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This paper proposed a moving vehicles segmentation approach combined two kinds of classifiers which are Gaussian mixture model and spatiotemporal saliency map. We extracted new spatial and temporal saliency features and improved spatiotemporal consistency optimization model to calculate more exact saliency map and to speed up the processing. Because misclassification appears when Gaussian background...
In order to improve adaptability of manipulator to automatic harvesting under the unstructured environment, a new tomato planting pattern and a picking manipulator structure form were designed based on biological characteristics, cultivation modes and engraftment features of tomato. After simplified fruits growth space of tomato from cuboid to rectangle equivalently, structure optimization mathematical...
Because the bio-signals are often very weak, they can be influenced by noise easily and become hard to distinguish. In this paper, an automatic analog synthesis platform is presented for bio-acquisition systems to generate the required circuits from specification to layout with low-noise consideration. Process variations and layout effects are also simultaneously considered to generate the required...
This paper presents a study of the detailed characteristics of the new Floating Island and Thick Bottom Oxide Trench Gate MOSFET (FITMOS) developed at Toyota. FITMOS has tremendous potential for automotive applications due to its low on-resistance, improved temperature coefficient of resistance and low gate charge. During the study, the key characteristics of this novel FITMOS were investigated; a...
In this paper the fundamental of the component mode synthesis was reviewed. In order to optimize the ride comfort of the vehicle, a rigid-flexible coupling model of a car was established by using multibody system dynamics method and component mode synthesis technology. The flexibility of the car body, twist beam of the rear suspension, and stabilizer rod was considered. The ride comfort of the vehicle...
Microbially assisted recovery of copper from low-grade chalcopyrite has been reported to be a very difficult process, conventional hydrometallurgical methods were limited by many parameters. This study focus on the design and the training of a Multi-Layer Perceptron classifier for the optimized preparation conditions for bioleaching of chalcopyrite. The proposed approach uses the heuristic Backpropagation...
This paper presents a new neural network for solving linear programming problems. After defining the neural dynamics of the proposed neural network, we have shown the existence of an equilibrium point and the asymptotic stability of the equilibrium point of the neural dynamics. As the time parameter approaches infinity, an optimal solution of the linear programming problem is shown to be the equilibrium...
Particle swarm optimization (PSO) is a population-based, self adaptive search optimization technique that has been applied to find optimal or near-optimal solutions for real-world optimization problems. In this paper, rank-based selection is proposed for the particle swarm optimizer. The method applies rank-based selection to replace half of the lower fitness population with the higher fitness population...
Cutting stock problems can be found in various industries. They arise, for examples, with machining, timber processing, paper-making, etc. 1.5-dimensional cutting stock problem is a problem between one-dimensional cutting and two-dimensional cutting. In this study, a two-stage approach is developed for 1.5 dimensional cutting problem. 1.5-dimensional cutting problem is changed into one-dimensional...
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