• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2305-2315
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• 2015

Frequency resource value is growing more and more with the development of the wireless communication. With the advent of the current information society comes a serious shortage of frequency resource, as the amount of supply is far from meeting its demands. Thus, cognitive radio (CR) technique is receiving more attention as a way to make use of the temporarily unoccupied frequency resource. In this paper we propose a novel out-of-band spectrum sensing and dynamic channel access scheme for frequency hopping-based cognitive radio ad-hoc networks. At the beginning of each current channel hopping time, member nodes perform spectrum sensing for the next hopping channel. Based on the proposed collision free primary detection notification, member nodes can determine whether they should execute a hopping time extension procedure of the current channel or not. When the primary detected hopping channel is re-idled, the hopping pattern recovery procedure is performed. In this paper we evaluated the performance of the proposed dynamic sensing and hopping channel extension mechanism for the various wireless network conditions. As a result, we show that the proposed method can increase channel utilization and provide reliable channel management operation.

• Journal of KIISE:Information Networking
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• v.32 no.5
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• pp.615-624
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• 2005

In Mobile IP, several types of messages - binding update, binding request and binding acknowledgement - are used to support user mobility. It is necessary to exchange those messages frequently for seamless mobility but it incurs both the increase of network overhead and poor usage of mobile node battery power Thus, we need a mechanism that the server detects users location and also copes with the problems effectively, which is our main concern in this paper Each user records all moving logs locally and periodically makes out profile based on them in HMIPv6. By using profile, estimated resident time can be computed whenever he enters an area and the time is set up as the binding update message lifetime. Of course, the more correct lifetime nay be obtained IP arrival time as well as average resident time Is considered in profile. Through extensive experiments, we measure the bandwidth usage for binding update messages by comparing the proposed schemes with that in HMIPv6. From the results, Gain gets over $80\%$ when mobile node stays more than 13 minutes in a subnet. Namely, we come to know that our schemes improve network usage and energy usage in mobile node by decreasing the number of messages while they also manage users locations like that in HMIPv6.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.473-476
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• 2007

Location determination of mobile user via RSSI approach has received ample attention from researchers lately. However, it remains a challenging issue due to the complexities of RSSI signal propagation characteristics, which are easily exacerbated by the mobility of user. Hence, a segmentation-based linear spline interpolation method is proposed to cater for the dynamic fluctuation pattern of radio signal in complex environment. This optimization algorithm is proposed in addition to the current radiolocation's (CC2431, Chipcon, Norway) algorithm, which runs on IEEE802.15.4 standard. The enhancement algorithm involves four phases. First phase consists of calibration model in which RSSI values at different static locations are collected and processed to obtain the mean and standard deviation value for the predefined distance. RSSI smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the user is moving. Distances are computed using the segmentation formula obtain in the first phase. In situation where RSSI value falls in more than one segment, the ambiguity of distance is solved by probability approach. The distance probability distribution function(pdf) for each distances are computed and distance with the highest pdf at a particular RSSI is the estimated distance. Finally, with the distances obtained from each reference node, an iterative trilateration algorithm is used for position estimation. Experiment results obtained position the proposed algorithm as a viable alternative for location tracking.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.375-382
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• 2008

A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

• Journal of KIISE:Information Networking
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• v.35 no.4
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• pp.345-354
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• 2008

Recently, small-scale mobile network which is composed of many mobile devices in a man becomes popular. Also, Examples of large-scale mobile network can be thought access networks deployed on public transportation such as ships, trains and buses. To provide seamless mobility for mobile nodes in this mobile network, binding update messages must be exchanged frequently. However, it incurs network overhead increasingly and decreases energy efficiency of mobile router. If we try to reduce the number of the messages to cope with the problem, it may happen the security -related problems conversely Thus, mobile router needs a effective algorithm to update location information with low cost and to cover security problems. In this paper, mobility management scheme based on mobile router's mobility pattern is proposed. Whenever each mobile router leaves a visiting network, it records related information as moving log. And then it periodically computes mean resident time for all visited network, and saves them in the profile. If each mobile router moves into the visited network hereafter, the number of binding update messages can be reduced since current resident time may be expected based on the profile. At this time, of course, security problems can happen. The problems, however, are solved using key credit, which just sends some keys once. Through extensive experiments, bandwidth usages are measured to compare binding update messages in proposed scheme with that in existing scheme. From the results, we can reduce about 65% of mobility-management-related messages especially when mobile router stays more than 50 minutes in a network. Namely, the proposed scheme improves network usage and energy usage of mobile router by decreasing the number of messages and authorization procedure.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.59-69
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• 2011

Since power analysis attack which uses a characteristic that power consumed by crypto device depends on processed data has been proposed, many logics that can block these correlation originally have been developed. DRP logic has been adopted by most of logics maintains power consumption balanced and reduces correlation between processed data and power consumption. However, semi-custom design is necessary because recently design circuits become more complex than before. This design method causes unbalanced design pattern that makes DRP logic consumes unbalanced power consumption which is vulnerable to power analysis attack. In this paper, we have developed new logic style which adds another discharge phase to discharge two output nodes at the same time based on DyCML to remove this unbalanced power consumption. Also, we simulated 1bit fulladder to compare proposed logic with other logics to prove improved performance. As a result, proposed logic is improved NED and NSD to 60% and power consumption reduces about 55% than any other logics.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• The KIPS Transactions:PartC
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• v.11C no.4
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• pp.429-438
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• 2004

This Paper Presents the control structure for incoming traffic from arbitrary node to Provide admission control in policy-based W network management structure using fuzzy logic control approach. The proposed control structure uses scheme for deciding network resource allocation depending on requirements predefined-policies and network states. The proposed scheme enhances policy adapting methods of existing binary methods, and can use resource of network more effectively to provide adaptive admission control, according to the unpredictable network states for predefined QoS policies. Simulation results show that the proposed controller improves the ratio of packet rejection up to 26%, because it Performs the soft adaption based on the network states instead of accept/reject action in conventional CAC(Connection Admission Controller).

• Journal of IKEEE
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• v.16 no.3
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• pp.274-282
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• 2012

In this paper, we propose the design of lighting control algorithm for intelligent LED lighting system. The proposed lighting control algorithm transmitted to MCU through a data bus the environmental information detected from respectively sensor node. The MCU control software was designed to determine the level maintained to depending on the set control method by comparing the results that calculated the dimming level using a signal value. Also, it was designed to be lighting by cross-performed periodically the rotation and reverse method by created fully symmetrical pattern using the control algorithm to LED lighting device. In this paper, the proposed lighting control algorithm improved the reliability of the data sent by designed the system that can be controlled lighting to stable, and it was maintained the event delivery ratio of 91%. Also, the lighting device was decreased the luminous intensity of 32%, the power consumption of 49%, and heat generation of 32%. As a result, it were could be improved the energy efficiency that the life-cycle of LED has been increased 50%.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.257-269
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• 2001

Because of increasing number of integrated circuit, there is many tries of making chip of neural network and some chip is exit. but this is not prefer because YLSI technology can't support so large hardware. So imitation of whole system of neural network is more prefer. There is common procedure in signal processing as in the neural network and pattern recognition. That is multiplication of large amount of signal and reading LUT. This is identical with some operation of MLP, and need iterative and large amount of calculation, so if we make this part with hardware, overall system's velocity will be improved. So in this paper, we design neutral network, not neuron which can be used to many other fields. We realize this part by following separated bits addition method, and it can be appled in the real time parallel process processing.