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Negative selection algorithm (NSA) is an important method for generating detectors in artificial immune systems. Traditional NSAs randomly generate detectors in the whole feature space. However, with increasing dimensions, data samples aggregate in some specific subspaces, not uniformly distributed in the whole space. The detectors randomly generated by traditional NSAs cannot exactly fall into these...
A ground-based optical telescope equipped with CCD sensor has become an important tool for space debris monitoring in order to maintain a space debris catalogues. In this paper, we emphasized on an enhanced technique for a small and dimming space object extraction. Traditionally, the static background subtraction based on median image technique is widely used to extract the moving space object in...
Image segmentation is one of the classic problems in image processing and computer vision field. Existed algorithms do not always reach a satisfactory purpose in fuzzy image segmentation. This paper is inspired by new development of medical immunology and proposes an artificial immune algorithm based on immune field. First, the article gives the concept of innate immune field, adaptive field and the...
Laparoscopic surgery requires rigorous training in order to overcome physical, spatial and visual constraints. We are developing a laparoscopic robot trainer. The robot trainer can learn the motion of the master surgeon when he is performing a virtual surgery, and drive the surgical tool by mimicking the learnt trajectory during training. This paper reports our investigation on robot learning using...
Laparoscopic Surgery poses significant complexity in hand-eye coordination to the surgeon. In order to improve their proficiency beyond the limited exposure in the operating theatre, surgeons need to practice on laparoscopic trainers. We have constructed a robotic laparoscopic trainer with identical degrees of freedom and range of motion as a conventional laparoscopic instrument. We hypothesize that...
The adaptive-network-based computational verb inference system (ANCVIS) is a kind of computational verb inference system implemented in adaptive networks. In this paper, a new type of ANCVIS, which uses trend-based computational verb similarities, is presented, and its learning algorithm is derived. Simulations show that the proposed model can tune system parameters well and yield reasonable results...
In this paper, an algorithm of learning computational verb decision trees (verb trees, for short) from training examples base on impact factors, which are calculated by using computational verb similarities, is presented. Some examples are used to show the creation of verb decision tree and the usefulness of verb decision trees. Examples are used to show that verb decision trees are powerful tools...
A semi-automatic method was developed for the segmentation of 3D gallbladders (GB) from CT images, in order to construct a patient-specific model for a surgical training system. First a support vector machine (SVM) classifier was trained to extract GB region from one single 2D slice in the intermediate part of a GB by voxel classification. Then the extracted GB contour, after some morphological operations,...
Protein fold recognition task is important for understanding the biological functions of proteins. The adaptive local hyperplane (ALH) algorithm has been shown to perform better than many other renown classifiers including support vector machines, K-nearest neighbor, linear discriminant analysis, K-local hyperplane distance nearest neighbor algorithms and decision trees on a variety of data sets....
Vibration isolation controllers are used to suppress undesirable disturbance in order to guarantee better performance in many industrial and scientific domains. To overcome the drawbacks of the conventional passive systems, a novel design based on the action dependent heuristic dynamic programming (ADHDP) is addressed in this paper for the semi-active vibration isolator. ADHDP, derived from dynamic...
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