• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.998-1007
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• 2018

The advent of Wireless Sensor Networks (WSN) has led to their use in numerous applications. Sensors are autonomous in nature and are constrained by limited resources. Designing an autonomous topology with criteria for economic and energy conservation is considered a major goal in WSN. The proposed honey-hive clustering consumes minimum energy and resources with minimal transmission delay compared to the existing approaches. The honey-hive approach consists of two phases. The first phase is an Intra-Cluster Min-Max Discrepancy (ICMMD) analysis, which is based on the local honey-hive data gathering technique and the second phase is Inter-Cluster Frequency Matching (ICFM), which is based on the global optimal data aggregation. The proposed data aggregation mechanism increases the optimal connectivity range of the sensor node to a considerable degree for inter-cluster and intra-cluster coverage with an improved optimal energy conservation.

• ETRI Journal
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• v.28 no.3
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• pp.311-319
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• 2006

This paper presents a terminal-assisted frame-based packet reservation multiple access (TAF-PRMA) protocol, which optimizes random access control between heterogeneous traffic aiming at more efficient voice/data integrated services in dynamic reservation TDMA-based broadband access networks. In order to achieve a differentiated quality-of-service (QoS) guarantee for individual service plus maximal system resource utilization, TAF-PRMA independently controls the random access parameters such as the lengths of the access regions dedicated to respective service traffic and the corresponding permission probabilities, on a frame-by-frame basis. In addition, we have adopted a terminal-assisted random access mechanism where the voice terminal readjusts a global permission probability from the central controller in order to handle the 'fair access' issue resulting from distributed queuing problems inherent in the access network. Our extensive simulation results indicate that TAF-PRMA achieves significant improvements in terms of voice capacity, delay, and fairness over most of the existing medium access control (MAC) schemes for integrated services.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.82-87
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• 2004

ECG consists of various waveforms of electric signals of heat. Datamining can be used for analyzing and classifying the waveforms. Conventional studies classifying electrocardiogram have problems like extraction of distorted characteristics, overfitting, etc. This study classifies electrocardiograms by using BP algorithm and SVM to solve the problems. As results, this study finds that SVM provides an effective prohibition of overfitting in neural networks and guarantees a sole global solution, showing excellence in generalization performance.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.397-410
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• 2016

This paper proposes a novel cooperative localization method for distributed wireless networks in 3-dimensional (3D) global positioning system (GPS) denied environments. The proposed method, which is referred to as hybrid ellipsoidal variational algorithm (HEVA), combines the use of non-parametric belief propagation (NBP) and variational Bayes (VB) to benefit from both the use of the rich information in NBP and compact communication size of a parametric form. InHEVA, two novel filters are also employed. The first one mitigates non-line-of-sight (NLoS) time-of-arrival (ToA) messages, permitting it to work well in high noise environments with NLoS bias while the second one decreases the number of calculations. Simulation results illustrate that HEVA significantly outperforms traditional NBP methods in localization while requires only 50% of their complexity. The superiority of VB over other clustering techniques is also shown.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1464-1471
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• 1999

This paper introduces complex-valued competitive learning neural network for spatio-temporal pattern recognition. There have been quite a few neural networks for spatio-temporal pattern recognition. Among them, recurrent neural network, TDNN, and avalanche model are acknowledged as standard neural network paradigms for spatio-temporal pattern recognition. Recurrent neural network has complicated learning rules and does not guarantee convergence to global minima. TDNN requires too many neurons, and can not be regarded to deal with spatio-temporal pattern basically. Grossberg's avalanche model is not able to distinguish long patterns, and has to be indicated which layer is to be used in learning. In order to remedy drawbacks of the above networks, unsupervised competitive learning using complex umber is proposed. Suggested neural network also features simultaneous recognition, time-shift invariant recognition, stable categorizing, and learning rate modulation. The network is evaluated by computer simulation with randomly generated patterns.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1909-1918
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• 1999

The terrestrial/satellite hybrid network may replace or supply the terrestrial network in some areas or certain applications. For example, it may play a major role in global B-ISDN or in certain areas where the deployment of optical cable is not feasible, especially at the early stage of implementing terrestrial B-ISDN. Furthermore, it can play an important role in the development of B-ISDN due to their features of flexible wide coverage, independent of ground distances and geographical constraints, multiple access and multipoint broadcast. Also, satellite have the capability to supply terrestrial B-ISDN/ATM with flexible links for access networks as well as trunk networks. This paper describes the design and verification of the interworking protocol between terrestrial B-ISDN뭉 satellite network. For the verification, the designed interworking protocol is modeled by Petri-net and the model is analyzed by reachability tree.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.911-914
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• 2009

멀티 네트워크는 여러 무선 접속 기술을 동시에 접속할 수 있도록 구성된 시스템으로 정의되며 Ambient Networks(ANs) 프로젝트로 연구가 진행 중에 있다. 우선 ANs은 여러 다른 무선 장치와 Multi-Radio Access(MRA) 기술이 군집된 동적 통신 환경에서의 네트워킹 개념이다. 따라서 3 세대로 불리는 Global System for Mobile communications(GSM), Universal Mobile Telecommunications System(UMTS) 그리고 무선랜(WLAN)등 다양한 네트워크 인터페이스로 구성된 mobile terminal(MT)이 다양한 무선 접속 기술을 지원하는 멀티네트워크에 접속하여 "Always Best Connected" 관점에서 효율적 접속 서비스를 제공 받아야 한다. 본 논문에서는 멀티네트워크 환경에서 단말에 high-performance를 제공하기 위한 자원관리 모델인 MRRM/RARM(Multi-Radio/Radio Access Resource Management)과 GLL(Generic Link Layer)에 대한 기술 요소를 정의하고 분석한다.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.89-99
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• 2018

Due to global warming, various natural disasters such as floods and droughts are increasing. If we can detect the possibility of natural disasters in advance, we can prevent massive damages caused by natural disasters. Recent advances in visual sensor technologies have enabled remote monitoring of a variety of natural environments, including lakes, rivers, and shores. In this paper, we propose a method to segment an image obtained from video sensor networks into regions in order to monitor the environment effectively. In the proposed method, we first partition the image into superpixels and model the connections between superpixels as a graph. Then, initial seeds for each region are set by using the prior information, and the initial seeds are expanded to form regions using agglomerative clustering. Experimental results show that the proposed method extracts the regions from natural environment images easily and accurately.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.481-484
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• 2009

멀티 네트워크는 여러 무선 접속 기술을 동시에 접속할 수 있도록 구성된 시스템으로 정의되며 Ambient Networks(ANs) 프로젝트로 연구가 진행 중에 있다. 우선 ANs은 여러 다른 무선 장치와 Multi-Radio Access(MRA) 기술이 군집된 동적 통신 환경에서의 네트워킹 개념이다. 따라서 3 세대로 불리는 Global System for Mobile communications(GSM), Universal Mobile Telecommunications System(UMTS) 그리고 무선랜(WLAN)등 다양한 네트워크 인터페이스로 구성된 mobile terminal(MT)이 다양한 무선 접속 기술을 지원하는 멀티네트워크에 접속하여 "Always Best Connected" 관점에서 효율적 접속 서비스를 제공 받아야 한다. 본 논문에서는 멀티네트워크 환경에서 단말에 high-performance를 제공하기 위한 자원관리 모델인 MRRM/RARM(Multi-Radio/Radio Access Resource Management)과 GLL(Generic Link Layer)에 대한 기술 요소를 정의하고 분석한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.483-486
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• 2015

The objective of this study is to develop generalized regression neural networks (GRNN) model for estimating daily solar radiation using limited weather variables at Champaign and Springfield stations in Illinois. The best input combinations (one, two, and three inputs) can be identified using GRNN model. From the performance evaluation and scatter diagrams of GRNN model, GRNN 3 (three input) model produces the best results for both stations. Results obtained indicate that GRNN model can successfully be used for the estimation of daily global solar radiation at Champaign and Springfield stations in Illinois. These results testify the generation capability of GRNN model and its ability to produce accurate estimates in Illinois.