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검색결과 774건 처리시간 0.025초

Distributed Construction of Connected Cover Graph in Wireless Sensor Networks

  • Le, Duc Tai;Duc, Thang Le;Hwang, Boram;Choo, Hyunseung
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2012년도 춘계학술발표대회
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    • pp.605-606
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    • 2012

  • In this paper, we consider the problem of scheduling sensor activity to prolong the network lifetime while guaranteeing both discrete target coverage and connectivity among all the active sensors and the sink, called connected target coverage (CTC) problem. We proposed a distributed scheme called Distributed Lifetime-Maximizing Scheme (DLMS) to solve the CTC problem. Our proposed scheme significantly reduces the cost of the construction of the connected cover graphs in comparison with the some conventional schemes. In addition, the energy consumption is more balanced so that the network lifetime will be increased. Our simulation results show that DLMS scheme performs much better than the conventional schemes in terms of the network lifetime.

  • https://doi.org/10.3745/PKIPS.y2012m04a.605 인용 PDF

Development of Analytical Method and Validation using HPLC/PDA for Discrimination between Artemisiae Argyi Folium and Artemisiae Iwayomogii Herba

  • Le, Duc Dat;Nguyen, Duc Hung;Zhao, Bing Tian;Min, Byung Sun;Woo, Mi Hee
    • Natural Product Sciences
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    • 제25권3호
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    • pp.275-283
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    • 2019

  • In this study, we described the new developed method to simultaneously discriminate two herbal drugs of Artemisiae Argyi Folium and Artemisiae Iwayomogii Herba using eight marker compounds (1 - 8) on an HPLC-PDA system. The developed method was applied to quantify the major components of two herbal drugs. The pattern analysis successfully discriminated and evaluated different components between Artemisiae Argyi Folium and Artemisiae Iwayomogii Herba. Results were used for classification of different species from collected samples.

  • https://doi.org/10.20307/nps.2019.25.3.275 인용 PDF KSCI HTML

Estimation of moment and rotation of steel rack connections using extreme learning machine

  • Shariati, Mahdi;Trung, Nguyen Thoi;Wakil, Karzan;Mehrabi, Peyman;Safa, Maryam;Khorami, Majid
    • Steel and Composite Structures
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    • 제31권5호
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    • pp.427-435
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    • 2019

  • The estimation of moment and rotation in steel rack connections could be significantly helpful parameters for designers and constructors in the initial designing and construction phases. Accordingly, Extreme Learning Machine (ELM) has been optimized to estimate the moment and rotation in steel rack connection based on variable input characteristics as beam depth, column thickness, connector depth, moment and loading. The prediction and estimating of ELM has been juxtaposed with genetic programming (GP) and artificial neural networks (ANNs) methods. Test outcomes have indicated a surpass in accuracy predicting and the capability of generalization in ELM approach than GP or ANN. Therefore, the application of ELM has been basically promised as an alternative way to estimate the moment and rotation of steel rack connection. Further particulars are presented in details in results and discussion.

  • https://doi.org/10.12989/scs.2019.31.5.427 인용 KSCI