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International conference on Big data and Artificial Intelligence (BDAI)

作者： Zhen Zhong Aihua Yang School of Military and Political Basic Education National University of Defense Technology Changsha China

ISBN: (数字)9798350352009

ISBN: (纸本)9798350352016

This article reviews 564 articles on China National Knowledge Infrastructure and 1551 articles on Web of Science from 2002 to 2024 under the theme of Key Core Technologies. Using CiteSpace bibliometric analysis software, the keywords, authors, and institutions of Chinese and foreign literature are visualized and analyzed, summarizing the current research status of key core technologies and assessing future research trends. The research results indicate that the hot topics in domestic and foreign literature are focused on the classification of key core technologies, the application of key core technologies in industrial transformation and upgrading, and path breakthroughs. The core technological breakthroughs in areas such as digital transformation, artificial intelligence, and big data in the future will be a key research topic in related fields.

关键词： Knowledge engineering visualization Reviews Digital transformation Bibliometrics Big data Market research Software

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Software quality analysis with the use of computational intelligence

Software quality analysis with the use of computational inte...

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IEEE International conference on Fuzzy Systems (FUZZ-IEEE)

作者： M. Reformat W. Pedrycz N.J. Pizzi University of Alberta Edmonton AB Canada National Research Council Winnipeg MAN Canada

Effectiveness and clarity of software objects, their adherence to coding standards and programming habits of programmers are important features of overall quality of software systems. This paper proposes an approach towards a quantitative software quality assessment with respect to extensibility, reusability, clarity and efficiency. It exploits techniques of Computational Intelligence (CI) that are treated as a consortium of granular computing, neural networks and evolutionary techniques. In particular, we take advantage of self-organizing maps to gain a better insight into the data, and study genetic decision trees-a novel algorithmic framework to carry out classification of software objects with respect to their quality. Genetic classifiers serve as a "quality filter" for software objects. Using these classifiers, a system manager can predict quality of software objects and identify low quality objects for review and possible revision. The approach is applied to an object-oriented visualization-based software system for biomedical data analysis.

关键词： Software quality Software systems Genetics Software standards Programming profession Computational intelligence Computer networks Neural networks Self organizing feature maps Decision trees

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Real-time reconstruction of wavelet encoded meshes for view-dependent transmission and visualization

Real-time reconstruction of wavelet encoded meshes for view-...

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IEEE International conference on Image Processing

作者： P. Gioia O. Aubault C. Bouville France Telecom R & D France

Wavelet methods for geometry encoding is a recently emerged superset of multiresolution analysis which has proven to be very efficient in term of compression and adaptive transmission of 3D content. The decorrelating power and space/scale localization of wavelets enable efficient compression of arbitrary meshes as well as progressive and local reconstruction. Recent techniques based on zerotree compression have shown to be among the best lossy mesh compression methods, while remaining compatible with selective transmission of geometric data at various level of detail. While some progressive reconstruction schemes have been proposed in the past, we show in this paper that this representation, recently proposed in the MPEG4 standard, can be efficiently used to perform real-time, view-dependent reconstruction of large meshes. The proposed system combines algorithms for local updates, cache management and server/client dialog. The local details management is an improvement of progressive reconstructions built on top of hierarchical structures. It enables fast, homogeneous accommodation and suppression of wavelet coefficients at any level of subdivision, with time complexity independent of the size of the reconstructed mesh. The cache structure wisely exploits the hierarchical character of the received data, in order to avoid redundant information transmission. The whole system enables the client to have total control on the quality of navigation according to its storage and processing capabilities, whatever the size of the mesh.

关键词： visualization Wavelet analysis Geometry Encoding Multiresolution analysis Decorrelation Propagation losses MPEG 4 Standard Wavelet coefficients Size control

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Face recognition using extended isomap

Face recognition using extended isomap

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IEEE International conference on Image Processing

作者： Ming-Hsuan Yang Honda Fundamental Research Laboratories Mountain View CA USA

The isomap method has demonstrated promising results in finding low dimensional manifolds from samples in high dimensional input space. While conventional subspace methods compute L/sub 1/ or L/sub 2/ metrics to represent distances between samples and apply principal component analysis or similar to induce linear manifolds, the isomap method estimates the geodesic distance between samples and then uses multidimensional scaling to induce a low dimensional manifold. Since the isomap method is based on the reconstruction principle, it may not be optimal from the classification viewpoint. We present an extended isomap method that utilizes the Fisher linear discriminant for pattern classification. Numerous experiments on image data sets show that our extension is more effective than the original isomap method for pattern classification. Furthermore, the extended isomap method shows promising results compared with the best classification methods in the literature.

关键词： Face recognition Principal component analysis Multidimensional systems Pattern classification Geophysics computing Geometry Image reconstruction data visualization Pattern recognition Euclidean distance

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Numerical image enhancement for THz time-domain spectroscopy

Numerical image enhancement for THz time-domain spectroscopy

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International conference on Terahertz Electronics

作者： C. Schildknecht T. Kleine-Ostmann P. Knobloch E. Rehberg M. Koch Institut for Hochfrequenztechnik Technische Universitäat Braunschweig Brunswick Germany Hals-Nasen-Ohrenklinik der Justus-Leibig Universität Gieβen Gieben Germany

Applies numerical image enhancement methods to THz time-domain spectroscopy images in order to improve the quality of experimental data suffering from low resolution and finite focus diameter aperture effects. As an e... 详细信息

关键词： Image enhancement Time domain analysis Spectroscopy Spatial resolution Apertures Image resolution Biomedical imaging visualization High-resolution imaging Focusing

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data mining information visualisation - beyond charts and graphs

Data mining information visualisation - beyond charts and gr...

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International conference on Information Visualisation (IV)

作者： N. Robinson M. Shapcott Faculty of Informatics University of Ulster Jordanstown UK

data mining has become a major academic research area over the last ten years. However, in the transition from academic prototypes to commercial products there have been few successes with commercial data mining applications failing to make any significant impact in the marketplace. In this paper it is argued that most data mining applications concentrate on the model-building phase of the data mining process and rarely engage the user in other stages. The paper reviews the challenges of producing successful data mining applications and in particular the role of information visualisation. Visualisation in data mining tends to be used to present final results, rather than playing an important part throughout the entire process. We argue that an immersive environment may provide the user with a more suitable interface than is commonly offered. We present a virtual data mining environment which attempts to integrate a data mining application interface and information visualisation in a seamless manner, using the concept of 'liquid data'.

关键词： data mining data visualization Business Informatics Application software Information technology Prototypes Virtual environment Visual databases Pattern analysis

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Analyzing the Research Hotspots and Trends in Crisis Leadership in the Big data Era —— A Bibliometric visualization analysis Based on WoSCC

Analyzing the Research Hotspots and Trends in Crisis Leaders...

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International conference on Big data and Information Analytics (BigDIA)

作者： Jiali Luo Qingqing Yang Guangda Liu College of Systems and Engineering National University of Defense Technology Changsha China

In order to comprehensively understand the development context and evolution trends of international crisis leadership research in the big data era, this study uses the journal papers retrieved from the Science Citation Index Expanded (SCI-EXPANDED) and Social Sciences Citation Index (SSCI) databases of the Web of Science Core Collection (WoSCC) as the main data source, and with the help of visual analysis tool CiteSpace software, carries out a scientific literature metric analysis on the core authors, research countries, research institutions, publishing journals, theme keywords, and hotspot trends of international crisis leadership research. The series of knowledge maps are drawn. The results show that: ① The annual number of publications on crisis leadership research has experienced three stages: a slow growth period (2002-2008), a significant growth period (2009-2019), and a rapid growth period (2020-2023). The cumulative publication volume shows a continuous increase trend. ② The crisis leadership field research literature mainly comes from a few core author groups, and the research of core authors has laid the foundation for crisis leadership. ③ The United States ranks first among the countries conducting research on crisis leadership, followed by England, and China is the most productive country in Asia.

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TDV: Intelligent system for Thyroid Disease visualization

TDV: Intelligent system for Thyroid Disease Visualization

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International conference on Computing, Electronic and Electrical Engineering (ICE Cube)

作者： Jamil Ahmed Chandio Attaullah Sahito M. Abdul Rehman Soomrani Siraj Ahmed Abbasi Department of Computer Science Sukkur Institute of Business Administration Sukkur Pakistan Sukkur Institute of Business Administration Sukkur PK Department of Radiotherapy LINAR Cancer Hospital Larkana Pakistan

Recently; AI based methods are frequently used in healthcare industry to unfold historical hindsight to explore the insight and envisage the foresight. For example, identification of epidemiological patterns of thyroid disease in targeted area(s) supports healthcare industry stakeholders (government agencies, health organizations, NGOs, policy makers and so on) in formulating proper policies to combat such kind of fatal diseases. Also, predictive Future visualization (FV) of prevalence patterns of the thyroid disease is really helpful for these stakeholders to properly focus on specific area(s). This paper offers a system so called TDV: Intelligent System for Thyroid Disease visualization, which offers a potential surveillance pattern of thyroid disease to policy makers for next ten years (2013-2022) by presenting thyroid disease prevalence facts of past ten year (2002-2012). The methodology of our system comprises upon three main steps, in first step, we apply data preprocessing techniques. In second step; we construct the decision model using Time Series Regression (TSR) in R software, finally we visualized the results by using a geographic map plotted in Q-GIS. As per results of our approach, we conclude that thyroid disease may increase more than 15% for next ten years in age group 21-30 and female gender is more prone to be affected from thyroid disease.

关键词： Diseases Biochemistry data visualization Mathematical model Time series analysis Geographic information systems Smoothing methods

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Multiresolution tetrahedral meshes: an analysis and a comparison

Multiresolution tetrahedral meshes: an analysis and a compar...

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International conference on Shape Modeling and Applications

作者： E. Danovaro L. De Floriani M. Lee H. Samet Dipartimento di Informatica e Scienze dellInformazione Università di Genova Genoa Italy Computer Science Department Center for Automation Research Institute for Advanced Computer Studies University of Maryland College Park MD USA

ISBN: (纸本)0769515460

We deal with the problem of analyzing and visualizing large-size volume data sets. To this aim, we consider multiresolution representations based on a decomposition of the field domain into tetrahedral cells. We compare two types of multiresolution representations that differ on the rule applied to refine an initial coarse mesh: one is based on tetrahedron bisection, and one based on vertex split. The two representations can be viewed as instances of a common multiresolution model, that we call a multiresolution mesh. Encoding data structures for the two representations are briefly described. An experimental comparison on structured volume data sets is presented.

关键词： Spatial resolution Finite element methods data mining data visualization data structures Shape Computer science Automation Educational institutions Encoding

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Network analysis of Design Automation Literature

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JOURNAL OF MECHANICAL DESIGN 2018年第10期140卷 101403-101403页

作者： Guo, Tinghao Xu, Jiarui Sun, Yue Dong, Yilin Davis, Neal Allison, James T. Univ Illinois Ind & Enterprise Syst Engn Urbana IL 60801 USA Carnegie Mellon Univ Language Technol Inst Pittsburgh PA 15213 USA Univ Illinois Comp Sci Urbana IL 61801 USA

In this paper, we present the results of a study of citation and co-authorship networks for articles published at the ASME Design Automation conference (DAC) during the years 2002-2015. Two topic-modeling methods are presented for studying the DAC literature: A frequency-based model was developed to explore DAC topic distribution and evolution, as well as citation analysis for each core topic. Correlation analysis and association-rule mining were used to discover relationships between topics. A new unsupervised learning algorithm, propagation mergence (PM), was created to address identified shortcomings of existing methods and applied to study the existing DAC citation network. Influential articles and important article clusters were identified and effective visualizations created. We also investigated the DAC co-authorship network by identifying key authors and showing that the network structure exhibits small-world-network properties. The resulting insights, obtained by the both the proposed and existing methods, may be beneficial to the engineering design research community, especially with respect to determining future research directions and possible actions for improvement. The data set used here is limited;expanding to include additional relevant conference proceedings and journal articles in the future would offer a more complete understanding of the engineering design research literature.

关键词： Design Design automation Modeling Engineering design visualization Network analysis Optimization Algorithms Energy sustainability Transportation systems

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