• ETRI Journal
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• v.26 no.4
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• pp.360-366
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• 2004

Synchronization Markup Language (SyncML) is a specification of a common data synchronization framework for synchronizing data on networked devices. SyncML is designed for use between mobile devices that are intermittently connected to a network and network services that are continuously available on the network. We have designed and developed a data synchronization system based on the SyncML protocol and evaluated the throughput of the system using the stochastic Petri nets package (SPNP) and analyzed the relationship between the arrival rate and the system resources. Using this model, we evaluate various performance measures in different situations, and we estimate the relationship between the arrival rate and the system resources. From the results, we can estimate the optimal amount of resources due to the arrival rate before deploying the developed system.

• Journal of Physiology & Pathology in Korean Medicine
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• v.26 no.5
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• pp.615-620
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• 2012

This research aims to analyze the trend of subhealth and meebyung(未病) research as a method of network analysis from 2007 to 2011 in China. A total of 3,933 papers were involved in analysis from 5,465 searched papers, which title have '未病', '亞健康' in CNKI (China National Knowledge Infrastructure). It is carried out that counts annual paper number, authors' publicized papers, and journals paper number related to subhealth. Network analysis was performed to reveal collaboration research trend and relations between Authors, Affiliations, and Regions. As a result, Number of related studies have increased for the last 5 years. East and south regions of China, which include Beijing, Guangxi, and Zhejiang have participated most in their studies, and also as collaborated researches. As affiliations, Researches done by College of Traditional Chinese medicine and their hospital's collaborations are most counted. Because of distance limit, many colleges or institutes seem to make contacts with nearby affiliations. This study is the first attempt to perform network analysis on subhealth research trend in CNKI. This study would contribute to related studies in case of network analysis method.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.14-17
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• 2006

To diagnosis abnormal compressor conditions in an air-conditioner, the acoustic emission (AE) signal, which is derived from wear condition, compressed air, and assembly error, was analyzed experimentally. Burst and continuous type AE signals resulted from metal contact and compressed air, and the raw AE signal of compressors was acquired in the production line. After extracting samples using waveforms, the Early Life Test (ELT) was conducted and the waveform was classified as normal or abnormal. Efficient parameters in the waveform pattern were investigated in time and frequency domains and a diagnosis algorithm for air-conditioners using Neural Network estimation is suggested.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.187-188
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• 2009

On this study, the artificial neural network, one of the nonlinear forecasting methods, is compared with ARIMA model through performing a forecast of container traffic. The existing studies have been used the rule of thumb in topology design for network which had a great effect on forecasting performance of the artificial neural network. However, this study applied the genetic algorithm, known as the effectively optimal algorithm in the huge and complex sample space, as the alternative.

• BMB Reports
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• v.45 no.4
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• pp.253-258
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• 2012

The dermal papilla cells (DPCs) of hair follicles are known to secrete paracrine factors for follicular cells. Shotgun proteomic analysis was performed to compare the expression profiles of the secretomes of human DPCs and dermal fibroblasts (DFs). In this study, the proteins secreted by DPCs and matched DFs were analyzed by 1DE/LTQ FTICR MS/MS, semi-quantitatively determined using emPAI mole percent values and then characterized using protein interaction network analysis. Among the 1,271 and 1,188 proteins identified in DFs and DPCs, respectively, 1,529 were further analyzed using the Ingenuity Pathway Analysis tool. We identified 28 DPC-specific extracellular matrix proteins including transporters (ECM1, A2M), enzymes (LOX, PON2), and peptidases (C3, C1R). The biochemically-validated DPC-specific proteins included thrombospondin 1 (THBS1), an insulin-like growth factor binding protein3 (IGFBP3), and, of particular interest, an integrin beta1 subunit (ITGB1) as a key network core protein. Using the shotgun proteomic technique and network analysis, we selected ITGB1, IGFBP3, and THBS1 as being possible hair-growth modulating protein biomarkers.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1066-1070
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• 2002

We propose a neural network based up-trend detector. An auto-associative neural network was trained with 'up-trend' data obtained from the KOSPI 200 future price. It was then used to predict an up-trend Simple investment strategies based on the detector achieved a two year return of $19.8\%$ with no leverage.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1107-1116
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• 2014

In this paper, we review recent developments in network analysis using the graph theory, and introduce ongoing research area with relevant theoretical results. In specific, we introduce basic notations in graph, and conditional and marginal approach in constructing the adjacency matrix. Also, we introduce the Marcenko-Pastur law, the Tracy-Widom law, the white Wishart distribution, and the spiked distribution. Finally, we mention the relationship between degrees and eigenvalues for the detection of hubs in a network.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.3
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• pp.67-81
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• 2018

We tried to analyze qualitatively a total of 110 the research papers which were related domestic ecological restoration technologies about 15 years through semantic network analysis in social network analysis. In order to understand the research trends of ecological restoration technologies, we analyzed the degree centrality and betweenness centrality of the Stream/Wetland, Slope, Soil/Others fields selected as Word Cloud. As a result, ecological restoration technologies have been changed. They were focused on the restoration of species or their habitats in the past. However, they have been evolved into the detailed systems to respond in unpredictable natural disasters and climate change, high-resolution image implementation technology to accurately grasp the practical environment and methods related to environmental restoration for human in urban ecosystem. In the future, investment and technology for the ecosystem restoration field will be continuously demanded for the symbiosis of human beings and species in the damaged ecosystem. Therefore, the research trend of ecological restoration technologies should be provided as reliable guidelines when decision makers establish the policy direction or when researchers select their subjects.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.459-465
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• 2008

Locations of nodes as well as gathered data from nodes are very important because generally multiple nodes are deployed randomly and data are gathered in wireless sensor network. Since the nodes composing wireless sensor network are low cost and low performance devices, it is very difficult to add specially designed devices for positioning into the nodes. Therefore in wireless sensor network, technology positioning nodes precisely using low cost is very important and valuable. This research proposes Cooperative Positioning System, which raises accuracy of location positioning and also can find positions on multiple sensors within limited times.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.105-108
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• 2003

In the next generation backbone networks based on dense-wavelength division multiplexing (DWDM), the routing and wavelength assignment with quality-of-service (QoS) recovery is essentially needed to support a wide range of communication-intensive and real-time multimedia services. This paper proposes a new dpmic routing method called as MW-MIPR (MultiWavelength-Minimum Interference Path Routing), which chooses a route that does not interfere too much with many potential future connection requests. This paper also proposes a differentiated RWA mechanisms combined with MW-MIPR algorithm to provide QoS recovery for various multimedia applications in the next generation backbone networks based on DWDM.