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40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06

作者： Calderbank, A.R. Howard, S.D. Moran, W. Pezeshki, A. Zoltowski, M. Program in Applied and Computational Mathematics Princeton University Princeton NJ United States Defence Science and Technology Organization Edinburgh Australia Electrical Engineering and Computer Science University of Melbourne Melbourne Australia Electrical and Computer Engineering Purdue University West Lafayette IN United States

ISBN: (纸本)1424407850

Fully Polarimetric radar systems are capable of simultaneously transmitting and receiving in two orthogonal polarizations. Instantaneous radar polarimetry exploits both polarization modes of a dually-polarized radar transmitter and receiver on a pulse by pulse basis, and can improve the radar detection performance and suppress range sidelobes. In this paper, we extend the use of instantaneous radar polarimetry for radar systems with multiple dually-polarized transmit and receive antennas. Alamouti signal processing is used to coordinate transmission of Golay pairs of phase codes waveforms across polarizations and multiple antennas. The integration of multi-antenna signal processing with instantaneous radar polarimetry can further improve the detection performance, at a computational cost comparable to single channel matched filtering.

关键词： Polarimeters

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Diagnosis of Leukemia Disease Based on Enhanced Virtual Neural Network

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Computers, Materials & Continua 2021年第11期69卷 2031-2044页

作者： K.Muthumayil S.Manikandan S.Srinivasan JoséEscorcia-Gutierrez Margarita Gamarra Romany F.Mansour Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622India Department of Information Technology K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Biomedical Engineering Saveetha School of EngineeringSIMATSChennai602105India Electronic and Telecommunicacions Program Universidad Autónoma del CaribeBarranquilla08001Colombia Department of Computational Science and Electronic Universidad de la CostaCUCBarranquilla08001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

White Blood Cell(WBC)cancer or leukemia is one of the serious cancers that threaten the existence of human *** spite of its prevalence and serious consequences,it is mostly diagnosed through manual *** risks of inappropriate,sub-standard and wrong or biased diagnosis are high in manual ***,there is a need exists for automatic diagnosis and classification method that can replace the manual *** is mainly classified into acute and chronic *** current research work proposed a computer-based application to classify the *** the feature extraction stage,we use excellent physical properties to improve the diagnostic system’s accuracy,based on Enhanced Color Co-Occurrence *** study is aimed at identification and classification of chronic lymphocytic leukemia using microscopic images of WBCs based on Enhanced Virtual Neural Network(EVNN)*** proposed method achieved optimum accuracy in detection and classification of leukemia from WBC ***,the study results establish the superiority of the proposed method in automated diagnosis of *** values achieved by the proposed method in terms of sensitivity,specificity,accuracy,and error rate were 97.8%,89.9%,76.6%,and 2.2%,***,the system could predict the disease in prior through images,and the probabilities of disease detection are also highly optimistic.

关键词： White blood cells enhanced virtual neural networking segmentation feature extraction chronic lymphocytic leukemia

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Evaluation of large language models for the classification of medical device software

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Bio-Design and Manufacturing 2024年第5期7卷 819-822页

作者： Yu Han Aaron Ceross Florence Bourgeois Paulo Savaget Jeroen H.M.Bergmann Department of Engineering Science University of OxfordOld Road CampusOxford OX37QDUK Harvard-MIT Center for Regulatory Science Harvard Medical SchoolBostonMAUSA Computational Health Informatics Program(CHIP) Boston Children’s HospitalBostonMAUSA Department of Technology and Innovation The University of Southern DenmarkOdenseDenmark

Amidst the rapidly expanding integration of large language models(LLMs)across various sectors(ranging from everyday applications to specialized fields demanding stringent regulatory adherence),our investigation seeks to determine how well these models can support medical device software *** device classification functions to systematically categorize devices according to their designated use,associated risk levels,and requisite regulatory oversight,thereby providing a structured framework for ensuring safety and efficacy as mandated by regulatory authorities.

关键词： everyday demanding thereby

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Deep Learning with Backtracking Search Optimization Based Skin Lesion Diagnosis Model

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Computers, Materials & Continua 2022年第1期70卷 1297-1313页

作者： C.S.S.Anupama L.Natrayan E.Laxmi Lydia Abdul Rahaman Wahab Sait Jose Escorcia-Gutierrez Margarita Gamarra Romany F.Mansour Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Mechanical Engineering Saveetha School of EngineeringSIMATSChennai602105India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Archives and Communication King Faisal University31982Kingdom of Saudi Arabia Electronic and Telecommunicacions Program Universidad Autonoma del CaribeBarranquilla08001Colombia Department of Computational Science and Electronic Universidad de la CostaCUCBarranquilla08001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Nowadays,quality improvement and increased accessibility to patient data,at a reasonable cost,are highly challenging tasks in healthcare *** of Things(IoT)and Cloud Computing(CC)architectures are utilized in the development of smart healthcare *** entities can support real-time applications by exploiting massive volumes of data,produced by wearable sensor *** advent of evolutionary computation algorithms andDeep Learning(DL)models has gained significant attention in healthcare diagnosis,especially in decision making *** cancer is the deadliest disease which affects people across the *** skin lesion classification model has a highly important application due to its fine-grained variability in the presence of skin *** current research article presents a new skin lesion diagnosis model i.e.,Deep Learning with Evolutionary Algorithm based Image Segmentation(DL-EAIS)for IoT and cloud-based smart healthcare ***,the dermoscopic images are captured using IoT devices,which are then transmitted to cloud servers for further ***,Backtracking Search optimization Algorithm(BSA)with Entropy-Based Thresholding(EBT)i.e.,BSA-EBT technique is applied in image *** by,Shallow Convolutional Neural Network(SCNN)model is utilized as a feature *** addition,Deep-Kernel Extreme LearningMachine(D-KELM)model is employed as a classification model to determine the class labels of dermoscopic *** extensive set of simulations was conducted to validate the performance of the presented method using benchmark *** experimental outcome infers that the proposed model demonstrated optimal performance over the compared techniques under diverse measures.

关键词： Intelligent models skin lesion dermoscopic images smart healthcare internet of things

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A parallel implementation of Chebyshev preconditioned conjugate gradient method

Bulletin of the Technical University of Istanbul

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Bulletin of the Technical University of Istanbul 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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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.

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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

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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