In this paper,we propose a new relational schema (R-schema) to XML schema translation algorithm, VQT, which analyzes the value cardinality and user query patterns and extracts the implicit referential integrities by u...In this paper,we propose a new relational schema (R-schema) to XML schema translation algorithm, VQT, which analyzes the value cardinality and user query patterns and extracts the implicit referential integrities by using the cardinality property of foreign key constraints between columns and the equi-join characteristic in user queries. The VQT algorithm can apply the extracted implied referential integrity relation information to the R-schema and create an XML schema as the final result. Therefore, the VQT algorithm prevents the R-schema from being incorrectly converted into the XML schema, and it richly and powerfully represents all the information in the R-schema by creating an XML schema as the translation result on behalf of the XML DTD.展开更多
This work presents a software tool for modeling of mass transfer physicochemical processes occurring in the atmosphere. The implemented algorithms provide an efficient theoretical frame for the interpretation of the r...This work presents a software tool for modeling of mass transfer physicochemical processes occurring in the atmosphere. The implemented algorithms provide an efficient theoretical frame for the interpretation of the results obtained from Coated Wall Flow Tube (CWFT) reactor experiments, which is one of the most adequate techniques to study heterogeneous kinetics. The numerical simulations are based on the fundamental Langmuir adsorption theory by ordinary differential equations and the second Fick’s law described by partial differential equations. The main application of the system is to estimate the basic parameters that characterize the processes. The best parameter estimation is found by minimizing the difference between experimental signals from the CWFT reactors and the obtained numerical simulations. A numerical example for an experimental data fit is given.展开更多
With the rapid growth of the Web, the volume of information on the Web is increasing exponentially. However, information on the current Web is only understandable to humans, and this makes precise information retrieva...With the rapid growth of the Web, the volume of information on the Web is increasing exponentially. However, information on the current Web is only understandable to humans, and this makes precise information retrieval difficult. To solve this problem, the Semantic Web was proposed. We must use ontology languages that can assign data the semantics for realizing the Semantic Web. One of the representative ontology languages is the Web ontology language OWL, adopted as a recommen-dation by the World-Wide Web Consortium (W3C). OWL includes hierarchical structural information between classes or prop-erties. Therefore, an efficient OWL storage model that considers a hierarchical structure for effective information retrieval on the Semantic Web is required. In this paper we suggest an XPath-based OWL storage (XPOS) model, which includes hierarchical information between classes or properties in XPath form, and enables intuitive and effective information retrieval. Also, we show the comparative evaluation results for the performance of the XPOS model, Sesame, and the XML file system-based storage (XFSS) model, in terms of query processing and ontology updating.展开更多
The prevalence of nonalcoholic fatty liver disease(NAFLD)is an important public health concern.Early diagnosis of NAFLD and potential progression to nonalcoholic steatohepatitis(NASH),could reduce the further advance ...The prevalence of nonalcoholic fatty liver disease(NAFLD)is an important public health concern.Early diagnosis of NAFLD and potential progression to nonalcoholic steatohepatitis(NASH),could reduce the further advance of the disease,and improve patient outcomes.Aiming to support patient diagnostic and predict specific outcomes,the interest in artificial intelligence(AI)methods in hepatology has dramatically increased,especially with the application of lessinvasive biomarkers.In this review,our objective was twofold:Firstly,we presented the most frequent blood biomarkers in NAFLD and NASH and secondly,we reviewed recent literature regarding the use of machine learning(ML)methods to predict NAFLD and NASH in large cohorts.Strikingly,these studies provide insights into ML application in NAFLD patients'prognostics and ranked blood biomarkers are able to provide a recognizable signature allowing cost-effective NAFLD prediction and also differentiating NASH patients.Future studies should consider the limitations in the current literature and expand the application of these algorithms in different populations,fortifying an already promising tool in medical science.展开更多
基金Project supported by the 2nd Brain Korea Project
文摘In this paper,we propose a new relational schema (R-schema) to XML schema translation algorithm, VQT, which analyzes the value cardinality and user query patterns and extracts the implicit referential integrities by using the cardinality property of foreign key constraints between columns and the equi-join characteristic in user queries. The VQT algorithm can apply the extracted implied referential integrity relation information to the R-schema and create an XML schema as the final result. Therefore, the VQT algorithm prevents the R-schema from being incorrectly converted into the XML schema, and it richly and powerfully represents all the information in the R-schema by creating an XML schema as the translation result on behalf of the XML DTD.
文摘This work presents a software tool for modeling of mass transfer physicochemical processes occurring in the atmosphere. The implemented algorithms provide an efficient theoretical frame for the interpretation of the results obtained from Coated Wall Flow Tube (CWFT) reactor experiments, which is one of the most adequate techniques to study heterogeneous kinetics. The numerical simulations are based on the fundamental Langmuir adsorption theory by ordinary differential equations and the second Fick’s law described by partial differential equations. The main application of the system is to estimate the basic parameters that characterize the processes. The best parameter estimation is found by minimizing the difference between experimental signals from the CWFT reactors and the obtained numerical simulations. A numerical example for an experimental data fit is given.
文摘With the rapid growth of the Web, the volume of information on the Web is increasing exponentially. However, information on the current Web is only understandable to humans, and this makes precise information retrieval difficult. To solve this problem, the Semantic Web was proposed. We must use ontology languages that can assign data the semantics for realizing the Semantic Web. One of the representative ontology languages is the Web ontology language OWL, adopted as a recommen-dation by the World-Wide Web Consortium (W3C). OWL includes hierarchical structural information between classes or prop-erties. Therefore, an efficient OWL storage model that considers a hierarchical structure for effective information retrieval on the Semantic Web is required. In this paper we suggest an XPath-based OWL storage (XPOS) model, which includes hierarchical information between classes or properties in XPath form, and enables intuitive and effective information retrieval. Also, we show the comparative evaluation results for the performance of the XPOS model, Sesame, and the XML file system-based storage (XFSS) model, in terms of query processing and ontology updating.
文摘The prevalence of nonalcoholic fatty liver disease(NAFLD)is an important public health concern.Early diagnosis of NAFLD and potential progression to nonalcoholic steatohepatitis(NASH),could reduce the further advance of the disease,and improve patient outcomes.Aiming to support patient diagnostic and predict specific outcomes,the interest in artificial intelligence(AI)methods in hepatology has dramatically increased,especially with the application of lessinvasive biomarkers.In this review,our objective was twofold:Firstly,we presented the most frequent blood biomarkers in NAFLD and NASH and secondly,we reviewed recent literature regarding the use of machine learning(ML)methods to predict NAFLD and NASH in large cohorts.Strikingly,these studies provide insights into ML application in NAFLD patients'prognostics and ranked blood biomarkers are able to provide a recognizable signature allowing cost-effective NAFLD prediction and also differentiating NASH patients.Future studies should consider the limitations in the current literature and expand the application of these algorithms in different populations,fortifying an already promising tool in medical science.
