• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.657-667
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• 2020

The Android framework allows apps to take full advantage of personal information through granting single permission, and does not determine whether the data being leaked is actual personal information. To solve these problems, we propose a tool with static/dynamic analysis. The tool analyzes the Source and Sink used by the target app, to provide users with information on what personal information it used. To achieve this, we extracted the Source and Sink through Control Flow Graph and make sure that it leaks the user's privacy when there is a Source-to-Sink flow. We also used the sensitive permission information provided by Google to obtain information from the sensitive API corresponding to Source and Sink. Finally, our dynamic analysis tool runs the app and hooks information from each sensitive API. In the hooked data, we got information about whether user's personal information is leaked through this app, and delivered to user. In this process, an automated Source/Sink classification model was applied to collect latest Source/Sink information, and the we categorized latest release version of Android(9.0) with 88.5% accuracy. We evaluated our tool on 2,802 APKs, and found 850 APKs that leak personal information.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.81-98
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• 2024

This study analyzed the impact of urban spatial factors on the thermal environment. The personal thermal sensation was set as the unit of thermal environment to analyze its correlation with environmental factors. To collect data on personal thermal sensation, Living Lab was applied, allowing citizens to record their thermal sensation and measure the temperature. Based on the input points of the collected personal thermal sensation, nearby urban spatial elements were collected to build a dataset for statistical analysis. Logistic regression analysis was conducted to analyze the impact of each factor on personal thermal sensation. The analysis results indicate that the temperature is influenced by the surrounding spatial environment, showing a negative correlation with building height, greenery rate, and road rate, and a positive correlation with sky view factor. Furthermore, the road rate, sky view factor, and greenery rate, in that order, had a strong impact on perceived heat. The results of this study are expected to be utilized as basic data for assessing the thermal environment to prepare local thermal environment measures in response to climate change.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.568-581
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• 2015

Predicting locations of users with portable devices such as IP phones, smart-phones, iPads and iPods in public wireless local area networks (WLANs) plays a crucial role in location management and network resource allocation. Many techniques in machine learning and data mining, such as sequential pattern mining and clustering, have been widely used. However, these approaches have two deficiencies. First, because they are based on profiles of individual mobility behaviors, a sequential pattern technique may fail to predict new users or users with movement on novel paths. Second, using similar mobility behaviors in a cluster for predicting the movement of users may cause significant degradation in accuracy owing to indistinguishable regular movement and random movement. In this paper, we propose a novel fusion technique that utilizes mobility rules discovered from multiple similar users by combining clustering and sequential pattern mining. The proposed technique with two algorithms, named the clustering-based-sequential-pattern-mining (CSPM) and sequential-pattern-mining-based-clustering (SPMC), can deal with the lack of information in a personal profile and avoid some noise due to random movements by users. Experimental results show that our approach outperforms existing approaches in terms of efficiency and prediction accuracy.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1141-1155
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• 2022

Multicultural education is not about learning about a specific ethnic group, but rather developing the ability to cross the border of one's own culture and have conversations with people of other cultures. I think the purpose is to promote empathy and consideration. This study emphasizes the importance of developing multi-dimensional educational programs for all members of society for multicultural social integration, and it is necessary to lead personal, social and civic action movements to create a fair society through media-based multicultural literacy education. said that In order to achieve harmony and integration in a multicultural society, it is the most important to acknowledge cultural diversity and to discard cultural prejudices and inequalities for symbiosis between the mainstream culture and the minority culture. In particular, the United States and Germany, which have successfully led multicultural social integration, are comprehensive in all areas, including interculturalism based on peaceful coexistence and respect, labor market issues, vocational education issues, housing and health issues, and communication issues through media literacy. He led a multicultural national integration system with approaches and methods. Therefore, our multicultural education policy should also pursue a new paradigm that presupposes a change in the public's awareness of a multicultural society.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.519-529
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• 2020

The purpose of this study is to establish a model for predicting academic achievement of college students and to reveal the interrelationship and relative influence of each factor. For this, we surveyed the personal factors and learning strategy factors of 1,310 learners at J University, and analyzed the discriminant factors and patterns of the predictors of academic achievement through the decision tree analysis, a data mining method, and examined the relative effects of each factor. Binary logistic regression analysis was performed for viewing. As a result, the most important factor for predicting academic achievement was efficacy, and other factors such as motivation, time management, and depression were predictive of academic achievement. The patterns of factors predicting academic achievement were found to be high in efficacy and time management, and high in motivation for learning even if the efficacy was moderate. Low efficacy and learning motivation, and high depression have been shown to decrease academic achievement. Based on these results, the study suggested the efficacy and motivation to improve academic achievement of college students, strengthening time management education, and managing negative emotions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-199
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• 2015

The purposes of this study are to examine the predictability of variables related to SNS intention to use in collaborative learning and provide some new implications. Based on Technology Readiness and Acceptance Model (TRAM), we hypothesized that optimism, innovativeness, discomfort, insecurity as personal disposition variables, subjective norm as a social variable, and perceived usefulness and perceived ease of use as cognitive variables would predict SNS intention to use. For this study, 274 'Share Leadership' students in E university completed surveys and it was analyzed by multiple regression analysis. The results of this study showed as follows. First, optimism, innovativeness, discomfort, and subjective norm predicted perceived ease of use. Second, optimism, insecurity, subjective norm and perceived ease of use predicted perceived usefulness. Third, subjective norm, perceived ease of use and perceived usefulness predicted SNS intention to use. From this, it is revealed that positive technology readiness predict much more than negative technology readiness do and the role of teacher and peers is very important.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.1.2-24
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• 2000

The field of neural networks has been a recent surge in activity as a result of progress in developments of efficient training algorithms. For this reason, and coupled with the widespread availability of powerful personal computer hardware for running simulations of networks, there is increasing focus on the potential benefits this field can offer. The neural network may be viewed as an advanced pattern recognition technique and can be applied in many areas such as financial time series forecasting, medical diagnostic expert system and etc.. The intention of this study is to build and implement one simple artificial neural networks hereinafter called ANN. For this purpose, some literature survey was undertaken to understand the structures and algorithms of ANN theoretically. Based on the review of theories about ANN, the system adopted 3-layer back propagation algorithms as its learning algorithm to simulate one case of medical diagnostic model. The adopted ANN algorithm was performed in PC by using turbo PASCAL and many input parameters such as the numbers of layers, the numbers of nodes, the number of cycles for learning, learning rate and momentum term. The system output more or less successful results which nearly agree with goals we assumed. However, the system has some limitations such as the simplicity of the programming structure and the range of parameters it can dealing with. But, this study is useful for understanding general algorithms and applications of ANN system and can be expanded for further refinement for more complex ANN algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2086-2097
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• 2021

The current cultural assets are being restored depending on the opinions of experts (craftsmen). We intend to introduce digitalized artificial intelligence techniques, excluding the personal opinions of experts on reconstruction of such cultural properties. The first step toward restoring digitized cultural properties is separation. The restoration of cultural properties should be reorganized based on recorded documents, period historical backgrounds and regional characteristics. The cultural properties in the form of photographs or images should be collected by separating the background. In addition, when restoring cultural properties most of them depend a lot on the tendency of the restoring person workers. As a result, it often occurs when there is a problem in the accuracy and reliability of restoration of cultural properties. In this study, we propose a search method for learning stored digital cultural assets using AI technology. Pagoda was selected for restoration of Cultural Properties. Pagoda data collection was collected through the Internet and various historical records. The pagoda data was classified by period and region, and grouped into similar buildings. The collected data was learned by applying the well-known CNN algorithm for artificial intelligence learning. The pagoda search used Yolo Marker to mark the tower shape. The tower was used a total of about 100-10,000 pagoda data. In conclusion, it was confirmed that the probability of searching for a tower differs according to the number of pagoda pictures and the number of learning iterations. Finally, it was confirmed that the number of 500 towers and the epochs in training of 8000 times were good. If the test result exceeds 8,000 times, it becomes overfitting. All so, I found a phenomenon that the recognition rate drops when the enemy repeatedly learns more than 8,000 times. As a result of this study, it is believed that it will be helpful in data gathering to increase the accuracy of tower restoration.

• Korean Journal of School Psychology
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• v.18 no.2
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• pp.153-174
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• 2021

The purpose of this study is to verify antecedent variables that positively influence behavioural engagement during school engagement, which is critical to adolescent socialization. The antecedent variable was categorized into the personal characteristics of adolescents who are the main agents of socialization and peer support and teacher support, which can be called social support at school sites. Individual characteristics include strength recognition, strength utilization, and learning goal orientation, and, peer supports include the supports for personality strength and academy, and, teacher supports include the supports for personality strength and perspective change. For this study, a survey was conducted on 539 high school students nationwide, collected data, 33 of them were removed, and 506 data were analyzed. Analysis shows that only learning goal orientation set as a sub-factor of individual characteristics has a static significant effect on behavioral engagement. Finally, based on the findings, we discuss the implications, limitations, and future research tasks of the study.

• Journal of Korean Academy of Nursing
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• v.29 no.4
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• pp.963-976
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• 1999

This study was undertaken to investigate the general characteristics of students, which include the degree of satisfaction, motives of admission, the recognition of advantages and disadvantages, opinion of students on self-directed learning, and planning and anticipatory effects after graduation. Data was collected through a questionnaire survey over a period of four months, from May 1997 to August 1997. The subjects used for this study consisted of 322 RN students sampled from six RN-to-BSN programs in Korea using the census sampling method. Statistical methods employed for this study included discriptive statistics, M ANOVA, and F-test. The results of the study are as follows 1. The RN students' motives of admission to RN-to-BSN programs were ‘for personal advancement’, ‘to earn a BSN degree’, and ‘for professional development’ in this order. 2. The RN students' responses to the advantages of RN-to-BSN programs were ‘acquisition of new knowledge and a BSN degree’ and ‘to gain professional thinking and a broader view’, while as the disadvantages of RN-to-BSN programs were ‘geographical isolation of institutions’, ‘limitation of information’, and ‘underdeveloped school environments’ in this order. 3. The survey based on opinions toward self-directed learning showed that there was a need of detailed guidelines for self-directed learning. Most agreed that it was a very effective learning method for a RN student, and the self-directed learning method Increases motives for learning. 4. The students' anticipatory effect after graduation were ‘self-achievement’, ‘development of professional skills’, and ‘admission to post-graduate school or programs to study abroad’. 5. The students were very satisfied with the quality of faculty members, and satisfied with the quality of lectures and teaching. However, students were unsatisfied with rented lecture rooms, and very unsatisfied with self-directed learning methods. 6. School nurses showed higher statistical significances in the need for teaching material and anticipatory effect after graduation than other RN students working in hospitals and public health agencies. Also, school nurses, public health nurses, and industry nurses showed higher statistical significances in motives of admission than RN students working in hospitals. Further more, staff nurses, school nurses, and industry nurses showed higher levels of satisfaction toward a RN-to-BSN programs than nurses in higher positions, such as administrators or directors of nursing. 7 City residents were more satisfied with RN-to-BSN programs than rural residents. Otherwise, the rural residents had higher motives for admission, a bigger need for teaching materials, and recognition of the disadvantages of RN-to-BSN programs than city residents. Finally, RN students who earned below a monthly income of ￦1,000,000 showed higher motivation for admission than those who earned more than ￦1,000,000.