Aiming to increase the efficiency of gem design and manufacturing, a new method in computer-aided-design (CAD) of convex faceted gem cuts (CFGC) based on Half-edge data structure (HDS), including the algorithms for th...Aiming to increase the efficiency of gem design and manufacturing, a new method in computer-aided-design (CAD) of convex faceted gem cuts (CFGC) based on Half-edge data structure (HDS), including the algorithms for the implementation is presented in this work. By using object-oriented methods, geometrical elements of CFGC are classified and responding geometrical feature classes are established. Each class is implemented and embedded based on the gem process. Matrix arithmetic and analytical geometry are used to derive the affine transformation and the cutting algorithm. Based on the demand for a diversity of gem cuts, CAD functions both for free-style faceted cuts and parametric designs of typical cuts and visualization and human-computer interactions of the CAD system including two-dimensional and three-dimensional interactions have been realized which enhances the flexibility and universality of the CAD system. Furthermore, data in this CAD system can also be used directly by the gem CAM module, which will promote the gem CAD/CAM integration.展开更多
Objective： To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage techn...Objective： To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage technology and knowledge support of computer-aided detecting （CAD）. Methods： 58 cases of peripheral lung cancer confirmed by clinical pathology were collected. The data were imported into the database after the standardization of the clinical and CT findings attributes were identified. The data was studied comparatively based on Association Rules （AR） of the knowledge discovery process and the Rough Set （RS） reduction algorithm and Genetic Algorithm（GA） of the generic data analysis tool （ROSETTA）, respectively. Results： The genetic classification algorithm of ROSETTA generates 5 000 or so diagnosis rules. The RS reduction algorithm of Johnson＇s Algorithm generates 51 diagnosis rules and the AR algorithm generates 123 diagnosis rules. Three data mining methods basically consider gender, age, cough, location, lobulation sign, shape, ground-glass density attributes as the main basis for the diagnosis of peripheral lung cancer. Conclusion： These diagnosis rules for peripheral lung cancer with three data mining technology is same as clinical diagnostic rules, and these rules also can be used to build the knowledge base of expert system. This study demonstrated the potential values of data mining technology in clinical imaging diagnosis and differential diagnosis.展开更多
This paper proposes a new computer aided pattern design system(CAPDS)in which a uniformmathematical expression is used to construct different objects. In the geometric model, 3 B-splineis adopted as a line model. The ...This paper proposes a new computer aided pattern design system(CAPDS)in which a uniformmathematical expression is used to construct different objects. In the geometric model, 3 B-splineis adopted as a line model. The new system with uniform mathematical expression has the distin-guishing features: curve smoothness and fidelity, convenience to process graphic data in thedatabase and etc.. This paper presents the data structure, the program structure and also the implementation.展开更多
In the engineering database system, multiple versions of a design including engineering drawings should be managed efficiently. The paper proposes an efficient spatial data structure, that is an expansion of the R tre...In the engineering database system, multiple versions of a design including engineering drawings should be managed efficiently. The paper proposes an efficient spatial data structure, that is an expansion of the R tree and HR tree, for version management of engineering drawings. A novel mechanism to manage the difference between drawings is introduced to the HR tree to eliminate redundant duplications and to reduce the amount of storage required for the data structure. Data management mechanism and structural properties of our data structure called the MVR + tree are described.展开更多
Lung cancer is a deadly disease, but there is a big chance for the patient to be cured if he or she is correctly diagnosed in early stage of his or her case. At a first glance, lung X-ray chest films being considered ...Lung cancer is a deadly disease, but there is a big chance for the patient to be cured if he or she is correctly diagnosed in early stage of his or her case. At a first glance, lung X-ray chest films being considered as the most reliable method in early detection of lung cancers, the serious mistake in some diagnosing cases giving bad results and causing the death, the computer aided diagnosis systems are necessary to support the medical staff to achieve high capability and effectiveness. Clinicians could predict patient’s behavior future and improve treatment programs by using data mining techniques and they can be better managing the health of patients today, in addition they do not become the problems of tomorrow. The lung cancer biological database which contains the medical images (chest X-ray) classifies the digital X-ray chest films into three categories: normal, benign and malignant. The normal ones are those characterizing a healthy patient (non nodules);, lung nodules can be either benign (non-cancerous) or malignant (cancer). Two steps are major in computer-aided diagnosis systems: pattern recognition approach, which is a combination of a feature extraction process and a classification process using neural network classifier.展开更多
The prevalence of a disease in a population is defined as the proportion of people who are infected. Selection bias in disease prevalence estimates occurs if non-participation in testing is correlated with disease sta...The prevalence of a disease in a population is defined as the proportion of people who are infected. Selection bias in disease prevalence estimates occurs if non-participation in testing is correlated with disease status. Missing data are commonly encountered in most medical research. Unfortunately, they are often neglected or not properly handled during analytic procedures, and this may substantially bias the results of the study, reduce the study power, and lead to invalid conclusions. The goal of this study is to illustrate how to estimate prevalence in the presence of missing data. We consider a case where the variable of interest (response variable) is binary and some of the observations are missing and assume that all the covariates are fully observed. In most cases, the statistic of interest, when faced with binary data is the prevalence. We develop a two stage approach to improve the prevalence estimates;in the first stage, we use the logistic regression model to predict the missing binary observations and then in the second stage we recalculate the prevalence using the observed data and the imputed missing data. Such a model would be of great interest in research studies involving HIV/AIDS in which people usually refuse to donate blood for testing yet they are willing to provide other covariates. The prevalence estimation method is illustrated using simulated data and applied to HIV/AIDS data from the Kenya AIDS Indicator Survey, 2007.展开更多
基金Supported by the National Natural Science Foundation of China(21576240)Experimental Technology Research Program of China University of Geosciences(Key Program)(SJ-201422)
文摘Aiming to increase the efficiency of gem design and manufacturing, a new method in computer-aided-design (CAD) of convex faceted gem cuts (CFGC) based on Half-edge data structure (HDS), including the algorithms for the implementation is presented in this work. By using object-oriented methods, geometrical elements of CFGC are classified and responding geometrical feature classes are established. Each class is implemented and embedded based on the gem process. Matrix arithmetic and analytical geometry are used to derive the affine transformation and the cutting algorithm. Based on the demand for a diversity of gem cuts, CAD functions both for free-style faceted cuts and parametric designs of typical cuts and visualization and human-computer interactions of the CAD system including two-dimensional and three-dimensional interactions have been realized which enhances the flexibility and universality of the CAD system. Furthermore, data in this CAD system can also be used directly by the gem CAM module, which will promote the gem CAD/CAM integration.
文摘Objective： To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage technology and knowledge support of computer-aided detecting （CAD）. Methods： 58 cases of peripheral lung cancer confirmed by clinical pathology were collected. The data were imported into the database after the standardization of the clinical and CT findings attributes were identified. The data was studied comparatively based on Association Rules （AR） of the knowledge discovery process and the Rough Set （RS） reduction algorithm and Genetic Algorithm（GA） of the generic data analysis tool （ROSETTA）, respectively. Results： The genetic classification algorithm of ROSETTA generates 5 000 or so diagnosis rules. The RS reduction algorithm of Johnson＇s Algorithm generates 51 diagnosis rules and the AR algorithm generates 123 diagnosis rules. Three data mining methods basically consider gender, age, cough, location, lobulation sign, shape, ground-glass density attributes as the main basis for the diagnosis of peripheral lung cancer. Conclusion： These diagnosis rules for peripheral lung cancer with three data mining technology is same as clinical diagnostic rules, and these rules also can be used to build the knowledge base of expert system. This study demonstrated the potential values of data mining technology in clinical imaging diagnosis and differential diagnosis.
文摘This paper proposes a new computer aided pattern design system(CAPDS)in which a uniformmathematical expression is used to construct different objects. In the geometric model, 3 B-splineis adopted as a line model. The new system with uniform mathematical expression has the distin-guishing features: curve smoothness and fidelity, convenience to process graphic data in thedatabase and etc.. This paper presents the data structure, the program structure and also the implementation.
文摘In the engineering database system, multiple versions of a design including engineering drawings should be managed efficiently. The paper proposes an efficient spatial data structure, that is an expansion of the R tree and HR tree, for version management of engineering drawings. A novel mechanism to manage the difference between drawings is introduced to the HR tree to eliminate redundant duplications and to reduce the amount of storage required for the data structure. Data management mechanism and structural properties of our data structure called the MVR + tree are described.
文摘Lung cancer is a deadly disease, but there is a big chance for the patient to be cured if he or she is correctly diagnosed in early stage of his or her case. At a first glance, lung X-ray chest films being considered as the most reliable method in early detection of lung cancers, the serious mistake in some diagnosing cases giving bad results and causing the death, the computer aided diagnosis systems are necessary to support the medical staff to achieve high capability and effectiveness. Clinicians could predict patient’s behavior future and improve treatment programs by using data mining techniques and they can be better managing the health of patients today, in addition they do not become the problems of tomorrow. The lung cancer biological database which contains the medical images (chest X-ray) classifies the digital X-ray chest films into three categories: normal, benign and malignant. The normal ones are those characterizing a healthy patient (non nodules);, lung nodules can be either benign (non-cancerous) or malignant (cancer). Two steps are major in computer-aided diagnosis systems: pattern recognition approach, which is a combination of a feature extraction process and a classification process using neural network classifier.
文摘The prevalence of a disease in a population is defined as the proportion of people who are infected. Selection bias in disease prevalence estimates occurs if non-participation in testing is correlated with disease status. Missing data are commonly encountered in most medical research. Unfortunately, they are often neglected or not properly handled during analytic procedures, and this may substantially bias the results of the study, reduce the study power, and lead to invalid conclusions. The goal of this study is to illustrate how to estimate prevalence in the presence of missing data. We consider a case where the variable of interest (response variable) is binary and some of the observations are missing and assume that all the covariates are fully observed. In most cases, the statistic of interest, when faced with binary data is the prevalence. We develop a two stage approach to improve the prevalence estimates;in the first stage, we use the logistic regression model to predict the missing binary observations and then in the second stage we recalculate the prevalence using the observed data and the imputed missing data. Such a model would be of great interest in research studies involving HIV/AIDS in which people usually refuse to donate blood for testing yet they are willing to provide other covariates. The prevalence estimation method is illustrated using simulated data and applied to HIV/AIDS data from the Kenya AIDS Indicator Survey, 2007.
