• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.367-367
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• 2000

In this paper, an Adaptive neuro-fuzzy Inference system(ANFIS) using fuzzy min-max network(FMMN) is proposed. Fuzzy min-max network classifier that utilizes fuzzy sets as pattern classes is described. Each fuzzy set is an aggregation of fuzzy set hyperboxes. Here, the proposed method transforms the hyperboxes into gaussian membership functions, where the transformed membership functions are inserted for generating fuzzy rules of ANFIS. Finally, we applied the proposed method to the classification problem of iris data and obtained a better performance than previous works.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.476-488
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• 2016

This study reviewed factors and causes that affect on reliability and accuracy of transportation demand forecasting. In general, the causes of forecasting errors come from variety and irregularity of trip behaviors, data limitation, data aggregation and model simplification. Theoretical understanding about the inevitable errors will be helpful for reasonable decision making for practical transportation policies. The study especially focused on traffic assignment with the KTDB data, and described the factors and causes of errors by classifying six categories such as (1) errors in input data, (2) errors due to spacial aggregation and representation method of network, (3) errors from representing values for variations of traffic patterns, (4) errors from simplification of traffic flow model, and (5) errors from aggregation of route choice behavior.

• The KIPS Transactions:PartC
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• v.18C no.6
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• pp.441-444
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• 2011

In this study, we present a method for efficiently aggregating network state information. It is especially useful for aggregating links that have both delay and bandwidth in an asymmetric network. Proposed method reduces the information distortion of logical link by integration process after similar measure and grouping of logical links in multi-level topology transformation to reduce the space complexity. It is applied to transform the full mesh topology whose Service Boundary Line (SBL) serves as its logical link into a spanning tree topology. Simulation results show that aggregated information accuracy and query response accuracy are higher than that of other known method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.66-73
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• 2008

At MANET, Broadcasting message transmission makes throughput decrease because all of MANET nodes are participated at retransmitting broadcasting messages. Especially, burst RREQ transmission causes broadcasting message congestion and inter-RREQ transmission delay. In this paper, we propose a RREQ aggregation method applied to the sender node and intermediate node for solving the problem caused by burst RREQ generation. And we analysis performance of the proposed method by examining at the real testbed.

• ETRI Journal
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• v.37 no.6
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• pp.1231-1241
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• 2015

In this study, we investigate the relationship between emotions and the physiological responses, with emotion recognition, using the proposed fuzzy information granulation-based neural network (FIGNN) for boredom, pain, and surprise emotions. For an analysis of the physiological responses, three emotions are induced through emotional stimuli, and the physiological signals are obtained from the evoked emotions. To recognize the emotions, we design an FIGNN recognizer and deal with the feature selection through an analysis of the physiological signals. The proposed method is accomplished in premise, consequence, and aggregation design phases. The premise phase takes information granulation using fuzzy c-means clustering, the consequence phase adopts a polynomial function, and the aggregation phase resorts to a general fuzzy inference. Experiments show that a suitable methodology and a substantial reduction of the feature space can be accomplished, and that the proposed FIGNN has a high recognition accuracy for the three emotions using physiological signals.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.11-19
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• 2011

In this paper, Service Boundary Line approximation method is proposed to improve the accuracy of aggregated link state information for source routing in transport networks that conduct hierarchical QoS routing. The proposed method is especially useful for aggregating links that have both delay and bandwidth as their QoS parameters. This method selects the main path weight in the network and transports the data to the external networks together with the aggregation information, reducing information distortion caused from the loss of some path weight during aggregation process. In this paper, the main path weight is defined as outlier. Service Boundary Line has 2k+5parameters. k is the number of outliers. The number of storage spaces of Service Boundary Line changes according to the number of outliers. Simulation results show that our approximation method requires a storage space that 1.5-2 times larger than those in other known techniques depending on outlier selection method, but its information accuracy of proposed method in the ratio between storage space and information accuracy is higher.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.10 s.340
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• pp.9-16
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• 2005

The growth of the Internet over the last several years has placed a tremendous strain on the high bandwidth Hence, the amount of internet traffic has risen sharply and it has demanded to use the limited resource. MPLS (Multiprotocol Label Switching) is regarded as a core technology for migrating to the next generation Internet. It is important to reduce the number of labels and LSP(Label Switched Path)s for network resource management. In this thesis, we considered an MPLS multicast mechanism in the current Internet. The scalability problem due to lack of labels and multicast property is one of the serious problems in MPLS multicast mechanism, we proposed a Label Aggregation algorithm that the multicast packets on same link in MPLS allocates the same label for the scalability problem. In order to support the proposed algorithm we defined a new LDP(Label Distribution Protocol) multicast field and multicast packet is copied and transmitted for multicast group links of next node in LSR(label Switch Router).

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.653-660
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• 2013

This paper deals with the problem of unfairness among uplink TCP (Transmission Control Protocol) flows associated with frame aggregation employed in IEEE 802.11n WLANs (Wireless Local Area Networks). When multiple stations have uplink TCP flows and transmit TCP data packets to an AP (Access Point), the AP has to compete for channel access with stations for the transmission of TCP ACK (acknowledgement) packets to the stations. Due to this contention-based channel access, TCP ACKs tend to be accumulated in the AP's downlink buffer. We show that the frame aggregation in the MAC (Medium Access Control) layer increases TCP ACK losses in the AP and leads to the serious unfair operation of TCP congestion control. To resolve this problem, we propose the TAC (TCP ACK Compression) mechanism operating at the top of the AP's interface queue. By exploiting the properties of cumulative TCP ACK and frame aggregation, TAC serves only the representative TCP ACK without serving redundant TCP ACKs. Therefore, TAC reduces queue occupancy and prevents ACK losses due to buffer overflow, which significantly contributes to fairness among uplink TCP flows. Also, TAC enhances the channel efficiency by not transmitting unnecessary TCP ACKs. The simulation results show that TAC tightly assures fairness under various network conditions while increasing the aggregate throughput, compared to the existing schemes.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.840-845
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• 2007

In a wireless sensor network, a middleware used to support efficient processing and fast delivering of sensing data should handle the data loss problem at an intermediate sensor node caused by unexpected sudden data burst. In his paper, it proposes a Delta-Average method for enhancing the efficiency of data aggregation and correctness where the sensed data should be delivered only with the limited computing power and energy resource. With the proposed method, unnecessary data transfer of the duplicate data is eliminated and data correctness is enhanced by using the proposed averaging and data differentiating scheme when an instantaneous data burst is occurred. Finally, with the TOSSTM simulation results on TinyDB, we verify that the correctness of the transferred data is enhanced.