Resampling techniques such as bagging are often used in supervised learning to produce more accurate classifiers. In this work, we show that multiple-instance learning admits a different form of resampling, which we call “shuffling.” In shuffling, we resample instances in such a way that the resulting bags are likely to be correctly labeled. We show that resampling results in both a reduction o...

Protein structure analysis is one of the most important research issues in the post-genomic era, and faster and more accurate index data structures for such 3-D structures are highly desired for research on proteins. The geometric suffix tree is a very sophisticated index structure that enables fast and accurate search on protein 3-D structures. By using it, we can search from 3-D structure dat...

The conventional parameter optimisation of PID controller is easy to produce surge and big overshoot, and therefore heuristics such as genetic algorithm (GA), particle swarm optimisation (PSO) are employed to enhance the capability of traditional techniques. But the major problem of these algorithms is that they may be trapped in the local optima of the objective and lead to poor performance. I...

Validation of robotics theory on real-world hardware platforms is important to prove the practical feasibility of algorithms. This paper discusses some of the lessons learned while adapting the EvoBot, a low-cost robotics platform that we designed and prototyped, for research in diverse areas in robotics. The EvoBot platform was designed to be a lowcost, open source, general purpose robotics pl...

This paper proposes an electoral cooperative particle swarm optimization approach to optimize the model of neural network from both structure and linked weights. Different with other related research work, a new encoding method is adopted to divide the neural network into several modules, each of them corresponding to a sub-swarm. Based on the experiments on typical problems and classic dataset...

We use three prevalent scoring methods to test the object-map hypothesis, since validity of this model boils down to fair model comparison with bottom-up saliency models. Please see Appendix B for explanation of state-of-the-art saliency models used here. We report results using the previously proposed Normalized Scanpath Saliency (NSS) (Peters et al., 2005; Parkhurst et al., 2002), Correlation...

With the development of large-scale hydrologic modeling, computational efficiency is becoming more and more important. Rapid modeling and analysis are needed to deal with emergency environmental disasters. The Soil and Water Assessment Tool (SWAT) is a popular hydrologic model, which is less applied in large-scale watershed simulation because of its sequential characteristics. For improving the...

Constraint solving is widely applied to many fields including computer aided design, 2 dimension (2D) model design and computer aided manufacturing. Geometric constraint solution is a difficult problem because there are a large number of entities and related parameters in 2D sketches. In this paper, a new method which decomposes geometric constraint relations based on entity-parameter graphs is...

High-accuracy motion modeling in three dimensions via digital images has been increasingly the matter of interest in photogrammetry and computer vision communities. Although accurate sub-pixel image registration techniques are the key elements of measurement, they still demand enhanced intelligence, autonomy, and robustness. In this paper, a new correlationbased technique of stereovision is pro...

The Say-All-Fast-Minute-Every-Day-Shuffled (SAFMEDS) strategy promotes fast and accurate recall. existing literature suggests that the can help learners improve academic outcomes. Thro...