• Journal of Communications and Networks
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• v.8 no.1
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• pp.28-37
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• 2006

State-dependent call admission control (SDCAC) is proposed to make efficient use of scarce wireless resource in a hierarchical wireless network with heterogeneous traffic. With SDCAC, new calls are accepted according to an acceptance probability taking account of not only cell dwell time but also call holding time and system state (i.e., occupied bandwidth). An analytical method is developed to calculate performance measures of interest, e.g., new call blocking probability, forced termination probability, over. all weighted blocking probability. Numerical results with not only stationary but nonstationary traffic loads are presented to show the robustness of SDCAC. It is shown that SDCAC performs much better than the other considered schemes under nonstationary traffic load.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.456-459
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• 2009

Sensor network has been a hot research topic for the past decade and has moved its phase into using multimedia sensors such as cameras and microphones [1]. Combining many types of sensor data will lead to more accurate and precise information of the environment. However, the use of sensor network data is still limited to closed circumstances. Thus, in this paper, we propose a web-service based framework to deploy multimedia sensor networks. In order to unify different types of sensor data and also to support heterogeneous client applications, we used ROA (Resource Oriented Architecture [2]).

• Journal of Communications and Networks
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• v.4 no.4
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• pp.302-313
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• 2002

In order to facilitate and to meet the ever increasing demands for the wireless communication in the next decade and also to satisfy the high data rates for the new services, the future development of 3G (IMT2000) and systems beyond 3G (B3G) are foreseen. This article presents the need for these developments and motivations for systems beyond 3G taking into account both strategic and technological challenges to be faced. Moreover, the concepts and potential technologies involved including multiple airinterfaces, efficient spectrum allocation and utilisation for the success of systems B3G are briefly reviewed.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.249-254
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• 2015

Buoys are widely used in marine areas because they can mark positions and simultaneously acquire and exchange underwater, surface, and airborne information. Recently, the need for controlling and optimizing a buoy's position and attitude has been raised to achieve successful communication in a heterogeneous collaborative network composed of an underwater robot, a surface robot, and an airborne robot. A buoy in the form of a marine robot would be ideal to address this issue, as it can serve as a moving node of the communication network. Therefore, a buoy-based autonomous surface robot-kit with the abilities of sonar-based avoidance, dynamic position control, and static attitude control was developed and is discussed in this paper. The test and evaluation results of this kit show the possibility of real-world applications and the need for additional studies.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3179-3189
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• 1999

In this paper, different methods of integrating heterogeneous network information systems into the Web are observed by comparing a cliented Java CGI model with a server-oriented CGI model. In addition, a load balanced(LB, for short) CGI model is proposed, which combines two models and decides its course of action depending on the load state of the web server, and compared with the other two models. Performance evaluation models for three models are also presented. The results of computer simulations indicate that the LB CGI model performs consistently well irrespective of system load or server performance.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.283-286
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• 2009

최근 홈 네트워크를 지원하기 위한 다양한 연구가 진행 중이다. 이러한 홈 네트워크를 지원하기 위해서 가정 단위의 네트워크 형성, 해당 네트워크에서 사용자가 요구하는 환경 정보의 효율적인 수집, 그리고 수집된 정보를 통해 서로 다른 기계적 특성이 있는 전자기기 간에 통신할 수 있어야 한다. 본 연구에서는 센서 네트워크와 다양한 전자기기 간의 통신을 가능하게 하는 통신 미들웨어를 제안한다. 제안하는 미들웨어는 이기종의 센서 네트워크에서 다양한 데이터를 수집하고 수집된 정보를 사용자의 요구에 맞게 가공하여, 요구하는 전자기기와 통신을 통해 사용자에서 다양한 서비스를 제공할 수 있도록 한다.

• ETRI Journal
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• v.31 no.3
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• pp.333-335
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• 2009

To match the requirements of heterogeneous mobile devices, video objects may be transcoded, which requires considerable CPU resources. Alternatively, multiple versions of the same video may be stored on servers, but this requires a lot of disk space. We formulate the trade-off between the versions that are stored on disk and the need for transcoding. We propose an optimal solution to this formulation based on dynamic programming. Experiments show that our scheme allows up to 68% more clients to be admitted than conventional schemes when a reasonable amount of storage is available.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1050-1061
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• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.17-26
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• 2023

A smart city is a massive internet of things (IoT) environment, where all terminal devices are connected to a network to create and share information. In accordance with massive IoT environments, millions of IoT devices are connected, and countless data are generated in real time. However, since heterogeneous IoT devices are used, collecting the logs for each IoT device is difficult. Due to these issues, when an IoT device is invaded or is engaged in malicious behavior, such as infection with malware, it is difficult to respond quickly, and additional damage may occur due to information leakage or stopping the IoT device. To solve this problem, in this paper, we propose identifying the attack technique used for initial access to IoT devices through MITRE ATT&CK, collect the logs that can be generated from the identified attack technique, and use them to identify the cause of malware infection.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.794-802
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• 2022

The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth prediction framework with coordinate attention and feature fusion. Specifically, the proposed framework contains attention, multi-scale and feature fusion modules. The attention module improves features based on coordinate attention to enhance the predicted effect, whereas the multi-scale module integrates useful low- and high-level contextual features with higher resolution. Moreover, we developed a feature fusion module to combine the heterogeneous features to generate high-quality depth outputs. We also designed a hybrid loss function that measures prediction errors from the perspective of depth and scale-invariant gradients, which contribute to preserving rich details. We conducted the experiments on public RGBD datasets, and the evaluation results show that the proposed scheme can considerably enhance the accuracy of depth prediction, achieving 0.051 for log10 and 0.992 for δ<1.25³ on the NYUv2 dataset.