The paper is to introduce a computational methodology that is based on ordinary differential equations(ODE)solver for the structural systems adopted by a super tall building in its preliminary design stage so as to fa...The paper is to introduce a computational methodology that is based on ordinary differential equations(ODE)solver for the structural systems adopted by a super tall building in its preliminary design stage so as to facilitate the designers to adjust the dynamic properties of the adopted structural system.The construction of the study is composed by following aspects.The first aspect is the modelling of a structural system.As a typical example,a mega frame-core-tube structural system adopted by some famous super tall buildings such as Taipei 101 building,Shanghai World financial center,is employed to demonstrate the modelling of a computational model.The second aspect is the establishment of motion equations constituted by a group of ordinary differential equations for the analyses of free vibration and resonant response.The solutions of the motion equations(that constitutes the third aspect)resorted to ODE-solver technique.Finally,some valuable conclusions are summarized.展开更多
Data production and exchange on the Web grows at a frenetic speed. Such uncontrolled and exponential growth pushes for new researches in the area of information extraction as it is of great interest and can be obtaine...Data production and exchange on the Web grows at a frenetic speed. Such uncontrolled and exponential growth pushes for new researches in the area of information extraction as it is of great interest and can be obtained by processing data gathered from several heterogeneous sources. While some extracted facts can be correct at the origin, it is not possible to verify that correlations among the mare always true (e.g., they can relate to different points of time). We need systems smart enough to separate signal from noise and hence extract real value from this abundance of content accessible on the Web. In order to extract information from heterogeneous sources, we are involved into the entire process of identifying specific facts/events of interest. We propose a gluing architecture, driving the whole knowledge acquisition process, from data acquisition from external heterogeneous resources to their exploitation for RDF trip lification to support reasoning tasks. Once the extraction process is completed, a dedicated reasoner can infer new knowledge as a result of the reasoning process defined by the end user by means of specific inference rules over both extracted information and the background knowledge. The end user is supported in this context with an intelligent interface allowing to visualize either specific data/concepts, or all information inferred by applying deductive reasoning over a collection of data.展开更多
This study investigates the use of computational frameworks for sepsis.We consider two dimensions for investi-gation-early diagnosis of sepsis(EDS)and mortality prediction rate for sepsis patients(MPS).We concentrate ...This study investigates the use of computational frameworks for sepsis.We consider two dimensions for investi-gation-early diagnosis of sepsis(EDS)and mortality prediction rate for sepsis patients(MPS).We concentrate on the clinical parameters on which sepsis diagnosis and prognosis are currently done,including customized treatment plans based on historical data of the patient.We identify the most notable literature that uses com-putational models to address EDS and MPS based on those clinical parameters.In addition to the review of the computational models built upon the clinical parameters,we also provide details regarding the popular publicly available data sources.We provide brief reviews for each model in terms of prior art and present an analysis of their results,as claimed by the respective authors.With respect to the use of machine learning models,we have provided avenues for model analysis in terms of model selection,model validation,model interpretation,and model comparison.We further present the challenges and limitations of the use of computational models,providing future research directions.This study intends to serve as a benchmark for first-hand impressions on the use of computational models for EDS and MPS of sepsis,along with the details regarding which model has been the most promising to date.We have provided details regarding all the ML models that have been used to date for EDS and MPS of sepsis.展开更多
Recent advances of single-cell transcriptomics technologies and allied computational methodologies have revolutionized molecular cell biology.Meanwhile,pioneering explorations in spatial transcriptomics have opened up...Recent advances of single-cell transcriptomics technologies and allied computational methodologies have revolutionized molecular cell biology.Meanwhile,pioneering explorations in spatial transcriptomics have opened up avenues to address fundamental biological questions in health and diseases.Here,we review the technical attributes of single-cell RNA sequencing and spatial transcriptomics,and the core concepts of computational data analysis.We further highlight the challenges in the application of data integration methodologies and the interpretation of the biological context of the findings.展开更多
The Computational Visual Media(CVM)conference series provides a leading international forum for the exchange of innovative research ideas and significant computational methodologies that both underpin and advance visu...The Computational Visual Media(CVM)conference series provides a leading international forum for the exchange of innovative research ideas and significant computational methodologies that both underpin and advance visual media.Its primary mission is to foster cross-disciplinary research that integrates computer graphics,computer vision,machine learning,image and video processing,visualization,and geometric computing.Topics of particular interest include classification,composition,retrieval,synthesis,cognition,and understanding of visual media,encompassing images,video,and 3D geometry.展开更多
基金Acknowledgment The research work was financially supported both by the Natural Science Foundation of China(51178164)and the Priority Discipline Foundation of Henan Province(507909).
文摘The paper is to introduce a computational methodology that is based on ordinary differential equations(ODE)solver for the structural systems adopted by a super tall building in its preliminary design stage so as to facilitate the designers to adjust the dynamic properties of the adopted structural system.The construction of the study is composed by following aspects.The first aspect is the modelling of a structural system.As a typical example,a mega frame-core-tube structural system adopted by some famous super tall buildings such as Taipei 101 building,Shanghai World financial center,is employed to demonstrate the modelling of a computational model.The second aspect is the establishment of motion equations constituted by a group of ordinary differential equations for the analyses of free vibration and resonant response.The solutions of the motion equations(that constitutes the third aspect)resorted to ODE-solver technique.Finally,some valuable conclusions are summarized.
文摘Data production and exchange on the Web grows at a frenetic speed. Such uncontrolled and exponential growth pushes for new researches in the area of information extraction as it is of great interest and can be obtained by processing data gathered from several heterogeneous sources. While some extracted facts can be correct at the origin, it is not possible to verify that correlations among the mare always true (e.g., they can relate to different points of time). We need systems smart enough to separate signal from noise and hence extract real value from this abundance of content accessible on the Web. In order to extract information from heterogeneous sources, we are involved into the entire process of identifying specific facts/events of interest. We propose a gluing architecture, driving the whole knowledge acquisition process, from data acquisition from external heterogeneous resources to their exploitation for RDF trip lification to support reasoning tasks. Once the extraction process is completed, a dedicated reasoner can infer new knowledge as a result of the reasoning process defined by the end user by means of specific inference rules over both extracted information and the background knowledge. The end user is supported in this context with an intelligent interface allowing to visualize either specific data/concepts, or all information inferred by applying deductive reasoning over a collection of data.
文摘This study investigates the use of computational frameworks for sepsis.We consider two dimensions for investi-gation-early diagnosis of sepsis(EDS)and mortality prediction rate for sepsis patients(MPS).We concentrate on the clinical parameters on which sepsis diagnosis and prognosis are currently done,including customized treatment plans based on historical data of the patient.We identify the most notable literature that uses com-putational models to address EDS and MPS based on those clinical parameters.In addition to the review of the computational models built upon the clinical parameters,we also provide details regarding the popular publicly available data sources.We provide brief reviews for each model in terms of prior art and present an analysis of their results,as claimed by the respective authors.With respect to the use of machine learning models,we have provided avenues for model analysis in terms of model selection,model validation,model interpretation,and model comparison.We further present the challenges and limitations of the use of computational models,providing future research directions.This study intends to serve as a benchmark for first-hand impressions on the use of computational models for EDS and MPS of sepsis,along with the details regarding which model has been the most promising to date.We have provided details regarding all the ML models that have been used to date for EDS and MPS of sepsis.
基金This work was supported in part by the National Key Basic Research and Development Program of China(Grant Nos.2019YFA0801402,2018YFA0107200,2018YFA0801402,2018YFA0800100,2018YFA0108000,and 2017YFA0102700)the“Strategic Priority Research Program”of the Chinese Academy of Sciences(Grant Nos.XDA16020501 and XDA16020404)+1 种基金the National Natural Science Foundation of China(Grant Nos.31630043 and 31900573)the China Postdoctoral Science Foundation Grant(Grant No.2018M642106).
文摘Recent advances of single-cell transcriptomics technologies and allied computational methodologies have revolutionized molecular cell biology.Meanwhile,pioneering explorations in spatial transcriptomics have opened up avenues to address fundamental biological questions in health and diseases.Here,we review the technical attributes of single-cell RNA sequencing and spatial transcriptomics,and the core concepts of computational data analysis.We further highlight the challenges in the application of data integration methodologies and the interpretation of the biological context of the findings.
文摘The Computational Visual Media(CVM)conference series provides a leading international forum for the exchange of innovative research ideas and significant computational methodologies that both underpin and advance visual media.Its primary mission is to foster cross-disciplinary research that integrates computer graphics,computer vision,machine learning,image and video processing,visualization,and geometric computing.Topics of particular interest include classification,composition,retrieval,synthesis,cognition,and understanding of visual media,encompassing images,video,and 3D geometry.
