scholarly journals Reconstruction of Non-linear Path Analysis Accompanied by Measurement Models on Food Security Models in Indonesia Post-Covid19 Pandemic Based on Big Data

2021 ◽  
Vol 20 ◽  
pp. 637-649
Author(s):  
Solimun - ◽  
Adji Achmad Rinaldo Fernandes ◽  
Nurjannah - ◽  
Indah Yanti ◽  
Luthfatul Amaliana ◽  
...  
Keyword(s):  
Food Security ◽  
Path Analysis ◽  
Predictor Variable ◽  
Measurement Model ◽  
Coefficient Of Determination ◽  
Linear Path ◽  
Measurement Models ◽  
Quantitative And Qualitative Research ◽  
Security Models ◽  
Non Linear

This study aims to map and model the determinants of food security. Mapping is done by cluster and biplot analysis, while modeling is done by non-linear path analysis. This research is mix-method research that combines quantitative and qualitative research. In the qualitative method, this study applies a qualitative Discourse Network Analysis (DNA) approach. Sources of DNA data come from various information in cyberspace (mass media, journals, articles, etc.) that are in accordance with the research context. In DNA data processing, statements, actors, concepts/issues, sentiments, along with the origin of the organization will be generated. As for the quantitative method, this study uses descriptive statistical analysis, biplot, cluster, and non-linear path analysis (square and cubic). The coefficient of determination for both quadratic and cubic path analysis is 0.88, which means that the influence of the independent variable simultaneously on the Y variable is 0.88, which is very strong. Thus, the model formed is quite good because the predictor variable is able to explain food security by 88% while the rest is explained by other factors outside the model. The originality of this research is the reconstruction of non-linear path analysis which is more flexible (no need for assumptions of normality and homogeneity) and is equipped with a measurement model.

Generalized Asymptotic Regression and Non-Linear Path Analysis

Biometrics ◽  
1961 ◽  
Vol 17 (1) ◽  
pp. 120 ◽  
Author(s):  
Malcolm E. Turner ◽  
Robert J. Monroe ◽  
Henry L. Lucas
Keyword(s):  
Path Analysis ◽  
Linear Path ◽  
Non Linear

An Analysis of National Food Security Models

2019 ◽  
Vol 5 ◽  
pp. 7-12
Author(s):  
V.A. Plotnikov ◽  
◽  
M.V. Suleymanova ◽  
Keyword(s):  
Food Security ◽  
Security Models ◽  
National Food Security

scholarly journals Measuring the Refined Theory of Individual Values in 49 Cultural Groups: Psychometrics of the Revised Portrait Value Questionnaire

Assessment ◽  
2021 ◽  
pp. 107319112199876
Author(s):  
Shalom H. Schwartz ◽  
Jan Cieciuch
Keyword(s):  
Measurement Model ◽  
Scaling Analysis ◽  
Refined Theory ◽  
Cultural Groups ◽  
Individual Values ◽  
Internal Reliability ◽  
Measurement Models ◽  
Circular Structure ◽  
Almost All ◽  
Portrait Value Questionnaire

Researchers around the world are applying the recently revised Portrait Value Questionnaire (PVQ-RR) to measure the 19 values in Schwartz’s refined values theory. We assessed the internal reliability, circular structure, measurement model, and measurement invariance of values measured by this questionnaire across 49 cultural groups ( N = 53,472) and 32 language versions. The PVQ-RR reliably measured 15 of the 19 values in the vast majority of groups and two others in most groups. The fit of the theory-based measurement models supported the differentiation of almost all values in every cultural group. Almost all values were measured invariantly across groups at the configural and metric level. A multidimensional scaling analysis revealed that the PVQ-RR perfectly reproduced the theorized order of the 19 values around the circle across groups. The current study established the PVQ-RR as a sound instrument to measure and to compare the hierarchies and correlates of values across cultures.

Aspects of project learning in construction: a socio-technical model

2014 ◽  
Vol 14 (2) ◽  
pp. 229-244 ◽  
Author(s):  
Ali Mohammed Alashwal ◽  
Hamzah Abdul-Rahman
Keyword(s):  
Latent Variable ◽  
Construction Projects ◽  
Team Building ◽  
Principal Component ◽  
Measurement Model ◽  
Survey Method ◽  
Path Modeling ◽  
Content Type ◽  
Measurement Models ◽  
Project Learning

Purpose – The purpose of this paper is to determine the measurement constructs of learning within construction projects' milieu. The literature indicated some mechanisms of learning in projects under four aspects, namely knowledge sharing, knowledge creation, team action to learn, and learning support. The empirical study attempts to verify whether intra-project learning can be measured through these aspects. Design/methodology/approach – The study used a survey method to collect the data from 36 mega-sized building projects in Malaysia. In total, 203 questionnaires were collected from professionals working in the sites of these projects. The data were analysed using principal component analysis (PCA) to determine the constructs of intra-project learning. Partial least squares-path modeling was used then to confirm the results of PCA and determine the contribution of each construct to intra-project learning. Findings – The results affirmed two constructs of intra-project learning, named, social and technical and each consisted of four indicators of learning. Originality/value – The paper emphasized the socio-technical perspective of learning and contributed to developing a hierarchical measurement model of learning in construction project. A project manager can propose new initiatives in response to the new perspective of learning for team building and continuous development. Lastly, the paper provides a comprehensive presentation of how to estimate the hierarchical measurement models of project learning as a latent variable.

scholarly journals Model Calibration for a Rigid Hexapod-Based End-Effector with Integrated Force Sensors

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3537
Author(s):  
Christian Friedrich ◽  
Steffen Ihlenfeldt
Keyword(s):  
Parameter Identification ◽  
Degrees Of Freedom ◽  
Force Measurement ◽  
Experimental Studies ◽  
Measurement Model ◽  
Calibration Procedure ◽  
Force Sensors ◽  
End Effector ◽  
Measurement Models ◽  
Fast Procedure

Integrated single-axis force sensors allow an accurate and cost-efficient force measurement in 6 degrees of freedom for hexapod structures and kinematics. Depending on the sensor placement, the measurement is affected by internal forces that need to be compensated for by a measurement model. Since the parameters of the model can change during machine usage, a fast and easy calibration procedure is requested. This work studies parameter identification procedures for force measurement models on the example of a rigid hexapod-based end-effector. First, measurement and identification models are presented and parameter sensitivities are analysed. Next, two excitation strategies are applied and discussed: identification from quasi-static poses and identification from accelerated continuous trajectories. Both poses and trajectories are optimized by different criteria and evaluated in comparison. Finally, the procedures are validated by experimental studies with reference payloads. In conclusion, both strategies allow accurate parameter identification within a fast procedure in an operational machine state.

Uncertainty quantification for aerodynamic pressure probes, using adaptive quasi-Monte Carlo

2021 ◽  
Author(s):  
Alexandros Christos Chasoglou ◽  
Panagiotis Tsirikoglou ◽  
Anestis I Kalfas ◽  
Reza S Abhari
Keyword(s):  
Monte Carlo ◽  
Measurement Model ◽  
Fast Response ◽  
Two Stage ◽  
Detailed Measurement ◽  
Underlying Distribution ◽  
Factors Affecting ◽  
Quasi Monte Carlo ◽  
Measurement Models ◽  
Aerodynamic Pressure

Abstract In the present study, an adaptive randomized Quasi Monte Carlo methodology is presented, combining Stein’s two-stage adaptive scheme and Low Discrepancy Sobol sequences. The method is used for the propagation and calculation of uncertainties related to aerodynamic pneumatic probes and high frequency fast response aerodynamic probes (FRAP). The proposed methodology allows the fast and accurate, in a probabilistic sense, calculation of uncertainties, ensuring that the total number of Monte Carlo (MC) trials is kept low based on the desired numerical accuracy. Thus, this method is well-suited for aerodynamic pressure probes, where multiple points are evaluated in their calibration space. Complete and detailed measurement models are presented for both a pneumatic probe and FRAP. The models are segregated in sub-problems allowing the evaluation and inspection of intermediate steps of MC in a transparent manner, also enabling the calculation of the relative contributions of the elemental uncertainties on the measured quantities. Various, commonly used sampling techniques for MC simulation and different adaptive MC schemes are compared, using both theoretical toy distributions and actual examples from aerodynamic probes' measurement models. The robustness of Stein's two-stage scheme is demonstrated even in cases when signiffcant deviation from normality is observed in the underlying distribution of the output of the MC. With regards to FRAP, two issues related to piezo-resistive sensors are addressed, namely temperature dependent pressure hysteresis and temporal sensor drift, and their uncertainties are accounted for in the measurement model. These effects are the most dominant factors, affecting all flow quantities' uncertainties, with signiffcance that varies mainly with Mach and operating temperature. This work highlights the need to construct accurate and detailed measurement models for aerodynamic probes, that otherwise will result in signiffcant underestimation (in most cases in excess of 50%) of the final uncertainties.

scholarly journals PENGARUH BAURAN PROMOSI, KUALITAS PELAYANAN, DAN CITRA PERUSAHAAN TERHADAP KEPUASAN JAMAAH UMROH AL-SHAHBA MALANG MELALUI KEPERCAYAAN JAMAAH SEBAGAI VARIABEL INTERVENING

2020 ◽  
Vol 14 (2) ◽  
pp. 161-172
Author(s):  
Maulidia Wulan Anggraini ◽  
Tin Agustina Karnawati ◽  
Widi Dewi Ruspitasari
Keyword(s):  
Data Collection ◽  
Service Quality ◽  
Path Analysis ◽  
Significant Influence ◽  
Sampling Technique ◽  
Corporate Image ◽  
Coefficient Of Determination ◽  
Purposive Sampling ◽  
Independent Variables ◽  
Variable Population

The purpose of the research is to determine the effect of the promotion mix, service quality, and company image toward satisfaction of Al-Shahba Malang pilgrims through the pilgrims’ trust as an intervening variable. Population of this research is based on consumer who choosing and using Al-Shahba Malang’s umrah package in 2016-2018 as many 276 people. Sample used in this research covers 163 consumer using purposive sampling technique. In this research, the data collection techniques is by questionnaires, interviews, observations, and documentations. The data gained from questionnaires was analyzed by using instrument test, path analysis, hypoteshis testing and the coefficient of determination with SPSS 21.0 version. The research proves that the three independent variables : promotion mix, service quality, and corporate image, has a positive and significant influence on the pilgrims’ trust. The promotion mix, service quality, and corporate image has a positive and significant influence on the pilgrims’ satisfaction. The pilgrims’ trust has a positive and significant influence on the pilgrims’ satisfaction. And the promotion mix, service quality, corporate image has a positive and significant indirect influence on the pilgrims’ satisfaction through pilgrims’ trust as an intervening variable.

scholarly journals Non-Linear Regression Models with Vibration Amplitude Optimization Algorithms in a Microturbine

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 130
Author(s):  
Omar Rodríguez-Abreo ◽  
Juvenal Rodríguez-Reséndiz ◽  
L. A. Montoya-Santiyanes ◽  
José Manuel Álvarez-Alvarado
Keyword(s):  
Linear Regression ◽  
Vibration Amplitude ◽  
Regression Models ◽  
Engineering Problem ◽  
Coefficient Of Determination ◽  
Model Parameters ◽  
Gray Wolf ◽  
Linear Regression Models ◽  
Machinery Condition Monitoring ◽  
Non Linear

Machinery condition monitoring and failure analysis is an engineering problem to pay attention to among all those being studied. Excessive vibration in a rotating system can damage the system and cannot be ignored. One option to prevent vibrations in a system is through preparation for them with a model. The accuracy of the model depends mainly on the type of model and the fitting that is attained. The non-linear model parameters can be complex to fit. Therefore, artificial intelligence is an option for performing this tuning. Within evolutionary computation, there are many optimization and tuning algorithms, the best known being genetic algorithms, but they contain many specific parameters. That is why algorithms such as the gray wolf optimizer (GWO) are alternatives for this tuning. There is a small number of mechanical applications in which the GWO algorithm has been implemented. Therefore, the GWO algorithm was used to fit non-linear regression models for vibration amplitude measurements in the radial direction in relation to the rotational frequency in a gas microturbine without considering temperature effects. RMSE and R2 were used as evaluation criteria. The results showed good agreement concerning the statistical analysis. The 2nd and 4th-order models, and the Gaussian and sinusoidal models, improved the fit. All models evaluated predicted the data with a high coefficient of determination (85–93%); the RMSE was between 0.19 and 0.22 for the worst proposed model. The proposed methodology can be used to optimize the estimated models with statistical tools.

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