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Illustrative implementations to show how logarithm based high dimensional model representation works for various functions structures

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WSEAS Transactions on Computers 2006年第6期5卷 1339-1344页

作者： Demiralp, Metin Computational Science and Engineering Program Informatics Institute Istanbul Technical University Maslak 34469 Istanbul Turkey

This paper is aimed at the illustration of how a recently proposed logarithm based high dimensional model representation (HDMR) works on the functions which have different structures. The main focus of the paper is on the dominantly multiplicative functions. Since the logarithm converts multiplicativity to additivity what we expect from this new representation is the sufficiency of less number of these new HDMR components than the number of components of plain High Dimensional Model Representation which works well for dominantly additive functions. In implementations we use MuPAD Computer Algebra System to have any desired precision in calculations and to use its symbolic programming nature. We do not use continuous functions instead we take discrete data about the function under consideration. However these data is produced from continuous functions for illustrative purposes. The comparison of the given function values and the values evaluated by truncated Logarithm Based HDMR.

关键词： Computer graphics

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Machine learning based prediction of cognitive metrics using major biomarkers in SuperAgers

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Scientific Reports 2025年第1期15卷 1-20页

作者： Hyo-Bin Lee Jang-Hwan Choi So-Yeon Kwon Ji-Hae Park Young Mi Park Bori Kim Geon-Ha Kim Department of Computational Medicine Graduate Program in System Health Science and Engineering Ewha Womans University Seoul 07804 Korea Department of Artificial Intelligence Ewha Womans University Seoul 03760 Korea Department of Molecular Medicine Ewha Womans University Seoul 07804 Korea Department of Neurology Ewha Womans University Mokdong Hospital Ewha Womans University Seoul 07985 Korea

As populations age, understanding cognitive decline and age-related diseases like dementia has become increasingly important. “SuperAgers,” individuals over 65 with cognitive abilities similar to those in their 40s, provide a unique perspective on cognitive reserve. This study analyzed 55 blood biomarkers, including cellular components and metabolism/inflammation-related factors, in 39 SuperAgers and 42 typical agers. While conventional statistical analyses identified significant differences in only four biomarkers, advanced feature selection and machine learning techniques revealed a broader set of 15 key biomarkers associated with SuperAger status. A predictive model built using these biomarkers achieved an accuracy of 76% in cognitive domain prediction. To address the limitation of small sample sizes, data augmentation leveraging large language models improved the model’s robustness. Shapley Additive exPlanations (SHAP) provided interpretability, revealing the impact of specific blood factors on cognitive function. These findings suggest that certain blood biomarkers are not only associated with cognitive performance but may also serve as indicators of cognitive reserve. By utilizing simple blood tests, this research presents a clinically significant method for predicting cognitive function and identifying SuperAger status in healthy elderly individuals, offering a foundation for future studies on the biological mechanisms underpinning cognitive resilience.

关键词： BORUTA Blood biomarkers Cognitive decline Cognitive function Cognitive metric prediction Machine learning Recursive feature elimination (RFE) Super-Agers

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A parallel implementation of Chebyshev preconditioned conjugate gradient method

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ARI Bulletin of the Istanbul Technical University 2003年第2期53卷 13-21页

作者： Dag, Hasan Akcadogan, Cagatay Computational Science and Engineering Program Informatics Institute Istanbul Technical University 34469 Maslak Istanbul Turkey

A parallel implementation for linear set of equations of the form Ax = b is presented in this paper. In this implementation, instead of the traditional direct solution of Ax = b, conjugate gradient method is used. The conjugate gradient method is accelerated with an approximate inverse matrix preconditioner obtained from a linear combination of matrix-valued Chebyshev polynomials. This implementation is tested on a Sun SMP machine. Since conjugate gradient method and preconditioner contain mainly matrix-vector and matrix-matrix multiplications, convincing results are obtained in terms of both speed and scalability.

关键词： Chebyshev polynomials Conjugate gradient method Iterative methods Preconditioner

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Importance and measurement of univariance in high dimensional model representation for multivariate analysis

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WSEAS Transactions on Computers 2006年第9期5卷 1788-1794页

作者： Demiralp, Metin Computational Science and Engineering Program Informatics Institute Istanbul Technical University Maslak 34469 Istanbul Turkey

High Dimensional Model Representation (HDMR) presents the possibility to measure how constant, how constant, how univariate, how bivariate (and so on) a given uniform discrete multivariate data or the multivariate function under consideration of HDMR is. Amongst these measurements the most important one is the one for univariance since univariance means additive separability which is the best thing to facilitate the computations in computers. In this paper we define the HDMR's univariance level for a given discrete data. We discuss the possibility of increasing univariance by using certain mappings although the details will not be explicitly given. The basic tool to this end is the recently developed Logarithmic High Dimensional Model Representation and related issues.

关键词： Mathematical models

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Efactagent: Agent architecture for management, search and retrievel of e-learning artifacts

Efactagent: Agent architecture for management, search and re...

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IADIS International Conference WWW/Internet 2011, ICWI 2011

作者： Braga, Regina Campos, Fernanda Santos, Neide Souza, Ana Cláudia Knowledge Engineering Research Center Computer Science Program Federal University of Juiz de Fora Juiz De Fora - Minas Gerais Brazil Computational Sciences Program State University of Rio de Janeiro Rio De Janeiro - RJ Brazil

ISBN: (纸本)9789898533012

E-Learning activities are growing around the world, accompanied by a proliferation of data, learning objects (LO) and tools. This imposes new challenges as, for example, how to find available artifacts. This work aims to propose an architecture based on intelligent agents to search, retrieve and execute LO, generated within research projects related to educational domains. It allows the search, retrieval and use of LO, through the use of ontological annotations and using intelligent mechanisms that will act on those annotations. To reach this goal, the paper presents BROAD ontology and proposes the EFACTAgent architecture. © 2011 IADIS.

关键词： Ontology

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When data disappear: public health pays as US policy strays

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The Lancet Digital Health 2025年 100874页

作者： McAndrew, Thomas Lover, Andrew A Hoyt, Garrik Majumder, Maimuna S Department of Biostatistics and Health Data Science College of Health Lehigh University BethlehemPA United States Department of Biostatistics and Epidemiology School of Public Health and Health Sciences University of Massachusetts Amherst AmherstMA United States Department of Computer Science and Engineering PC Rossin College of Engineering and Applied Sciences Lehigh University BethlehemPA United States Department of Pediatrics Harvard Medical School BostonMA United States Computational Health Informatics Program Boston Children's Hospital BostonMA United States

Presidential actions on Jan 20, 2025, by President Donald Trump, including executive orders, have delayed access to or led to the removal of crucial public health data sources in the USA. The continuous collection and maintenance of health data support public health, safety, and security associated with diseases such as seasonal influenza. To show how public health data surveillance enhances public health practice, we analysed data from seven US Government-maintained sources associated with seasonal influenza. We fit two models that forecast the number of national incident influenza hospitalisations in the USA: (1) a data-rich model incorporating data from all seven Government data sources;and (2) a data-poor model built using a single Government hospitalisation data source, representing the minimal required information to produce a forecast of influenza hospitalisations. The data-rich model generated reliable forecasts useful for public health decision making, whereas the predictions using the data-poor model were highly uncertain, rendering them impractical. Thus, health data can serve as a transparent and standardised foundation to improve domestic and global health. Therefore, a plan should be developed to safeguard public health data as a public good. © 2025 The Author(s)

关键词： Health insurance

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A Player Position Tracking Method Based on a Wide-Area Pan-Tilt-Zoom Video 12

A Player Position Tracking Method Based on a Wide-Area Pan-T...

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Proceedings of the 12th International Conference on Sport sciences Research and Technology Support, icSPORTS 2024

作者： Yamagishi, Shunzo Xie, Chun Shishido, Hidehiko Kitahara, Itaru Master's and Doctoral Program in Intelligent Mechanical Interaction Systems University of Tsukuba Ibaraki Japan Center for Computational Sciences University of Tsukuba Ibaraki Japan Faculty of Science and Engineering Department of Information Systems Engineering Soka University Tokyo Japan

ISBN: (纸本)9789897587191

This paper proposes a method to estimate the posture of an athlete moving on a vast field in a sporting event using a pan-tilt-zoom camera. In order to estimate the posture of an athlete on a sports field from a dynamic video sequence, our method extracts image features to search correspondence points among successive frames and computes the homography transformation matrix that compensates for changes the camera parameters (e.g., angle of view and posture). The effectiveness of this method is qualitatively verified using MLB TV broadcast video. The accuracy and error factors are also quantitatively verified by CG simulation. Copyright © 2024 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Pan-Tilt-Zoom Camera Player Tracking Sports Analytics Video Processing Wide-Area

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A parallel implementation of chebyshev preconditioned conjugate gradient method

A parallel implementation of chebyshev preconditioned conjug...

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International Symposium on Parallel and Distributed Computing

作者： C. Akcadogan H. Dag Computational Science and Engineering Program Informatics Institute Istanbul Technical University Istanbul Turkey

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Interannual variability and climatic sensitivity of global wildfire activity

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Advances in Climate Change Research 2021年第5期12卷 686-695页

作者： Rongyun TANG Jiafu MAO Mingzhou JIN Anping CHEN Yan YU Xiaoying SHI Yulong ZHANG Forrest M.HOFFMAN Min XU Yaoping WANG Institute for a Secure and Sustainable Environment University of TennesseeKnoxville37996USA Environmental Sciences Division and Climate Change Science Institute Oak Ridge National LaboratoryOak Ridge37830USA Department of Biology and Graduate Degree Program in Ecology Colorado State UniversityFort Collins80523USA Atmospheric and Oceanic Sciences Program Princeton UniversityPrinceton08544USA Computational Sciences and Engineering Division and Climate Change Science Institute Oak Ridge National LaboratoryOak Ridge37830USA

Understanding historical wildfire variations and their environmental driving mechanisms is key to predicting and mitigating wildfires. However, current knowledge of climatic responses and regional contributions to the interannual variability (IAV) of global burned area remains limited. Using recent satellite-derived wildfire products and simulations from version v1.0 of the land component of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM land model [ELM] v1) driven by three different climate forcings, we investigated the burned area IAV and its climatic sensitivity globally and across nine biomes from 1997 to 2018. We found that 1) the ELM simulations generally agreed with the satellite observations in terms of the burned area IAV magnitudes, regional contributions, and covariations with climate factors, confirming the robustness of the ELM to the usage of different climate forcing sources;2) tropical savannas, tropical forests, and semi-arid grasslands near deserts were primary contributors to the global burned area IAV, collectively accounting for 71.7%–99.7% of the global wildfire IAV estimated by both the satellite observations and ELM simulations;3) precipitation was a major fire suppressing factor and dominated the global and regional burned area IAVs, and temperature and shortwave solar radiation were mostly positively related with burned area IAVs;and 4) noticeable local discrepancies between the ELM and remote-sensing results occurred in semi-arid grasslands, croplands, boreal forests, and wetlands, likely caused by uncertainties in the current ELM fire scheme and the imperfectly derived satellite observations. Our findings revealed the spatiotemporal diversity of wildfire variations, regional contributions and climatic responses, and provided new metrics for wildfire modeling, facilitating the wildfire prediction and management.

关键词： Wildfire Burned area Climatic sensitivity E3SM land model Global fire emission database

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IMAGE INPAINTING IN MICROMETEOROLOGICAL ANALYSIS

IMAGE INPAINTING IN MICROMETEOROLOGICAL ANALYSIS

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IEEE International Conference on Image Processing

作者： Carlos Ramirez Miguel Argaez Aline Jaimes Craig E. Tweedie Computational Science Program University of Texas at El Paso USA Environmental Science and Engineering Program University of Texas at El Paso USA

Digital image inpainting is the process by which corrupted or defective areas in an image are systematically corrected. New digital image inpainting techniques have been developed in recent years, leading to numerous successful applications, particularly in the area of image restoration. We propose a new image inpainting algorithm based on wavelet sparse representation, and extend its applicability as a new approach for gap-filling in micrometeorological data. Our approach consists of treating the incomplete data set as a structured image that has a sparse representation in the wavelet domain. Therefore, an l_1 minimization problem is formulated in order to characterize the sparsest solution associated with the complete data set. A numerical experimentation on a real micrometeorological data set is conducted, demonstrating the effectiveness of the proposed approach.

关键词： Decision support systems Manganese Mercury (metals)

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