• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.652-662
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• 2016

This paper proposes a user mobility management scheme which supports seamless service even if a user changes his accessing terminal in service in IP-based convergence network. Most of ongoing researches concerning mobility management as well as the existing mobility schemes have been focused to support terminal mobility. It is limited to support a variety of mobility types such as user mobility. The proposed scheme uses the mapping relationship between UID(User Identifier), user specific identifier and TID(Terminal Identifier), specific terminal identifier and forms packet address with user specific permanent 3 layer address for session continuity in case of user mobility. We numerically analyze and compare handover signaling cost between the existing user mobility scheme and the proposed scheme. The result shows that the proposed scheme has lower handover signaling cost than the existing one, [1].

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.163-173
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• 1999

The CORBA provides a object-oriented middleware that lets applications extend their range across networks, languages, component boundaries, and operating systems. Java can provide a potable object that works in any operating system. Mapping Java into CORBA helps large scale information system operate through the Web by using the mobile code property of Java and object component technique of CORBA. This development environment is called the Object Web. This paper proposes an architecture of OSI network management with a CORBA manager using Object Web and an CORBA/CMIS gateway which apply a CMIS-level gateway model to gateway. In this architecture, CORBA manager is based on Object Web and can manage MOs in the OSI domain. The gateway has a role to translate CORBA IDLs into CMIS services and vice versa. In addition, an OSI agent is abstracted into a CORBA agent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.617-624
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• 2014

A campus network nowadays adapts the security policies in detail and even in variety, along with firewall based access control. Nevertheless, security threats, such as information hacking, intrusion and DoS, are not decreasing yet. This paper proposes an enabling method of discriminative security policies to enforce an adaptive security for security objects on basis of the security elements. The security level of a security devices is decided based on the mapping between the users and the objects. The proposed security policies could improve the security effect in terms of investment in creative campus environment, and aim to provide fast and stable services to users.

• Journal of Neurogastroenterology and Motility
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• v.24 no.4
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• pp.512-527
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• 2018

This review provides a comprehensive overview of brain imaging studies of the brain-gut interaction in functional gastrointestinal disorders (FGIDs). Functional neuroimaging studies during gut stimulation have shown enhanced brain responses in regions related to sensory processing of the homeostatic condition of the gut (homeostatic afferent) and responses to salience stimuli (salience network), as well as increased and decreased brain activity in the emotional response areas and reduced activation in areas associated with the top-down modulation of visceral afferent signals. Altered central regulation of the endocrine and autonomic nervous responses, the key mediators of the brain-gut axis, has been demonstrated. Studies using resting-state functional magnetic resonance imaging reported abnormal local and global connectivity in the areas related to pain processing and the default mode network (a physiological baseline of brain activity at rest associated with self-awareness and memory) in FGIDs. Structural imaging with brain morphometry and diffusion imaging demonstrated altered gray- and white-matter structures in areas that also showed changes in functional imaging studies, although this requires replication. Molecular imaging by magnetic resonance spectroscopy and positron emission tomography in FGIDs remains relatively sparse. Progress using analytical methods such as machine learning algorithms may shift neuroimaging studies from brain mapping to predicting clinical outcomes. Because several factors contribute to the pathophysiology of FGIDs and because its population is quite heterogeneous, a new model is needed in future studies to assess the importance of the factors and brain functions that are responsible for an optimal homeostatic state.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.1-14
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• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.301-312
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• 2013

Landslides are caused by complex interaction among a large number of interrelated factors such as topography, geology, forest and soils. In this study, a comparative study was carried out using fuzzy relationship method and artificial neural network to evaluate landslide susceptibility. For landslide susceptibility mapping, maps of the landslide occurrence locations, slope angle, aspect, curvature, lithology, soil drainage, soil depth, soil texture, forest type, forest age, forest diameter and forest density were constructed from the spatial data sets. In fuzzy relation analysis, the membership values for each category of thematic layers have been determined using the cosine amplitude method. Then the integration of different thematic layers to produce landslide susceptibility map was performed by Cartesian product operation. In artificial neural network analysis, the relative weight values for causative factors were determined by back propagation algorithm. Landslide susceptibility maps prepared by two approaches were validated by ROC(Receiver Operating Characteristic) curve and AUC(Area Under the Curve). Based on the validation results, both approaches show excellent performance to predict the landslide susceptibility but the performance of the artificial neural network was superior in this study area.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.363-383
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• 2007

Global map of science, which is visualizing large scientific domains, can be used to visually analyze the structural relationships between major areas of science. This paper reviewed previous efforts on global science map, and then tried to making a science map of Korea with some new methods. There are several research groups on making global map of science including Dr. Small and Dr. Garfield of ISI (now Thompson Scientific), SCImago research group at the University of Granada, and Dr. Borner's InfoVis Lab at the Indiana University. They called their maps as science map or scientogram and called the activity of mapping science as scientography. Most of the previous works are based on citations between scientific articles. However citation database for Korean journal articles is still under construction. This research tried to make a Korean science map with the text in the proposals suggested for funding from Korean Research Foundation. Two kinds of method for generating networks of scientific fields are used. One is Pathfinder network (PFNet) alogorithm which has been used in several published bibliometric studies. The other is clustering-based network (CBnet) algorithm which was proposed recently as an alternative to PFNet. In order to take into account both views of the two algorithms, the resulting maps are combined to a final science map of Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.16-24
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• 2002

Classification of the land cover characteristics is a major application of remote sensing. The goal of this study is to propose an optimal classification process for electro-optical camera(EOC) of Korea Multi-Purpose Satellite(KOMPSAT). The study was carried out on Landsat TM, high spectral resolution image and KOMPSAT EOC, high spatial resolution image of Miho river basin, Korea. The study was conducted in two stages: one was image fusion of TM and EOC to gain high spectral and spatial resolution image, the other was land cover classification on fused image. Four fusion techniques were applied and compared for its topographic interpretation such as IHS, HPF, CN and wavelet transform. The fused images were classified by radial basis function neural network(RBF-NN) and artificial neural network(ANN) classification model. The proposed RBF-NN was validated for the study area and the optimal model structure and parameter were respectively identified for different input band combinations. The results of the study propose an optimal classification process of KOMPSAT EOC to improve the thematic mapping and extraction of environmental information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2B
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• pp.250-262
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• 2004

In IPv6 environment, the Internet Telephony, VoD(Video on Demand) and high capacity file exchange service will be more increased than IPv4. Therefore, the strict guarantee of QoS based on End-to-End and differentiated quality control schemes are simultaneously required. This paper proposes the flow control schemes on IPv6 network that the traffic is identified by flow and the QoS of multi-service is improved by QoS information in IPv6 hop-by-hop option header. The object of flow control includes not only non-default QoS traffic, which uses the flow label, but also best-effort or encrypted traffic. Therefore, the guarantee of real-time service is strengthened and the flow, which abuses unnecessarily the network resources, is effectively controlled. Also, this paper proposes the mapping scheme between the flow and MPLS by reflecting the minimum change of the existed network resource and the status of backbone network of ISP(Internet Service Provider). In the simulation result, It is shown that the proposed scheme is effective in the side of QoS on real-time services and utilization of backbone resources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.3
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• pp.191-201
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• 2015

Measuring and mapping connectivity among habitats is a key component of sustainable urban planning and design process. In this study, we examined how functional corridors connect forest bird habitats in a metropolitan area of Korea using graph theory-based techniques. High-quality forest habitat was defined as a function of forest cover, presence of residential areas, and road networks. We then constructed a network of high-quality forest habitats using the FunConn (functional connectivity) tools, and computed metrics ($T_i$) of patch importance based on the minimum ($Q_1$) and the 25th percentile ($Q_{25}$) rank least-cost distance values. We investigated the relative influence of two values of patch importance on forest bird species richness. As a result, the patch importance index based on the $Q_{25}$ effective distance threshold was most positively correlated with species richness (P < 0.001) after controlling for the area effect. Thus, using the $Q_{25}$ effective distance threshold, we mapped not only the locations of important habitat patches and functional corridors, but also the network backbone of forest bird habitats. The network developed in this study can help guide urban planning for biodiversity conservation.