Shen Y.,Toyota USA
Proteins: Structure, Function and Bioinformatics | Year: 2013
Since the fourth evaluation for critical assessment of prediction of interactions (CAPRI), we have made improvements in three major areas in our refinement approach, namely the treatment of conformational flexibility, the binding free energy model, and the search algorithm. First, we incorporated backbone flexibility into our previous approach, which only optimized rigid backbone poses with limited side-chain flexibility. Here, we formulated and solved the conformational search as a hierarchical optimization problem (involving rigid-body poses, backbone flexibility, and side-chain flexibility). Second, we used continuum electrostatic calculations to include solvation effects in the binding free energy model. Finally, we eliminated sloppy modes (directions in which the free energy is essentially constant) to improve the efficiency of the search. With these improvements, we produced correct predictions for 6 of the 10 latest CAPRI targets, including one high, three medium, and two acceptable accuracy predictions. Compared to our previous performance in CAPRI, substantial improvements have been made for targets requiring homology modeling. © 2013 Wiley Periodicals, Inc.
Sarwate A.D.,Toyota USA |
Dimakis A.G.,University of Southern California
IEEE Transactions on Information Theory | Year: 2012
The influence of node mobility on the convergence time of averaging gossip algorithms in networks is studied. It is shown that a small number of fully mobile nodes can yield a significant decrease in convergence time. A method is developed for deriving lower bounds on the convergence time by merging nodes according to their mobility pattern. This method is used to show that if the agents have 1-D mobility in the same direction, the convergence time is improved by at most a constant. Upper bounds on the convergence time are obtained using techniques from the theory of Markov chains and show that simple models of mobility can dramatically accelerate gossip as long as the mobility paths overlap significantly. Simulations verify that different mobility patterns can have significantly different effects on the convergence of distributed algorithms. © 2012 IEEE.
Parikh D.,Toyota USA
Proceedings of the IEEE International Conference on Computer Vision | Year: 2011
The performance of current state-of-the-art computer vision algorithms at image classification falls significantly short as compared to human abilities. To reduce this gap, it is important for the community to know what problems to solve, and not just how to solve them. Towards this goal, via the use of jumbled images, we strip apart two widely investigated aspects: local and global information in images, and identify the performance bottleneck. Interestingly, humans have been shown to reliably recognize jumbled images. The goal of our paper is to determine a functional model that mimics how humans recognize jumbled images i.e. exploit local information alone, and further evaluate if existing implementations of this computational model suffice to match human performance. Surprisingly, in our series of human studies and machine experiments, we find that a simple bag-of-words based majority-vote-like strategy is an accurate functional model of how humans recognize jumbled images. Moreover, a straightforward machine implementation of this model achieves accuracies similar to human subjects at classifying jumbled images. This indicates that perhaps existing machine vision techniques already leverage local information from images effectively, and future research efforts should be focused on more advanced modeling of global information. © 2011 IEEE.
Kenney J.B.,Toyota USA
Proceedings of the IEEE | Year: 2011
Wireless vehicular communication has the potential to enable a host of new applications, the most important of which are a class of safety applications that can prevent collisions and save thousands of lives. The automotive industry is working to develop the dedicated short-range communication (DSRC) technology, for use in vehicle-to-vehicle and vehicle-to-roadside communication. The effectiveness of this technology is highly dependent on cooperative standards for interoperability. This paper explains the content and status of the DSRC standards being developed for deployment in the United States. Included in the discussion are the IEEE 802.11p amendment for wireless access in vehicular environments (WAVE), the IEEE 1609.2, 1609.3, and 1609.4 standards for Security, Network Services and Multi-Channel Operation, the SAE J2735 Message Set Dictionary, and the emerging SAE J2945.1 Communication Minimum Performance Requirements standard. The paper shows how these standards fit together to provide a comprehensive solution for DSRC. Most of the key standards are either recently published or expected to be completed in the coming year. A reader will gain a thorough understanding of DSRC technology for vehicular communication, including insights into why specific technical solutions are being adopted, and key challenges remaining for successful DSRC deployment. The U.S. Department of Transportation is planning to decide in 2013 whether to require DSRC equipment in new vehicles. © 2006 IEEE.
Chuzhoy J.,Toyota USA
Proceedings of the Annual ACM Symposium on Theory of Computing | Year: 2012
Given an undirected graph G=(V,E) with edge capacities c e ≥ 1 for e ε E and a subset T of k vertices called terminals, we say that a graph H is a quality-q cut sparsifier for G iff T ⊆ V(H), and for any partition (A,B) of T, the values of the minimum cuts separating A and B in graphs G and H are within a factor q from each other. We say that H is a quality-q flow sparsifier for G iff T ⊆ V(H), and for any set D of demands over the terminals, the values of the minimum edge congestion incurred by fractionally routing the demands in D in graphs G and H are within a factor q from each other. So far vertex sparsifiers have been studied in a restricted setting where the sparsifier H is not allowed to contain any non-terminal vertices, that is V(H)=T. For this setting, efficient algorithms are known for constructing quality-O(log k/log log k) cut and flow vertex sparsifiers, as well as a lower bound of Ω(√log k) on the quality of any flow or cut sparsifier. We study flow and cut sparsifiers in the more general setting where Steiner vertices are allowed, that is, we no longer require that V(H)=T. We show algorithms to construct constant-quality cut sparsifiers of size O(C 3) in time poly(n)·2 C, and constant-quality flow sparsifiers of size C O(log log C) in time n O(log C)·2 C, where C is the total capacity of the edges incident on the terminals. © 2012 ACM.