• Journal of Fashion Business
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• v.15 no.6
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• pp.1-22
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• 2011

This paper is a study on the information required for developing Korean clothing products intended for Chinese students in Korea and for opening markets of Korean clothing and brands in China. It analyses the buying behaviors, purchasing ability, the favourite apparel type for clothing, and satisfaction with Korean clothing and brands of Chinese students in Korea, with which it seeks a program for South Korea branding to enter into the Chinese clothing market. Three hundred fifty seven students of Hannam University and PaiChai University Chung nam National University in Daejeon-city took part in this study. This paper adopts Descriptive Analysis, Crossing Analysis, Bivariate Correlations, and One-way ANOVA in SPSS 17.0 with Post Hoc Multiple Comparisons to know about the impact of demographic variables of Chinese students in Korea on buying information sources, the criteria for store selection, buying capacity, praise degree on various properties of Korean clothes products and their satisfaction with Korean clothes products. The first proposal of expanding China market for Korean merchants is to achieve maximum sales based on sales promotion strategies, such as the credit card corporations, the store display and sales person service development, SPA, design size development, and to upgrade consumption values. The second proposal is Korean clothes corporations should open the Internet shopping corresponding to the physical stores, the most frequently used information source of Chinese students is the network, from the age distribution of Internet users in 2008 in China, population above 10 and below 30 accounts for 66.7% of all users, In recommending clothes made in Korea to Chinese young people, on-line advertising will get better effects than other strategies, specially during advertisement, they should take good use of Korean television shows and variety shows or help Chinese poor areas to do the social contribution hereby to improve the public image of Korean clothes corporations, which can bring good sale promotion effects as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.115-123
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• 2015

As LTE service and smartphone are emerging as the mainstream of mobile communications market, the value and importance of mobile data service has been further increased. MNO(mobile network operator)s already recognized the data service as essential market needs, and have appealed to consumers based on various satisfaction elements of data service such as faster transmission speed, expended data volume provided as default, and introduction of unlimited plan. So, in the smartphone market where has been mature, investigating what service attributes affect users' selection of data service is very meaningful from the perspectives of both the industry and the academic. Under this background, this study explores determinants influencing consumer's choice for mobile data service and analyzes relative importance of the attributes among different type of users. The findings of this study makes us extend our understanding of consumer characteristics and their service needs in data service centric era, and it provides some implications for establishing telecommunications policies and business strategies.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.6
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• pp.264-273
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• 2006

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) by means of consecutive optimization and also discuss its comprehensive design methodology involving mechanisms of genetic optimization. The network is based on a structurally as well as parametrically optimized fuzzy polynomial neurons (FPNs) conducted with the aid of information granulation and genetic algorithms. In structurally identification of FPN, the design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). For the parametric identification, we obtained the effective model that the axes of MFs are identified by GA to reflect characteristic of given data. Especially, the genetically dynamic search method is introduced in the identification of parameter. It helps lead to rapidly optimal convergence over a limited region or a boundary condition. To evaluate the performance of the proposed model, the model is experimented with using two time series data(gas furnace process, nonlinear system data, and NOx process data).

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.8-17
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• 2014

In this research, we employed various data mining techniques to build predictive models for win-loss prediction in Korean professional baseball games. The historical data containing information about players and teams was obtained from the official materials that are provided by the KBO website. Using the collected raw data, we additionally prepared two more types of dataset, which are in ratio and binary format respectively. Dividing away-team's records by the records of the corresponding home-team generated the ratio dataset, while the binary dataset was obtained by comparing the record values. We applied seven classification techniques to three (raw, ratio, and binary) datasets. The employed data mining techniques are decision tree, random forest, logistic regression, neural network, support vector machine, linear discriminant analysis, and quadratic discriminant analysis. Among 21(= 3 datasets${\times}$7 techniques) prediction scenarios, the most accurate model was obtained from the random forest technique based on the binary dataset, which prediction accuracy was 84.14%. It was also observed that using the ratio and the binary dataset helped to build better prediction models than using the raw data. From the capability of variable selection in decision tree, random forest, and stepwise logistic regression, we found that annual salary, earned run, strikeout, pitcher's winning percentage, and four balls are important winning factors of a game. This research is distinct from existing studies in that we used three different types of data and various data mining techniques for win-loss prediction in Korean professional baseball games.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.407-416
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• 2020

Recent complex battle field demands Network Centric Warfare(NCW) ability to control various parts into a cohesive unit. In path planning filed, the NCW ability increases complexity of path planning algorithm, and it has to consider a communication coverage map as well as traditional parameters such as minimum radar exposure and survivability. In this paper, pros and cons of various propagation models are summarized, and we suggest a coverage map generation method using a Longley-Rice propagation model. Previous coverage map based on line of sight has significant discontinuities that limits selection of path planning algorithms such as Dijkstra and fast marching only. If there is method to remove discontinuities in the coverage map, optimization based path planning algorithms such as trajectory optimization and Particle Swarm Optimization(PSO) can also be used. In this paper, the Longley-Rice propagation model is used to calculate continuous RF strengths, and convert the strength data using smoothed leaky BER for the coverage map. In addition, we also suggest other types of rough coverage map generation using a lookup table method with simple inputs such as terrain type and antenna heights only. The implemented communication coverage map can be used various path planning algorithms, especially in the optimization based algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.831-834
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• 2011

LEACH(One of the leading algorithms in the field of WSN) for the life of the system, even by the number of all nodes to ensure that the cluster header. However, each round does not guarantee a certain number of cluster header. So sometimes cluster header is elected of small number or not elected. If cluster header number is to small, takes a heavy load on cluster header. And empty cluster is occur depending on the location of the cluster header. The algorithm proposed in this paper, the area of interest is divided into sectors. And randomly, cluster header be elected one the in each sector. When clustering the sensor nodes will belong to the nearest cluster header. So clustering is independent of the sector. This algorithm is guarantee a certain number of cluster header in each round. And has prevent occurrence of empty cluster.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.787-793
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• 2008

3GPP evolved packet system (EPS) is an all-IP based system that supports various access networks such LTE, HSPA/HSPA+, and non-3GPP networks. Recently, the support of IP flows with packet level QoS profiles was added to the requirements of the EPS. This paper proposes an adaptive modulation and coding (AMC) scheme that supports the QoS of such IP flows in the 3G LTE access network of the EPS. Defining the retransmission as a critical factor for QoS, the proposed scheme applies different maximum packet error probability $P_{max}$ to each packet when selecting the AMC transmission mode. In determining $P_{max}$, the QoS constraints and NACK-to-ACK error as well as channel condition are considered, balancing two objectives: the satisfaction of the QoS and the maximization of spectral efficiency. The simulation results show that it is able to reduce both delay violation and status report by 10%, while improving the throughput 10% in comparison with an existing scheme.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1797-1803
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• 1997

Message handling function of the SS7(Signaling System N0.7) provides signaling traffic routing capabilities to transfer the signaling traffic to the destination nodes in the signaling network. This message handling function should be handled without any transfer delay for real time processing of large amount of signaling traffic for data communication service, and visual information service. In this paper, we suggest two routing algorithms working on the distributed message handling processors which were specially designed for message handling function. The one is an internal distributing algorithm for equal distribution of signaling traffic among the distributed message handling processors and the other is a distributing algorithm for distribution of signaling traffic in the multiple signaling routes. Both of algorithms are using signaling link selection codes labled in each signaling messages. It is shown that the suggested algorithms are very efficient for routing signaling traffic at the fault condition of signaling routes and the restoration of unavailable signaling routes.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.424-436
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• 2003

In this paper, we propose the Centroid-based Backbone Core Tree(CBCT) generation algorithm for the shared tree-based IP multicasting. The proposed algorithm is based on the Core Based Tree(CBT) protocol. Despite the advantages over the source-based trees in terms of scalability, the CBT protocol still has the following limitations; first, the optimal core router selection is very difficult, and second, the multicast traffic is concentrated near a core router. The Backbone Core Tree(BCT) protocol, as an extension of the CBT protocol has been proposed to overcome these limitations of the CBT Instead of selecting a specific core router for each multicast group, the BCT protocol forms a backbone network of candidate core routers which cooperate with one another to make multicast trees. However, the BCT protocol has not mentioned the way of selecting candidate core routers and how to connect them. The proposed CBCT generation algorithm employs the concepts of the minimum spanning tree and the centroid. For the performance evaluation of the proposed algorithm, we showed the performance comparison results for both of the CBT and CBCT protocols.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1124-1134
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• 2003

The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it expectedly helps us to exactly predict and diagnose cancer. It is essential to efficiently analyze DNA microarray data because the amount of DNA microarray data is usually very large. Since accurate classification of cancer is very important issue for treatment of cancer, it is desirable to make a decision by combining the results of various expert classifiers rather than by depending on the result of only one classifier. Generally combining classifiers gives high performance and high confidence. In spite of many advantages of ensemble classifiers, ensemble with mutually error-correlated classifiers has a limit in the performance. In this paper, we propose the ensemble of neural network classifiers learned from negatively correlated features using three benchmark datasets to precisely classify cancer, and systematically evaluate the performances of the proposed method. Experimental results show that the ensemble classifier with negatively correlated features produces the best recognition rate on the three benchmark datasets.