• Journal of Fashion Business
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• v.10 no.4
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• pp.1-15
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• 2006

The purpose of this study was to analyze the image perception of dress shirts according to perceiver's residency and shirts style, and to investigate the shirts preference according to style of dress shirts, and to find out the men's aesthetics consciousness for shirts, and to analyze between the image perception and the usage of mass-media, for developing the possibility & strategy of the dress shirts market in men's wear market for the apparel marketers and manufactures. For this study, the data obtained from 321 respondents were analyzed by descriptive statistics, Pearson's simple correlation, ANOVA. The results from the study were as follow ; The 6 stimuli for image perception rated on 5 point Likert-type scales in the 12 features were evaluated by perceivers. By the best 3 features abstracted, shirts style concepts were decided such as, Basic style by the best 3 features of the first stimulus, and Soft style by the best 3 features of the second stimulus, and Sophisticate style by the best 3 features of the third stimulus, and Modern casual style by the best 3 features of the fourth stimulus, and Modern mannish style by the best 3 features of the fifth stimulus, and Trendy style by the best 3 features of the sixth stimulus. The modern casual style was estimated highly by respondents in Daejon. The respondents in Seoul prfered the basic style to other style. There were significant differences in evaluating between preferences of shirts style and pattern. Of the 82 respondents(26.8%) with the preference of bold london stripe, the 52 respondents estimated Modern casual style in bold london stripe. The fashion consciousness of the respondents in Seoul was estimated higher than in Daejon. But, the respondents in Daejon in the consciousness for the coordination knit cardigan and V zone was estimated higher than in Seoul. Also, the 31 respondents with the preference of Sophisticate style were the highest in fashion consciousness. The respondents estimated that the first important thing in buying dress shirts is 'Design(41.4%). and next is quality(17.8%). Results revealed that Daks ranked best brand (13.7%), and Renoma ranked best two brand (6,5%). And, the 35.5% respondents estimated that the first important information which influenced on buying dress shirts was the store display, next was internet(15.9%). Finally, I propose that the best strategy for men with low fashion consciousness is to upgrade salesmen' coordination technic and fabric knowledge, and store management with story attracting customers.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.821-830
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• 2006

As internet worms are spread out worldwide, the detection and filtering of worms becomes one of hot issues in the internet security. As one of implementation methods to detect worms, the Linux Netfilter kernel module can be used. Its basic operation for worm detection is a string matching where coming packet(s) on the network is/are compared with predefined worm signatures(patterns). A worm can appear in a packet or in two (or more) succeeding packets where some part of worm is in the first packet and its remaining part is in its succeeding packet(s). Assuming that the maximum length of a worm pattern is less than 1024 bytes, we need to perform a string matching up to two succeeding packets of 2048 bytes. To do so, Linux Netfilter keeps the previous packet in buffer and performs matching with a combined 2048 byte string of the buffered packet and current packet. As the number of concurrent connections to be handled in the worm detection system increases, the total size of buffer (memory) increases and string matching speed becomes low In this paper, to reduce the memory buffer size and get higher speed of string matching, we propose a string matching scheme without using buffer. The proposed scheme keeps the partial matching result of the previous packet with signatures and has no buffering for previous packet. The partial matching information is used to detect a worm in the two succeeding packets. We implemented the proposed scheme by modifying the Linux Netfilter. Then we compared the modified Linux Netfilter module with the original Linux Netfilter module. Experimental results show that the proposed scheme has 25% lower memory usage and 54% higher speed compared to the original scheme.

• Information Systems Review
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• v.22 no.1
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• pp.147-165
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• 2020

The sharing economy service is now spreading in various fields such as accommodation, cars and bicycles. In particular, bicycle-sharing service have become very popular around the world, and since September 2015, Seoul has been providing a bicycle-sharing service called 'Ttareungi'. However, the number of bicycles is unbalanced among rental stations continuously according to the user's bicycle use. In order to solve these problems, we employed social network analysis using Ttareungi data in Seoul, Korea. We analyzed degree centrality, closeness centrality, betweenness centrality and k-core. As a result, the degree centrality was found to be closely linked with bus or subway transfer center. Closeness centrality was found to be in an unbalanced departure and arrival frequency or poor public transport proximity. Betweenness centrality means where the frequency of departure and arrival occurs frequently. Finally, the k-core analysis showed that Mapo-gu was the most important group by time zone. Therefore, the results of this study may contribute to the planning of relocation and additional installation of bike rental station in Seoul.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.529-538
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• 2012

This study analyzed a variety of different kinds of usage patterns of four-digit personal identification numbers(PINs) based on the data collected from students attending at A-university in 2011. According to the analysis, the 4 digit PINs '1234' was being used most frequently which is similar to the findings of the study by the Daniel Amitay research. In addition, almost 50 percent of the students were using the four-digit PINs closely related to their personal information, and more than 10 percent of them were using it only by the reason of easiness to remember or convenience to use. Number '0' was the most frequently used, and girl students used it more than boys did. According to the result of analysis of four-digit PINs, it was found that number '1' was the most frequently used in the first and the third position. It was also found that number '2' and number '4' were the most frequently used in the second and the forth position respectively. Among students who had used number 3 in third position, around 63.6 percent of those students were using number 4 in the forth position in their PINs which showed highest frequency from analysis of double-digits connected together in each position. The analysis of PINs were represented by the polygonal (type) graph with that X-axis showed from first to forth position and Y-axis showed number had been used at each position. Among many polygonal graphs, the form showed an N-type which was called in type 1 took the first place by 35 percent.

• Journal of Biomedical Engineering Research
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• v.24 no.5
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• pp.411-419
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• 2003

This paper aims at developing 'gyro-mouse' which provides decent and comfortable human-computer interface that supports the usage of such software as an internet-browser in PC for the people paralyzed in upper limbs. This interface operates on information collected from head movement to get the cursor control. The interface is composed of two modules. One is hardware module in which the head horizontal and vertical angular velocities are detected and transmitted into PC. The other is a PC software that translates the received data into movement and click signals of the mouse. The ANN (artificial neural network) learns the quick nodding pattern of each user as click input so that it can provide user-friendly interface. The performance of the system was evaluated by three indices that are click recognition rate. error in cursor position control. and click rate of the moving target box. The performance result of the gyro-mouse was compared with that of the optical-mouse to assess the efficiency of the gyro-mouse. The average click recognition rate was 93%, average error in cursor position control was 1.4∼5 times of optical mouse. and the click rate with 50 pixels target box was 40%(30 clicks/min) to that of optical mouse. The click rate increased monotonously with the number of trial from 35% to 44%. The suggested system is expected to provide a new possibility to communicate with the society.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.461-470
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• 2005

This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

• Journal of Families and Better Life
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• v.29 no.2
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• pp.23-37
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• 2011

This study examined the preference and the purchase intention of male and female from 20s through 405 to smart phones. This study verified the differences between the groups according to the socio-demographic factors, the usage pattern of mobile phone, and the perceived cost and the expected benefit. The analysis of the relative influence of those relevant factors was followed. The summaries of this study are as follows; First, the high level factors in purchasing smart phones were the perceived cost and the expected benefit pointed over 3.82. It means that they arc interested in smart phones highly, and if they can support to buy smart phones and situations can be permitted, they would like to buy them. Second, the differences between groups of the preference and the purchase intention were found according to the ages, the marital status and the education level. The results showed that those preference and the purchase intension were measured high at the group of the 20s-30s, the married, and the higher educational level of collage students. Third, expected benefit on smart phones was shown to be divided into two characterized factors through factor analysis. One was 'functional expected benefit' and the other was 'emotional expected benefit'. The functional and the emotional benefit on the using of smart phones were presented high level in group of over graduated students. Forth, the results of the stepwise multiple analysis, which was carried out to find out the influencing factors on the preference and the purchasing intension to smart phones, showed that the most effective factor was the functional expected benefit. The self-expressive propensity, and the education level were followed sequentially. The purchase intention was influenced by both of the functional and the emotional expected benefit. The result of this study shows that the level of the consumer's perceived cost(economic, psychological) and the expected benefit were measured high at the same time. That means that it is necessary to make the consumer information and communicating smoothly in order to lower the cost and enhance the benefit. In addition, This study has its meaning because it found out that functional expected benefit is a factor which has an influence on the Consumer Preference and Purchase Intention on Smart phone. If consumer's function requirements on smart phone are satisfied, it will be able to reduce the consumer problems and increase the consumer satisfaction. The result of this study would be applicable when Smart Phone is used as one of the auxiliary tools for smart consumption.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.69-85
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• 2006

Broadcast has been often used to disseminate the frequently requested data efficiently to a large volume of mobile clients over a single or multiple channels. Conventional concurrency control protocols for mobile transactions are not suitable for the wireless broadcast environments due to the limited bandwidth of the up-link communication channel. In wireless broadcast environments, the server often broadcast different data items with different frequency to incorporate the data access patterns of mobile transactions. The previously proposed concurrency control protocols for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. However, these protocols perform poorly when the data access pattern of update mobile transaction are not uniform but skewed. The update mobile transactions with skewed data access patterns will be frequently aborted and restarted due 4o the update conflict of the same data items with a high access frequency. In this paper, we propose an energy-efficient concurrence control protocol for mobile transactions with skewed data access as well as uniform data access patterns. Our protocol use a random back-off technique to avoid the frequent abort and restart of update mobile transactions. We present in-depth experimental analysis of our method by comparing it with existing concurrency control protocols. Our performance analysis show that it significantly decrease the average response time, the amount of upstream and downstream bandwidth usage over existing protocols.

• Management & Information Systems Review
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• v.36 no.3
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• pp.131-150
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• 2017

The purpose of this study is to observe the spread pattern of open source software (OSS) while establishing relations with surrounding actors during its operation period. In order to investigate the change pattern of participants in the OSS, we use a netnography on the basis of online data, which can trace the change patterns of the OSS depending on the passage of time. For this, the cases of three OSSs (e.g. jQuery, MooTools, and YUI), which are JavaScript frameworks, were compared, and the corresponding data were collected from the open application programming interface (API) of GitHub as well as blog and web searches. This research utilizes the translation process of the actor-network theory to categorize the stages of the change patterns on the OSS translation process. In the project commencement stage, we identified the type of three different OSS-related actors and defined associated relationships among them. The period, when a master commences a project at first, is refined through the course for the maintenance of source codes with persons concerned (i.e. project growth stage). Thereafter, the period when the users have gone through the observation and learning period by being exposed to promotion activities and codes usage respectively, and becoming to active participants, is regarded as the 'leap of participants' stage. Our results emphasize the importance of promotion processes in participants' selection of the OSS for participation and confirm the crowding-out effect that the rapid speed of OSS development retarded the emergence of participants.