Longitudinal Study on the Effects of Child Maltreatment Experiences on School Bullying Experiences: Focusing on the Mediating Effects of School Violence Victimization Experiences and Aggression

    Hyung-hee Kim , KIM, Yong-Seob | 2022, 27(8) | pp.203~210 | number of Cited : 0
    Abstract PDF
    In this study, we tried to examine the longitudinal mediating effects of school violence damage experience and aggression in the relationship between child maltreatment experiences and school bullying experiences. For the analysis data for this purpose, the 3rd, 5th, 6th, and 7th data of the Korean Children and Youth panel data of the Korea Youth Policy Research Institute were used. A total of 1,813 data were analyzed using the statistical program SPSS 26.0 and Amos 26.0 version as a multivariate latent growth model. As a result of the analysis, it was possible to confirm the mediating effects of school violence victimization experiences and aggression. These results suggest that multilateral efforts are needed to lower the level of maltreatment, school violence victimization, and aggression that affect the school bullying experiences. Based on the results of this analysis, this study specifically suggested practical measures to prevent adolescents' maltreatment experiences from being reproduced as school bullying experiences.
  • 24.

    The development of the photoreflectance program for the analysis of semiconductor optical properties

    Sang-Hoon Shin , Geun-Hyeong Kim | 2022, 27(8) | pp.211~218 | number of Cited : 0
    Abstract PDF
    In this paper, a computer simulation program was developed to interpret the results measured by photoreflectance spectroscopy. The developed program is implemented so that the user can easily change the factors required for optical modulation characteristic interpretation, and the result of the value can be checked simultaneously with the actual measurement result. The results obtained by photoreflectance spectroscopy are obtained by mixing a third derivative function form (TDFF) modulated around a bandgap with a Franz-Keldysh oscillation (FKO) signal due to an electric field at a surface and an interface higher than the bandgap. Through the computer simulation program, the optical characteristics that appear in the GaSb Epi layer formed as a single layer were analyzed, and very useful results were obtained by specializing in optical modulation analysis. In addition, a Fast Fourier Transform (FFT) analysis tool was added to facilitate frequency characteristics analysis of FKO.
  • 25.

    Seasonal Weather Factors and Sensibility Change Relationship via Textmining

    Hyun-Jin Yeo | 2022, 27(8) | pp.219~224 | number of Cited : 0
    Abstract PDF
    The Korea Meteorological Administration(KMA) has been released life-related indexes such as ‘Life industrial weather information’ and ‘Safety weather information’ while other countries’ meteorological administrations have been made ‘Human-biometeorology’ and ‘Health meteorology’ indexes that concern human sensibility effections to diverse criteria. Although human sensibility changes have been studied in psychological research criteria with diverse and innumerous application areas, there are not enough studies that make data mining based validation of sensibility change factors. In this research I made models to estimate sensibility change caused by weather factors such as temperature and humidity, and validated by collecting sensibility data from SNS text crawling and weather data from KMA public dataset. By Logistic Regression, I clarify factors affecting sensibility changes.
  • 26.

    Do Leisure Activities Reduce the Level of Depressive Symptoms after Social Distancing Restrictions to be Lifted?: Focused on Offline Leisure Activities and Online Leisure Activities

    Jong Man Lee | 2022, 27(8) | pp.225~232 | number of Cited : 0
    Abstract PDF
    The purpose of this study was to analyze the effect of offline leisure activities and online leisure activities on depressive symptoms in the COVID-19 endemic. To do this, this study proposed a theoretical model consisting of demographic characteristics such as gender, age, academic background, and monthly income, offline leisure activity types such as socially-oriented activities, online leisure activity types such as information searching activities, entertainment activities, and the level of depressive symptoms. A survey was conducted to confirm research hypotheses, and a total of 99 questionnaires were used for statistical analysis. The major results of analysis reveal that first, monthly income is an important factor in predicting the level of depressive symptoms. Second, both offline socially-oriented activities and online entertainment activities have a negative effect on the level of depressive symptoms. This study has implications in that it identified the characteristics of leisure activities that can reduce the level of depressive symptoms.
  • 27.

    An Empirical Study on the Specialization Policy of Tourism Resources through the Brand Strategy of Traditional Markets - A Case on Anyang Central Market -

    Rack-In Choi | 2022, 27(8) | pp.233~240 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a marketing strategy for traditional markets that lays the foundation for regional economic development by developing traditional markets as regionally specialized tourism resources. This study conducted a survey of local residents and tourists, who are market users, and conducted a factor analysis to establish a market brand strategy using SPSS 25 and a reliability analysis to verify internal consistency. In addition, correlation analysis was performed to verify the significance to confirm the relevance. The analysis results of Anyang Central Market brand tourism products for traditional market marketing strategies are as follows. First, it is necessary to establish a brand identity that activates brand elements and brand criteria and brand positioning. Second, it is required to improve brand awareness, which can elicit brand awareness and brand information and brand memory. Third, it is necessary to improve the brand image that can increase brand association and brand loyalty. Fourth, it is necessary to make efforts to improve brand equity, which can improve brand value, brand concern, and brand life. By developing and proposing marketing policies for traditional markets by utilizing market brand strategies, it can be expected to revitalize traditional markets and local economies as specialized local tourism resources.
  • 28.

    Development of an intelligent skin condition diagnosis information system based on social media

    Hyung-Hoon Kim , Seung-Ho Ohk | 2022, 27(8) | pp.241~251 | number of Cited : 0
    Abstract PDF
    Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.
  • 29.

    The Effect of the Project Learning Method on the Learning Flow and AI Efficacy in the Contactless Artificial Intelligence Based Liberal Arts Class

    Ae-ri Lee | 2022, 27(8) | pp.253~261 | number of Cited : 0
    Abstract PDF
    In this study, the educational effect were sought to be identified after developing and applying project learning for the artificial intelligence based liberal arts education for the non-computer majors. A paired-sample t-test was performed within each group to determine the extent of improvement in the learning flow and artificial intelligence efficacy in the experimental and control groups. After class, an independent sample t-test was performed to examine the statistical effects of pre-test and post-test on the learning flow and artificial intelligence efficacy in the experimental and control groups. The experimental group and control group demonstrated significant improvements in the learning flow and artificial intelligence efficacy before and after class, each respectively. There was no statistically significant difference in the learning flow between the experimental group for which the project learning method was applied and the control group for which only theory and practice were conducted in the artificial intelligence class. It was also confirmed that the experimental group for which the project learning method was applied improved the efficacy of artificial intelligence to a significant level compared to the control group which only proceeded with theory and practice.
  • 30.

    Study on FOCUS Teaching & Learning Model for Improving Digital Competency of Freshmen of Early Childhood Education Department

    Yan Ha | 2022, 27(8) | pp.263~269 | number of Cited : 0
    Abstract PDF
    This study is to propose a FOCUS Teaching & Learning model to educate pre-service early childhood teachers and in the era of convergence and integration and the Fourth Industrial Revolution. In an era where the use of digital technology is maximized due to COVID-19, boundaries of each fields are blurred and convergence is emphasized, a teaching and learning model is needed to strengthen capabilities of freshmen at colleges that train specialists. This study proposes ways to vitalize ICT education in early childhood education and proposes an integrated teaching and learning model. Through this model, pre-service early childhood teachers will be able to enhance their digital capabilities and contribute to the field of early childhood education by producing video content, activities and teaching aids to be provided to early childhood education institutions. In addition, the model can be applied to areas other than early childhood education to improve digital capabilities through video production and utilization.
  • 31.

    An Analysis of Achievement Goals Changeability in a Software Liberal Arts Class

    Seung-Hun Shin , Joo-Young Seo | 2022, 27(8) | pp.271~281 | number of Cited : 0
    Abstract PDF
    The importance and necessity of software(SW) education as a liberal arts was fully recognized by society. However, according to the previous research results, learners' motivation to learn in SW liberal arts was kept low for various reasons. Therefore, understanding the learning motivation and its changeability in SW liberal arts is necessary, but the related studies are not sufficient. In this paper, we analyzed changes in achievement goals using a 3 × 2 achievement goal model to examine changeability of achievement goals in a SW liberal arts class during one semester. As a result, we confirmed that the achievement goals were stable at both the group level and the individual level, but the order of each achievement goal was different from that of the previous studies. We also confirmed that the mastery goal of the classroom goal structure had a higher correlation with most achievement goals, but the performance goals had a correlation with some avoidance goals only. This means that additional research is needed for each key classroom goal structure type in SW education because the learning motivation in SW liberal arts has different aspect from the other existing liberal arts classes.