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pISSN : 1598-849X / eISSN : 2383-9945

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2022, Vol.27, No.5

  • 1.

    Counting and Localizing Occupants using IR-UWB Radar and Machine Learning

    Geonwoo Ji , Changwon Lee , Jaeseok Yun | 2022, 27(5) | pp.1~9 | number of Cited : 0
    Abstract PDF
    Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.
  • 2.

    Improving Availability of Embedded Systems Using Memory Virtualization

    Sunghoon Son | 2022, 27(5) | pp.11~19 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a fault tolerant embedded system using memory redundancy on the full-virtualization based virtual machine monitor. The proposed virtual machine monitor first virtualizes main memory of embedded system utilizing efficient shadow page table scheme so that the embedded system runs as a virtual machine on the virtual machine monitor. The virtual machine monitor makes the backup of the embedded system run as another virtual machine by copying memory contents of the embedded system into memory space of backup system according to predefined schedules. When an error occurs in the target virtual machine, the corresponding standby virtual machine takes the role of target virtual machine and continues its operation. Performance evaluation studies show that such backups and switches of virtual machines are performed with minor performance degradation.
  • 3.

    Heart Disease Prediction Using Decision Tree With Kaggle Dataset

    Young-Dan Noh , Kyu-Cheol Cho | 2022, 27(5) | pp.21~28 | number of Cited : 0
    Abstract PDF
    All health problems that occur in the circulatory system are refer to cardiovascular illness, such as heart and vascular diseases. Deaths from cardiovascular disorders are recorded one third of in total deaths in 2019 worldwide, and the number of deaths continues to rise. Therefore, if it is possible to predict diseases that has high mortality rate with patient’s data and AI system, they would enable them to be detected and be treated in advance. In this study, models are produced to predict heart disease, which is one of the cardiovascular diseases, and compare the performance of models with Accuracy, Precision, and Recall, with description of the way of improving the performance of the Decision Tree(Decision Tree, KNN (K-Nearest Neighbor), SVM (Support Vector Machine), and DNN (Deep Neural Network) are used in this study.). Experiments were conducted using scikit-learn, Keras, and TensorFlow libraries using Python as Jupyter Notebook in macOS Big Sur. As a result of comparing the performance of the models, the Decision Tree demonstrates the highest performance, thus, it is recommended to use the Decision Tree in this study.
  • 4.

    A Design and Implement of Efficient Agricultural Product Price Prediction Model

    Jung-Ju Im , Tae-Wan Kim , Ji-Seoup Lim and 3 other persons | 2022, 27(5) | pp.29~36 | number of Cited : 0
    Abstract PDF
    In this paper, we propose an efficient agricultural products price prediction model based on dataset which provided in DACON. This model is XGBoost and CatBoost, and as an algorithm of the Gradient Boosting series, the average accuracy and execution time are superior to the existing Logistic Regression and Random Forest. Based on these advantages, we design a machine learning model that predicts prices 1 week, 2 weeks, and 4 weeks from the previous prices of agricultural products. The XGBoost model can derive the best performance by adjusting hyperparameters using the XGBoost Regressor library, which is a regression model. The implemented model is verified using the API provided by DACON, and performance evaluation is performed for each model. Because XGBoost conducts its own overfitting regulation, it derives excellent performance despite a small dataset, but it was found that the performance was lower than LGBM in terms of temporal performance such as learning time and prediction time.
  • 5.

    Design and Implementation of YouTube-based Educational Video Recommendation System

    Young Kook Kim , Myung Ho Kim | 2022, 27(5) | pp.37~45 | number of Cited : 0
    Abstract PDF
    As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.
  • 6.

    A Study on Recognition of Dangerous Behaviors using Privacy Protection Video in Single-person Household Environments

    Chae Hyun Lim , Myung Ho Kim | 2022, 27(5) | pp.47~54 | number of Cited : 0
    Abstract PDF
    Recently, with the development of deep learning technology, research on recognizing human behavior is in progress. In this paper, a study was conducted to recognize risky behaviors that may occur in a single-person household environment using deep learning technology. Due to the nature of single-person households, personal privacy protection is necessary. In this paper, we recognize human dangerous behavior in privacy protection video with Gaussian blur filters for privacy protection of individuals. The dangerous behavior recognition method uses the YOLOv5 model to detect and preprocess human object from video, and then uses it as an input value for the behavior recognition model to recognize dangerous behavior. The experiments used ResNet3D, I3D, and SlowFast models, and the experimental results show that the SlowFast model achieved the highest accuracy of 95.7% in privacy-protected video. Through this, it is possible to recognize human dangerous behavior in a single-person household environment while protecting individual privacy.
  • 7.

    A Proposal of Sensor-based Time Series Classification Model using Explainable Convolutional Neural Network

    Youngjun Jang , KimJiho , LEE, Hong Chul | 2022, 27(5) | pp.55~67 | number of Cited : 0
    Abstract PDF
    Sensor data can provide fault diagnosis for equipment. However, the cause analysis for fault results of equipment is not often provided. In this study, we propose an explainable convolutional neural network framework for the sensor-based time series classification model. We used sensor-based time series dataset, acquired from vehicles equipped with sensors, and the Wafer dataset, acquired from manufacturing process. Moreover, we used Cycle Signal dataset, acquired from real world mechanical equipment, and for Data augmentation methods, scaling and jittering were used to train our deep learning models. In addition, our proposed classification models are convolutional neural network based models, FCN, 1D-CNN, and ResNet, to compare evaluations for each model. Our experimental results show that the ResNet provides promising results in the context of time series classification with accuracy and F1 Score reaching 95%, improved by 3% compared to the previous study. Furthermore, we propose XAI methods, Class Activation Map and Layer Visualization, to interpret the experiment result. XAI methods can visualize the time series interval that shows important factors for sensor data classification.
  • 8.

    The Direction of AI Classes using AI Education Platform

    Mi-Young Ryu , Han Sun Gwan | 2022, 27(5) | pp.69~76 | number of Cited : 0
    Abstract PDF
    In this paper, we presented the contents and methods of AI classes using AI platforms. First, we extracted the content elements of each stage of the AI class using the AI education platform from experts. Classes using the AI education platform were divided into 5 stages and 25 class elements were selected. We also conducted a survey of 82 teachers and analyzed the factors that they acted importantly at each stage of the AI platform class. As a result of the analysis, teachers regarded the following contents as important factors for each stage that are AI model preparation stage (the learning stage of the AI model), problem recognition stage (identification of problems and AI solution potential), data processing stage (understanding the types of data), AI modelingstage (AI value and ethics), and problem solvingstage (AI utilization in real life).
  • 9.

    Unsupervised feature selection using orthogonal decomposition and low-rank approximation

    Hyunki Lim | 2022, 27(5) | pp.77~84 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a novel unsupervised feature selection method. Conventional unsupervised feature selection method defines virtual label and uses a regression analysis that projects the given data to this label. However, since virtual labels are generated from data, they can be formed similarly in the space. Thus, in the conventional method, the features can be selected in only restricted space. To solve this problem, in this paper, features are selected using orthogonal projections and low-rank approximations. To solve this problem, in this paper, a virtual label is projected to orthogonal space and the given data set is also projected to this space. Through this process, effective features can be selected. In addition, projection matrix is restricted low-rank to allow more effective features to be selected in low-dimensional space. To achieve these objectives, a cost function is designed and an efficient optimization method is proposed. Experimental results for six data sets demonstrate that the proposed method outperforms existing conventional unsupervised feature selection methods in most cases.
  • 10.

    Hair and Fur Synthesizer via ConvNet Using Strand Geometry Images

    Jong-Hyun Kim | 2022, 27(5) | pp.85~92 | number of Cited : 0
    Abstract PDF
    In this paper, we propose a technique that can express low-resolution hair and fur simulations in high-resolution without noise using ConvNet and geometric images of strands in the form of lines. Pairs between low-resolution and high-resolution data can be obtained through physics-based simulation, and a low-resolution-high-resolution data pair is established using the obtained data. The data used for training is used by converting the position of the hair strands into a geometric image. The hair and fur network proposed in this paper is used for an image synthesizer that upscales a low-resolution image to a high-resolution image. If the high-resolution geometry image obtained as a result of the test is converted back to high-resolution hair, it is possible to express the elastic movement of hair, which is difficult to express with a single mapping function. As for the performance of the synthesis result, it showed faster performance than the traditional physics-based simulation, and it can be easily executed without knowing complex numerical analysis.
  • 11.

    A study on the Metaverse based memorial service platform

    Byong-Kwon Lee | 2022, 27(5) | pp.93~100 | number of Cited : 0
    Abstract PDF
    Korea's ancestral culture has limited travel and contact due to Corona (COVID-19). In addition, Korean ancestral culture meets in person to commemorate the deceased. In this paper, we propose a non-face-to-face metaverse memorial platform service that can commemorate the deceased and perform ancestral rites in the cyber world (virtual reality) by applying the metaverse technology. The services proposed in the study consisted of a remembrance hall that displays the life story of the deceased, a ancestral hall that conducts ancestral rites for the deceased, and a deceased pavilion that checks the remains and wills of the deceased. In addition, the virtual reality device (HMD: Head Mounted Display) set the teleportation and content resolution to 4K to minimize dizziness. In particular, the priests applied interaction technology to provide an immersive service for ancestral rites between family members. The researched memorial hall metaverse service is a metaverse-based platform service that allows anyone to commemorate the deceased as a family unit in a non-face-to-face state rather than face-to-face.
  • 12.

    Script-based Test System for Rapid Verification of Atomic Models in Discrete Event System Specification Simulation

    Su-Man Nam | 2022, 27(5) | pp.101~107 | number of Cited : 0
    Abstract PDF
    Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.
  • 13.

    A Study on Applying a Consistent UML Model to Naval Combat System Software Using Model Verification System

    Seung-Mo Jung , Woo-Jin Lee | 2022, 27(5) | pp.109~116 | number of Cited : 0
    Abstract PDF
    Recently, a model-based development method centered on highly readable and standardized UML (Unified Modeling Language) models has been applied to solve unclear communications in large-scale software development. However, it is difficult to apply consistent UML models depending on software developers' proficiency, understanding of models and modeling tools. In this paper, we propose a method for developing a Model Verification System to apply an consistent UML model to software development. Then, the developed Model Verification System is partially applied to the Naval Combat System Software development to prove its function. The Model Verification System provides automatic verification of models created by developers according to domain characteristics. If the Model Verification System proposed in this paper is used, It has the advantage of being able to apply the consistent UML model more easily to Naval Combat System Software Development.
  • 14.

    Travel Route Recommendation Utilizing Social Big Data

    Yang Woo Yu , Seong Hyuck Kim , Hyeon Gyu Kim | 2022, 27(5) | pp.117~125 | number of Cited : 0
    Abstract PDF
    Recently, as users’ interest for travel increases, research on a travel route recommendation service that replaces the cumbersome task of planning a travel itinerary with automatic scheduling has been actively conducted. The most important and common goal of the itinerary recommendations is to provide the shortest route including popular tour spots near the travel destination. A number of existing studies focused on providing personalized travel schedules, where there was a problem that a survey was required when there were no travel route histories or SNS reviews of users. In addition, implementation issues that need to be considered when calculating the shortest path were not clearly pointed out. Regarding this, this paper presents a quantified method to find out popular tourist destinations using social big data, and discusses problems that may occur when applying the shortest path algorithm and a heuristic algorithm to solve it. To verify the proposed method, 63,000 places information was collected from the Gyeongnam province and big data analysis was performed for the places, and it was confirmed through experiments that the proposed heuristic scheduling algorithm can provide a timely response over the real data.
  • 15.

    FinDID : A DID service supporting the standard service scheme for the financial sector

    Young-Eun Lee , Hye-Won Kim , Myung-Joon Lee | 2022, 27(5) | pp.127~138 | number of Cited : 0
    Abstract PDF
    In this paper, we present FinDID (Financial Decentralized IDentity), a blockchain-based DID(Decentralized IDentity) service that can flexibly control personal information or credentials through a systematic verification method while complying with the standard service scheme of decentralized identity for the financial sector. DID is an identity management system used in a decentralized environment without a specific certification authority, and as a technology that allows users to control their own information, it can realize self-sovereignty over users' own personal information. Through FinDID, users receive credentials that authenticate their various personal information from the issuer, select only the claims required by the target financial service using their personal electronic wallet, create presentations from credentials. Then they submit it to the financial service, leading to their qualification from the service. FinDID consists of electronic wallet, credential issuer, credential storage, DID service including DID management contract and credential management contract, and financial services using this service scheme. The DID service manages each user's DID and supports all verification processes of the associated identity management scheme.
  • 16.

    Effect of lifelong education center service quality on psychological well-being through positive psychological capital

    Sin-Bok Lee , Chanuk Park | 2022, 27(5) | pp.139~148 | number of Cited : 0
    Abstract PDF
    The lifelong education center is an educational system that provides adults with learning from cradle to tomb to people, and it is difficult to provide smooth educational services due to the period of COVID-19. Through this, the purpose of this study is to investigate how the service quality of lifelong education centers affects psychological well-being through positive psychological capital based on previous studies on service quality, positive psychological capital, and psychological well-being. This study distributed and collected questionnaires from November 1st to November 14th, 2021, targeting 212 students attending the lifelong education center. As a result of hypothesis verification, first, it was found that the service quality had no effect on self-efficacy, but all of them had an significant effect on hope. Second, it was found that the assurance and responsiveness had a positive effect on resiliency, and it was found that responsiveness had a positive effect on optimism. Finally, hope, resilience, and optimism were found to have a significant effect on psychological well-being. Through the results of this study, it is expected that it can be used as data for the policy direction to provide better quality lifelong education center services to lifelong education center learners.
  • 17.

    OLE File Analysis and Malware Detection using Machine Learning

    Hyeong Kyu Choi , Ah Reum Kang | 2022, 27(5) | pp.149~156 | number of Cited : 0
    Abstract PDF
    Recently, there have been many reports of document-type malicious code injecting malicious code into Microsoft Office files. Document-type malicious code is often hidden by encoding the malicious code in the document. Therefore, document-type malware can easily bypass anti-virus programs. We found that malicious code was inserted into the Visual Basic for Applications (VBA) macro, a function supported by Microsoft Office. Malicious codes such as shellcodes that run external programs and URL-related codes that download files from external URLs were identified. We selected 354 keywords repeatedly appearing in malicious Microsoft Office files and defined the number of times each keyword appears in the body of the document as a feature. We performed machine learning with SVM, naïve Bayes, logistic regression, and random forest algorithms. As a result, each algorithm showed accuracies of 0.994, 0.659, 0.995, and 0.998, respectively.
  • 18.

    Game-bot Detection based on Analysis of Harvest Coordinate

    Jae Woong Choi , Ah Reum Kang | 2022, 27(5) | pp.157~163 | number of Cited : 0
    Abstract PDF
    As the online game market grows, the use of game bots is causing the most serious problem for game services. We propose a harvest coordinate analysis model to detect harvesting bots among game bots of the Massively Multiplayer Online Role-Playing Games(MMORPGs) genre. The proposed model analyzes the player's harvesting behavior using the coordinate data. Game bots can obtain in-game goods and items more easily than normal players and are not affected by realistic restrictions such as sleep time and character manipulation fatigue. As a result, there is a difference in harvesting coordinates between normal players and game bots. We divided the coordinate zones and used these coordinate zone differences to distinguish between game bot players and normal players. We created a dataset with NCSoft's AION log and applied it to a random forest model to detect game bots, and as a result, we derived performance with a recall of 0.72 and a precision of 0.92.
  • 19.

    The Effect of Non-Face-to-Face Classes on Class Satisfaction of Nursing Students after COVID-19

    Young-Su Kim | 2022, 27(5) | pp.165~172 | number of Cited : 0
    Abstract PDF
    This study was attempted to investigate the effect of non-face-to-face online classes on class satisfaction of nursing students after COVID-19. The research method was a structured self-report questionnaire targeting 3rd graders(n=133) of the Department of Nursing at K University, and the collected data were analyzed using the SPSS/WIN 25.0 program. The results of the study were achievement motivation , interaction , self-regulated learning, and achievement motivation showed a statistically significant positive correlation with class satisfaction, and self-regulated learning showed a significant positive correlation with achievement motivation. Accordingly, in order to increase class satisfaction, the development and application of non-face-to-face online teaching methods to increase self-regulated learning, achievement motivation, and interaction are required.
  • 20.

    The Effects of Bullying on the Life Satisfaction of Multicultural Adolescents: The Mediation Effects of Self-esteem and Social Withdrawal

    Hyung-hee Kim , Yong Seob Kim | 2022, 27(5) | pp.173~179 | number of Cited : 0
    Abstract PDF
    The purpose of this study is to examine the mediating effects of social withdrawal and self-esteem in the relationship between the experiences of group bullying victimization damage and life satisfaction of multicultural adolescents and to find ways to improve the level of life satisfaction of multicultural adolescents. To this end, a structural equation model analysis was conducted using panel data for the 6th year of multicultural youth (2016) to verify the mediating effects. Looking at the results of the analysis, it was confirmed that self-esteem had a statistically significant complete mediating effects. Based on these analysis results, implications for improving the level of life satisfaction of multicultural adolescents were presented.
  • 21.

    Characteristics of noise generated during treatment in dental clinic

    Mi-Suk Choi , Dong-Ha Ji | 2022, 27(5) | pp.181~188 | number of Cited : 0
    Abstract PDF
    In this paper, we proposed of the results of the noise level and appropriate conversation distance by applying the noise characteristics generated during treatment at a dental clinic to the NR-curve and PSIL. As a result of analyzing the noise characteristics during treatment at a dental clinic, it was analyzed that the noise level exceeded 60dB(A), which is the health preservation limit value caused by noise, and the noise level increased as the frequency increased. the result of evaluation applying it to the NR curve, some treatment exceeded the workplace noise standard, and as a result of analyzing the level of conversational disturbance between the worker and the patient, it is desirable to have the conversation at a distance of less than 1M for accurate communication. In order to improve the quality of medical service in dental clinic and to reduce dental fear, it is judged that soundproofing protective equipment is provided to workers, and soundproofing measures are needed for noise sources (treatment devices used in treatment) and sound sources (patients and workers).
  • 22.

    Legal review of public officials' leave of absence for law school enrollment training

    Jong-Ryeol Park , Sang-Ouk Noe | 2022, 27(5) | pp.189~197 | number of Cited : 0
    Abstract PDF
    It is not seen as discrimination based on reasonable grounds for the National Public Officials Act to discriminate between public officials entering general graduate schools and public officials entering law schools. The degree of discrimination cannot be said to be appropriate. Therefore, it is judged that it violates the principle of equality under Article 11 of the Constitution for the relevant laws and regulations to treat them differently by excluding those public officials who went to law schools from the application of the State Public Officials Act because the criteria for discrimination cannot be said to have a substantial relationship to realize its purpose. The degree of discrimination is not appropriate, so related laws and regulations are arbitrary legislation that discriminates against public officials entering law schools without reasonable reasons. Articles 71(2)3 and 72(6) of the National Public Officials Act and Article 90 of the Rules on the Appointment of Public Officials stipulate that public officials who want to go to "research institutions or educational institutions designated by the head of the central personnel agency" can use the training leave system. However, it is reasonable to assume that there is no reasonable basis for discrimination because it does not allow such benefits to public officials who wish to enter law schools. I think it is desirable to utilize a special admission system that allows students to enter night law school or to enter while working for a living.
  • 23.

    Analysis on Media Reports of the 「Security Services Industry Act」 Using News Big Data –Focusing on the Period from 1990 to 2021-

    Cho Cheol Kyu , Su-Hyeon Park | 2022, 27(5) | pp.199~204 | number of Cited : 0
    Abstract PDF
    The purpose of this study is to broaden the understanding of the Security Services Industry Act, and also to examine the meanings of various phenomena by analyzing the media report big data rather than the researchers’ perspective on the Security Services Industry Act. In the research method, this study searched for a keyword 「Security Services Industry Act」 that prescribes the security work as an important subject of crime prevention and maintenance of public order in Korea. The data was searched from 1990 to 2021 the BIG KINDS could provide. Also, for the concrete analysis during the period of data search, it was divided into settlement period(1976~2001), growth period-quantitative(2002~2012), and growth period-qualitative(2013~2021). In the results of this study, the media report perception of the Security Services Industry Act is continuously emphasizing the social roles and importance of private security according to the flow of time. The consequent marketability of private security will play great roles in the protection of people’s lives and properties in the combination with various other industries in the future. However, the private security industry that provides public peace service together with the police, could be rising as an element that hinders the development of private security industry because of various social issues caused by legal regulations and illegal problems, so it would be necessary to more strengthen its responsibility and roles accordingly.
  • 24.

    Analysis of Factors Affecting Academic Ability of Preschool-age Children

    Kyung-Im Moon | 2022, 27(5) | pp.205~213 | number of Cited : 0
    Abstract PDF
    This study is to analyze the relationship among potential variables of self-development, social development, learning readiness, and academic ability using data from the Panel Study on Korean Children, which was surveyed in 2014, and to find factors affecting the academic ability of preschool children will be. The subjects of this study were 6-year-old children of 1113 households among 2150 households in the 7th Panel Study on Korean Children(2014) data, excluding non-responders and system-missing 1037 households. As a result of analyzing the path effect of the research model, it was found that, between self-development and academic skills, self-development had a direct effect on academic skills and also had a significant indirect effect through social development and learning readiness as a medium. In addition, it was found that learning readiness had the greatest influence among self-development, social development, and learning readiness on academic skills. As a result, the academic skills of preschool-age children should be treated with great importance in order to develop them into talents with creativity and problem-solving ability.
  • 25.

    Effects of Czech get up Exercise on Functional Movement and Dynamic Balance in Female Office Worker

    chanyang kim , Jin-Wook Lee | 2022, 27(5) | pp.215~224 | number of Cited : 0
    Abstract PDF
    The purpose of this study is to analyze how it affects functional movement and dynamic balance applying Czech get up exercise based on the principle of motor development of child for office worker women in 30s and 40s. Through random allocation, an Czech get up exercise group(n=15) and a control group(n=14) were formed to apply exercise for 12 weeks, 3 times a week, and 60 minutes a day, and the control group maintained daily life at the same period. As a result of the study, showed that Deep squat(p<.05), Hurdle step(p<.01), In-line lunge(p<.05), Trunk stability push-up(p<.001), Rotary stability (p<.01), Total score(p<.001), were significantly in the Czech get up Group, and Dynamic Balance of Lower Extremity(p<.001), Right Dynamic Balance of Lower Extremity(p<.001) were also significantly in the Czech get up Group. In conclusion, it is thought that Czech get up exercise based on the principle of motor development of child will have a positive effect on the functional movement and dynamic balance in office women, thereby increasing work efficiency as well as healthy life.
  • 26.

    The effect of consumers’ awareness of e-commerce firms’ Corporate Social Responsibilities(CSR) activities on consumers' purchase intentions

    Cui Dong , Sung-joon Yoon | 2022, 27(5) | pp.225~232 | number of Cited : 0
    Abstract PDF
    This study aims to empirically examine whether consumers’ perceptions of Chinese e-commerce firms’s CSR activities, along with psychological construct of company-consumer identification, and corporate trust affect their purchase intention based on theory of reasoned action. The study used a survey method for data collection to confirm research hypotheses with a total of 240 respondents used for final analysis. The results showed that economic responsibility, ethical responsibility, and legal responsibility have a positive effect on consumers’ purchase intention. In addition, corporate trust and company-consumer identification were found to mediate the relationship between consumers’ CSR perceptions and purchase intention. The result of this study is expected to provide useful theoretical as well as practical implications to advance the current understanding on the effects of consumers’ CSR perception on business performance.