In this research, a new fault detection method based on kernel independent component analysis （kernel ICA） is developed. Kernel ICA is an improvement of independent component analysis （ICA）, and is different from ...In this research, a new fault detection method based on kernel independent component analysis （kernel ICA） is developed. Kernel ICA is an improvement of independent component analysis （ICA）, and is different from kernel principal component analysis （KPCA） proposed for nonlinear process monitoring. The basic idea of our approach is to use the kernel ICA to extract independent components efficiently and to combine the selected essential independent components with process monitoring techniques. 12 （the sum of the squared independent scores） and squared prediction error （SPE） charts are adopted as statistical quantities. The proposed monitoring method is applied to Tennessee Eastman process, and the simulation results clearly show the advantages of kernel ICA monitoring in comparison to ICA monitoring.展开更多
In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The pro...In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The proposed method is called CHK (KDE of Collage error and Hu moment) and it is tested on the Vistex texture database with 640 natural images. Experimental results show that the Average Retrieval Rate (ARR) can reach into 78.18%, which demonstrates that the proposed method performs better than the one with parameters respectively as well as the commonly used histogram method both on retrieval rate and retrieval time.展开更多
Objective To assess inter-observer variations of pulmonary nodule marking in routine clinical chest digital radiograph (DR) softcopy reading by using a lung nodule computer toolkit.Methods A total of 601 chest posteri...Objective To assess inter-observer variations of pulmonary nodule marking in routine clinical chest digital radiograph (DR) softcopy reading by using a lung nodule computer toolkit.Methods A total of 601 chest posterior-anterior DR images were randomly selected from routine outpatient screening in Peking Union Medical College Hospital. Two chest radiologists with experience more than ten years were first asked to read the images and mark all suspicious nodules independently by using computer toolkit IQQA-Chest, and to indicate the likelihood for each nodule detected. They were also asked to draw the boundary of the identified nodule manually on an enlarged region of interest, which was instantly analyzed by IQQA-Chest. Two sets of diagnostic reports, including the marked nodules, likelihood, manually drawn boundaries, quantitative measurements, and radiologists’ names, were automatically generated and stored by the computer system. One week later, the two radiologists read the same images together by using the same computer toolkit without referring to their previous reading results. Marking procedure was the same except that consensus was reached for each suspicious region. Statistical analysis tools provided in the IQQA-Chest were used to compare all the three sets of reading results.Results In the independent readings, Reader 1 detected 409 nodules with a mean diameter of 12.4 mm in 241 patients, and Reader 2 detected 401 nodules with a mean diameter of 12.6 mm in 253 patients. In the consensus reading, a total of 352 nodules with a mean diameter of 12.4 mm were detected in 220 patients. Totally, 42.3% of Reader 1’s and 45.1% of Reader 2’s marks were confirmed by the consensus reading. About 40% of each reader’s marks agreed with the other. There were only 130 (14.4%) out of the total 904 unique nodules were confirmed by both readers and the consensus reading. Moreover, 5.6% (51/904) of the marked regions were rated identical likelihood in all three readings. Statistical analysis showed significant differences between Readers 1 and 2, and between consensus and Reader 2 in determining the likelihood of the marks (P<0.01), but not between consensus and Reader 1. No significant difference in terms of size was observed in nodule segmentation between either two of the three readings. Conclusion Large variations in nodule marking and nodule-likelihood determination but not in nodule size were observed between experts as well as between single-person reading and consensus reading.展开更多
In order to satisfy the safety-critical requirements,the train control system(TCS) often employs a layered safety communication protocol to provide reliable services.However,both description and verification of the sa...In order to satisfy the safety-critical requirements,the train control system(TCS) often employs a layered safety communication protocol to provide reliable services.However,both description and verification of the safety protocols may be formidable due to the system complexity.In this paper,interface automata(IA) are used to describe the safety service interface behaviors of safety communication protocol.A formal verification method is proposed to describe the safety communication protocols using IA and translate IA model into PROMELA model so that the protocols can be verified by the model checker SPIN.A case study of using this method to describe and verify a safety communication protocol is included.The verification results illustrate that the proposed method is effective to describe the safety protocols and verify deadlocks,livelocks and several mandatory consistency properties.A prototype of safety protocols is also developed based on the presented formally verifying method.展开更多
基金Shanghai Leading Academic Discipline Project,China(No.B504) Key Laboratory of Advanced Control and Optimization for Chemical Processes,Ministry of Education,China
文摘In this research, a new fault detection method based on kernel independent component analysis （kernel ICA） is developed. Kernel ICA is an improvement of independent component analysis （ICA）, and is different from kernel principal component analysis （KPCA） proposed for nonlinear process monitoring. The basic idea of our approach is to use the kernel ICA to extract independent components efficiently and to combine the selected essential independent components with process monitoring techniques. 12 （the sum of the squared independent scores） and squared prediction error （SPE） charts are adopted as statistical quantities. The proposed monitoring method is applied to Tennessee Eastman process, and the simulation results clearly show the advantages of kernel ICA monitoring in comparison to ICA monitoring.
基金Supported by the Fundamental Research Funds for the Central Universities (No. NS2012093)
文摘In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The proposed method is called CHK (KDE of Collage error and Hu moment) and it is tested on the Vistex texture database with 640 natural images. Experimental results show that the Average Retrieval Rate (ARR) can reach into 78.18%, which demonstrates that the proposed method performs better than the one with parameters respectively as well as the commonly used histogram method both on retrieval rate and retrieval time.
文摘Objective To assess inter-observer variations of pulmonary nodule marking in routine clinical chest digital radiograph (DR) softcopy reading by using a lung nodule computer toolkit.Methods A total of 601 chest posterior-anterior DR images were randomly selected from routine outpatient screening in Peking Union Medical College Hospital. Two chest radiologists with experience more than ten years were first asked to read the images and mark all suspicious nodules independently by using computer toolkit IQQA-Chest, and to indicate the likelihood for each nodule detected. They were also asked to draw the boundary of the identified nodule manually on an enlarged region of interest, which was instantly analyzed by IQQA-Chest. Two sets of diagnostic reports, including the marked nodules, likelihood, manually drawn boundaries, quantitative measurements, and radiologists’ names, were automatically generated and stored by the computer system. One week later, the two radiologists read the same images together by using the same computer toolkit without referring to their previous reading results. Marking procedure was the same except that consensus was reached for each suspicious region. Statistical analysis tools provided in the IQQA-Chest were used to compare all the three sets of reading results.Results In the independent readings, Reader 1 detected 409 nodules with a mean diameter of 12.4 mm in 241 patients, and Reader 2 detected 401 nodules with a mean diameter of 12.6 mm in 253 patients. In the consensus reading, a total of 352 nodules with a mean diameter of 12.4 mm were detected in 220 patients. Totally, 42.3% of Reader 1’s and 45.1% of Reader 2’s marks were confirmed by the consensus reading. About 40% of each reader’s marks agreed with the other. There were only 130 (14.4%) out of the total 904 unique nodules were confirmed by both readers and the consensus reading. Moreover, 5.6% (51/904) of the marked regions were rated identical likelihood in all three readings. Statistical analysis showed significant differences between Readers 1 and 2, and between consensus and Reader 2 in determining the likelihood of the marks (P<0.01), but not between consensus and Reader 1. No significant difference in terms of size was observed in nodule segmentation between either two of the three readings. Conclusion Large variations in nodule marking and nodule-likelihood determination but not in nodule size were observed between experts as well as between single-person reading and consensus reading.
基金supported by the New Century Excellent Researcher Award Program from Ministry of Education of China (Grant No. NCET-07-0059)the Fundamental Research Funds for the Central Universities (Grant No.2011YJS006)+1 种基金the National High Technology Research and DevelopmentProgram of China ("863" Program) (Grant No. 2011AA010104)the State Key Laboratory of Rail Traffic Control and Safety Research Project(Grant Nos. RCS2008ZZ001, RCS2008ZZ005)
文摘In order to satisfy the safety-critical requirements,the train control system(TCS) often employs a layered safety communication protocol to provide reliable services.However,both description and verification of the safety protocols may be formidable due to the system complexity.In this paper,interface automata(IA) are used to describe the safety service interface behaviors of safety communication protocol.A formal verification method is proposed to describe the safety communication protocols using IA and translate IA model into PROMELA model so that the protocols can be verified by the model checker SPIN.A case study of using this method to describe and verify a safety communication protocol is included.The verification results illustrate that the proposed method is effective to describe the safety protocols and verify deadlocks,livelocks and several mandatory consistency properties.A prototype of safety protocols is also developed based on the presented formally verifying method.
