• International Journal of Costume and Fashion
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• v.14 no.1
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• pp.1-15
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• 2014

Fashion leadership is divided into visual influence, linguistic influence, and dual leadership. We refer to people exercising such influential power as fashion innovators, fashion opinion leaders, and fashion double leaders, respectively. Scholars and marketers have raised continuous questions on this issue: who are these fashion leaders and what characteristics do they have? In this study, social network analysis is applied to grasp the existence of three types of fashion leaders in college clubs, examine their positions in fashion process networks and investigate their individual and social characteristics. For this study, three college clubs were recruited through convenience sampling and surveyed online. Peer nomination questions for structuring fashion process networks and self-evaluation questions for measuring personal characteristics are included. Two fashion networks, an opinion leadership network and an innovativeness network, embrace four to six leaders and illustrate similar structure patterns in the three groups, which indicates that dual leaders enjoyed the lion's share in college clubs. The number of fashion innovators tends to be fewer compared to that of fashion opinion leaders, and we infer that peer relationship appears to intervene with fashion opinion leadership. Other personal characteristics supporting results from previous studies are also confirmed in this study.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.70-75
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• 1999

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process paramters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry composition micrrostructure appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristicso f penetration through the learning. After learning the neural network can predict the pene-traition desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. partial-penetration single-pass bead-on-plate welds were fabricated in 12mm mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and gurarantee the uniform weld quality.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.464-467
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• 1996

This paper aims to exploit inter/intra-speaker phoneme sub-class variations as criteria for adaptation in a phoneme recognition system based on a novel neural network architecture. Using a subcluster neural network design based on the One-Class-in-One-Network (OCON) feed forward subnets, similar to those proposed by Kung (2) and Jou (1), joined by a common front-end layer. the idea is to adapt only the neurons within the common front-end layer of the network. Consequently resulting in an adaptation which can be concentrated primarily on the speakers vocal characteristics. Since the adaptation occurs in an area common to all classes, convergence on a single class will improve the recognition of the remaining classes in the network. Results show that adaptation towards a phoneme, in the vowel sub-class, for speakers MDABO and MWBTO Improve the recognition of remaining vowel sub-class phonemes from the same speaker

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.169-172
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• 2002

Web-based virtual machine/manufacturing system (VMS) utilizes Virtual Device Network (VDN.) VDN inevitably involves the implementation of Distributed Monitoring and Control Networks (DMCN). In general, one needs to integrate device (control) network and IP network to realize DMCN over IP network or internet, which can be viewed as a VDN. In this study, LonWorks networking technology is used fer device network and the transmission characteristics of LonWorks/IP-based VDN is investigated. A method to minimize the transmission delay in the LonWorks/IP networks is also suggested.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.438-445
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• 2007

In this paper, we consider the problem of optimum selection of quality-of-service(QoS) classes in interworking between the networks in a next-generation-network(NGN) environment. After introducing the delay-cost and loss-cost characteristics, we discuss the time-invariant(TI) and time-variant(TV) scenarios. For the TI case, we show that under nearly lossless transmission condition, each network can make its own optimization regardless of other networks. For the TV case, we present sufficient conditions under which the optimum QoS class of each network can be considered fixed with respect to time without considerable degradation in the optimization target. Therefore, under the conditions presented in this paper, the QoS of a flow in each network can be determined solely by considering the characteristics of that network and this QoS class can be held fixed during the flow period.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.53-58
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• 2003

Wear debris can be collected from the lubricants of operating machinery and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated machinery. But in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefore, if the shape characteristics of wear debris is identified by computer image analysis and the neural network, The four parameter (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction. It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We resented how the neural network recognize wear debris on driving condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10B
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• pp.936-944
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• 2006

In order to enhance their own customer satisfaction index that is one of the top level managerial performance indices, Internet communication service providers endeavor onto establishing a total quality management system. Specifically, it is under discussion that some critical Internet communication network quality characteristics closely related to customer satisfaction index should be controlled aiming to this managerial goal. This paper presents an application scheme of I-MR control charts for monitoring Internet communication network quality characteristics. This statistical quality control scheme generates a signal to practitioners when it detects the network quality characteristics out-of control. It is designed based on; 1) individual measurements; and 2) moving ranges between two consecutive individual measurements collected with a constant time interval. Empirical analyses are illustrated to estimate the expected quality improvement ratios that can be realized with the application scheme proposed in this paper. Assuming that the assignable causes can be revealed and eradicated, regarding two Internet communication services A, B, seven network quality characteristics for each service, eleven distinct measuring spots for each network quality characteristic, the expected quality improvement ratios are calculated with which the effect of the application scheme is evaluated. Results show the ranges of the expected quality improvement ratios; 1) Service A, (1) mean (0.31%-11.44%), (2) standard deviation (9.82%-71.10%): 2) Service B, (1) mean (0.29%-17.64%), (2) standard deviation (8.05%-60.59%). Hence, It is anticipated that the I-MR control charts based application scheme can be effective not only to improving the mean and dispersion of the network quality characteristics concerned but also to maintaining the network quality characteristics in-control consequently.

• Health Policy and Management
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• v.14 no.2
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• pp.1-16
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• 2004

The study purpose was to find which factors affect selection of hospital network types. This study used the 1998 American Hospital Association Annual Survey Database from Health Forum. Among these U.S. hospitals, the researcher selected hospitals located in Metropolitan Statistical Areas. Therefore the final observation cases for analysis are 1,971 Metropolitan Statistical Area hospitals in the United States. To identify significant variables influencing hospital network types, the study used proportional odds logistics regression model on population size, Health Maintenance Organization penetration rate, and market competition rate of area including a hospital, types of hospital ownership, hospital bed size, proportion of Medicare patients and Medicaid patients in total hospital patients, and occupancy rate. Contrary to conventional wisdom, selection of hospital network types was influenced by population size of area which a hospital located, types of ownership, hospital bed size, and proportion of medicare patients rather than Health Maintenance Organization penetration. Population size 1,000,000-2,499,999 had the highest probability of selecting type IV (clinical-vertical integration) from an independent hospital, and a religious group owned hospitals and for-profit owned hospitals had the highest probability of selecting Type IV (clinical-vertical integration) from an independent hospital. A bed size had positive relation on selecting Type IV (clinical-vertical integration) from an independent hospital. Unlikely general belief that the selecting types of hospital network was determined by the change of health insurance policy such as Health Maintenance Organizations and Preferred Provider Organizations, the types of hospital network were influenced by community characteristics such as population size, and hospital characteristics.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.116-130
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• 2012

This study focuses on analyzing the design industry in creative industry in the context of upbringing growth engine of regional development policy and strategy. This research probe the spatial characteristics and inter-organizational network structure change from 2000 to 2010 using social network analysis(SNA) in terms of structural, spatial and temporal aspects. first, with the statistical data of design industry, this research evaluate spatial distribution and agggglomeration compared with 16 cities and 7metropolitan scales in Korea. Next, the group of density in the knowledge network of design industry explained with the spatial characteristics and inter-organizational network evolution in time series. After considering the government policy and strategy providing as a result of establishing regional innovation center strengthen cooperation among industry-university-research center.