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共 1489 条记录，以下是161-170 订阅

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A Comprehensive Framework for Brain MRI analysis: Classification, Segmentation, and Survival Prediction 12th

A Comprehensive Framework for Brain MRI Analysis: Classifica...

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12th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA 2024

作者： Raju, Bh. V. S. R. K. Jonnala, Mohan Satya Durga Dasari, Jaswanth Annem, Ravi Seshu Challa, Satya Suryanarayana Department of Information Technology S.R.K.R. Engineering College Bhimavaram India

ISBN: (纸本)9789819601424

Brain tumor refers to the unusual and uncontrolled development of brain cells within the brain. Brain tumors are rapidly overtaking all other causes of death worldwide. Effective treatment for brain tumors depends on early identification and precise diagnosis, which also improves the patient’s chance of recovery. Nowadays, deep learning models have become highly effective tools in the analysis of medical images, such as MRI scans. Hence, this work offers a comprehensive approach that incorporates survival prediction, segmentation, and classification of brain tumors. CNN is used in this study for classification. A diverse dataset of brain MRI images is employed to classify brain tumors into four distinct categories—meningioma, pituitary, glioma, and non-tumor. Additionally, the U-Net method is utilized to segment images and determine the amount of impacted regions by comparing tumor pixels to all other pixels in the image, hence yielding useful details regarding the tumor’s growth. Furthermore, a CNN-based approach provides survival prediction. the accuracies achieved for classification, segmentation, and survival prediction based on this approach are 98.12%, 92%, 96% respectively. this integrated strategy provides a comprehensive solution to improve the efficiency of brain tumor management by combining classification, segmentation, and survival prediction. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Implementations of Data analysis tools Into the Biomedical Modular System 12

Implementations of Data Analysis Tools Into the Biomedical M...

引用

12th IEEE international conference on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications, IDAACS 2023

作者： Kostolny, Jozef Blahova, Linda Sutora, David University of Zilina Faculty of Management Science and Informatics Zilina Slovakia

ISBN: (纸本)9798350358056

systems that utilise biological data typically necessitate a module with the capacity to analyse biomedical data. this article investigates the problem at the specified location and outlines the potential solutions at our disposal. then, we'll examine the deployed technology. this technology has the potential to be bundled as a container for a microservice architecture and provides data analysis capabilities. Each module must contain fundamental features and capabilities, such as fuzzy machine learning and data mining methods. Similarly, this component must be able to generate an accurate report based on the results of its analysis. the primary benefit of such a system is its modularity, which enables quick adaptations and expansion for various data types, as well as simpler adaptation of the modules to newer technologies. © 2023 IEEE.

关键词： Biobank D3.js dotNet IKVMdotNET Weka

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Research on Dynamic Equation construction Method with Clearance 12th

Research on Dynamic Equation Construction Method with Cleara...

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12th international conference on Green Intelligent Transportation systems and Safety, 2021

作者： Zhang, Yunhe Zhang, Faping Wang, Wuhong Wu, Kai Li, Yang Laboratory of Industrial and System Engineering Beijing Institute of Technology Beijing China The Second Institute of China Aerospace Science and Industry Corporation Limited Beijing China Sinosteel Group Chifeng Jinxin Mining Co. Ltd Beijing China

ISBN: (纸本)9789811956140

the gap problem has always been a difficulty in dynamic analysis because it is mainly non-linear in the process of motion. Based on the L–N contact force model, the dynamic equation with clearance was built in this paper. At the same time, factors such as friction force and oil film force in the operation process were taken into account to obtain the dynamic model with comprehensive multiple factors, which laid a theoretical reference foundation for future motion analysis. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Friction

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Composite Indicators Building Based on Concordant of Expert-Statistical Information Using Biased Ridge Kernel Regression 12

Composite Indicators Building Based on Concordant of Expert-...

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12th IEEE international conference on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications, IDAACS 2023

作者： Lyubchyk, Leonid Grinberg, Galyna Konokhova, Zoia Yamkovyi, Klym National Technical University Kharkiv Polytechnic Institute Computer Mathematics and Data Analysis Department Ukraine National Technical University Kharkiv Polytechnic Institute Marketing Department Ukraine

ISBN: (纸本)9798350358056

the problem of constructing a complex composite indicator based on expert scores and statistical information about particular indicators is considered. A procedure for estimating the parameters of a nonlinear model of a composite indicator based on the method of biased kernel ridge regression is proposed;at the same time, the problem of optimal concordant of expert and statistical information is solved by choosing the appropriate regularization functional. Using the method of Lagrange multipliers, expressions for estimating the parameters of a nonlinear model and a kernel-based model of a composite indicator are obtained. the results of a numerical experiment on the construction of a composite indicator model using real data are presented. © 2023 IEEE.

关键词： composite indicator concordat expert assessment kernel model regularization ridge regression

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Comparative Verification of the Digital Library of Mathematical Functions and Computer Algebra systems 28th

Comparative Verification of the Digital Library of Mathemati...

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28th international conference on tools and algorithms for the construction and analysis of systems (TACAS) Held as Part of the 25th European Joint conferences on theory and Practice of Software (ETAPS)

作者： Greiner-Petter, Andre Cohl, Howard S. Youssef, Abdou Schubotz, Moritz Trost, Avi Dey, Rajen Aizawa, Akiko Gipp, Bela Univ Wuppertal Wuppertal Germany NIST Mission Viejo CA USA George Washington Univ Washington DC USA FIZ Karlsruhe Berlin Germany Brown Univ Providence RI 02912 USA Univ Calif Berkeley Berkeley CA 94720 USA Natl Inst Informat Tokyo Japan

ISBN: (纸本)9783030995249;9783030995232

Digital mathematical libraries assemble the knowledge of years of mathematical research. Numerous disciplines (e.g., physics, engineering, pure and applied mathematics) rely heavily on compendia gathered findings. Likewise, modern research applications rely more and more on computational solutions, which are often calculated and verified by computer algebra systems. Hence, the correctness, accuracy, and reliability of both digital mathematical libraries and computer algebra systems is a crucial attribute for modern research. In this paper, we present a novel approach to verify a digital mathematical library and two computer algebra systems with one another by converting mathematical expressions from one system to the other. We use our previously developed conversion tool (referred to as LACAST) to translate formulae from the NIST Digital Library of Mathematical Functions to the computer algebra systems Maple and Mathematica. the contributions of our presented work are as follows: (1) we present the most comprehensive verification of computer algebra systems and digital mathematical libraries with one another;(2) we significantly enhance the performance of the underlying translator in terms of coverage and accuracy;and (3) we provide open access to translations for Maple and Mathematica of the formulae in the NIST Digital Library of Mathematical Functions.

关键词： Presentation to Computation LaCASt LaTeX Semantic LaTeX Computer Algebra systems Digital Mathematical Library

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An Algorithm for the construction of Improved Training Sets for Neural Networks

An Algorithm for the Construction of Improved Training Sets ...

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international IEEE conference on Intelligent systems, IS

作者： Kalin Stoyanov Department of Automation University of Chemical Technology and Metallurgy Sofia Bulgaria

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

In this paper we represent a novel approach for improving the training process of an arbitrary backprop-based (e.g. convolution) neural networks, in terms of accuracy and speed. the gain in the performance is due to the alternative method of selection of the samples, to be included in the training set. In the presented Entropy Maximal (EntMax) approach, the samples having higher relative entropy are to be selected to comprise the training set. the images of handwritten characters are considered as discrete random independent and identically distributed (i.i.d.) variables. By applying this approach one takes advantage not only by improving the prediction ability of the neural network, over the validation set, but also by decreasing the time necessary for training, due to the lower number of samples, necessary to provide satisfactory classification ability and the lower number of epochs, needed to assure satisfactory level of the error rate.

关键词： Training Machine learning algorithms Accuracy Error analysis Neural networks Prediction algorithms Entropy Classification algorithms Random variables Proposals

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A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic systems 29th

A Learner-Verifier Framework for Neural Network Controllers ...

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29th international conference on tools and algorithms for the construction and analysis of systems, TACAS 2023, held as part of the 26th European Joint conferences on theory and Practice of Software, ETAPS 2023

作者： Chatterjee, Krishnendu Henzinger, thomas A. Lechner, Mathias Žikelić, Đorđe Klosterneuburg Austria CambridgeMA United States

ISBN: (纸本)9783031308222

Reinforcement learning has received much attention for learning controllers of deterministic systems. We consider a learner-verifier framework for stochastic control systems and survey recent methods that formally guarantee a conjunction of reachability and safety properties. Given a property and a lower bound on the probability of the property being satisfied, our framework jointly learns a control policy and a formal certificate to ensure the satisfaction of the property with a desired probability threshold. Both the control policy and the formal certificate are continuous functions from states to reals, which are learned as parameterized neural networks. While in the deterministic case, the certificates are invariant and barrier functions for safety, or Lyapunov and ranking functions for liveness, in the stochastic case the certificates are supermartingales. For certificate verification, we use interval arithmetic abstract interpretation to bound the expected values of neural network functions. © 2023, the Author(s).

关键词： Stochastic systems

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FMEA 2.0: Machine Learning Applications in Smart Microgrid Risk Assessment

FMEA 2.0: Machine Learning Applications in Smart Microgrid R...

引用

international Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Akash Kadechkar Hakob Grigoryan Smart Energy Dept. N Vision Systems And Technologies Barcelona Spain

ISBN: (数字)9798350361612

ISBN: (纸本)9798350361629

Modern Smart Grids are complex systems incorporating physical components like distributed energy resources and storage, along with cyber components for advanced control, networking, and monitoring. Reliability assessment is a systematic evaluation process used to identify, interpret, and eliminate potential failures and enhance overall reliability of the systems such as Smart Grids where safety is a critical factor. Failure Mode and Effects analysis (FMEA) is one of the risk analysis tools used for evaluating and prioritizing potential failure modes and improving reliability of systems and processes. Within traditional FMEA, failure modes are ranked using a numerical assessment called the Risk Priority Number (RPN), derived from the multiplication of three factors: severity, occurrence, and detection. While commonly used, the FMEA approach has shortcomings, such as assuming equal importance of factors and not adhering to the ordered weighted rule. For this reason, this study proposes an integrated methodology for risk prioritization and failure mode classification into low, moderate and high-risk faults using Grey Relational analysis (GRA) together with FMEA and Deep Learning algorithms. the results demonstrate that, especially in complex systems like Smart Microgrids, the proposed method more accurately captures the coupling relationships between failure modes compared to the conventional FMEA method.

关键词： Decision support systems Machine learning algorithms Heuristic algorithms Ecosystems Knowledge based systems Clustering algorithms Smart grids

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Study of Sub-Synchronous Oscillation Using Time-Frequency analysis in Wind Energy systems 12

Study of Sub-Synchronous Oscillation Using Time-Frequency An...

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12th IEEE Energy Conversion Congress and Exposition-Asia (ECCE-Asia)

作者： Sarkar, Prerna Chilukuri, M., V Vellore Inst Technol Sch Elect Engn Vellore Tamil Nadu India

ISBN: (纸本)9781728163444

Sub-synchronous Resonance (SSR) or Sub-synchronous Oscillation (SSO) is an important phenomenon occurring on electrical grids connected with wind energy systems. According to the recently published IEEE PES technical report TR80 by Wind Energy SSO Taskforce there were several SSR/SSO events reported in China and US which triggered further research from utility engineers and academics. this paper investigates the SSO/SSR phenomena to study its characteristics better in time-frequency domain and highlights the need of real-time time-frequency analysis tools for studying the dynamics of power system for developing advanced protection technology for distributed generation and smart grid. the main contribution of this paper is an application of advanced time-frequency analysis algorithms such as Morse Wavelet Transform, S-Transform and Bi-Gaussian Transform for the study of SSO/SSR phenomenon. the presented results are useful in the design and development of pattern recognition and machine learning tools for the protection as well as health monitoring of wind energy system for future Smart Grid.

关键词： Wind Energy Subsynchronus Oscillations Time-Frequency analysis S-Transform

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Midas: An Open-Source Framework for Simulation-Based analysis of Energy systems 1

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12th international conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2022

作者： Balduin, Stephan Veith, Eric M. S. P. Lehnhoff, Sebastian OFFIS - Institute for Information Technology Oldenburg26121 Germany Carl von Ossietzky University Oldenburg26129 Germany

ISBN: (数字)9783031438240

ISBN: (纸本)9783031438233

the analysis of cyber-physical energy systems is often limited to the individual sub-domains. On the one side, this is caused by the system’s complexity. On the other side, there are many specialized tools but only a few open-source solutions, and bringing those tools together is a complex task. For this reason, we built the open-source framework midas that aims to couple multiple domains into a single simulation scenario. Midas is modularly built, extensible, and uses the co-simulation framework mosaik. It includes a power grid simulation based on pandapower, load and generation time series, weather time series, and several simulation models for distributed energy resources. there are also first advances to integrate a local reactive power market and an ICT simulator into the midas ecosystem. We will present midas in this paper and use it to build surrogate models for a medium-voltage power grid using different sampling strategies. Because of the modularity of midas, the power grid model can easily be replaced by one of the surrogate models for testing purposes. Although the prediction quality of the surrogate models leaves room for improvement, the overall process with midas works quite well and allows fast iterations of different experiment configurations. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cyber Physical System

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