• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.149-159
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• 1999

Purpose: The purpose of this study was to evaluate cervical lymph node metastasis of oral squamous cell carcinoma patients by MRI film and neural network system. Materials and Methods: The oral squamous cell carcinoma patients(21 patients. 59 lymph nodes) who have visited SNU hospital and been taken by MRI. were included in this study. Neck dissection operations were done and all of the cervical lymph nodes were confirmed with biopsy. In MR images. each lymph node were evaluated by using 6 MR imaging criteria(size. roundness. heterogeneity. rim enhancement. central necrosis, grouping) respectively. Positive predictive value. negative predictive value. and accuracy of each MR imaging criteria were calculated. At neural network system. the layers of neural network system consisted of 10 input layer units. 10 hidden layer units and 1 output layer unit. 6 MR imaging criteria previously described and 4 MR imaging criteria (site I-node level II and submandibular area. site II-other node level. shape I-oval. shape II-bean) were included for input layer units. The training files were made of 39 lymph nodes(24 metastatic lymph nodes. 10 non-metastatic lymph nodes) and the testing files were made of other 20 lymph nodes(10 metastatic lymph nodes. 10 non-metastatic lymph nodes). The neural network system was trained with training files and the output level (metastatic index) of testing files were acquired. Diagnosis was decided according to 4 different standard metastatic index-68. 78. 88. 98 respectively and positive predictive values. negative predictive values and accuracy of each standard metastatic index were calculated. Results: In the diagnosis of using single MR imaging criteria. the rim enhancement criteria had highest positive predictive value (0.95) and the size criteria had highest negative predictive value (0.77). In the diagnosis of using single MR imaging criteria. the highest accurate criteria was heterogeneity (accuracy: 0.81) and the lowest one was central necrosis (accuracy: 0.59). In the diagnosis of using neural network systems. the highest accurate standard metastatic index was 78. and that time. the accuracy was 0.90. Neural network system was more accurate than any other single MR imaging criteria in evaluating cervical lymph node metastasis. Conclusion: Neural network system has been shown to be more useful than any other single MR imaging criteria. In future. Neural network system will be powerful aiding tool in evaluating cervical node metastasis.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.3
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• pp.39-49
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• 2010

Ad hoc network is infrastructureless network, that the network topology is configured by each node. Each node capacity device function namely, accomplishes a network control and a function of management because not being Network device of the exclusively. Ad hoc networks what kind of node join or leave the network topology to facilitate the expansion of arbitrary topology, to the case which is the distance whose traffic is distant the place must overtake through the route of intermediate nodes, like these facts give an effect to performance fluctuation. Consequently, each node in order to maintain traffic of oneself stably there is a necessity which will consider traffic and congestion control from the node which traffic of a condition and oneself of traffic of the circumference and the route which compose the network will overtake through. This paper assumes the path of the band with a finite resource, and path traffic to occupy the competition and its impact on transmission performance of these competing arguments to configure the model factor to analyse the performance impact on the results presented. Like this result with the fact that from the study, it will contribute in network management policy and the technique.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.153-163
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• 2023

This study is situated in the context of intelligent transport systems, where in-vehicle devices assist drivers to avoid accidents and therefore improve road safety. The vehicles present in a given area form an ad' hoc network of vehicles called vehicular ad' hoc network. In this type of network, the nodes are mobile vehicles and the messages exchanged are messages to warn about obstacles that may hinder the correct driving. Node mobilities make it impossible for inter-node communication to be end-to-end. Recognizing this characteristic has led to delay-tolerant vehicular networks. Embedded devices have small buffers (memory) to hold messages that a node needs to transmit when no other node is within its visibility range for transmission. The performance of a vehicular delay-tolerant network is closely tied to the successful management of the nodes' transit buffer. In this paper, we propose a message transit buffer management model for nodes in vehicular delay tolerant networks. This model consists in setting up, on the one hand, a policy of dropping messages from the buffer when the buffer is full and must receive a new message. This drop policy is based on the concept of intermediate node to destination, queues and priority class of service. It is also based on the properties of the message (size, weight, number of hops, number of replications, remaining time-to-live, etc.). On the other hand, the model defines the policy for selecting the message to be transmitted. The proposed model was evaluated with the ONE opportunistic network simulator based on a 4000m x 4000m area of downtown Bouaké in Côte d'Ivoire. The map data were imported using the Open Street Map tool. The results obtained show that our model improves the delivery ratio of security alert messages, reduces their delivery delay and network overload compared to the existing model. This improvement in communication within a network of vehicles can contribute to the improvement of road safety.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1100-1101
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• 2007

This paper proposes an efficient mechanism of node membership verification within the groups of sensors in a wireless sensor network (WSN). We utilize one-way accumulator to check the memberships of the legitimate nodes in a secure way. Our scheme also supports the addition and deletion of nodes in the groups in the network. Our analysis shows that, our scheme could be well-suited for the resource constrained sensors in a sensor network and it provides a lightweight mechanism for secure node membership verification in WSN.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.768-772
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• 1991

The Self Creating and organizing (SCO) is a new architecture and one of the unsupervized learning algorithm for the artificial neural network. SCO begins with only one output node which has a sufficiently wide response range, and the response ranges of all the nodes decrease with time. Self Creating and Organizing Neural Network (SCONN) decides automatically whether adapting the weights of existing node or creating a new node. It is compared to the Kohonen's Self Organizing Feature Map (SOFM). The results show that SCONN has lots of advantages over other competitive learning architecture.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.676-682
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• 2011

Sybil attack can disrupt proper operations of wireless sensor network by forging its sensor node to multiple identities. To protect the sensor network from such an attack, a number of countermeasure methods based on RSSI (Received Signal Strength Indicator) and LQI (Link Quality Indicator) have been proposed. However, previous works on the Sybil attack detection do not consider the fact that Sybil nodes can change their RSSI and LQI strength for their malicious purposes. In this paper, we present a Sybil attack detection method based on a transmission power range. Our proposed method initially measures range of RSSI and LQI from sensor nodes, and then set the minimum, maximum and average RSSI and LQI strength value. After initialization, monitoring nodes request that each sensor node transmits data with different transmission power strengths. If the value measured by monitoring node is out of the range in transmission power strengths, the node is considered as a malicious node.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3C
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• pp.251-258
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• 2012

In this paper, we propose a novel method of multi-node frequency synchronization for distributed networks. The proposed method synchronizes carrier frequencies of all nodes in the network and this enables new entry node to synchronize immediately. Moreover, when several groups exist in the network, inter-group synchronization method is proposed. The proposed distributed frequency synchronization method is expected to be very useful for the military operation scenario that new node entry is in a state of flux and group merging and splitting frequently happen.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.310-313
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• 2011

Broadcasting nature of wireless communications makes it possible to apply opportunistic network coding (OPNC) by overhearing transmitted packets from a source to sink nodes. However, it is difficult to apply network coding to the topology of multiple relay and sink nodes. We propose to use relay node selection, which finds a proper node for network coding since the OPNC alone in the topology of multiple relays and sink nodes cannot guarantee network coding gain. The proposed system is a novel combination of wireless network coding and relay selection, which is a key contribution of this paper. In this paper, with the consideration of channel state and potential network coding gain, we propose relay node selection techniques, and show performance gain over the conventional OPNC and a channel-based selection algorithm in terms of average system throughput.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.47-53
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• 2012

In this paper, we present an algorithm called redundant logical paths (RLP) for efficient HSR traffic reduction. It creates redundant logical paths between each HSR node and all the other nodes. Eventually, a logical full-meshed network or paths will be established among all HSR node types, except the Quadbox type, which is used only for interconnection. The logical full-meshed network will be used instead of using the standard HSR protocol that depends on the concepts of the duplication and forwarding of the received frame until it reaches the destination node. The RLP algorithm results in significantly less frame traffic because there is no random forwarding as in the standard HSR protocol. For the sample network in this paper simulation results showed a 61.5-80% reduction in network frame traffic compared to the standard HSR. Our algorithm will avoid latency issues in the network and even network congestion, thus improving network efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.746-748
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• 2011

MANET(Mobile Ad-hoc Network) is a self-configuration network or wireless multi-hop network based on inference topology. The proposed ATICC(Adaptive Time Interval Clustering Control) algorithm for hierarchical cluster based MANET. The proposed ATICC algorithm is time interval control technique for node management considering the attribute of node and network traffic. ATICC could be made low the network traffic. Also it could be improving the network life time by using timing control method.