but often the main goal is to avoid congestion, i.e. overloading of links, and the standard heuristic recommended by Cisco (a major router vendor) is to make the weight of a link inversely proportional to its capacity. We study the problem of optimizing OSPF weights for a given a set of projected demands so as to avoid congestion. We show this problem is NP-hard and propose a local search heuristic to solve it. We also provide worst-case results about the performance of OSPF routing vs. an optimal multi-commodity flow routing. Our numerical experiments compare the results obtained with our local search heuristic to the optimal multi-commodity flow routing, as well as simple and commonly used heuristics for setting the weights. Experiments were done with a proposed nextgeneration AT&T WorldNet backbone as well as synthetic internetworks.

In this paper, we present a new approach to recognizing hand signs. In this approach, motion recognition (the hand movement) is tightly coupled with spatial recognition (hand shape). The system uses multiclass, multidimensional discriminant analysis to automatically select the most discriminating linear features for gesture classification. A recursive partition tree approximator is proposed to do classification. This approach combined with our previous work on hand segmentation forms a new framework which addresses the three key aspects of hand sign interpretation: the hand shape, the location, and the movement. The framework has been tested to recognize 28 different hand signs. The experimental results show that the system achieved a 93.2% recognition rate for test sequences that have not been used in the training phase. It is shown that our approach provides better performance than the nearest neighbor classification in the eigen-subspace. 1 1 Introduction The ability to i...

In this paper, we have presented a three-stage framework to analyze time-varying image sequences. The focus of this paper is the second stage: segmentation. We propose a prediction-and-verification segmentation scheme which efficiently utilizes the attention images from the multiple fixations. The experimental results show 95% correct segmentation rate with 3% false rejection rate of 805 testing images. The recognition of hand sign based on the segmentation results has shown that the system has achieved a good performance for this very difficult vision task. 1 Introduction The ability to interpret hand signs is essential for human machine interface. Recently, there is a significant amount of research on vision-based hand sign recognition (e.g. [1, 3, 4, 6, 8, 9]). One of the major difficulties faced by the vision-based approaches is the segmentation of the moving hand from sometimes complex backgrounds. To avoid the above problem, some of the systems rely on markers. The others use r...

This paper presents a prediction-and-verification segmentation scheme using attention images from multiple fixations. The scheme has two major components: (a) a hierarchical quasi-Voronoi diagram which organizes training attention images for prediction of the segmentation masks; (b) a learning-based function approximation scheme to verify the segmentation result. A major advantage of this scheme is that it can handle a large number of different deformable objects presented in complex backgrounds. The scheme is also relatively efficient since the segmentation is guided by the past knowledge through a prediction-and-verification scheme. The system was tested to segment hands in sequences of intensity images, where each sequence represents a hand sign in American Sign Language. The experimental result showed a 95% correct segmentation rate with a 3% false rejection rate. Categories: 2D segmentation, hand sign recognition, visual learning, nearest neighbor, and feature derivatio...

This paper presents a prediction-and-verification segmentation scheme using attention images from multiple fixations. A major advantage of this scheme is that it can handle a large number of different deformable objects presented in complex backgrounds. The scheme is also relatively efficient since the segmentation is guided by the past knowledge through a prediction-andverification scheme. The system has been tested to segment hands in the sequences of intensity images, where each sequence represents a hand sign. The experimental result showed a 95% correct segmentation rate with a 3% false rejection rate. 1 Introduction The ability to interpret hand signs is essential for human machine interface. Recently, there is a significant amount of research on vision-based hand sign recognition (e.g. [1, 3, 4, 7, 11, 13]). One of the major difficulties faced by the vision-based approach is segmentation of the moving hand from sometimes complex backgrounds. To avoid the above problem, some of...

A hardware self-managing heap memory (RCM) for languages like LISP, SMALLTALK, and JAVA has been designed, built, tested and benchmarked. On every pointer write from the processor, reference-counting transactions are performed in real time within this memory, and garbage cells are reused without processor cycles. A processor allocates new nodes simply by reading from a distinguished location in its address space. The memory hardware also incorporates support for off-line, multiprocessing, mark-sweep garbage collection. Performance statistics are presented from a partial implementation of SCHEME over five different memory models and two garbage collection strategies, from main memory (no access to RCM) to a fully operational RCM installed on an external bus. The performance of the RCM memory is more than competitive with main memory.

Abstract. We consider the issues of implicitness and cache-obliviousness in the classical dictionary problem for n distinct keys over an unbounded and ordered universe. One finding in this paper is that of closing the longstanding open problem about the existence of an optimal implicit dictionary over an unbounded universe. Another finding is motivated by the antithetic features of implicit and cache-oblivious models in data structures. We show how to blend their best qualities achieving O(log n) time and O(log B n) block transfers for searching and for amortized updating, while using just n memory cells like sorted arrays and heaps. As a result, we avoid space wasting and provide fast data access at any level of the memory hierarchy. 1

It is well-known, and was first established by Knuth in 1969, that the number of 321-avoiding permutations is equal to that of 132-avoiding permutations. In the literature one can find many subsequent bijective proofs of this fact. It turns out that some of the published bijections can easily be obtained from others. In this paper we describe all bijections we were able to find in the literature and show how they are related to each other via “trivial” bijections. We classify the bijections according to statistics preserved (from a fixed, but large, set of statistics), obtaining substantial extensions of known results. Thus, we give a comprehensive survey and a systematic analysis of these bijections. We also give a recursive description of the algorithmic bijection given by Richards in 1988 (combined with a bijection by Knuth from 1969). This bijection is equivalent to the celebrated bijection of Simion and Schmidt (1985), as well as to the bijection given by Krattenthaler in 2001, and it respects 11 statistics — the largest number of statistics any of the bijections respects.

In the classical dictionary problem, a set of n distinct keys over an unbounded and ordered universe is maintained under insertions and deletions of individual keys while supporting search operations. An implicit dictionary has the additional constraint of occupying the space merely required by storing the n keys, that is, exactly n contiguous words of space in total. All what is known is the starting position of the memory segment hosting the keys, as the rest of the information is implicitly encoded by a suitable permutation of the keys. This paper describes the at implicit tree, which is the rst implicit dictionary requiring O(log n) time per search and update operation.

Introduction Balancing networks were devised by Aspnes et al. [4] as a novel class of distributed data structures that provide highly-concurrent, low-contention solutions to a varietyofmultiprocessor synchronization problems. A balancing network is constructed from elementary switches with # input wires and # output wires, called (## #)-balancers. A (## #)-balancer accepts a stream of tokens on its # input wires. The #-th token to enter the balancer leaves on output wire # mod #, where # =0# 1####. One can think of a balancer as having a \toggle" state variable tracking which output wire the next token should exit from. A token traversal amounts to a Fetch&Increment operation to the toggle variable. This operation includes reading the current state of the toggle,