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A decision support system with data-driven methods is of great significance for the prognosis of scoliosis. However, developing an accurate and interpretable data-driven decision support system is challenging: 1) the scoliosis data collected from clinical environments is heterogeneous, unstructured, and incomplete; 2) the cause of adolescent idiopathic scoliosis is still unknown, and the effects of...
This study proposed a support vector regression model applied in prediction of intraoperative somatosensory evoked potential changes associated with physiological and anesthetic changes. This model was developed from probability distribution and support vector machines. The predicted results showed that observed and predicted SEP has similar variation trend with different values, with acceptable errors...
In China stock market, more than 95% are non-professional investors. Due to the lack of professional skill and the complexity of financial indicators and the varying investment environment, non-professional investors are in great need of a data mining-based intelligent stock trading decision-support system. Considering the existence of concept drift phenomenon, this study proposes an adaptive learning...
Because of various inflammations and fractures of low limbs, the number of patients with knee joint stiffness is increasing. Walkers are commonly prescribed to improve these patients' stability and ambulatory ability. The evaluation on the assisted walking effect has become a hot problem, whose prerequisite is a comprehensive mechanical understanding of the upper extremity force. In order to study...
Mental tasks such as motor imagery in synchronization with a cue which result event related desynchronization (ERD) and event related synchronization (ERS) are usually studied in brain-computer interface (BCI) system. In this paper we analyze and classify the ERD/ERS response evoked by the motor imagery of left hand, right hand, foot and tongue. The signals were spatially filtered by Independent Component...
Software project development is a risky process with high failure rate. This paper proposes an intelligent model that can predict and control software development risks from an overall project perspective rather than focusing only on the single factor, project output. In this study, we first constructed a formal model for risk identification, and then collected actual cases from software development...
Gait recognition is a relatively new subfield in biometric recognition, which attempts to recognize people from the way they walk or run. This paper discusses silhouette-based feature descriptor. Human silhouette geometry is generated by boundary tracking approach and resampled to a normalized format. Boundary-centroid distance is proposed to describe gait modality. Then, we apply wavelet transform...
Gait is a potential behavioral feature, and many allied studies have demonstrated that it can be served as a useful biometric feature for recognition. This paper described a novel gait recognition technique based on support vector machine fusion of contour projection and skeleton model features. A principal component analysis method was used to lower the dimension of contour projection after segmenting...
Human body is a natural emitter of infrared ray. Usually the body temperature is different from that of surrounding. This leads to gray-scale difference between human body and background in infrared thermal image. So the method of infrared thermal imaging was presented to classify gaits. Firstly, infrared videos of 23 subjects were collected by using infrared thermal camera. Body silhouettes were...
Direction parameter thetas is one of the important parameters of GLCM (gray level co-occurrence matrix). A fixed angle (such as thetas=45deg) or the average of the measurements in four direction (thetas=0deg,45deg,90deg,135deg) were usually used in calculating GLCM. However, these methods are just empiristic idea, lacking of theoretical support. In fact, the above-mentioned idea are usually failed...
Software project development has high failure rate. Software project risk management may gain a high rate of return in investment. Establishing an intelligent risk evaluation model for project will be valuable in the analysis and control of project risks. In this paper, we employed neural network (NN) and support vector machine (SVM) approaches to establish a model for risk evaluation in project development...
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