• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.99-108
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• 2010

The traffic classification is a preliminary but essentialstep for stable network service provision and efficient network resource management. While various classification methods have been introduced in literature, the payload signature-based classification is accepted to give the highest performance in terms of accuracy, completeness, and practicality. However, the collection and maintenance of up-to-date signatures is very difficult and time consuming process to cope with the dynamics of Internet traffic over time. In this paper, We propose an automatic payload signature generation mechanism which reduces the time for signature generation and increases the granularity of signatures. Furthermore, We describe a signature update system to keep the latest signatures over time. By experiments with our campus network traffic we proved the feasibility of our mechanism.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.29-39
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• 2006

With the increasing popularity of the wireless network, the vulnerability issue on IEEE 802.1x Wireless Local Area Network (WLAN) are more serious than we expected. Security issues range from mis-configured wireless Access Point(AP) such as session hijacking to Denial of Service(DoS) attack. We propose a new system based on intrusion detection or prevention mechanism to protect the wireless network against these attacks. The proposed system has a security solution on AP that includes an intrusion detection and protection system(IDS/IPS) as an embedded module. In this paper, we suggest integrated wireless IDS/IPS module on AP with wireless traffic monitoring, analysis and packet filtering module against malicious wireless attacks. We also present that the system provides both enhanced security and performance such as on the university wireless campus network.

• Journal of the Korean Society of School Health
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• v.22 no.2
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• pp.169-181
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• 2009

Purpose: Mood disorders such as depression and bipolar disorder are a major mental health problem in college students. We investigate the prevalence of depression and bipolar disorder and the relevance of risk factors for these mood disorders among one college freshmen. Methods: The subjects were 2,865 college students who entered one university located in Seoul and Ansung in 2009. We used BDI (Beck Depression Inventory) for depression assessment and K-MDQ (Mood Disorder Questionnaire) for bipolar disorder assessment. Demographic and socioeconomic factors were measured by questionnaire. Height, weight, blood pressure, total cholesterol, complete blood cell count, and liver function test data were obtained by physical examination for freshmen. Chi-square test and multiple logistic regression were performed to analyze the possible risk factors for depression and bipolar disorder. Results: With different BDI cutoff value, 16 and 21, the prevalence of depression was 8.7% (male: 7.6%, female: 10.1%) and 2.4% (male: 2.5%, female: 2.3%), separately. 'Low economic status', 'urban birth place', and 'low grade at entrance' were significantly associated with depression. Using the original cutoff criterion, defined as clustering of 7 or more symptoms that caused moderate or severe problems, the prevalence of bipolar disorder was 1.3% (male: 1.4%, female: 1.1%). The risk factor of bipolar disorder was academic fields (art fields). Conclusion: Depression and bipolar disorder are common disease in college freshmen. Therefore, Campus-based mental health service program is needed to help with prevention of and early intervention of these mood disorders.

• Journal of Fashion Business
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• v.24 no.4
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• pp.85-98
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• 2020

The Internet of Things (IoT) shopping environment can provide benefits and risks to consumers, including shopping convenience and invasion of consumer rights, respectively. We experimentally tested whether exposure to information regarding the benefits and risks of IoT shopping would elicit changes to consumer perceptions of the importance of shopping convenience and rights to information, as well as shopping intention among young online shopping consumers. The participants (N=218) were randomly assigned into one of two experimental conditions. The control group was exposed to a news article and a video emphasizing the shopping convenience of the Amazon Dash Button service, while the experimental group was exposed to the same news article and video provided to the control group, along with a news article about the judgment of the Munich court that the Dash Button violates German consumer law. We found an interaction effect of experimental condition and time on changes to the perceived importance of shopping convenience and shopping intention. The changes to the perceived relative importance of shopping convenience to consumer rights to information from pre- to post-manipulation differed significantly between the two experimental groups. The results of this study emphasize the importance of providing information on both the benefits and risks of IoT shopping. This was the first experimental study to examine the possibility of the invasion of consumer rights to information in the IoT shopping environment. This study urges researchers, marketers, and policy makers to focus more on consumer rights to information in the newly coming IoT shopping environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1287-1294
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• 2010

The traffic classification is a preliminary and essential step for stable network service provision and efficient network resource management. While a number of classification methods have been introduced in literature, the payload signature-based classification method shows the highest performance in terms of accuracy, completeness, and practicality. However, the payload signature-based method has a significant drawback in high-speed network environment that the processing speed is much slower than other classification method such as header-based and statistical methods. In this paper, We describes various design options to improve the processing speed of traffic classification in design of a payload signature based classification system and describes our selections on the development of our traffic classification system. Also the feasibility of our selection was proved through experimental evaluation on our campus traffic trace.

• Industry Promotion Research
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• v.1 no.2
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• pp.103-108
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• 2016

This study analyzed the effect of female insurance planners' personal traits on job performance in Dangjin, Chungnam. The study results showed that job importance recognition(p<.05, ${\beta}=.321$) significantly affected job satisfaction, so highly recognizing the importance and social reputation improved job satisfaction. Personal traits didn't significantly affected contract performace and workplace satisfaction, but job performance varied by continuos service year. This study provided implications by finding out the degree of importance of personal traits on job performance improvement and verifying the effect of personal factors on performace enhancement of female insurance planners.

• Journal of the Korean Society for Railway
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• v.16 no.4
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• pp.305-310
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• 2013

In general, it is difficult to measure dynamic responses of a bridge with stepwise increasing speed of a train during commercial service on a high speed railroad. However, before opening the 2nd stage of the Gyeongbu high speed railroad, there was an opportunity for field tests and measurements of the bridge with stepwise increasing speed(from 170km/ h to 315km/h). The measured responses were compared with the results of a developed bridge/train interaction analysis. Although good agreement was found throughout almost the entire range of speeds, relatively large differences were found in the vicinity of the critical speed at which resonance behavior of the bridge occurs. To investigate the cause of this, reanalyses are performed with re-estimated damping ratios from field tests.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.237-262
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• 2011

The purpose of this study is to understand the acceptance of the electronic journals among undergraduate students. Using a survey questionnaire, this study collected the data collected from 813 students taking 11 courses offered in five different universities. The levels of electronic jounal and its service awareness appeared to be low as 63.7% and 59.9% respectively. Only 43.8% of the respondents report their experience of using Korean e-journals. There is a statistically significant difference in use among college groups and students' major of study. E-journals are mostly used off-campus and within the library, using simple search techniques. In spite of difficulties in search and gathering information, the satisfaction level marked above average. Reasons of nonuse are lack of opportunity and knowledge. However, 93.8% of nonusers report a willingness to use the e-journals in the future. LIS students show higher e-journal awareness and use experience compared to non-LIS students. Yet, the levels of using simple search techniques and satisfaction show little difference from those of the non-LIS students. The findings of the study suggest implications to promote the acceptance of e-journals among college students.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.725-732
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• 2002

Presented is a Genetic Algorithm (GA) for dynamic partitioning an ATM LANE(LAN Emulation) network. LANE proves to be one of the best solutions to provide guaranteed Quality of Service (QoS) for mid-size campus or enterprise networks with minor modification of legacy LAN facilities. However, there are few researches on the efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, proposed is a decision model named LANE Partitioning Problem (LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs (ELANS), each of which works as an independent virtual LAN.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.65-73
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• 2009

IEEE802.11 Wireless LAN(WLAN) is being widely used in public space such as airport, and increases the networking boundary in campus and enterprise, and it has lastly attracted considerable attention for mesh network and converged network with other 3G mobile communication networks. In WLAN, load balancing among Access Points(AP) is an important issue for efficient resource management or supporting the Quality of Service(QoS) of traffic, but most researches focused on the AP selection in network entry or roaming of Stations(STA). In this paper, we propose an AP-Initiated Flow Redirection(FR) for AP load balancing by monitoring AP's availability in the true sense. When the AP's resource becomes almost saturated, that is used more than a specific threshold, the AP queries the roaming possible neighbor APs about their availability and calculates the distribution of traffic load with statistical methods such as entropy or chi-square. Finally, the AP decides flows and new APs for redirection and performs it. Our simulation results show that our FR mechanism increases the performance in the various views.