scholarly journals A perturbation-based hybrid methodology for control drum worth prediction applied to the HOLOS-Quad microreactor concept

2021 ◽  
pp. 108903
Author(s):  
Dean Price ◽  
Shai Kinast ◽  
Kaitlyn Barr ◽  
Brendan Kochunas ◽  
Claudio Filippone
Keyword(s):  
Hybrid Methodology

Ensemble Visual Content based Search and Retrieval for Natural Scene Images

2019 ◽  
Vol 12 ◽  
Author(s):  
Pushpendra Singh ◽  
P.N. Hrisheekesha ◽  
Vinai Kumar Singh
Keyword(s):  
Template Matching ◽  
Feature Descriptor ◽  
Natural Scene ◽  
Visual Content ◽  
Other Information ◽  
Similar Images ◽  
State Of Art ◽  
Natural Scene Images ◽  
Hybrid Methodology ◽  
Search And Retrieval

Content based image retrieval (CBIR) is one of the field for information retrieval where similar images are retrieved from database based on the various image descriptive parameters. The image descriptor vector is used by machine learning based systems to store, learn and template matching. These feature descriptor vectors locally or globally demonstrate the visual content present in an image using texture, color, shape, and other information. In past, several algorithms were proposed to fetch the variety of contents from an image based on which the image is retrieved from database. But, the literature suggests that the precision and recall for the gained results using single content descriptor is not significant. The main vision of this paper is to categorize and evaluate those algorithms, which were proposed in the interval of last 10 years. In addition, experiment is performed using a hybrid content descriptors methodology that helps to gain the significant results as compared with state-of-art algorithms. The hybrid methodology decreases the error rate and improves the precision and recall for large natural scene images dataset having more than 20 classes.

scholarly journals Designing a hybrid methodology for the Life Cycle Valuation of capital goods

2021 ◽  
Vol 32 ◽  
pp. 382-395
Author(s):  
W. Haanstra ◽  
A.J.J. Braaksma ◽  
L.A.M. van Dongen
Keyword(s):  
Life Cycle ◽  
Capital Goods ◽  
Hybrid Methodology

Critical Reflection Mapping as a Hybrid Methodology for Examining Sociospatial Perceptions of New Research Sites

2014 ◽  
Vol 105 (1) ◽  
pp. 22-47 ◽  
Author(s):  
Timothy L. Hawthorne ◽  
Patricia Solís ◽  
Brittney Terry ◽  
Marie Price ◽  
Christopher L. Atchison
Keyword(s):  
Critical Reflection ◽  
New Research ◽  
Hybrid Methodology

Analysis of a Rotor in Hover using Hybrid Methodology

2014 ◽  
Author(s):  
Ritu Marpu ◽  
Lakshmi Sankar ◽  
T Alan Egolf ◽  
Nathan S. Hariharan
Keyword(s):  
Hybrid Methodology

A Hybrid Methodology for Dental Hospital Quality Performance Gap Using HOQ and Process Analysis

2021 ◽  
Vol 12 (6) ◽  
pp. 16-42
Author(s):  
Shamsuddin Ahmed
Keyword(s):  
Correlation Analysis ◽  
Service Quality ◽  
Process Analysis ◽  
Real Life ◽  
Phenomenological Approach ◽  
Expectations Gap ◽  
Dental Hospital ◽  
Unique Method ◽  
Strategy Map ◽  
Hybrid Methodology

A hybrid methodology is described to identify a quality gap in a dental hospital. The research case study illustrates how to implement quality improvement in a real-life context. A combination of an ethnographic, narrative, and phenomenological approach in data collection and observations within the dental hospital validates the case findings. A unique method based on systems study and Taguchi loss function is shown to reduce the service quality gap in a dental hospital. A house of quality (HOQ) combines the correlation between “patient's expectations” and the hospital's “technical” characteristics. The correlation between service quality and technical characteristics measures a patient's expectations gap. Factor analysis helps to group service and technical factors for better patient management. A strategy map correlation analysis is generated to manage the quality gap. The correlation analysis between patient expectations and the hospital's technical characteristics identify areas of immediate attention.

A hybrid methodology for structure damage detection uniting FEM and 1D-CNNs: Demonstration on typical high-pile wharf

2022 ◽  
Vol 168 ◽  
pp. 108738
Author(s):  
Yujue Zhou ◽  
Yonglai Zheng ◽  
Yongcheng Liu ◽  
Tanbo Pan ◽  
Yubao Zhou
Keyword(s):  
Damage Detection ◽  
Structure Damage ◽  
Hybrid Methodology

New Hybrid Methodology for the Development of MEMS Multivariable Sensors

2001 ◽  
Author(s):  
Emily J. Pryputniewicz ◽  
John P. Angelosanto ◽  
Gordon C. Brown ◽  
Cosme Furlong ◽  
Ryszard J. Pryputniewicz
Keyword(s):  
Process Control ◽  
Microelectromechanical Systems ◽  
Absolute Pressure ◽  
Single Chip ◽  
Specific Test ◽  
Mems Sensor ◽  
Test Conditions ◽  
Mems Technology ◽  
Functional Operation ◽  
Hybrid Methodology

Abstract Using recent advances in microelectromechanical systems (MEMS) technology, a new multivariable sensor was developed. This MEMS sensor, capable of measuring temperature, absolute pressure, and differential pressure on a single chip, is particularly suitable for applications in process control industry. However, functional operation of the sensor depends on validation of its performance under specific test conditions. We have developed a hybrid methodology, based on analysis and measurements, that allows such validation. In this paper, the MEMS multivariable sensor is described, the hybrid methodology is outlined, and its use is illustrated with representative results.

Optimization of Flexible Pipes Dynamic Analysis Using Artificial Neural Networks

2016 ◽  
Author(s):  
Victor Chaves ◽  
Luis V. S. Sagrilo ◽  
Vinícius Ribeiro Machado da Silva
Keyword(s):  
Dynamic Analysis ◽  
Fem Simulation ◽  
Training Data ◽  
Local Analysis ◽  
Flexible Pipe ◽  
Nonlinear Fem ◽  
Irregular Wave ◽  
Flexible Pipes ◽  
Artificial Neural ◽  
Hybrid Methodology

Irregular wave dynamic analysis is an extremely computational expensive process on flexible pipes design. One emerging method that aims to reduce these computational costs is the hybrid methodology that combines Finite Element Analyses (FEA) and Artificial Neural Network (ANN). The proposed hybrid methodology aims to predict flexible pipe tension and curvatures in the bend stiffener region. Firstly using short FEA simulations to train the ANN, and then using only the ANN and the prescribed floater motions to get the rest of the response histories. Two approaches are developed with respect to the training data. One uses an ANN for each sea state in the wave scatter diagram and the other develops an ANN for each wave incidence direction. In order to evaluate the accuracy of the proposed approaches, a local analysis is applied, based on the predicted tension and curvatures, to calculate stresses in tension armour wires and the corresponding flexible pipe fatigue lifes. The results are compared to those from full nonlinear FEM simulation.

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