• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.417-424
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• 2007

Mesh networks using WLAN technology have been paid attention as a key wireless access technology. However, many technical issues still exist for its successful deployment. One of those issues is the routing problem that addresses the path setup through a WLAN mesh network for the data exchanges between a station and a wired network. Since the characteristics of a WLAN mesh network can be very dynamic, the use of single routing protocol would not fit for all environments whether it is reactive or proactive. Therefore, it is required to develop an adaptive routing protocol that modifies itself according to the changes in the network parameters. As a logical first step for the development, an analytical model considering all the dynamic features of a WLAN mesh network is required to evaluate the performance of a reactive and a proactive routing scheme. In this paper, we propose an analytical model that makes us scrutinize the impact of the network and station parameters on the performance of each routing protocol. Our model includes the size of a mesh network, the density of stations, mobility of stations. and the duration of network topology change. We applied our model to the AODV that is a representative reactive routing protocol and DSDV that is a representative proactive routing protocol to analyze the tradeoff between AODV and DSDV in dynamic network environments. Our model is expected to help developing an adaptive routing protocol for a WLAN mesh network.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.39-47
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• 2005

The range of hardware implementation increases in communication systems as high-speed processing is required for high data rate. In the broadband wireless access (BWA) system based on IEEE standard 802.16 the functions of higher part in the MAC layer to Provide data needed for generating MAC PDU are implemented in software, and the tasks from formatting MAC PDUs by using those data to transmitting the messages in a modem are implemented in hardware. In this paper, the interface hardware for efficient message exchange between MAC and PHY layers in the BWA system is designed. The hardware performs the following functions including those of the transmission convergence(TC) sublayer; (1) formatting TC PDU(Protocol data unit) from/to MAC PDU, (2) Reed-solomon(RS) encoding/decoding, and (3) resolving DL MAP and UL MAP, so that it controls transmission slot and uplink and downlink traffic according to the modulation scheme of burst profile. Also, it provides various control signal for PHY modem. In addition, the truncated binary exponential backoff (TBEB) algorithm is implemented in a subscriber station to avoid collision on contention-based transmission of messages. The VLSI architecture performing all these functions is implemented and verified in VHDL.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.13-21
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• 2009

The sensor nodes that form a wireless sensor network must perform both routing and sensing roles, since each sensor node always has a regular energy drain. The majority of sensors being used in wireless sensor networks are either unmanned or operated in environments that make them difficult for humans to approach. Furthermore, since many wireless sensor networks contain large numbers of sensors, thus requiring the sensor nodes to be small in size and cheap in price, the amount of power that can be supplied to the nodes and their data processing capacity are both limited. In this paper, we proposes the WSN(Wireless Sensor Network) algorithm which is applied sensor node that has low power consumption and efficiency measurement. Moreover, the efficiency routing protocol is proposed in this paper. The proposed algorithm reduces power consumption of sensor node data communication. It has not researched in LEACH(Low-Energy Adaptive Clustering Hierarchy) routing protocol. As controlling the active/sleep mode based on the measured data by sensor node, the energy consumption is able to be managed. In the event, the data is transferred to the local cluster head already set. The other side, this algorithm send the data as dependent on the information such as initial and present energy, and the number of rounds that are transformed into cluster header and then transferred. In this situation, the assignment of each node to cluster head evenly is very important. We selected cluster head efficiently and uniformly distributed the energy to each cluster node through the proposed algorithm. Consequently, this caused the extension of the WSN life time.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.25-32
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• 2005

Frequency hopping system has been adopted to many communication systems in order to overcome the inferior situation such as jamming environment. But typically its processing gain being limited, data interfered by jamming signal could not be fully recovered. This can be enhanced by combing FH system with spatial interference canceller which is a kind of active beamformer In this Paper, we proposed the compensation method of weight vector discrepancy according to the hopped frequencies and the PMBF method which is able to eliminate the inference effectively with less computational complexity. That is, the steering vector of wanted signals can be calculated from the frame without jamming signals using eigen analysis. New projection matrix extracted by the steering vector of wanted signal eliminates the interferences from the covariance matrix of received signal including wanted signal and jamming signals. This PMBF has similar performance of SINR beamformer with less computational complexity.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.717-722
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• 2004

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer using neural network with weighted fuzzy membership functions (NNWFM). NNWFM is capable of self-adapting weighted membership functions to enhance accuracy in prediction from the given clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from the enhanced bounded sums of n set of weighted fuzzy membership functions. Two number of prediction rules extracted from NNWFM outperforms to the current published results in number of rules and accuracy with 99.41%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.58-64
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• 2016

In this paper presents Robust k-means clustering-based high-speed bar code decoding method to blur and lighting. for fast operation speed and robust decoding to blur, proposed method uses adaptive local threshold binarization methods that calculate threshold value by dividing blur region and a non-blurred region. Also, in order to prevent decoding fail from the noise, decoder based on k-means clustering algorithm is implemented using area data summed pixel width line of the same number of element. Results of simulation using samples taken at various worst case environment, the average success rate of proposed method is 98.47%. it showed the highest decoding success rate among the three comparison programs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6069-6091
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• 2017

Augmented Reality (AR) overlays virtual information on real world data, such as displaying useful information on videos/images of a scene. This paper presents an Enhanced AR (EAR) system that displays useful statistical players' information on captured images of a sports game. We focus on the situation where the input image is degraded by strong sunlight. Proposed EAR system consists of an image enhancement technique to improve the accuracy of subsequent player and face detection. The image enhancement is followed by player and face detection, face recognition, and players' statistics display. First, an algorithm based on multi-scale retinex is proposed for image enhancement. Then, to detect players' and faces', we use adaptive boosting and Haar features for feature extraction and classification. The player face recognition algorithm uses boosted linear discriminant analysis to select features and nearest neighbor classifier for classification. The system can be adjusted to work in different types of sports where the input is an image and the desired output is display of information nearby the recognized players. Simulations are carried out on 2096 different images that contain players in diverse conditions. Proposed EAR system demonstrates the great potential of computer vision based approaches to develop AR applications.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.84-90
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• 2010

DBMS is used for a range of applications from data warehousing through on-line transaction processing. As a result of this demand, DBMS has continued to grow in terms of its size. This growth invokes the most important issue of manually tuning the performance of DBMS. The DBMS tuning should be adaptive to the type of the workload put upon it. But, identifying workloads in mixed database applications might be quite difficult. Therefore, a method is necessary for identifying workloads in the mixed database environment. In this paper, we propose a SVM workload classifier to automatically identify a DBMS workload. Database workloads are collected in TPC-C and TPC-W benchmark while changing the resource parameters. Parameters for SVM workload classifier, C and kernel parameter, were chosen experimentally. The experiments revealed that the accuracy of the proposed SVM workload classifier is about 9% higher than that of Decision tree, Naive Bayes, Multilayer perceptron and K-NN classifier.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9B
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• pp.908-913
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• 2009

Mobile phones became important household appliance that cannot be without in our daily lives. And the short messaging service (SMS) in these mobile phones is 1.5 to 2 times more than the voice service. However, the spam filtering functions installed in mobile phones take a method to receive specific number patterns or words and recognize spam messages when those numbers or words are present. However, this method cannot properly filters various types of spam messages currently dispatched. This paper proposes a more powerful and more adaptive spam filtering system using SVM and thesaurus. The system went through a process of isolating words from sample data through pro-processing device and integrating meanings of isolated words using a thesaurus. Then it generated characteristics of integrated words through the chi-square statistics and studied the characteristics. The proposed system is realized in a Window environment and the performance is confirmed through experiments.