6156793
Optimum Robot Control for 3D Virtual Fixture in Constrained ENT Surgery
In ENT surgery, the operating volume is very limited. This is especially true in sinus surgery, when the instrument passes through the sinus cavity to reach the pathological area. The sinus bones impose geometric constraints on the work volume. During the surgery, the surgeon needs to take care of the motion of the instrument tip to accomplish some delicate procedure; meanwhile he/she needs to avoid hitting anatomic constraints. In this paper, we present a method to assist the path following task in a constrained area. We project instrument tip motion, boundary information on the joint displacement via robot kinematics, and then use a constrained quadratic optimization algorithm to compute the optimal set of corresponding joint displacements. In the preliminary study, we show that the optimization constrained control can avoid collision with geometric constraints on the work volume, while keeping the precision of the tool motion.
12850359
Recognition of operator motions for real-time assistance using virtual fixtures
Hidden Markov Models (HMMs) are used for automatic segmentation and recognition of user motions. A new algorithm for real-time HMM recognition was developed. The segmentation results are used to provide appropriate assistance in a combined curve following and object avoidance task. This assistance takes the form of a virtual fixture, whose compliance can be altered online. Recognition and assistance experiments were performed using force and position data recorded from a cooperative manipulation system, where a robot and a human operator hold an instrument simultaneously. Recognition accuracy exceeds 90%, even when the users training the HMMs differ from those executing the task. For a task consisting of both path following and avoidance motions, an HMM-based virtual fixture switches the compliance from low to high when the user is trying to move away from the path. The HMM method improves operator performance in comparison with a constant virtual fixture and no virtual fixture.
13977817
Analysis of multi-hop traffic grooming in WDM mesh networks
Traffic grooming is an essential functionality of WDM optical networks to provision multi-granularity subwave-length connections. Depending on the number of lightpaths allowed in a connection route, traffic grooming can be classified as single-hop traffic grooming (SH-TG) and multi-hop traffic grooming (MH-TG). MH-TG is more general and resource-efficient than SH-TG, because it allows connections from different source-destination pairs to share the bandwidth of a lightpath. In this paper, we propose a MH-TG algorithm, namely the fixed-order multi-hop (FOMH) grooming algorithm, based on the fixed-alternate routing approach. We introduce the grooming node selection (GNS) problem in MH-TG and propose three grooming policies, namely exhaustive sequential (ES), limited-hop sequential (LHS) and load sharing (LS) policies, to address the GNS problem. Given that the analysis of MH-TG is a relatively unexplored area, we propose an analytical model to evaluate the blocking performance of MH-TG using FOMH and the LS grooming policy. To address the multi-layered routing and multi-rate connection characteristics of traffic grooming, we introduce a novel multi-level decomposition approach in our analytical model which decomposes traffic at four different levels, namely alternate path, connection route, lightpath and link levels. The Erlang fixed-point approximation method is used to solve the analytical model. Numerical results show that analytical results matches well with simulation results. We also evaluate the effect of the grooming policies, the number of virtual hops (lightpaths) within a connection route and the number of alternate paths on the performance of the grooming algorithm.
33110840
A Level Set Approach for Shape Recovery of Open Contours
In this paper, a geometric deformable model for shape recovery of open contours in noisy images is presented. We use two level set functions to model the open contour and find the end points of the open contour as the intersection of the two level set functions. The evolutions of both level set functions do not depend on the gradient of the images, as in the classical geometric deformable models, but are decided by a region-based band velocity. The band velocity is different from region information introduced by other deformable models which can only be used to find the closed contours in images, it is designed for evolutions of both closed and open contours and particularly unique for contours which are open and do not enclose any region. Prior shape information is also integrated into the contour evolution process, which prevents two level set functions from intersecting at other places than at the contour end points. With the described method open contours can be recovered from noisy images. Successful experiments on several data sets are presented in this paper.
1529480
A compression algorithm for DNA sequences and its applications in genome comparison
We present a lossless compression algorithm, <italic>Gen-Compress</italic>, for DNA sequences, based on searching for approximate repeats. Our algorithm achieves the best compression ratios for benchmark DNA sequences, comparing to other DNA compression programs [3, 7]. Significantly better compression results show that the approximate repeats are one of the main hidden regularities in DNA sequences.
We then describe a theory of measuring the relatedness between two DNA sequences. We propose to use <italic>d</italic>(<italic>x</italic>, <italic>y</italic>) = 1 — <italic>K</italic>(<italic>x</italic>) - <italic>K</italic>(<italic>x</italic>|<italic>y</italic>)/<italic>K</italic>(<italic>xy</italic> to measure the distance of any two sequences, where <italic>K</italic>  stands for Kolmogorov complexity [5]. Here, <italic>K</italic>(<italic>x</italic>) - <italic>K</italic>(<italic>x</italic>|<italic>y</italic>) is the mutual information shared by <italic>x</italic> and <italic>y</italic>. But mutual information is not a distance, there is no triangle inequality. The distance <italic>d</italic>(<italic>x</italic>, <italic>y</italic>) is symmetric. It also satisfies the triangle inequality, and furthermore, it is universal [4].
It has not escaped our notice that the distance measure we have postulated can be immediately used to construct evolutionary trees from DNA sequences, especially those that cannot be aligned, such as complete genomes. With more and more genomes sequenced, constructing trees from genomes becomes possible [1, 2, 6, 8].  Kolmogorov complexity is not computable. We use <italic>GenCompress</italic> to approximate it. We present strong experimental support for this theory, and demonstrate its applicability by correctly constructing a 16S (18S) rRNA tree, and a whole genome tree for several species of bacteria. Larger scale experiments are underway at the University of Waterloo, with very promising results.
32091631
K One-Way Heads Cannot Do String-Matching
We settle a conjecture raised by Z. Galil and J. Seiferas 14 years ago (J. Comput. System Sci.26(1983), 280?294):k-head one-way deterministic finite automata cannot perform string-machine (i.e., accept the language {x#y??u?vy=uxv}), for anyknonsensing heads.
368077
Approximation of Walrasian equilibrium in single-minded auctions
We consider a social optimization model of pricing scheme in single-minded auctions, in cases where Walrasian equilibrium does not exist. We are interested in the maximization of the ratio, R, of happy bidders over all agents, in a feasible allocation-pricing scheme. We show NP-hardness of the optimization problem, establish lower and upper bounds of R, as well as develop greedy algorithms to approximate the optimal value of R.