36931032
A Roof Edge Detection Model
We have generalized the Mumford-Shah model to obtain a new model capable of detecting roof edges. In this new model, we have assumed a piecewise planar surface for each bounded region. We have also shown that this new model is less dependent on the scale parameter ν than the original Mumford-Shah model. We have proved that the gradient projection method can produce the minimal energy. The validity of the new model is demonstrated by experimental results.
5432165
Newimage segmentation models
16148368
A model-based evolutionary algorithm for bi-objective optimization
The Pareto optimal solutions to a multi-objective optimization problem often distribute very regularly in both the decision space and the objective space. Most existing evolutionary algorithms do not explicitly take advantage of such a regularity. This paper proposed a model-based evolutionary algorithm (M-MOEA) for bi-objective optimization problems. Inspired by the ideas from estimation of distribution algorithms, M-MOEA uses a probability model to capture the regularity of the distribution of the Pareto optimal solutions. The local principal component analysis (local PCA) and the least-squares method are employed for building the model. New solutions are sampled from the model thus built. At alternate generations, M-MOEA uses crossover and mutation to produce new solutions. The selection in M-MOEA is the same as in non-dominated sorting genetic algorithm-II (NSGA-II). Therefore, MOEA can be regarded as a combination of EDA and NSGA-II. The preliminary experimental results show that M-MOEA performs better than NSGA-II.
1741788
A Compound TCP Approach for High-Speed and Long Distance Networks
Many applications require fast data transfer over high speed and long distance networks. However, standard TCP fails to fully utilize the network capacity due to the limitation in its conservative congestion control (CC) algorithm. Some works have been proposed to improve the connection 鈂s throughput by adopt- ing more aggressive loss-based CC algorithms. These algorithms, although can effectively improve the link utilization, have the weakness of poor RTT fairness. Further, they may severely de- crease the performance of regular TCP flows that traverse the same network path. On the other hand, pure delay-based ap- proaches that improve the throughput in high-speed networks may not work well when the traffic is mixed with both delay- based and greedy loss-based flows. In this paper, we propose a novel Compound TCP (CTCP) approach, which is a synergy of delay-based and loss-based approach. Specifically, we add a scal- able delay-based component into the standard TCP Reno conges- tion avoidance algorithm (a.k.a., the loss-based component). The sending rate of CTCP is controlled by both components. This new delay-based component can rapidly increase sending rate when network path is under utilized, but gracefully retreat in a busy network when bottleneck queue is built. Augmented with this delay-based component, CTCP provides very good bandwidth scalability with improved RTT fairness, and at the same time achieves good TCP-fairness, irrelevant to the windows size. We developed an analytical model of CTCP and implemented it on the Windows operating system. Our analysis and experiment results verify the properties of CTCP.
3994784
Error minimization for approximate computation of range aggregates
Histogram techniques are widely used in commercial database management systems for an estimation of query results. Recently, they have been also used in approximately, processing database queries, especially aggregation queries. Existing research results in this area have been mainly focused on constructing a histogram to approximately represent, as accurate as possible on an intuitive base, the original data frequencies. We propose a novel histogram construction method aiming to minimize the average approximate aggregation errors; and we have developed an efficient algorithm to construct near optimal histograms to achieve this goal. Our experiment results showed that the new histogram construction techniques lead to more accurate results than those by existing histogram techniques, and also out-perform the existing wavelet techniques.
14103418
Front Tracking: A Parallelized Approach for Internal Boundaries and Interfaces
Internal boundaries and interfaces are an important part of many fluid and solid modeling problems. Front Tracking contains a general interface framework, closely related to the non-manifold geometry used in CAD solid modeling packages, to support numerical simulation of such fluid problems. It can thus be considered to be a systematic application of the ideas of computational geometry to computational fluid dynamics. It is based on the principle that finite differences behave best when applied to differentiable functions, and that weak derivatives of nondifferentiable functions can be replaced by regularized expressions such as jump conditions. Front Tracking offers superior resolution for fluid problems with important discontinuities and interfaces, and in some cases, it has provided the unique method to obtain correct answers. Here we present Computer Science issues which have contributed to the success of Front Tracking: software design and organization — modularity, data structures and data hiding.
12387425
Self-Protection for Wireless Sensor Networks
Wireless sensor networks have recently been suggested for many surveillance applications such as object monitoring, path protection, or area coverage. Since the sensors themselves are important and critical objects in the network, a natural question is whether they need certain level of protection, so as to resist the attacks targeting on them directly. If this is necessary, then who should provide this protection, and how it can be achieved? We refer to the above problem as self-protection, as we believe the sensors themselves are the best (and often the only) candidate to provide such protection. In this papel; we for the jirst time present a formal study on the selfprotection problem in wireless sensor networks. We show that, if we simply focus on the quality ofjield or object covering, the sensors might not necessarily be self-protected, which in turn makes the system vulnerable. We then investigate dzreerent forms of self-pmtections, and show that the problems are generally NP-complete. We develop eficient approximation algorithms for centrally-controlled sensors. We then extend the algorithms to filly distributed implementation, and introduce a smart sleep-scheduling algorithm that minimize the energy consumption.