scholarly journals A Novel Comprehensive Model of Suitability Analysis for Matching Area in Underwater Geomagnetic Aided Inertial Navigation

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Hongmei Zhang ◽  
Le Yang ◽  
Minglong Li
Keyword(s):  
Autonomous Navigation ◽  
Comprehensive Evaluation ◽  
Inertial Navigation ◽  
Principal Component ◽  
Bohai Bay ◽  
Comprehensive Model ◽  
Suitability Analysis ◽  
Geophysical Field ◽  
Factors Affecting ◽  
Model Combining

Geomagnetic aided inertial navigation is a way to use the geophysical field for navigation. It can locate the carrier position by the correlation between geomagnetic data and running track. It is an effective mean to realize autonomous navigation. Matching area suitability is one of the important factors affecting geomagnetic aided inertial navigation. Through the suitability analysis of matching areas, the areas with obvious geomagnetic features and rich information are selected as matching areas, which can effectively improve the real-time and accuracy of geomagnetic aided navigation. However, matching area suitability analysis for geomagnetic aided navigation is a complex process and needs to consider diverse factors, based on which a decision may be made. The area suitability analysis inherently can be considered as a multicriterion decision analysis (MCDA) problem. This paper presented a novel comprehensive model combining principal component analysis (PCA) and analytical hierarchy process (AHP) to evaluate the suitability of the navigation matching area. Firstly, according to the features of the areas, key feature parameters and the corresponding weights are determined by PCA and AHP, respectively. Then comprehensive evaluation values of the navigation matching areas are calculated through the comprehensive model. Finally, experiments were implemented in Bohai Bay; the correlation-matching algorithm is applied to verify the validity of the model in the areas. The experiment results well indicate the consistency between the comprehensive evaluation value and the matching area suitability. It is reasonable to regard the comprehensive evaluation value as a basis for area suitability analysis.

scholarly journals Innovation Efficiency in the Spanish Service Sectors, and Open Innovation

2021 ◽  
Vol 7 (1) ◽  
pp. 62 ◽  
Author(s):  
Rocío Guede-Cid ◽  
Leticia Rodas-Alfaya ◽  
Santiago Leguey-Galán ◽  
Ana I. Cid-Cid
Keyword(s):  
Comprehensive Evaluation ◽  
Principal Component ◽  
Efficiency Score ◽  
Innovation Activity ◽  
Data Envelopment ◽  
Large Dataset ◽  
Model Combining ◽  
Service Sectors ◽  
New Variables ◽  
The Relationship

This paper analyzes the relationship between efficiency and innovation activity in Spanish industrial and service sectors by introducing a new methodology framework. A new model combining principal component analysis (PCA) and data envelopment analysis (DEA) is applied in order to obtain an efficiency score. To achieve a more comprehensive evaluation, a large dataset is included, but a large number of variables compared with the number of decision-making units (DMUs) may diminish the discriminatory power of DEA. To avoid this effect, we first apply PCA to separately obtain the input and output main factors. We then apply DEA to the new variables. The PCA–DEA model allows us to identify 5 efficient sectors out of 42. If only DEA were applied, 16 sectors would turn out to be efficient. This shows that the model improves the discriminatory capability of DEA. Methodologically, this work contributes to the literature by proposing an efficiency measurement using a large number of inputs and outputs that could be applied in different fields. Likewise, this analysis allows for the evaluation and interpretation of innovation activity in the different sectors, which can be taken into account in the management and allocation of resources by institutions.

scholarly journals Suitability Analysis of 17 Probiotic Type Strains of Lactic Acid Bacteria as Starter for Kimchi Fermentation

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1435
Author(s):  
Hee Seo ◽  
Jae-Han Bae ◽  
Gayun Kim ◽  
Seul-Ah Kim ◽  
Byung Hee Ryu ◽  
...  
Keyword(s):  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
Growth Rates ◽  
Principal Component ◽  
Fermented Foods ◽  
Suitability Analysis ◽  
Moderate Growth ◽  
Health Promoting ◽  
Highly Correlated ◽  
Type Strains

The use of probiotic starters can improve the sensory and health-promoting properties of fermented foods. This study aimed to evaluate the suitability of probiotic lactic acid bacteria (LAB) as a starter for kimchi fermentation. Seventeen probiotic type strains were tested for their growth rates, volatile aroma compounds, metabolites, and sensory characteristics of kimchi, and their characteristics were compared to those of Leuconostoc (Le.) mesenteroides DRC 1506, a commercial kimchi starter. Among the tested strains, Limosilactobacillus fermentum, Limosilactobacillus reuteri, Lacticaseibacillus rhamnosus, Lacticaseibacillus paracasei, and Ligilactobacillus salivarius exhibited high or moderate growth rates in simulated kimchi juice (SKJ) at 37 °C and 15 °C. When these five strains were inoculated in kimchi and metabolite profiles were analyzed during fermentation using GC/MS and 1H-NMR, data from the principal component analysis (PCA) showed that L. fermentum and L. reuteri were highly correlated with Le. mesenteroides in concentrations of sugar, mannitol, lactate, acetate, and total volatile compounds. Sensory test results also indicated that these three strains showed similar sensory preferences. In conclusion, L. fermentum and L. reuteri can be considered potential candidates as probiotic starters or cocultures to develop health-promoting kimchi products.

scholarly journals Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1055
Author(s):  
Qingyun Zhang ◽  
Jian Yang ◽  
Panpan Huang ◽  
Xin Liu ◽  
Shanpeng Wang ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
System Model ◽  
Degree Of Polarization ◽  
Positioning System ◽  
Integration Model ◽  
Position Errors ◽  
Model Combining ◽  
Polarization Compass

In this paper, to address the problem of positioning accumulative errors of the inertial navigation system (INS), a bionic autonomous positioning mechanism integrating INS with a bioinspired polarization compass is proposed. In addition, the bioinspired positioning system hardware and the integration model are also presented. Concerned with the technical issue of the accuracy and environmental adaptability of the integrated positioning system, the sun elevation calculating method based on the degree of polarization (DoP) and direction of polarization (E-vector) is presented. Moreover, to compensate for the latitude and longitude errors of INS, the bioinspired positioning system model combining the polarization compass and INS is established. Finally, the positioning performance of the proposed bioinspired positioning system model was validated via outdoor experiments. The results indicate that the proposed system can compensate for the position errors of INS with satisfactory performance.

scholarly journals A Dynamic Calibration Method of Installation Misalignment Angles between Two Inertial Navigation Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2947
Author(s):  
Ming Hua ◽  
Kui Li ◽  
Yanhong Lv ◽  
Qi Wu
Keyword(s):  
Autonomous Navigation ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Measurement Information ◽  
Dynamic Calibration ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Additional Information ◽  
Two Systems ◽  
Dynamic Calibration Method

Generally, in order to ensure the reliability of Navigation system, vehicles are usually equipped with two or more sets of inertial navigation systems (INSs). Fusion of navigation measurement information from different sets of INSs can improve the accuracy of autonomous navigation effectively. However, due to the existence of misalignment angles, the coordinate axes of different systems are usually not in coincidence with each other absolutely, which would lead to serious problems when integrating the attitudes information. Therefore, it is necessary to precisely calibrate and compensate the misalignment angles between different systems. In this paper, a dynamic calibration method of misalignment angles between two systems was proposed. This method uses the speed and attitude information of two sets of INSs during the movement of the vehicle as measurements to dynamically calibrate the misalignment angles of two systems without additional information sources or other external measuring equipment, such as turntable. A mathematical model of misalignment angles between two INSs was established. The simulation experiment and the INSs vehicle experiments were conducted to verify the effectiveness of the method. The results show that the calibration accuracy of misalignment angles between the two sets of systems can reach to 1″ while using the proposed method.

scholarly journals Multiplexed profiling of single-cell extracellular vesicles secretion

2019 ◽  
Vol 116 (13) ◽  
pp. 5979-5984 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cell Analysis ◽  
Comprehensive Evaluation ◽  
Single Cells ◽  
Deep Understanding ◽  
Principal Component ◽  
Cell Heterogeneity ◽  
Indispensable Tool

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g.,CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current single-cell analysis and EV research.

An Exploration of Provincial Low-Carbon Economy Evaluation System Based on Principal Component-Variable Fuzzy Evaluation

2013 ◽  
Vol 291-294 ◽  
pp. 1562-1567
Author(s):  
Ji Min Hu ◽  
Jian Long Gu ◽  
Chang Cui Hu ◽  
Hai Feng Wang
Keyword(s):  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Principal Component ◽  
Fuzzy Comprehensive Evaluation ◽  
Fuzzy Evaluation ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Component Variable ◽  
The Status ◽  
Carbon Economy

According to indicators’ information repetition and subjectivity of the indicators’ weight set during the variable fuzzy comprehensive evaluation, Principal Component analysis can help solve the weight of the relative indicators and reduce comprehensive evaluation dimensions of the variable fussy comprehensive evaluation. This paper has made a comprehensive evaluation of the status quo of Yunnan’s low carbon economy development(2005-2009), which turns out to be more practical compared with the mere variable fussy theory analysis, thus, principal component-variable fuzzy evaluation is a kind of feasible way to analyze the regional low carbon development status.

Reliability Parameters Forecasting for Transmission Lines Based on Principal Component Regression

2013 ◽  
Vol 291-294 ◽  
pp. 2381-2386 ◽  
Author(s):  
Wen Xia Liu ◽  
Ji Kai Xu ◽  
Hong Yuan Jiang ◽  
Yong Tao Shen
Keyword(s):  
Principal Component Analysis ◽  
Transmission Lines ◽  
Principal Component Regression ◽  
Principal Component ◽  
Forecasting Accuracy ◽  
Factors Affecting ◽  
Reliability Parameters ◽  
Impacting Factors ◽  
Simulation Results

It is the foundation for evaluating the reliability of transmission lines to obtain and analyze the original reliability parameters. However, these parameters depend on long- term statistic and calculation. In the case of lacking such parameters in a new project , this paper proposes a method of Principal Component Analysis to obtain the principal component of the impacting factors ,in which various factors affecting reliability parameters are taken into account. Through this method, we can use PCR to obtain the failure rate of the unknown transmission lines on the base of the known credible lines’ rates. The simulation results show that the proposed approach possesses higher forecasting accuracy and provides references for the power system dispatching departments and transmission lines maintenance departments.

Classification and Prediction of Goldfish Population and Water Quality Using a Potentiometric E-Tongue

2017 ◽  
Vol 60 (4) ◽  
pp. 1037-1044
Author(s):  
Zhenbo Wei ◽  
Yu Zhao ◽  
Jun Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Pattern Recognition ◽  
Comprehensive Evaluation ◽  
Back Propagation ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Pattern Recognition Methods

Abstract. In this study, a potentiometric E-tongue was employed for comprehensive evaluation of water quality and goldfish population with the help of pattern recognition methods. Four water quality parameters, i.e., pH and concentrations of dissolved oxygen (DO), nitrite (NO2-N), and ammonium (NH3-N), were tested by conventional analysis methods. The differences in water quality parameters between samples were revealed by two-way analysis of variance (ANOVA). The cultivation days and goldfish population were classified well by principal component analysis (PCA) and canonical discriminant analysis (CDA), and the distribution of each sample was clearer in CDA score plots than in PCA score plots. The cultivation days, goldfish population, and water parameters were predicted by a T-S fuzzy neural network (TSFNN) and back-propagation artificial neural network (BPANN). BPANN performed better than TSFNN in the prediction, and all fitting correlation coefficients were >0.90. The results indicated that the potentiometric E-tongue coupled with pattern recognition methods could be applied as a rapid method for the determination and evaluation of water quality and goldfish population. Keywords: Classify, E-tongue, Goldfish water, Prediction.

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