Mechanical and Manufacturing Engineering

In this paper, we have proposed a time efficient, energy saving and robust broadcast/multicast protocol for reconfigurable cluster-based sensor network. In our broadcast protocol, a broadcast can be executed in rounds and each node needs to be awake in rounds, where and d are the degrees of G and the sub-network induced by the network backbone, respectively, and h is the height of the backbone. When k channels are available, the broadcast can be executed in rounds and each. We show that our broadcast protocol can be readily modified to the one for multicast. The cluster-based architecture used in this paper for a sensor network is an improved version in . The proposed network architecture is self-constructible and self-reconfigurable by using two topological management operations: node-move-in and node-move-out. Details of the protocol along with experimental results are discussed. Simulation results show that the protocol performance is much better than that in the theoretical analysis. ) ( 2 2 D hd O ) ( 2 D O D ) / ) (( 2 2 k D hd O

Lab-on-a-chip platforms present many new opportunities to study bacterial cells and cellular assemblies. Here, a new platform is described that allows application of uniaxial stress to individual bacterial cells while observing the cell and its subcellular assemblies using a high resolution optical microscope. The microfluidic chip consists of arrays of miniature pressure actuated valves. By placing a bacterium under one of such valves and partially closing the valve by externally applied pressure, the cell can be deformed. Although large pressure actuated valves used in integrated fluidic circuits have been extensively studied previously, here those microfluidic valves are downsized and flow channels with rectangular cross-sections are used to maintain the bacteria in contact with cell culture medium during the experiments. The closure of these valves has not been characterized before. First, these valves are modeled using finite element analysis, and then the modeling results are compared to the actual closing profiles of the valves, which is determined from absorption measurements. The measurements and modeling show with good agreement that the deflection of valves is a linear function of externally applied pressure and the deflection scales proportionally to the width of the flow channel. In addition to characterizing the valve, the report also demonstrates at a proof-of-principle level that the device can be used to deform a bacterial cell at considerable magnitude. The largest deformations are found in 5 lm wide channels where the bacterial width and length increase by 1.6 and 1.25 times, respectively. Narrower and broader channels are less optimal for these studies. The platform presents a promising approach to probe, in a quantitative and systematic way, the mechanical properties of not only bacterial cells but possibly also yeast and other single-celled organisms. V

Center of Excellence For Battlefield Sensor Fusion  There is an emerging need for precise detection, tracking, identification, and classification of vehicles in SAR imaging.  Deep learning classifiers require large-scale training imagery datasets.  Comprehensive SAR Image datasets are often classified, preventing the researchers to develop dependable ATR systems.  Generation of large-scale SAR imagery datasets in the physical environments are tedious, time consuming, and costly.