The Experts below are selected from a list of 2241 Experts worldwide ranked by ideXlab platform
Hong Wenxue - One of the best experts on this subject based on the ideXlab platform.
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Visualization Classification Method of Multi-dimensional Data Based on Fourier Transform
Computer Engineering, 2008Co-Authors: Hong WenxueAbstract:A novel method for designing the classifier of multi-dimensional data is proposed,which uses Radar Chart of multi-statistics to show multidimensional data and applies Fourier descriptors to recognize the Radar Chart.Different multi-dimensional data forms different Radar Chart and distinguishes different category.And Fourier descriptor takes as Chart characteristic,by Fourier transform on the boundary curve of Radar Chart.Based on the improved Probabilistic Neural network(PNN),Radar Chart is recognised automatically.Experimental results show this method has better result of classification,classification precision is out approximately 8.25 percentage,compared with the traditional classifier.
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Research on classifier of multi-dimensional data based on Radar Chart mapping
Computer Engineering and Applications, 2007Co-Authors: Hong WenxueAbstract:Analyzes the basically methods that Radar Chart presents multi-dimensional data,and then introduces feature selection and information fusion technique based on Radar Chart feature.A novel method based on Chart feature for designing the classifier of multi-dimensional data is proposed,which uses Radar Chart to map.This method is also simple and intuitionistic.Multi-dimensional data and applied fuzzy rules to recognize the Radar Chart in order to achieve automatic classification.Different category multi-dimensional data forms different Radar Chart.Radar Chart feature shows the mostly data feature.The result of experiment presents better result of category and precision.
David B. Volkin - One of the best experts on this subject based on the ideXlab platform.
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Radar Chart Array Analysis to Visualize Effects of Formulation Variables on IgG1 Particle Formation as Measured by Multiple Analytical Techniques
Journal of pharmaceutical sciences, 2013Co-Authors: Cavan Kalonia, Ozan S. Kumru, Jae Hyun Kim, C. Russell Middaugh, David B. VolkinAbstract:This study presents a novel method to visualize protein aggregate and particle formation data to rapidly evaluate the effect of solution and stress conditions on the physical stability of an immunoglobulin G (IgG) 1 monoclonal antibody (mAb). Radar Chart arrays were designed so that hundreds of microflow digital imaging (MFI) solution measurements, evaluating different mAb formulations under varying stresses, could be presented in a single figure with minimal loss of data resolution. These MFI Radar Charts show measured changes in subvisible particle number, size, and morphology distribution as a change in the shape of polygons. Radar Charts were also created to visualize mAb aggregate and particle formation across a wide size range by combining data sets from size-exclusion chromatography, Archimedes resonant mass measurements, and MFI. We found that the environmental/mechanical stress condition (e.g., heat vs. agitation) was the most important factor in influencing the particle size and morphology distribution with this IgG1 mAb. Additionally, the presence of NaCl exhibited a pH and stress-dependent behavior resulting in promotion or inhibition mAb particle formation. This data visualization technique provides a comprehensive analysis of the aggregation tendencies of this IgG1 mAb in different formulations with varying stresses as measured by different analytical techniques.
Cavan Kalonia - One of the best experts on this subject based on the ideXlab platform.
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Radar Chart Array Analysis to Visualize Effects of Formulation Variables on IgG1 Particle Formation as Measured by Multiple Analytical Techniques
Journal of pharmaceutical sciences, 2013Co-Authors: Cavan Kalonia, Ozan S. Kumru, Jae Hyun Kim, C. Russell Middaugh, David B. VolkinAbstract:This study presents a novel method to visualize protein aggregate and particle formation data to rapidly evaluate the effect of solution and stress conditions on the physical stability of an immunoglobulin G (IgG) 1 monoclonal antibody (mAb). Radar Chart arrays were designed so that hundreds of microflow digital imaging (MFI) solution measurements, evaluating different mAb formulations under varying stresses, could be presented in a single figure with minimal loss of data resolution. These MFI Radar Charts show measured changes in subvisible particle number, size, and morphology distribution as a change in the shape of polygons. Radar Charts were also created to visualize mAb aggregate and particle formation across a wide size range by combining data sets from size-exclusion chromatography, Archimedes resonant mass measurements, and MFI. We found that the environmental/mechanical stress condition (e.g., heat vs. agitation) was the most important factor in influencing the particle size and morphology distribution with this IgG1 mAb. Additionally, the presence of NaCl exhibited a pH and stress-dependent behavior resulting in promotion or inhibition mAb particle formation. This data visualization technique provides a comprehensive analysis of the aggregation tendencies of this IgG1 mAb in different formulations with varying stresses as measured by different analytical techniques.
Chin-laung Lei - One of the best experts on this subject based on the ideXlab platform.
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Radar Chart: scanning for satisfactory QoE in QoS dimensions
IEEE Network, 2012Co-Authors: Yu-chun Chang, Chi-jui Chang, Kuan-ta Chen, Chin-laung LeiAbstract:The ongoing convergence of QoE and QoS studies to give a thorough understanding of the end user has posed numerous exciting possibilities for network and multimedia researchers. However, there is not yet a proper visualization tool that is able to map the many-to-one relationship between QoS metrics and QoE, leaving researchers speechless in the cacophony of traditional two-dimensional diagrams. Although mostly employed in qualitative analysis, we found the Radar Chart, with a few tweaks, surprisingly suitable for the purpose. In this article, we present our adaptation of the Radar Chart, and demonstrate in a voice-over-IP context its use in single- and cross-application performance analysis, application recommendation, and network diagnosis.
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Radar Chart: Scanning for high QoE in QoS dimensions
2010 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR 2010), 2010Co-Authors: Yu-chun Chang, Chi-jui Chang, Kuan-ta Chen, Chin-laung LeiAbstract:The ongoing convergence of QoE (Quality of Experience) and QoS (Quality of Service) studies to give a thorough understanding of the end-user has posed numerous exciting possibilities for network and multimedia researchers. However, there is not yet a proper visualization tool that is able to map the many-to-one relationship between QoS metrics and QoE, leaving researchers speechless in the cacophony of traditional two-dimensional diagrams. Though mostly employed in qualitative analysis, we found that the Radar Chart, with a few tweaks, surprisingly suitable for the purpose. In this article, we present our adaptation of the Radar Chart, and demonstrate in a Voice-over-IP context its use in single- and cross-application performance analysis, application recommendation, and network diagnosis.
Jia-tai Zhao - One of the best experts on this subject based on the ideXlab platform.
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Study of Comprehensive Evaluation Method on NIMBY Syndrome Based on Improved Radar Chart for Power Grid Project
DEStech Transactions on Computer Science and Engineering, 2018Co-Authors: Ding Yaqian, Guo Jianghua, Tian Youcheng, Lin-xin Long, Jia-tai ZhaoAbstract:In order to slow down the serious NIMBY (Not In My Back Yard) syndrome on power grid project, maintain stable development of power grid and social harmony, this paper establishes a reasonable and scientific NIMBY risk comprehensive evaluation system of power grid project. Comprehensive NIMBY factors that affect power grid project is proposed. Making quantitative analysis to NIMBY syndrome on the basis of improved Radar Chart and improved AHP (Analytic Hierarchy Process). The improved Radar Chart supplies the gap that traditional Radar Chart evaluation result is not unique, the improved AHP does not need consistency check and it can reduce calculation amount apparently and simplicity. Finally, example analysis of different substations verifies the rationality and feasibility of the proposed evaluation system, it shows that this system can provide scientific basis for the facility siting and governance of risk in power grid project.
