• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.5
• /
• pp.818-828
• /
• 2018

Nowadays, various security systems are developed and used for protecting information on the network. Although security solutions can prevent some of the security risks, they provide high performance only if used appropriately in accordance with their purposes and functionality. Security solutions commonly used in information protection systems include firewalls, IDS, and IPS. However, despite various information protection systems are introduced, there are always techniques that can threaten the security systems through bypassing them. The purpose of this paper is to develop effective training techniques for responding to the bypass attack techniques in the information security systems and to develop effective techniques that can be applied to the training. In order to implement the test bed we have used GNS3 network simulator, and deployed it on top of virtual operating system using VirtualBox. The proposed correspondence training scenario against bypassing information protection system attacks could be very effectively used to counteract the real attacks.

• Childhood Kidney Diseases
• /
• v.5 no.2
• /
• pp.136-146
• /
• 2001

Purpose : One of the most difficult problems in the care of children with nephrotic syndrome remains the occurrence of relapses, despite initial response to steroids. Constantinescu reported that rapidity of initial response to steroid therapy could predict fewer relapses in the first year. So we evaluated the changes in serum lipid abnormalities in children with corticosensitive nephrotic syndrome before steroid treatment and the correlation between serum lipid levels and renal function, days to remission. Methods . We analyzed the Medical records of children who were managed by us between October 1994 and August 2000. In 33 patients with corticosensitive nephrotic syndrome, we evaluated the correlation between serum lipid levels and renal function [Creatinine clearance(Ccr)] and proteinuria before steroid treatment, and days to remission defined as the third day when the patient's urine becomes protein free. Results : There were 21 males and 12 females. Median age at presentation was 6.4 years (range: 1.8-17.3 years). Median days to remission were 15.4 days (range 4-42 days) on Prednisolone $60mg/m^2$ daily. The increased levels of triglyceride, total cholesterol, LDL cholesterol, apolipoprotein B, total cholesterol/HDL cholesterol, Lipoprotein(a) were observed. But the level of HDL cholesterol was not increased. Serum albumin was decreased a]id proteinuria was increased before steroid treatment. But Ccr was not decreased. There were negative correlation between serum albumin and total cholesterol (r = -0.5157, P<0.005), LDL cholesterol (r = -0.5543, P<0.005), total cholesterol/HDL cholesterol (r = -0.4506, P<0.01), lipoprotein(a) (r = -0.4570, P<0.025), apolipoprotein B (r = -0.5297, P<0.025), apolipoprotein B/apolipoprotein Al (r = -0.5851, P<0.01), apolipoprotein B/HDL cholesterol (r = -0.4961, P<0.05) before steroid treatment. There was no correlation between proteinuria and serum lipid profiles. Also Ccr and serum lipid profiles were not correlated. There was positive correlation between days to remission and HDL cholesterol (r = +0.4511, P<0.05), apolipoprotein B (r = +0.5190, P<0.05), apolipoprotein B/HDL cholesterol (r = +0.7169, P<0.005). Conclusions : This results reveal that HDL cholesterol, apolipoprotein B and apolipoprotein B/HDL cholesterol can be used as a predictive factor in corticosensitive nephrotic syndrome. We could not determine the significant level of these lipids for insufficient patients number, but these level may predict future relapses of corticosensitive nephrotic syndrome patients and thus may allow to better management and treatment protocols. More data and long term follow up studies should be needed. (J Korean Soc Pediatr Nephrol 2001;5 : 136-46)

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.35 no.8
• /
• pp.1088-1096
• /
• 2006

The purpose of this study was to identify the service encounter blueprint by types of restaurants in order to manage moment of truth when customers who visit a restaurant encounter services. The service encounter blueprint gives an overall picture of the service provision to visualize an entire service process and its integrated structure. The blueprint is used for service process analysis technique. The random samples of 15 customers were observed by types of restaurants and the records were collected for three-days' observation. Interviews were performed by 3 managers, 3 service encounter employees, 3 cashiers, 3 cooks and 10 customers by types of restaurants. After drawing the first service blueprint, it was revised by the interview with the 3 managers and 6 service encounter employees. In this paper, restaurant service processes are reviewed and analyzed. By use of service blueprint, the processes are analyzed to find a fail point, customer wait, employee decision. As a result of making a blueprint of service encounter by types of restaurant, blueprints of fine-dining restaurants and family restaurants were similar, while fast-food restaurants showed a little difference. In particular, difference was indicated in a point where interaction of service encounter occurred. Difference was indicated depending on types of restaurants. Therefore, the efforts to improve this problem were needed. The blueprint is a map or flowchart (called a process chart in manufacturing) of all transactions constituting the service delivery process. The results showed that service encounter blueprint can be used to improve the service process in the restaurant's encounter.

• Korean Journal of Social Welfare Studies
• /
• v.47 no.4
• /
• pp.255-280
• /
• 2016

This study examined sexual violence characteristics among the individuals who utilized victim support services provided by National Rape Crisis Intervention Centers in Korea. The study is the part of a Korean longitudinal study on sexual assault characteristics and its implications for post-abuse adjustments, which is supported by Korean Mental Health Technology R&D Project. Eleven national rape crisis centers nationwide and 29 NGO's participated in the study. The participating centers provided the data on sexual abuse characteristics from their standardized case management system. The cases were randomly selected from the system. Total of 1077 cases were gleaned from the system and utilized for this analysis. Results indicated that the abuse characteristics differed by victims' age (children, adolescent vs. adults) as well as relationship with perpetrator. We could identify six different profile groups based on the detailed violence characteristics. The results assured us of the importance to understand the detailed characteristics of sexual violence and the old notion that 'one size may not fit all'. The results from the profile analyses may have important implication for developing victim support programs and appropriately allocating agency resources according to the different profiles of the service users.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.93-111
• /
• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.