• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.152-163
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• 2019

In this paper, effect of steel fiber inclusion, compressive strength of matrix, shear reinforcement and shear span to depth ratio on the flexural behavior of UHPFRC(Ultra High Performance Fiber Reinforced Concrete) were investigated with test of 10-UHPFRC beam specimens. All test specimens were subjected to the flexural static loading. It was shown that steel fiber significantly improve the shear strength of UHPFRC beams. 2% volume fraction of steel fiber change the mode of failure from shear failure to flexural failure and delayed the failure of compressive strut with comparatively short shear span to depth ratio. UHPFRC beams without steel fiber had a 45-degree crack angle and fiber reinforced one had lower crack angle. Shear reinforcement contribution on shear strength of beams can be calculated by 45-degree truss model with acceptable conservatism. Using test results, French and Korean UHPFRC design recommendations were evaluated. French recommendation have shown conservative results on flexural behavior but Korean recommendation have shown overestimation for flexural strength. Both recommendations have shown the conservatism on the flexural ductility and shear strength either.

• Journal of the Korean Society of Food Culture
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• v.19 no.3
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• pp.336-347
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• 2004

This study was conducted to investigate eating-out behavior patterns of youths, especially junior high and senior high school students. 1600 questionnaire surveys were distributed and 1487 were used for analysis. In order to consider regional differences as well as overall characteristics of youths' eating-out behaviors, the subjects were evenly sampled from north Seoul, south Seoul, big cities, middle/small cities and small towns. As for the frequency of eating-out, 62.7% of respondents answered once to twice per week. For the can of more than 5 times of eating-out per week, the respondents from south Seoul showed the highest frequency. For the case of no eating-out, the highest frequency was shown from the small towns. As for the most frequently visited place for eating-out, 33.6% of respondents answered Korean style restaurants, and 17.6% Boon-sik(Sanck-bar). Regarding the preference of Korean style restaurants, the highest rate was shown from the residents of big cities. For the question of when they eat out, 89.6% answered dinner and 6.3% lunch. For the question about reason of choosing particular restaurants, 61.5% of respondents referred to tastes and 16.6% price. For the question of the most important reason of eating out, 52.6% point out 'meal solution' and 25.6% 'for meeting.' As for the people accompanied when eating out, 67.2% of the respondents answered family. For the cost of eating out per person, 45.7% of the respondents spent 2000-4000 won for lunch; 31.1% spent 5000-10,000 won for dinner; 33.7% of the respondents spent more than 20,000 won for the special events. Regarding the regional differences of eating-out cost, respondents from south Seoul tended to spend the biggest amount of money for lunch, dinner and special day.

• KIISE Transactions on Computing Practices
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• v.22 no.3
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• pp.139-144
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• 2016

There exist many threats in cyber space, however current anti-virus software and other existing solutions do not effectively respond to malware that has become more complex and sophisticated. It was shown experimentally that it is possible for the proposed approach to provide an automatic execution environment for the detection of malicious behavior of active malware, comparing the virtual-machine environment with the real-machine environment based on user interaction. Moreover, the results show that it is possible to provide a dynamic analysis environment in order to analyze the intelligent malware effectively, through the comparison of malicious behavior activity in an automatic binary execution environment based on real-machines and the malicious behavior activity in a virtual-machine environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.368-378
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• 2018

This study examined the relationship between hostility and obsessive-compulsive symptoms to clarify the differential role of overt hostility and covert hostility on obsessive-compulsive symptoms. In addition, this study examined whether impulsivity has a moderating effect on the relationship between hostility measures and obsessive-compulsive symptoms. The Buss Durkee Hostility Inventory (BDHI), Revised Obsessive Compulsive Inventory (OCI-R), and Barratt Impulsivity Scale (BIS) were used to measure hostility, obsessive-compulsive symptoms, and impulsivity, respectively. Data were collected from 150 online university students and analyzed using the correlation and moderated multiple regression model. The result showed that overt hostility was positively correlated with obsessive thoughts; covert hostility was positively correlated with obsessive thoughts and compulsive behavior. In addition, the regression results, which set the hostility variables as the predicting variable, revealed covert hostility to increase obsessive thinking and compulsive behavior, whereas overt hostility had no significant effect on both variables. Impulsivity was found to function as a moderator in the prediction of covert hostility on obsessive thought. With the result, the implications and limitations of this study are discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2370-2378
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• 2016

Social Network Service(SNS) users are increasing globally. Within that trend, 'SNS attacking' victims are increasing in social network service space like KakaoStory, facebook, or Instargram as people damage others' personality or reputation. In this paper is to investigate and analyze awareness of negative behavior attributed to disinhibition effect with undergraduates who are the group of people using social network service the most diversely in smart environment and devise preventive measures to reduce social network service attacking victims and attackers. In social network service space, undergraduates are hardly aware of other people's personality, defamation, or invasion of privacy, and the level of guilt they feel towards social network service attacking is seriously low. To solve this problem, this study suggests preventive measures so that they can be equipped with awareness and regulations right for this social network service age and can prevent negative behavior resulted from disinhibition effect.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.167-174
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• 2019

The purpose of this study was to analyze the factors affecting the drinking behavior of adolescents. Based on this, it aims to suggest the practical and policy measures to prevent the drinking behavior of adolescents and to mediate / reduce them. We used binomial logistic analysis as an analysis method.As a result of this study, the individual factors affecting alcohol drinking were gender, smoking experience over the past year, sexual satisfaction, cyber delinquency, self-esteem, parental abuse, peer as family factors. Peer trust was significantly associated with attachment factors, and school adaptation factors were not found to be associated with alcohol drinking in adolescents. This suggests that multilateral efforts such as individuals, families, and communities are needed to mediate and reduce the drinking behavior of adolescents.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.754-762
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• 2010

Nowadays, email-based targeted attacks using malcode-bearing documents have been steadily increased. To improve the success rate of the attack and avoid anti-viruses, attackers mainly employ zero-day exploits and relevant social engineering techniques. In this paper, we propose an architecture of the email vaccine cloud system to prevent targeted attacks using malcode-bearing documents. The system extracts attached document files from email messages, performs behavior analysis as well as signature-based detection in the virtual machine environment, and completely removes malicious documents from the messages. In the process of behavior analysis, the documents are regarded as malicious ones in cases of creating executable files, launching new processes, accessing critical registry entries, connecting to the Internet. The email vaccine cloud system will help prevent various cyber terrors such as information leakages by preventing email based targeted attacks.

• Journal of KIISE
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• v.45 no.3
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• pp.294-302
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• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.225-238
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play that reflects the social activities of gamers: In a Massively Multi-user Online Role Playing Game (MMORPG), party play log includes a distinguished information that can classify game users under normal-user and abnormal-user. That is because the bot users' main activities target on the acquisition of cyber assets. Through a statistical analysis of user behaviors in game activity logs, we establish the threshold levels of the activities that allow us to identify game bots. Also, we build a knowledge base of detection rules based on this statistical analysis. We apply these rule reasoner to the sixth most popular online game in the world. As a result, we can detect game bot users with a high accuracy rate of 95.92%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1224-1230
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• 2020

Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.