• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1474-1482
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• 2006

Recently, it is advanced about the variable research of IPv6 and the wireless sensor network. However, the existed researches are not enough about the internetworking technology between the wireless sensor network and the Internet based on IPv6 for supporting ubiquitous service. Accordingly, this paper proposes two internetworking models for connecting the wireless sensor network and Internet based on IPv6. The relay router in the first model and the sink node of the wireless sensor network in the second mode] were used as a gateway. Then we analyze and compare with two internetworking models. Additionally we construct the test-bed connected between the wireless sensor network and KOREN(KOrea advanced REsearch Network) based on IPv6 using the first model. And we verified the operation of the test-bed by experiments.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.546-554
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• 2014

For improvement of network RTK performance in survey field, Spatial Information Research Institute (SIRI), LX Korea Cadastral Survey Corporation installed 30 GNSS permanent stations in Korea Peninsula, and has been running the MAC-based network RTK service as a test version. In this paper, we introduce the LX GNSS network and analyze the positioning accuracy of the LX MAC RTK service. For field test of the LX MAC RTK service, we installed temporally fixed anchor points and observed simultaneously with VRS of National Geographic Information Institute. As a result, the horizontal position differences and initial times of LX MAC with respect to NGII VRS are $1{\sim}2{\pm}1cm$ and <10 seconds, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1139-1145
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• 2019

In order to efficiently use defined satellite network resources, it is a priority to understand the performance and usage of the network. In this paper, in order to analyze the operational efficiency and stability of the system in the satellite communication system operated by K-water flood forecast and alarm network, FTP and ping testing and network traffic analysis methods of measuring download and upload speed between central and observational countries were introduced. As a result of measuring the transmission speed by the introduced test method, the effects of TCP accelerators have been improved by 120% upon download from the observational station. Through the performance test and traffic analysis of the satellite hydrologic observation system introduced, environmental improvement and improvement points of the satellite communication system were derived so that the operational efficiency and stability of the communication network could be expected.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.25-36
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• 2021

This paper presents a topology based on packet tracer and a five-step scenario model to make it easier for students to understand the network on which VLANs are applied. Virtual LAN (VLAN), developed as an alternative solution to the Routers that distribute broadcast traffic, is a virtual local area network that logically configured regardless of the physical network. The VLAN prevents the network performance degradation resulting from the broadcast traffic by dividing the broadcast domain so that the bandwidth can be used more efficiently. In addition, it enhances the security because on communication between the devices belonging to different VLANs is impossible. The five-step scenarios in this paper presented an efficient implementation case for students to understand and validate the various functions of VLANs through ping/telnet/tracert test and simulation, after setting up each step of programming switches and routers in the virtual network.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.103-110
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• 2022

Since satellite images generally include clouds in the atmosphere, it is essential to detect or mask clouds before satellite image processing. Clouds were detected using physical characteristics of clouds in previous research. Cloud detection methods using deep learning techniques such as CNN or the modified U-Net in image segmentation field have been studied recently. Since image segmentation is the process of assigning a label to every pixel in an image, precise pixel-based dataset is required for cloud detection. Obtaining accurate training datasets is more important than a network configuration in image segmentation for cloud detection. Existing deep learning techniques used different training datasets. And test datasets were extracted from intra-dataset which were acquired by same sensor and procedure as training dataset. Different datasets make it difficult to determine which network shows a better overall performance. To verify the effectiveness of the cloud detection network such as Cloud-Net, two types of networks were trained using the cloud dataset from KOMPSAT-3 images provided by the AIHUB site and the L8-Cloud dataset from Landsat8 images which was publicly opened by a Cloud-Net author. Test data from intra-dataset of KOMPSAT-3 cloud dataset were used for validating the network. The simulation results show that the network trained with KOMPSAT-3 cloud dataset shows good performance on the network trained with L8-Cloud dataset. Because Landsat8 and KOMPSAT-3 satellite images have different GSDs, making it difficult to achieve good results from cross-sensor validation. The network could be superior for intra-dataset, but it could be inferior for cross-sensor data. It is necessary to study techniques that show good results in cross-senor validation dataset in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2C
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• pp.81-88
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• 2006

This study performed field and laboratory tests for poor subsoils taken in six regions of the country and determined undrain shear strength. Su values and preconsolidation pressure are predicted using Back Propagation neural network (BPNN) and the application of BPNN is verified. The result of BPNN shows that correlation coefficient between test and neural network result is over 0.9, which means high correlativity. Especially the neural network uses only 6 parameters such as natural water content, void ratio, specific gravity, rate of passing 200th sieve, liquid limits and plasticity index among various affecting factors to estimate value and the correlation coefficent is 0.93. The conclusions obtained in this paper are from the tests performed for poor subsoils taken in the several regions of the country. If there were more test results, the prediction and influence of various soil properties could be effectively performed by neural network.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.135-138
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• 1998

In this paper, we propose an software architecture for home network gateway set-top-box that supports the connectivity between various consumer devices and the Internet simultaneously. To improve the scalability of the software, the proposed architecture uses the abstracted protocol driving structure, and to enhance the user-friendliness, the unified device access and management user interface is implemented using web technology. A prototype for the proposed architecture is implemented for evaluating the usability under the home network test bed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.877-884
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• 1994

In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

• Tunnel and Underground Space
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• v.6 no.4
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• pp.316-325
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• 1996

A new accelerated neural network adopting modified sigmoid function was developed and applied to estimate engineering properties of rock from insufficient geological data. Developed network was tested on the well-known XOR and character recognition problems to verify the validity of the algorithms. Both learning speed and recognition rate were improved. Test learn on the Lee and Sterling's problems showed that learning time was reduced from tens of hours to a few minutes, while the output pattern was almost the same as other studies. Application to the various case studies showed exact coincidence with original data or measured results.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.390-395
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• 1988

The implementation of MAP(Manufacturing Automation Protocol) NIU(network interface uint) is studied and presented in this paper. Hardwares and system softwares for network management, user interface, and medium access control are developed. Also LLC(Logical Link Control) protocol is implemented. Afterwards, The operations of NIU using self-test functions are tested. Compatibility between interfaces according to IEEE 802.4 standard is also tested.