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检索条件"任意字段=2nd International Conference on Computational Modeling, Simulation and Data Analysis, CMSDA 2022"

共 201 条记录，以下是81-90 订阅

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Application of a dynamic computational gis modeling methodology for exposure and dose risk assessment

Application of a dynamic computational gis modeling methodol...

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2nd IASTED international conference on Environmental Modelling and simulation

作者： Magro, G. Scarpanti, S. Sumini, M. Teodori, F. Univ Bologna Dept Energy & Nucl Engn Environm Control Via dei Colli 16 I-40136 Bologna Italy

ISBN: (纸本)9780889866171

An application of Dynamic computational G.I.S methodology in an Exposure Risk Assessment and Dose Assessment based on numerical matrix interaction is here presented. Dynamic computational G.I.S. (DCGIS) is a methodology based on U.S E.P.A. Ecological Risk Assessment and Exposure Assessment Guidelines. Such a methodology is supported by a newly developed Java based software tool working by means of the setup of stressor-vulnerability maps correlations. In this framework it is possible to set several kinds of correlations between stressor matrixes and vulnerability maps in order to compute multi-level risk maps for any specific correlation frame. The software tool produces also technical reports with numerical data concerning the exposure surfaces and the specific dose distribution. The domain of the assessed area can be characterized in a grid-matrix frame and several stressor matrixes can be set for each emission source. The software tool analyser produces comparative risk maps, which are useful for both assessors and managers, mainly when they need different information levels. It is significant to say that the methodology is very appropriate for cumulative and/or interacting effects evaluation which are strategically important in planning activities involving also wide critical areas with ecological protected sites, population centres and industrial developments.

关键词： assessment geographic information systems dynamic GIS stressor-vulnerability analysis dose exposure

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Technologies Integration With Semantic Web Techniques For Business Valuation: Identifying Equities' Intrinsic Value Without Market Bias 2

Technologies Integration With Semantic Web Techniques For Bu...

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2nd international conference on Cyber Resilience, ICCR 2024

作者： Faccia, Alessio Itani, Rania Eltweri, Ahmed Ae Wanganoo, Leena Pio, Leonardo Luigi University Of Birmingham Dubai United Arab Emirates Murdoch University Dubai United Arab Emirates Applied Science Research Center Applied Science Private University Amman Jordan Liverpool John Moores University United Kingdom Universita Di Foggia Italy

ISBN: (纸本)9798350394962

This text sets out to present an innovative approach to intrinsic equity value estimation, deploying state-of-the-art mechanisms and new technologies, but in particular, focusing on the integration of Semantic Web techniques. Its focus is on the problem of market sentiment, which commonly causes the value of equities to be far from their real worth. The proposed solution is to use in a mixed way sophisticated computational techniques and the capability of the Semantic Web's structured data handling to keep the valuations free of bias. The methodology employs advanced analytics, machine learning models, and Natural Language Processing (NLP) for the discovery of patterns and insights that may not easily be visible from traditional valuation methodologies. The holistic approach also involves qualitative analysis to enhance the understanding of the company's prospects. This approach integrates these technologies into the framework of the Semantic Web to provide a transparent and replicable way of determining the intrinsic value of equities, with minimum distortion by market sentiment. The paper argues that this method is quite opposite to traditional business valuation models that use a framework that emphasizes upon empirical evidence and methodological rigor. It postulates that, in the future, if these Semantic Web tools can be put into use for the systematic gathering of varied datasets for contextual analysis, the way valuation functions are handled will undergo a revolution. It would mean a shift in business valuation towards one that is more empirical and technology-enabled towards potentially changing investment analysis by methodological stringency and empirical data. CCS CONCEPTS. Computing methodologies modeling and simulation Model development and analysis modeling methodologies © 2024 IEEE.

关键词： data handling

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Characterizing point spread signals for subsurface synthetic imaging

Characterizing point spread signals for subsurface synthetic...

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2nd international conference on Subsurface Sensing Technologies and Applications

作者： Rodriguez, D Univ Puerto Rico Dept Elect & Comp Engn Computat Signal Proc Grp Mayaguez PR 00681 USA

ISBN: (纸本)0819437743

This work concentrates on the analysis of radar signature signals for the characterization and efficient computation of finite discrete two-dimensional point spread functions. A general simple model for ground penetrating raw data image formation is assumed in order to concentrate on the efficient computation of point spread functions. The point spread functions are used as impulse response functions for the simulation of high resolution image of two dimensional synthetic aperture imaging kernels. A methodology has been developed to serve as a tool aid in the analysis, design, and efficient implementation of one-dimensional and two-dimensional fast Fourier transform (FFT) algorithms prevalent in SAR image formation operations with the idea in mind of reducing the computational effort and improving the hardware implementation process. Kronecker products algebra, a branch of finite dimensional multilinear algebra, has been demonstrated to be a useful tool aid in the devel-opment of fast algorithms for unitary transformations and in the identification of similarities and differences among FFT computational frameworks.

关键词： Image acquisition Synthetic aperture radar Algorithm development Image processing Point spread functions Fourier transforms data modeling Signal processing Radar Image resolution

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Remote sensing integration survey of typical land types and analysis of its spectral properties in southeast of yunnan province

Remote sensing integration survey of typical land types and ...

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2nd international conference on Advances in computational modeling and simulation (ACMS 2013)

作者： Zhang, Xiaolun Gan, Shu Li, Ying Huang, Jilei Gao, Shuai Kunming Univ Sci & Technol Fac Land Resource Engn Kunming 650093 Yunnan Province Peoples R China

ISBN: (纸本)9783037859063

Karst rocky desertification is a major ecological disaster faced by the southeastern region of Yunnan Province, in China. The research of land use status in rocky desertification area is more and more concerned by human. Through remote sensing integrated survey ways to establish the spectral database of six kinds of typical land types, such as water, forest land, paddy field, grassland, dry land and bare land;then, Normalized Difference Vegetation Index (ndVI) processing and Tasseled Cap transformation processing for the spectral data;finally, the spectral characteristics and the variation of typical land types was analyzed and studied. The results indicated that, there are no significant differences of spectral of the six kinds of typical land types, after the processing of ndVI, the water, the forest land and grassland with larger vegetation coverage, and the paddy land, dry land and bare land with smaller vegetation coverage, can be well distinguish, but the distinction between forest land and grassland is bad, the distinction of paddy land, dry land and bare land is also bad;after the Tasseled Cap transformation processing, the dispersion degree of water, forest land, paddy field and grassland is better, the dispersion degree of dry land and bare land is a bit poor, need to be further studied. The remote sensing integrated survey and the analysis of spectral properties are important foundation for the Land Use / Land Cover Change (LUCC) and the dynamic monitoring of rocky desertification in southeastern rocky desertification region of Yunnan province.

关键词： the analysis of spectral properties ndVI Tasseled Cap transformation rocky desertification southeastern of Yunnan province in China

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Aircraft Engine Fault Detection Algorithm Based on Multivariate Time Series Sensor data 2

Aircraft Engine Fault Detection Algorithm Based on Multivari...

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2nd international conference on Inventive Computing and Informatics (ICICI)

作者： Bian, Hongning Zou, Qian Kong, Xinyi Jinan Vocat Coll Jinan 250100 Shandong Peoples R China

ISBN: (纸本)9798350373301;9798350373295

In the rapidly evolving landscape of civil air transportation, ensuring the safety and reliability of aircraft engines remains a critical concern. This study presents a novel aircraft engine fault detection algorithm based on multivariate time series sensor data, with the aim of enhancing the reliability and safety of air transportation. The proposed algorithm utilizes advanced data analysis techniques and intelligent algorithms to accurately predict potential engine failures, thereby facilitating proactive maintenance and minimizing aircraft delays. The study reviews state-of-the-art methods in aircraft engine fault detection, highlighting advances in dynamic radius support vector data description, modified moving window kernel principal component analysis, hybrid extended Kalman filter, and cross-domain guided learning methods, among others. In addition, the study proposes a comprehensive methodology for aircraft engine fault detection that integrates sensor data acquisition, pre-processing, fault detection algorithms, and performance optimization using multivariate time series analysis. Experimental results demonstrate the effectiveness of the proposed algorithm in achieving high detection rates and specificity for known fault types, while addressing challenges related to computational complexity and generalization.

关键词： Aircraft Engine Fault Detection Multivariate Time Series Sensor data

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Battens Modelling and Optimization in Air-Sail Interaction analysis 2nd

Battens Modelling and Optimization in Air-Sail Interaction A...

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2nd international conference on Design Tools and Methods in Industrial Engineering (ADM)

作者： Cali, Michele Sapienza, Ignazio Oliveri, Salvatore Massimo Univ Catania Dept Elect Elect & Comp Engn Catania Italy

ISBN: (纸本)9783030912345;9783030912338

Numerical codes can play an important function in the nautical design when advanced simulation tools are increasingly adopted for prediction purposes, and in particular for the calculation of the interaction between boat parts and surrounding fluids. Fluid-structure interaction analysis (FSI) can help engineers to set the optimum design of a sail and also the influence of panels and battens sail arrangement. The paper describes amethodology that enhances the understanding of panel and battens arrangement, as well as their stiffness on sail performance. Specifically, through the battens position, shape and stiffness parametrization, the sail non-developable shape was optimized, in order to compensate the variation in the angle of attack that occurs following variations in the speed of the wind at different sail heights. For an efficient and robust implementation of integrated Reynolds Averaged Navier Stokes (RANS) equations with Shear Stress Transport (SST) turbulence model and computational StructuralMechanics (CSM) analysis, the constitutive sailcloth and battens characterization was conducted experimentally. The case study of a mainsail in Dacron (c) TNF 240 of a Vaurien dinghy boat, offered tangible results to support the methodology by validating it with experimental data.

关键词： Triangular membrane modeling CFD-CSM analysis SST model Sail battens arrangement Flying shape Twisting

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Linear Mixed Model for Analyzing Longitudinal data: A simulation Study of Children Growth Differences 2nd

Linear Mixed Model for Analyzing Longitudinal Data: A Simula...

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2nd international conference on Computer Science and computational Intelligence (ICCSCI)

作者： Pusponegoro, Novi Hidayat Rachmawati, Ro'fah Nur Notodiputro, Khairil Anwar Sartono, Bagus Inst Stat Otista Raya 64C Jakarta 13330 Indonesia Bina Nusantara Univ Kebun Jeruk Raya 27 Jakarta 11530 Indonesia Bogor Agr Univ Jl Raya Darmaga Bogor Bogor 16680 Indonesia

ISBN: (纸本)9781510849914

Growth developmental research is one example of the application of longitudinal data that have correlated value over time. Linear Mixed Model (LMM) is an extension of classic statistical procedures that provides flexibility analysis in correlated longitudinal data and allows researcher to model the covariance structures that represent its random effects. This paper briefly describes growth curves model as a single LMM that represent two levels of observation, which focused on modeling its covariance structure to capture correlated information over time of individual performance. We apply LMM and model different types of its covariance structure in the simulation study of children's growth differences based on the feeding methods. We perform simulation scenario using MIXED procedure in SAS system, based on three fit indices (-2RLL, AIC and SBC) and p-value significance level, we obtain Unstructured (UN) covariance is always be the best fit in presenting the characteristic of data but not the best choice considering inefficient numbers of parameters while Heterogeneous First-order Autoregressive (ARH(1)) is a proper alternative covariance structure with ease of data interpretation from fewer numbers of estimated parameters. (C) 2017 The Authors. Published by Elsevier B.V.

关键词： covariance structure reapated measurement within-subject growth curves marjinal model

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Coordination of Models for Describing and Making Agro-Technological Decisions 2nd

Coordination of Models for Describing and Making Agro-Techno...

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2nd international conference on Information Systems and Design, ICID 2021

作者： Ereshko, Felix Budzko, Vladimir Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Vavilova 44-2 Moscow119333 Russia

ISBN: (纸本)9783030954932

The analysis of transformations of ideas and management practices in modern conditions of the formation of digital economy models and information support in the agro-industrial complex is carried out. Since the main generator of data affecting the final result of production is external natural conditions, the description of the initial processes is carried out using an agrophysical model of plant growth. The formulation of strategic management tasks in the specified conditions is formulated, a scheme for combining agrophysical and economic descriptions is substantiated, mathematical decision-making models and fundamental simulation computational procedures are considered. © 2022, Springer Nature Switzerland AG.

关键词： Strategic planning

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2nd international conference on Signal and data Processing, ICSDP 2022

2nd International Conference on Signal and Data Processing, ...

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2nd international conference on Signal and data Processing, ICSDP 2022

ISBN: (纸本)9789819914098

The proceedings contain 48 papers. The special focus in this conference is on Signal and data Processing. The topics include: Process Mining-Based Behavioral modeling of Learners in Self-paced Learning Environment;blockchain Scalability: Solutions, Challenges and Future Possibilities;Solution of Unit Commitment Problems in GAMS computational Environment;taxonomy and Implications of Machine Learning for Internet of Things: Qualities, Uses and Algorithms;auto Organizer: A Machine Learning-Based Tool for Automatic Organization of Files;twitter Spam Detection Using Different Machine Learning Techniques;on the Role of Perceptual Information in Image Classification;bengali Text Classification Based on Probability Measure;comprehensive analysis on the Performance of Antenna Design Using Machine Learning Techniques;design and analysis of Novel Miniaturized Metamaterial Structures for Multiband Applications;hybrid Particle Swarm Optimization Based Deep Learning Model for the Stage Classification of Lung Cancer;Interference Cancellation by Using Viterbi Algorithm for Space Base AIS System;a Stacked Multichannel Feature Map Based U-Net Model for Brain Tumor Segmentation;spatial Attention Gated U-Net Structure for Capsule Endoscopy Image Super-Resolution;feature Engineering and Selection for the Identification of Fake News in Social Media;early Detection of Pathological Myopia in Fundus Images Using Deep Learning;an Investigation on the Extractive Summarization of Kannada Text;rice Plant Leaf Disease Detection—A Comparison of Various Methodologies;combating Fake News with Machine Learning and Deep Learning Methods;Employing Soft Computing-Based GGA-MLP for Hyperparameter Optimization in COVID-19-Infected Lung Image data Classification;Design of Compact UWB MIMO Antenna with High Isolation Using Square Swirl Shape EBG Structure;forecasting with Fuzzy Time Series and Variation.

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2nd international conference on Smart Computing and Informatics, SCI 2018

2nd International Conference on Smart Computing and Informat...

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2nd international conference on Smart Computing and Informatics, SCI 2018

ISBN: (纸本)9789811319204

The proceedings contain 70 papers. The special focus in this conference is on Smart Computing and Informatics. The topics include: computational modeling and parametric analysis of an implantable patch antenna using finite-difference time-domain algorithm;a survey on acronym–expansion mining approaches from text and web;deformable facial fitting using active appearance model for emotion recognition;Grey wolf optimization-based improved closed-loop speed control for a BLDC motor drive;energy-aware workflow scheduling algorithm for the deployment of scientific workflows in cloud;A framework for evaluating performance of MADA-AODV protocol by considering multi-dimensional parameters on MANET;a comparative analysis of breast cancer data set using different classification methods;Energy efficient forwarding data and route selection (EEFDRS) algorithm for wireless body area network;skin melanoma assessment using Kapur’s entropy and level set—A study with bat algorithm;a dynamic hierarchical load balancing service architecture for cloud data centre virtual machine migration;estimation of distance of a target speech source by involving monaural features and statistical properties;termite-motivated simulation of cooperative behavior;combined feature extraction for multi-view gender recognition;resource allocation using modified banker’s algorithm for next-generation wireless networks;Synthesis methods of Baugh-Wooley multiplier and non-restoring divider to enhance primitive’s results of QCA circuits;elegant energy competent lighting in green buildings based on energetic power control using IoT design;Energy-efficient routing protocols for WSNs: A comparative analysis;analysis of cancer data set with statistical and unsupervised machine learning methods;performance analysis of array multiplier using low-power 10T full adder;websocket-evented real-time online coding collaborator.

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