An Improved GAC Model Combining with GNGVF

2011 ◽  
Author(s):  
Yanqing Guo ◽  
Meiqing Wang ◽  
Choi-Hong Lai
Keyword(s):  
Model Combining

scholarly journals Personality and Behavioral Predictors of Cyclist Involvement in Crash-Related Conditions

2019 ◽  
Vol 16 (24) ◽  
pp. 4881 ◽  
Author(s):  
Yubing Zheng ◽  
Yang Ma ◽  
Nan Li ◽  
Jianchuan Cheng
Keyword(s):  
Personality Traits ◽  
Road Safety ◽  
Sensation Seeking ◽  
Structural Equation ◽  
Personal Characteristics ◽  
Equation Modeling ◽  
Online Questionnaire ◽  
Road Crashes ◽  
Crash Rates ◽  
Model Combining

In recent years, the increasing rate of road crashes involving cyclists with a disproportionate overrepresentation in injury statistics has become a major concern in road safety and public health. However, much remains unknown about factors contributing to cyclists’ high crash rates, especially those related to personal characteristics. This study aims to explore the influence of cyclist personality traits and cycling behaviors on their road safety outcomes using a mediated model combining these constructs. A total of 628 cyclists completed an online questionnaire consisting of questions related to cycling anger, impulsiveness, normlessness, sensation seeking, risky cycling behaviors, and involvement in crash-related conditions in the past year. After the psychometric properties of the employed scales were examined, the relationships among the tested constructs were investigated using structural equation modeling. The results showed that cyclists’ crash risks were directly predicted by risky cycling behaviors and cycling anger, and the effects of cycling anger, impulsiveness, as well as normlessness on crash risks, were mediated by cycling behaviors. The current findings provide insight into the importance of personality traits in impacting cycling safety and could facilitate the development of evidence-based prevention and promotion strategies targeting cyclists in China.

scholarly journals Improved Hough Transform and Total Variation Algorithms for Features Extraction of Wood

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 466
Author(s):  
Weiwei Du ◽  
Yarui Xi ◽  
Kiichi Harada ◽  
Yumei Zhang ◽  
Keiko Nagashima ◽  
...  
Keyword(s):  
Total Variation ◽  
Hough Transform ◽  
Annual Ring ◽  
Wood Quality ◽  
Volume Density ◽  
Low Noise ◽  
Impact Factors ◽  
Annual Rings ◽  
New Model ◽  
Model Combining

Research shows that the intensity impact factors of wood, such as late timber ratio, volume density and the intensity of itself, correlate with the width of wood annual rings. Therefore, extracting wood annual ring information from wood images is helpful for evaluating wood quality. During the past few years, many researchers have conducted defect detection by studying the information of wood images. However, there are few in-depth studies on the statistics and calculation of wood annual ring information. This study proposes a new model combining the Total Variation (TV) algorithm and the improved Hough transform to accurately measure the wood annual ring information. The TV algorithm is used to suppress image noise, and the Hough transform is for detecting the center of the wood image. Moreover, the edges of wood annual rings are extracted, and the statistical ring information is calculated. The experimental results show that the new model has good denoising capability, clearly extract the edges of wood annual rings and calculate the related parameters from the indoor wood images of the processed logs and the unprocessed low-noise logs.

scholarly journals Application of an Innovative Model for the Risk Management of COVID-19 in a Multinational Manufacturing Company

2021 ◽  
Vol 13 (11) ◽  
pp. 5771
Author(s):  
Piero Lovreglio ◽  
Angela Stufano ◽  
Francesco Cagnazzo ◽  
Nicola Bartolomeo ◽  
Ivo Iavicoli
Keyword(s):  
Risk Management ◽  
Manufacturing Industry ◽  
Incidence Rates ◽  
Manufacturing Plants ◽  
Model Combining ◽  
Innovative Model ◽  
Global Prevention ◽  
The Relationship ◽  
Physician Team ◽  
The Eu

The COVID-19 incidence in 61 manufacturing plants in Europe (EU), North America (NA) and Latin-America (LATAM) was compared with the incidence observed in the countries where the plants are located in order to evaluate the application of an innovative model for COVID-19 risk management. Firstly, a network of local and global teams was created, including an external university occupational physician team for scientific support. In July 2020, global prevention guidelines for the homogenous management of the pandemic were applied, replacing different site or regional procedures. A tool for COVID-19 monitoring was implemented to investigate the relationship between the incidence rates inside and outside the plants. In the period of May–November 2020, 565 confirmed cases (EU 330, NA 141, LATAM 94) were observed among 20,646 workers with different jobs and tasks, and in the last two months 85% EU and 70% NA cases were recorded. Only in 10% of cases was a possible internal origin of the contagion not excluded. In the EU and NA, unlike LATAM, the COVID-19 incidence rates inside the sites punctually followed the rising trend outside. In conclusion, the model, combining a global approach with the local application of the measures, maintains the sustainability in the manufacturing industry.

scholarly journals Developing a Fuzzy TOPSIS Model Combining MACBETH and Fuzzy Shannon Entropy to Select a Gamification App

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1034
Author(s):  
María Carmen Carnero
Keyword(s):  
Shannon Entropy ◽  
Fuzzy Topsis ◽  
Preference Ranking ◽  
Promethee Ii ◽  
Ciudad Real ◽  
Industrial Manufacturing ◽  
Model Combining ◽  
La Mancha ◽  
University Course ◽  
The University

Due to the important advantages it offers, gamification is one of the fastest-growing industries in the world, and interest from the market and from users continues to grow. This has led to the development of more and more applications aimed at different fields, and in particular the education sector. Choosing the most suitable application is increasingly difficult, and so to solve this problem, our study designed a model which is an innovative combination of fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and Shannon entropy theory, to choose the most suitable gamification application for the Industrial Manufacturing and Organisation Systems course in the degree programmes for Electrical Engineering and Industrial and Automatic Electronics at the Higher Technical School of Industrial Engineering of Ciudad Real, part of the University of Castilla-La Mancha. There is no precedent in the literature that combines MACBETH and fuzzy Shannon entropy to simultaneously consider the subjective and objective weights of criteria to achieve a more accurate model. The objective weights computed from fuzzy Shannon entropy were compared with those calculated from De Luca and Termini entropy and exponential entropy. The validity of the proposed method is tested through the Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE) II, ELimination and Choice Expressing REality (ELECTRE) III, and fuzzy VIKOR method (VIsekriterijumska optimizacija i KOmpromisno Resenje). The results show that Quizizz is the best option for this course, and it was used in two academic years. There are no precedents in the literature using fuzzy multicriteria decision analysis techniques to select the most suitable gamification application for a degree-level university course.

scholarly journals A predictable smoothing evolution model for computer-controlled polishing

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Jing Hou ◽  
Pengli Lei ◽  
Shiwei Liu ◽  
Xianhua Chen ◽  
Jian Wang ◽  
...  
Keyword(s):  
Evolution Model ◽  
Quantitative Prediction ◽  
Theoretical Support ◽  
Model Combining ◽  
Process Guidance ◽  
Dependent Model ◽  
Computer Controlled Optical Surfacing ◽  
Computer Controlled ◽  
Time Dependent Model ◽  
Selection Of

AbstractQuantitative prediction of the smoothing of mid-spatial frequency errors (MSFE) is urgently needed to realize process guidance for computer controlled optical surfacing (CCOS) rather than a qualitative analysis of the processing results. Consequently, a predictable time-dependent model combining process parameters and an error decreasing factor (EDF) were presented in this paper. The basic smoothing theory, solution method and modification of this model were expounded separately and verified by experiments. The experimental results show that the theoretical predicted curve agrees well with the actual smoothing effect. The smoothing evolution model provides certain theoretical support and guidance for the quantitative prediction and parameter selection of the smoothing of MSFE.

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 deep learning based approach for prediction of Chlamydomonas reinhardtii phosphorylation sites

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Niraj Thapa ◽  
Meenal Chaudhari ◽  
Anthony A. Iannetta ◽  
Clarence White ◽  
Kaushik Roy ◽  
...  
Keyword(s):  
Deep Learning ◽  
Chlamydomonas Reinhardtii ◽  
Protein Phosphorylation ◽  
Short Term Memory ◽  
Phosphorylation Site ◽  
Specific Protein ◽  
Training Dataset ◽  
Phosphorylation Sites ◽  
Site Prediction ◽  
Model Combining

AbstractProtein phosphorylation, which is one of the most important post-translational modifications (PTMs), is involved in regulating myriad cellular processes. Herein, we present a novel deep learning based approach for organism-specific protein phosphorylation site prediction in Chlamydomonas reinhardtii, a model algal phototroph. An ensemble model combining convolutional neural networks and long short-term memory (LSTM) achieves the best performance in predicting phosphorylation sites in C. reinhardtii. Deemed Chlamy-EnPhosSite, the measured best AUC and MCC are 0.90 and 0.64 respectively for a combined dataset of serine (S) and threonine (T) in independent testing higher than those measures for other predictors. When applied to the entire C. reinhardtii proteome (totaling 1,809,304 S and T sites), Chlamy-EnPhosSite yielded 499,411 phosphorylated sites with a cut-off value of 0.5 and 237,949 phosphorylated sites with a cut-off value of 0.7. These predictions were compared to an experimental dataset of phosphosites identified by liquid chromatography-tandem mass spectrometry (LC–MS/MS) in a blinded study and approximately 89.69% of 2,663 C. reinhardtii S and T phosphorylation sites were successfully predicted by Chlamy-EnPhosSite at a probability cut-off of 0.5 and 76.83% of sites were successfully identified at a more stringent 0.7 cut-off. Interestingly, Chlamy-EnPhosSite also successfully predicted experimentally confirmed phosphorylation sites in a protein sequence (e.g., RPS6 S245) which did not appear in the training dataset, highlighting prediction accuracy and the power of leveraging predictions to identify biologically relevant PTM sites. These results demonstrate that our method represents a robust and complementary technique for high-throughput phosphorylation site prediction in C. reinhardtii. It has potential to serve as a useful tool to the community. Chlamy-EnPhosSite will contribute to the understanding of how protein phosphorylation influences various biological processes in this important model microalga.

scholarly journals Valuation of the EQ-5D-3L in Russia

2021 ◽  
Author(s):  
Vitaly Omelyanovskiy ◽  
Nuriya Musina ◽  
Svetlana Ratushnyak ◽  
Tatiana Bezdenezhnykh ◽  
Vlada Fediaeva ◽  
...  
Keyword(s):  
Health Problems ◽  
Cost Utility ◽  
Economic Evaluations ◽  
Computer Assisted ◽  
Health State ◽  
Primary Analysis ◽  
Health States ◽  
Value Set ◽  
Model Combining ◽  
Life Years

Abstract Purpose The most widely used generic questionnaire to estimate the quality of life for yielding quality-adjusted life years in economic evaluations is EQ-5D. Country-specific population value sets are required to use EQ-5D in economic evaluations. The aim of this study was to establish an EQ-5D-3L value set for Russia. Methods A representative sample aged 18+ years was recruited from the Russia`s general population. Computer-assisted face–to–face interviews were conducted based on the standardized valuation protocol using EQ-Portable Valuation Technology. Population preferences were elicited utilizing both composite time trade-off (cTTO) and discrete choice experiment (DCE) techniques. To estimate the value set, a hybrid regression model combining cTTO and DCE data was used. Results A total of 300 respondents who successfully completed the interview were included in the primary analysis. 120 (40.0%) respondents reported no health problems of any dimension, and 56 (18.7%) reported moderate health problems in one dimension of the EQ‐5D‐3L. Median self-rated health using EQ‐VAS was 80 with IQR 70–90. Comparing cTTO and DCE-predicted values for 243 health states resulted in a similar pattern. This supports the use of hybrid models. The predicted value based on the preferred model for the worst health state “33333” was −0.503. Mobility dimension had the most significant impact on the utility decrement, and anxiety/depression had the lowest decrement. Conclusion Determining a Russian national value set may be considered the first step towards promoting cost-utility analysis use to increase comparability among studies and improve the transferability of healthcare decision-making in Russia.

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