The dynamic origin-destination (OD) information is crucial for traffic operations and control. This paper presents a dynamic traffic demand prediction framework based on an anomaly detection algorithm. The Principal Component Analysis (PCA) method is applied to extract main demand patterns which are used to detect the abnormal conditions. The proposed approach can select prediction methods (parametric or nonparametric) automatically based on the pattern detection results. Both simulation and field observed Automatic Number Plate Recognition (ANPR) data are used to verify the proposed approach where the Kalman filter model and the K-nearest neighbor model are chosen as the basic prediction methods. The results show that the prediction framework can effectively reduce the noise of a single prediction model particularly in the abnormal conditions and provide more accurate and reliable prediction results.@en

BACKGROUND: Ultrasound guidance of cryotherapy could be improved if changes of tissue characterization parameters during freezing could be used to monitor freezing profiles and estimate frostbite distributions. OBJECTIVE: To investigate if B-mode ultrasonic imaging can provide sufficient information to define the damaged zone during cryotherapy by quantifying the differences of texture features between fresh and frozen-thawed porcine liver tissue. MATERIALS AND METHODS: The B-mode ultrasonic images were obtained from ten porcine liver tissue samples before and after frozen-thawing treatment, then 20 texture parameters of the grey level histogram (GLH) and the grey level co-occurrence matrix (GLCM) from each image were extracted and analyzed statistically. RESULTS: It was found that the differences in two texture parameters between the fresh and frozen-thawed tissue are significant enough for diagnostic purpose (variance: 317.0%, contrast: 144.4%). CONCLUSION: Texture feature analysis of B-mode ultrasonic images can effectively differentiate the fresh and frozen-thawed porcine liver tissues, which offers a prospect for the future practice of evaluating the effectiveness of cryotherapy using Ultrasound.

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