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RISS 인기검색어
- 검색키워드
- 저자 : Varalakshmi Perumal (검색결과 3 건)
- 무료
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A Honey-Hive based Efficient Data Aggregation in Wireless Sensor Networks
Nandhakumar Ramachandran,Varalakshmi Perumal 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.2
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.
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A Honey-Hive based Efficient Data Aggregation in Wireless Sensor Networks
Ramachandran, Nandhakumar,Perumal, Varalakshmi The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.2
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.
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Navanietha Krishnaraj Rathinam,Chandran Saravanan,Pal Parimal,Varalakshmi Perumal,Malliga Perumal 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.5
Graphene draws considerable attention among biomedical researchers because of its unique physical, chemicaland biological properties. The wide applications of graphene in the biomedical arena such as diagnostics, drug immobilizationand drug delivery were well documented in the literature. However the therapeutic potential of the graphenetowards retroviruses and the interactions of the graphene with receptors/proteins are still unexplored. Herein we reportthe antagonistic molecular interactions of graphene with the three key target proteins of HIV infections namely HIVVpr,Nef and Gag proteins. The docking investigations were performed to find the binding energy of the graphene ligandsto the key target proteins of HIV. The high binding affinity of the graphene to these proteins indicates the antagonisticmolecular interaction of graphene to the disease targets. The therapeutic potential of graphene was also studied by changingthe size and the number of layers of the graphene. The experimental results confirm the good therapeutic potential ofthe graphene to combat HIV mediated retroviral infections.
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