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Adaptive Energy Optimization for Object Tracking in Wireless Sensor Network
( Juan Feng ),( Baowang Lian ),( Hongwei Zhao ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.4
Energy efficiency is critical for Wireless Sensor Networks (WSNs) since sensor nodes usually have very limited energy supply from battery. Sleep scheduling and nodes cooperation are two of the most efficient methods to achieve energy conservation in WSNs. In this paper, we propose an adaptive energy optimization approach for target tracking applications, called Energy-Efficient Node Coordination (EENC), which is based on the grid structure. EENC provides an unambiguous calculation and analysis for optimal the nodes cooperation theoretically. In EENC, the sleep schedule of sensor nodes is locally synchronized and globally unsynchronized. Locally in each grid, the sleep schedule of all nodes is synchronized by the grid head, while globally the sleep schedule of each grid is independent and is determined by the proposed scheme. For dynamic sleep scheduling in tracking state we propose a multi-level coordination algorithm to find an optimal nodes cooperation of the network to maximize the energy conservation while preserving the tracking performance. Experimental results show that EENC can achieve energy saving of at least 38.2% compared to state-of-the-art approaches.
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Xiaomin Liu,Chengbin Yang,Jing Liu,Jianwei Liu,Rui Hu,Hongwei Lian,Guimiao Lin,Liwei Liu,Ken-Tye Yong,Ling Ye 한국생물공학회 2015 Biotechnology and Bioprocess Engineering Vol.20 No.4
The optimization of aldose reductase (AR) expression levels and tracking of the AR expression sites within the cell is an essential step in developing a platform for the effective production of aldose reductase inhibitors (ARIs). In this study, we have demonstrated the use of both immunocytochemistry and quantum dots-based immunofluorescence techniques for observing and detecting the expression level and localization of AR in the cytoplasm and cell membrane of a eukaryotic cell model with high levels of AR protein expression. Our results show that high expression levels of human AR can be achieved using the eukaryotic cell model that we have developed. The overexpressed AR can be used for translational studies of hAR and the screening of ARIs. More importantly, the use of the established quantum dots-based immunofluorescence technique in the intracellular labeling of AR allows the determination of the expression and distribution of the AR gene. Overall, the use of the interdisciplinary approach of both genetic engineering and quantum dot-based immunofluorescence allows not only the effective production of a desired protein, but also the determination of the cellular localization of such an expressed protein.
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