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Vartika Shah,Sanjiv Sharma 보안공학연구지원센터 2014 International Journal of Grid and Distributed Comp Vol.7 No.5
Wireless sensor network (WSN) is a collection of densely deployed sensor nodes. These nodes are prone to attack and also resource constrained. Resource accountability is also required for Security implementation in WSN. Some researchers proposed different methods, algorithms and frameworks for WSN security implementation. SPINS is a framework for implementing overall security in WSN using SNEP (Sensor Network Encryption Protocol) and μTESLA (the “micro” version of the Timed, Efficient, Streaming, Loss-tolerant Authentication Protocol) protocol. Existing research works reveal that SNEP employed RC5 encryption algorithm for WSN. This paper analyzed efficient encryption algorithm XTEA for SNEP & evaluate that it is better as compare to RC5 in terms of energy, storage and time.
Synthesis, Characterization and Antimicrobial Activity of Zirconium (IV) Complexes
Sharma, Shobhana,Jain, Asha,Saxena, Sanjiv Korean Chemical Society 2012 대한화학회지 Vol.56 No.4
Heteroleptic complexes of zirconium (IV) derived from bulky Schiff base ligands containing a sulphur atom and oximes of heterocyclic ${\beta}$-diketones of the general formula ZrLL' (where $LH_2=RCNH(C_6H_4)SC:C(OH)N(C_6H_5)N:CCH_3$, $R=-C_6H_5$, $-C_6H_4Cl(p)$ and $L^{\prime}H_2=R^{\prime}C:(NOH)C:C(OH)N(C_6H_5)N:CCH_3$, $R^{\prime}=-CH_2CH_3$, $-C_6H_5$, $-C_6H_4Cl(p)$ were prepared by the reactions of zirconium tetrachloride with disodium salts of Schiff bases ($L\;Na_2$) and oximes of heterocyclic ${\beta}$-diketones ($L^{\prime}\;Na_2$) in 1:1:1 molar ratio in dry refluxing THF. The structures of these monomeric zirconium (IV) complexes were elucidated with the help of elemental analysis, molecular weight measurements, spectroscopic (IR, NMR and mass) studies. A distorted trigonal bipyramidal geometry may be suggested for these heteroleptic zirconium (IV) complexes. The ligands (bulky Schiff base ligands containing a sulphur atom and oximes of heterocyclic ${\beta}$-diketones) and their heteroleptic complexes of zirconium (IV) were screened against A. flavus, P. aeruginesa and E. coli.
A Comparative Study of Existing Cluster-Based Routing Protocols in Wireless Sensor Networks
Pooja Mishra,Sanjiv Sharma 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.7
Wireless Sensor Network (WSN) has grown vastly in the past few years and pointing out the crucial need for scalable and energy efficient network. Routing in WSN is challenging task because of limited resources of available energy and processing power. On the basis of network structure, routing protocol in WSN can be classified into two different categories such as flat routing and cluster-based or hierarchical routing. In literature review, researchers proposed a number of routing protocols in WSN. In which cluster-based routing protocols shows better performance as compare to other routing protocols. Therefore, the objective of this paper is to provide a review on some efficient cluster-based routing protocols with advantages and limitations.
Elisa Cuadrado-Godia,Pratistha Dwivedi,Sanjiv Sharma,Angel Ois Santiago,Jaume Roquer Gonzalez,Mercedes Balcells,John Laird,Monika Turk,Harman S. Suri,Andrew Nicolaides,Luca Saba,Narendra N. Khanna,Jas 대한뇌졸중학회 2018 Journal of stroke Vol.20 No.3
Cerebral small vessel disease (cSVD) has a crucial role in lacunar stroke and brain hemorrhages and is a leading cause of cognitive decline and functional loss in elderly patients. Based on underlying pathophysiology, cSVD can be subdivided into amyloidal and non-amyloidal subtypes. Genetic factors of cSVD play a pivotal role in terms of unraveling molecular mechanism. An important pathophysiological mechanism of cSVD is blood-brain barrier leakage and endothelium dysfunction which gives a clue in identification of the disease through circulating biological markers. Detection of cSVD is routinely carried out by key neuroimaging markers including white matter hyperintensities, lacunes, small subcortical infarcts, perivascular spaces, cerebral microbleeds, and brain atrophy. Application of neural networking, machine learning and deep learning in image processing have increased significantly for correct severity of cSVD. A linkage between cSVD and other neurological disorder, such as Alzheimer’s and Parkinson’s disease and non-cerebral disease, has also been investigated recently. This review draws a broad picture of cSVD, aiming to inculcate new insights into its pathogenesis and biomarkers. It also focuses on the role of deep machine strategies and other dimensions of cSVD by linking it with several cerebral and non-cerebral diseases as well as recent advances in the field to achieve sensitive detection, effective prevention and disease management.