10,000 publications from this institution
We propose a practical and scalable technique for point-to-point routing in wireless sensornets. This method, called Beacon Vector Routing (BVR), assigns coordinates to nodes based on the vector of hop count distances to a small set of beacons, and then defines a distance metric on these coordinates. BVR routes packets greedily, forwarding to the next hop that is the closest (according to this beacon vector distance metric) to the destination. We evaluate this approach through a combination of high-level simulation to investigate scaling and design tradeoffs, and a prototype implementation over real testbeds as a necessary reality check.
Abstract Multisubstituted tetrahydrofurans are enantioselectively and diastereoselectively obtained by cyclization reactions of 2‐aryl‐1,3‐diols.
Li-ion batteries are one of the most advanced energy storage technologies in use today. Li-ion batteries are used in a multitude of applications ranging from consumer electronics, medical devices, sensors and grid storage. However, improving the capacity and energy density delivered by current Li-ion technology requires advanced materials research into novel chemical systems. In this project we have focused particularly in the use of solid-state electrolytes with lithium metal electrodes. Research into all solid-state batteries (ASSB) with Li metal electrodes has significantly expanded in recent years, however most studies reported experimental findings, which left substantial room for theoretical and modeling work as a tool to understand and determine design principles allowing reliable and safe use of ASSBs with Li metal. Among the remaining obstacles preventing reliable use of ASSBs with a Li metal electrode, the stability of the interface between the solid electrolyte and Li metal, and the propagation/dendrite formation of Li metal and resulting mechanical degradation of the electrolyte are key phenomenon that are yet to be fully understood. In the current project we have addressed these two coupled phenomena using first principles calculations and mesoscale continuum modeling. We have obtained chemical and electrochemical stability windows for several solid electrolyte materials. Additionally, from mathematical and numerical modeling of Li protrusion and dendrite initiation during plating and stripping we have determined design criteria in terms of chemical, electrochemical, and mechanical properties and operating conditions for which stable deposition can occur. We also considered the effects of mixed electronic-ionic conduction in solid electrolytes, which has more recently been suggested as another important mechanism involved in ASSB failure. Throughout our work we have successfully addressed important questions necessary for the use of ASSB’s. We have determined guiding principles for materials properties and operating conditions necessary to operate ASSB’s. And have proposed novel solid electrolyte materials with predicted chemical stability an ionic conductivity. Although this represents significant progress in our understanding, open questions remain in order to fully develop reliable and safely operate ASSBs with Li metal. Future work, building on this project will require further experimental, theoretical and simulation efforts to address remaining questions.
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Abstract not Available.
Mid-level vision refers to a collection of visual processes and their associated principles, including contour grouping, region grouping, and figure/ground organization. Evidence from psychophysics strongly suggests that mid-level vision is a key component of the visual system and heavily interacts with object and scene recognition. We develop a unified probabilistic framework of mid-level vision, both motivated by and evaluated on human-annotated collections of natural images. We use human-marked boundaries in natural images as ground-truth data. Empirical studies of these boundaries reveal a number of power laws distributions, confirming the intuition that natural images are multi-scale or near scale-invariant in nature. We show that pixel-based Markov models fail to capture such invariance. We propose a scale-invariant mid-level representation from bottom-up. We detect edges in an image, build a discrete piecewise linear approximation of the edges, and finally use constrained Delaunay triangulation (CDT) to complete gradient-less gaps and partition the image into regions. We show that the CDT graph is a compact representation with little loss of structure. On top of the CDT representation, we formulate mid-level vision as contour and region labeling problems. We use conditional random fields (CRF) to capture interactions between contours, junctions and regions. Efficient inference on the CRF is done with loopy belief propagation, and maximum likelihood parameters are obtained through gradient descent. We apply the CDT/CRF framework on various mid-level vision problems, including curvilinear grouping, figure/ground assignment, and figure/ground segmentation. By extensive experimentation on large annotated datasets, we are able to demonstrate, quantitatively, the effectiveness of mid-level visual cues in natural images: we show that curvilinear grouping improves boundary detection; we show that figure/ground organization is feasible without object knowledge; and we show how low-, mid-, and high-level visual cues can be integrated and systematically analyzed in our framework.