• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.776-782
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• 2018

After CNN basic structure was introduced by LeCun in 1989, there has not been a major structure change except for more deep network until recently. The deep network enhances the expression power due to improve the abstraction ability of the network, and can learn complex problems by increasing non linearity. However, the learning of a deep network means that it has vanishing gradient or longer learning time. In this study, we proposes a CNN structure with MLP layer. The proposed CNNs are superior to the general CNN in their classification performance. It is confirmed that classification accuracy is high due to include MLP layer which improves non linearity by experiment. In order to increase the performance without making a deep network, it is confirmed that the performance is improved by increasing the non linearity of the network.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.4_5
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• 2009

A new protection coordination algorithm in Multi-Agent based distribution automation system is proposed in this paper. Distribution network protection coordination is acted by normal state distribution operation. But, in more and more complex distribution network structure, it has a big problem that central server processed all measurement data, coordination setting and controls for operation. So, a algorithm to change coordination setting is proposed automatically in terminal devices which Recloser and OCR to include Multi-Agent concepts in distribution network.

• 전기의세계
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• v.24 no.4
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• pp.80-82
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• 1975

This paper presents a synthesis procedure of multi-channel active filters, which realizes an arbitrary N*N matrix of real rational functions in the complex variable s as a voltage transfer matrix. The resultant network reveals a transformerless grounded active RC(2N+1)-terminal network. The active network is consisted of six 2N-port RC networks with 2N single-ended operational amplifiers.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.1-146
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• 2001

The researches of science and engineering need the latest information from internet resources. But searching and filtering processes of appropriate web documents from huge internet resources are very complex as well as having some repeated procedures. In this paper, I propose a Personalized Agent System(PAS), which can filter World Wide Web Documents that the user is interested, such as papers. To do this, PAS uses a modified spreading activation neural network which 1 propose here. PAS observes the user´s local paper database to analyze, adapt and learn the user interests, and the then constructs the user-specified neural network model by the analyzed interests ...

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.105-108
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• 2002

This paper analytical models of a centralized approach based on SNMP Protocol, distributed approach based on mobile agent, and mixed model which is tile existing mobile agent model in order to overcome large communication numbers of SNMP and accumulated data of mobile agent. And then, we compare and analyze these analytical models. Performance evaluation results show that performance of mobile agent and the mixed model is less sensitive to the network traffic and more profitable for complex network environment than that of SNMP.

• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.15-23
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• 2002

As recently the network environment and application services have been more complex and diverse, there has. In this paper we introduce a scheme the extract useful information for network management by analyzing traffic data in user login file. For this purpose we use classification and association rule based on episode concept in data mining. Since login data has inherently time series characterization, convertible data mining algorithms cannot directly applied. We generate virtual transaction, classify transactions above threshold value in time window, and simulate the classification algorithm.

• Genomics & Informatics
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• v.10 no.4
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.

• Atmosphere
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• v.20 no.3
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• pp.343-353
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• 2010

A regional wind network with complex surface conditions must be designed with sufficient space and time resolution to resolve the local circulations. In this study, the spatial variations of the wind field observed in the Seoul and Jeju regional networks were evaluated in terms of annual, seasons, and months to assess the spatial homogeneity of wind fields within the regional networks. The coherency of the wind field as a function of separation distance between stations indicated that significant coherency was sometimes not captured by the network, as inferred by low correlations between adjacent stations. A meso-velocity scale was defined in terms of the spatial variability of the wind within the network. This problem is predictably most significant with weak winds, dull prevailing wind, clear skies and significant topography. The relatively small correlations between stations imply that the wind at a given point cannot be estimated by interpolating winds from the nearest stations. For the Seoul and Jeju regional network, the meso-velocity scale has typically a same order of magnitude as the speed of the network averaged wind, revealing the large spatial variability of the Jeju network station imply topography and weather. Significant scatter in the relationship between spatial variability of the wind field and the wind speed is thought to be related to thermally-generated flows. The magnitude of the mesovelocity scale was significantly different along separation distance between stations, wind speed, intensity of prevailing wind, clear and cloudy conditions, topography. Resultant wind vectors indicate much different flow patterns along condition of contributing factors. As a result, the careful considerations on contributing factors such as prevailing wind in season, weather, and complex surface conditions with topography and land/sea contrast are required to assess the spatial variations of wind field on a regional network. The results in the spatial variation from the mesovelocity scale are useful to represent the characteristics of regional wind speed including lower surface conditions over the grid scale of large scale atmospheric model.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.128-135
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• 2015

The purpose of this study is to propose a planning method for increasing visitors' usage attraction by understanding user circulation in the large scale commercial complex. Focusing on the impact of anchor tenant on the pedestrian traffic arousing visitors' usage attraction flow, this study analyzed pedestrian circulation and traffic volume of Lotte World Mall, a large scale commercial complex. In this study, the change of pedestrian traffic in the commercial complex was investigated and the circulation flow of anchor tenant visitors such as movie theater in the commercial complex was simulated by computer. By analyzing both characteristics of pedestrian circulation and traffic volume in large scale commercial complex and movie theater users' pedestrian traffic with network-based computer simulation, positive relationship between pedestrian traffic to movie theater and pedestrian traffic dispersion of the whole commercial complex users was emerged. In addition, It is necessary to plan of distributing pedestrian traffic of vertical moving line in central space appropriately for using attraction function of anchor tenant.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.9-20
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• 2021

Abstraction applied in computer networking hides network details behind a well-defined representation by building a model that captures an essential aspect of the network system. Two current methods of representation are available, one based on graph theory, where a network node is reduced to a point in a graph, and the other the use of non-methodological iconic depictions such as human heads, walls, towers or computer racks. In this paper, we adopt an abstract representation methodology, the thinging machine (TM), proposed in software engineering to model computer networks. TM defines a single coherent network architecture and topology that is constituted from only five generic actions with two types of arrows. Without loss of generality, this paper applies TM to model the area of network monitoring in packet-mode transmission. Complex network documents are difficult to maintain and are not guaranteed to mirror actual situations. Network monitoring is constant monitoring for and alerting of malfunctions, failures, stoppages or suspicious activities in a network system. Current monitoring systems are built on ad hoc descriptions that lack systemization. The TM model of monitoring presents a theoretical foundation integrated with events and behavior descriptions. To investigate TM modeling's feasibility, we apply it to an existing computer network in a Kuwaiti enterprise to create an integrated network system that includes hardware, software and communication facilities. The final specifications point to TM modeling's viability in the computer networking field.