• Journal of the Korean Geographical Society
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• v.43 no.4
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• pp.526-543
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• 2008

Based on the social network analysis(SNA), this study examines the structural and spatial characteristics of the actor networks of the manufacturing industries for the elderly. In the field of economic geography, former researches on network have mainly focused on the network governance. However, this study focused on the social network analysis. Centrality indexes are used to analyze the topological structure of actor networks of firms and organizations. In order to investigate the spatial structure of actor networks, not only the regional distribution of actors but also the correlation between centrality index and distance are analyzed. Network matrixes among actors are transformed to network matrixes among regions using block modeling method to reveal the spatial characteristics of the actor networks. In spite of the importance of the Capital Region, networks in the non-Capital Region like Chungnam and Pusan were showed high network density. This suggested that some kinds of policy project operating in the non-Capital Region had the influence on this network in the initial stage of industry.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.729-741
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• 1999

ATM networks are widely deployed as the network that is capable of supporting multimedia services efficiently now. To date, a large portion of ATM connections, particularly in the WAN environment, have been of a permanent virtual circuits-requiring management intervention for set-up and tear-down. However, switched virtual circuits are required to support a range of desired characteristics on demand, to a reachable end user. To establish, maintain and release on-demand call/connections, the user-network interface(UNI) and node-node interface(NNI) signalling capabilities are required. Two protocols have been specified for NNI signalling within a public network: the broadband integrated-services user part(B-ISUP) protocol specified by the ITU-T, and the private network-network interface(PNNI) protocol specified by the ATM Forum. PNNI offers different type of internetwork or internodal interface from the traditional B-ISUP approach favored to date public network operators. In spite of its name, PNNI may find its place in network service provide networks as well as in private networks. Thus many public network operators and ATM equipment manufacturers are still unable to choose the NNI interface architecture of their system. In this paper, we survey the characteristics of the B-ISUP and PNNI protocols, and investigate the applicability issue of these specifications to the ATM-based Information Infra-Network of Korea. Analyzing the characteristics of the two protocols and clarifying the NNi requirements of the ATM-based Information Infra-Network of Korea, we propose that the B-ISUP protocol is more suitable than PNNI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3761-3771
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• 2010

This study, based on social capital theory, aims to explore how social network characteristics among organization members affect the absorptive capacity which is the ability to recognize the value of new information, assimilate it, and apply it to commercial ends. This paper also empirically investigates how the absorptive capacity will have an effect on organizational innovation performances toward achieving competitive advantages in the knowledge society. According to the degree of relationship intensity, social network shows two different characteristics: strong tied network and weak tied network. As strong tied network and weak tied network have relatively different network characteristics, this study assumes that each network affects the absorptive capacity with different aspects. Furthermore, we consider the moderation effect of a social network manager's ability in the relationship between social network and absorptive capacity. We surveyed innovative project performers who are engaged in the knowledge based industries. The empirical analysis results show that both strong tied and weak tied network positively affect the absorptive capacity. Successively, the absorptive capacity also has a positive impact on innovation performances.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.555-561
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• 2009

The established mathematical modeling methods have limitation to know the hydraulic characteristics at the wastewater treatment plant which are complex and nonlinear systems. So, an artificial neural network (ANN) model based on hydraulic characteristics is applied for modeling wastewater quality of a full-scale wastewater treatment plant using DNR (Daewoo nutrient removal) process. ANN was trained using data which are influents (TSS, BOD, COD, TN, TP) and effluents (COD, TN, TP) components in a year, and predicted the effluent results based on the training. To raise the efficiency of prediction, inputs of ANN are added the influent and effluent information that are in yesterday and the day before yesterday. The results of training data tend to have high accuracy between real value and predicted value, but test data tend to have lower accuracy. However, the more hydraulic characteristics are considered, the results become more accuracy.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.251-257
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• 1998

Spherical space frame structure with triangular network pattern, which has the various characteristics for the mechanic property, a funtional property, an aesthetic property and so on, has often been used as one of the most efficient space structures. It is expected that this type will be used widely in large-span structural roofs. But because this structure is made of network by combination of line elements there me many nodes therefore, the structure behavior is very complicated and there can be an overall collapse of structure by buckling phenomenon if the external force reaches a limitation. This kind of buckling is due to geometric shape, network pattern, the number of layer and so on, of structure. Therefore spherical space frame with triangle network pattern have attracted many designers and researchers attention all over the world. The number of layer of space frame is divided in to the simgle, double, multi layer. That is important element which is considered deeply in the beginning of structural design. The buckling characteristics of single-layer model and double-layer model for the spherical space frame structure with triangular network pattern are evaluated and the buckling loads of these types are compared with investigation their structural efficiency in this study.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.75-84
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• 2021

For analyzing big data, the social network is increasingly being utilized through relational data, which means the connection characteristics between entities such as people and objects. When the relational data does not exist directly, a social network can be configured by calculating relational data such as attribute similarity from attribute data of entities and using it as links. In this paper, the composition method of the social network using the attribute similarity between entities as a connection relationship, and the clustering method using subgroups for the configured social network are suggested, and the clustering effectiveness of the clustering results is evaluated. The analysis results can vary depending on the type and characteristics of the data to be analyzed, the type of attribute similarity selected, and the criterion value. In addition, the clustering effectiveness may not be consistent depending on the its evaluation method. Therefore, selections and experiments are necessary for better analysis results. Since the analysis results may be different depending on the type and characteristics of the analysis target, options for clustering, etc., there is a limitation. In addition, for performance evaluation of clustering, a study is needed to compare the method of this paper with the conventional method such as k-means.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• Convergence Security Journal
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• v.20 no.4
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• pp.197-208
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• 2020

Based on the network infrastructure advanced in the information knowledge society, the structure of computer net work is operated by establishing the composition of network in various forms that have secured the security. In case of computer network of national/public organizations, it is necessary to establish the technical and managerial securit y environment even considering the characteristics of each organization and connected organizations. For this, the im portance of basic researches for cyber training by analyzing the technical/managerial vulnerability and cyber threats based on the classification and map of cyber threats according to the characteristics of each organization is rising. T hus, this study aims to analyze each type of external/internal cyber threats to computer network of national/public o rganizations established based on the dualistic infrastructure network of internet and national information network, a nd also to present the cyber threat framework for drawing the elements of cyber security training, by drawing and analyzing the actual elements of cyber threats through the case-based scenario.

• 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.