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대심도 지하터널 주변의 암반 손상영역에 미치는 지보의 영향에 대한 수치해석적 연구
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Infrared Metasurface Augmented by Deep Learning for Monitoring Dynamics between All Major Classes of Biomolecules
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De Economist
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Insomnia disorder and long‐term mortality in adult patients treated with extracorporeal membrane oxygenation in South Korea
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한국경제물류비용의 결정요인에 관한 연구
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Anthralin - UVB 광요법에 의한 건선의 치료
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Dynamic Session Key based Pairwise Key Management Scheme for Wireless Sensor Networks
( Premamayudu B ),( K. Venkata Rao ),( P. Suresh Varma ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.12
Security is one of the major challenges in the Wireless Sensor Networks (WSNs). WSNs are more vulnerable to adversarial activities. All cryptographic security services indirectly depend on key management. Symmetric key management is the best key establishment process for WSNs due to the resource constraints of the sensors. In this paper, we proposed dynamic session key establishment scheme based on randomly generated nonce value and sensor node identity, in which each sensor node is equipped with session key on expire basis. The proposed scheme is compare with five popular existing key management systems. Our scheme is simulated in OMNET++ with MixiM and presented experimental results. The analytical study and experimental results show the superiority of the proposed scheme over the existing schemes in terms of energy, storage, resilience and communication overhead.
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Acquiring Business Intelligence through Temporal Mining of Smart Meter Data
Siva Koteswara Rao Chinnam,AV Krishna Prasad,B.Premamayudu,Moka Vinod,Hye-Jin Kim 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.9
More and more enterprises are switching over to Machine learning applications to improve their analyzing and predicting capabilities of their business. In this paper we propose a new outlook towards utility computing where public services can be view as a business. A public service can be better delivered by viewing it as a business model rather than a service model. The demand supply can be better analyzed and predicted by our model. This paper is about using efficient mining techniques on real time smart meter data for any utility like water, power or gas etc. The parameters that smart meters provide from time to time over a network can give us real time readings of the consumption which in itself adds enough intelligence to the service. Now by applying temporal mining techniques on this smart meter data we attempt to show how the Business intelligence can be improved by data analysis and analytics. Though there is an opposition from some point of views that smart meters are hazardous to health due to its RF technology we can only improve utility computing by smarter data so that the service in efficient and effective.
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