Efficient and power-awareness query over sensor networks

Sensor networks consisted of low-cost, low-power, multifunctional miniature sensor devices have played an important role in our daily life. Light and humidity monitoring, seismic and animal activity detection, environment and habitat monitoring are the most common applications. However, due to the limited power supply, ordinary query methods and algorithms can not be applied on sensor networks. Queries over sensor networks should be power-aware to guarantee the maximum power savings. The minimal power consumption by avoiding the expensive communication of the redundant sensor nodes is concentrated on. A lot of work have been done to reduce the participated nodes, but none of them have considered the overlapping minimum bounded rectangle (MBR) of sensors which make them impossible to reach the optimization solution. The proposed OMSI-tree and OMR algorithm can efficiently solve this problem by executing a given query only on the sensors involved. Experiments show that there is an obvious improvement compared with TinyDB and other spatial index, adopting the proposed schema and algorithm.     

Structural Changes of Water Molecules Upon the Reduction of Quinones in The Reaction Center from Rhodobactery Sphaeroides

1 Results The photosynthetic bacterial reaction center (RC) is a membrane protein complex.The RC is composed of three protein subunits and redox components such as bacteriochlorophylls, bacteriopheophytins,and quinones.The RC performs the photochemical electron transfer from the bacteriochlorophyll dimer through a series of electron donor and acceptor molecules to a secondary quinone,QB.QB accepts electrons from a primary quinone,QA,in two sequential electron transfer reactions.The second electron trans...     

ROLE OF α-PSEUDO-UNIVEX FUNCTIONS IN VECTOR VARIATIONAL-LIKE INEQUALITY PROBLEMS

In this paper, we introduce a new class of generalized convex function, namely, a-pseudounivex function, by combining the concepts of pseudo-univex and α-invex functions. Further, we establish some relationships between vector variational-like inequality problems and vector optimization problems under the assumptions of α-pseudo-univex functions. Results obtained in this paper present a refinement and improvement of previously known results.