Analysis of Energy-saving Behavior among University Students in Vietnam

Currently, in the course of serious environmental problems where the cause is anthropogenic, such as global wanning, not only the technology and policies but also the promotions of pro-environmental behavior are required. However, previous studies reported a gap between high environmental awareness and behavior. So to promote this practice, it is necessary to clarify the determinants that lead to practice. Because of the rapid economic growth in developing countries, including Vietnam, pollution problems and energy consumption are of major importance. This study aims to propose methods to promote pro-environmental practices based on a questionnaire and statistical analysis that investigated university students in Vietnam＇s Ho Chi Minh city. From the factor analysis, in actions to do with the power-saving behavior of standby power and home electronics, and the use of air conditioning, four evaluation criteria including effectiveness, cost feasibility, convenience, and social norms are extracted. The covariance structure analysis showed that the evaluation of convenience represented the strongest causal relation to a given power-saving action, and the action, in turn, can lead to improvements in most practical activities so as to enhance their convenience. Finally, several methods to save energy are proposed based on the results of the questionnaire.

Inference Procedures on the Generalized Poisson Distribution from Multiple Samples: Comparisons with Nonparametric Models for Analysis of Covariance (ANCOVA) of Count Data

Count data that exhibit over dispersion (variance of counts is larger than its mean) are commonly analyzed using discrete distributions such as negative binomial, Poisson inverse Gaussian and other models. The Poisson is characterized by the equality of mean and variance whereas the Negative Binomial and the Poisson inverse Gaussian have variance larger than the mean and therefore are more appropriate to model over-dispersed count data. As an alternative to these two models, we shall use the generalized Poisson distribution for group comparisons in the presence of multiple covariates. This problem is known as the ANCOVA and is solved for continuous data. Our objectives were to develop ANCOVA using the generalized Poisson distribution, and compare its goodness of fit to that of the nonparametric Generalized Additive Models. We used real life data to show that the model performs quite satisfactorily when compared to the nonparametric Generalized Additive Models.

Measurement of^(134)Xe(n,2n)^(133m),gXe reaction cross sections in 14‑MeV region with detailed uncertainty quantification

A lead-shielded HPGe detector and offlineγ-ray spectra of the residual product were used to measure the cross section(CS)and ratios of isomeric CS(σm/σg)in^(134)Xe(n,2n)^(133m),gXe reactions at different energies(13.5 MeV,13.8 MeV,14.1 MeV,14.4 MeV,14.8 MeV)relative to the^(93)Nb(n,2n)^(92)mNb reaction CS.The target was high-purity natural Xe gas under high pressure.The T(d,n)4He reaction produces neutrons.TALYS code(version 1.95)for nuclear reactions was used for calculations,with default parameters and nuclear level density models.The uncertainties in the measured CS data were thoroughly analyzed using the covariance analysis method.The results were compared with theoretical values,evaluation data,and previous experimental findings.CS data of the 134Xe(n,2n)133mXe and 134Xe(n,2n)133gXe reactions and the corresponding isomeric CS ratios at 13.5 MeV,13.8 MeV,and 14.1 MeV neutron energies are reported for the first time.This research advances our knowledge of pre-equilibrium emission in the(n,2n)reaction channel by resolving inconsistencies in the Xe data.

Over-limit risk assessment method of integrated energy system considering source-load correlation

In an integrated energy system,source-load multiple uncertainties and correlations lead to an over-limit risk in operating state,including voltage,temperature,and pressure over-limit.Therefore,efficient probabilistic energy flow calculation methods and risk assessment theories applicable to integrated energy systems are crucial.This study proposed a probabilistic energy flow calculation method based on polynomial chaos expansion for an electric-heat-gas integrated energy system.The method accurately and efficiently calculated the over-limit probability of the system state variables,considering the coupling conditions of electricity,heat,and gas,as well as uncertainties and correlations in renewable energy unit outputs and multiple types of loads.To further evaluate and quantify the impact of uncertainty factors on the over-limit risk,a global sensitivity analysis method for the integrated energy system based on the analysis of covariance theory is proposed.This method considered the source-load correlation and aimed to identify the key uncertainty factors that influence stable operation.Simulation results demonstrated that the proposed method achieved accuracy to that of the Monte Carlo method while significantly reducing calculation time.It effectively quantified the over-limit risk under the presence of multiple source-load uncertainties.

Investigation of 58Ni(n, p)58Co reaction cross-section with covariance analysis

The excitation function of the 58Ni(n,p)58Co reaction was measured using the well-established neutron activation technique andγ-ray spectroscopy.Neutrons in the energy range of 1.7 to 2.7 MeV were generated using the 7Li(p,n)reaction.The neutron flux was measured using the standard 115In(n,n’)115mIn monitor reaction.The results of the neutron spectrum averaged cross-section of 58Ni(n,p)58Co reactions were compared with existing cross-section data available in the EXFOR data library as well as with various evaluated data libraries such as ENDF/B-VIII.0,JEFF-3.3,JENDL-4.0,and CENDL-3.2.Theoretical calculations were performed using the nuclear reaction code TALYS.Various nuclear level density(NLD)models were tested,and their results were compared with the present findings.Realistic NLDs were also obtained through the spectral distribution method(SDM).The cross-section results,along with the absolute errors,were obtained by investigating the uncertainty propagation and using the covariance technique.Corrections forγ-ray true coincidence summing,low-energy background neutrons,andγ-ray self attenuation were performed.The experimental cross-section obtained in the present study is consistent with previously published experimental data,evaluated libraries,and theoretical calculations carried out using the TALYS code.

Comprehensive analysis of uncertainty quantification for the^(58)Ni(n,p)^(58)Co reaction cross section

In this study,we measured the^(58)Ni(n,p)^(58)Co reaction cross section with neutron energies of 1.06,1.86,and 2.85 MeV.The cross section was measured using neutron activation techniques andγ-ray spectroscopy,and it was compared with cross section data available in the EXFOR.Furthermore,we calculated the covariance matrix of the measured cross section for the aforementioned nuclear reaction.The uncertainties of the theoretical calculation for^(58)Ni(n,p)^(58)Co reaction cross section were calculated via Monte Carlo method.In this study,we used uncertainties in the optical model and level density parameters to calculate uncertainties in the theoretical cross sections.The theoretical calculations were performed by using TALYS-1.96.In this study,we aim to analyze the effect of uncertainties of the nuclear model input as well as different experimental variables used to obtain the values of reaction cross section.

Novel data-driven sparse polynomial chaos and analysis of covariance for aerodynamics of compressor cascades with dependent geometric uncertainties

Polynomial Chaos Expansion(PCE)has gained significant popularity among engineers across various engineering disciplines for uncertainty analysis.However,traditional PCE suffers from two major drawbacks.First,the orthogonality of polynomial basis functions holds only for independent input variables,limiting the model’s ability to propagate uncertainty in dependent variables.Second,PCE encounters the"curse of dimensionality"due to the high computational cost of training the model with numerous polynomial coefficients.In practical manufacturing,compressor blades are subject to machining precision limitations,leading to deviations from their ideal geometric shapes.These deviations require a large number of geometric parameters to describe,and exhibit significant correlations.To efficiently quantify the impact of high-dimensional dependent geometric deviations on the aerodynamic performance of compressor blades,this paper firstly introduces a novel approach called Data-driven Sparse PCE(DSPCE).The proposed method addresses the aforementioned challenges by employing a decorrelation algorithm to directly create multivariate basis functions,accommodating both independent and dependent random variables.Furthermore,the method utilizes an iterative Diffeomorphic Modulation under Observable Response Preserving Homotopy regression algorithm to solve the unknown coefficients,achieving model sparsity while maintaining fitting accuracy.Then,the study investigates the simultaneous effects of seven dependent geometric deviations on the aerodynamics of a high subsonic compressor cascade by using the DSPCE method proposed and sensitivity analysis of covariance.The joint distribution of the dependent geometric deviations is determined using Quantile-Quantile plots and normal copula functions based on finite measurement data.The results demonstrate that the correlations between geometric deviations significantly impact the variance of aerodynamic performance and the flow field.Therefore,it is crucial to consider these correlations for accurately assessing the aerodynamic uncertainty.

Analytic Initial Relative Orbit Solution for Angles-Only Space Rendezvous Using Hybrid Dynamics Method

A closed-form solution to the angles-only initial relative orbit determination(IROD)problem for space rendezvous with non-cooperated target is developed,where a method of hybrid dynamics with the concept of virtual formation is introduced to analytically solve the problem.Emphasis is placed on developing the solution based on hybrid dynamics(i.e.,Clohessy-Wiltshire equations and two-body dynamics),obtaining formation geometries that produce relative orbit state observability,and deriving the approximate analytic error covariance for the IROD solution.A standard Monte Carlo simulation system based on two-body dynamics is used to verify the feasibility and evaluate the performance proposed algorithms.The sensitivity of the solution accuracy to the formation geometry,observation numbers is presented and discussed.

Parametric Methods for the Regional Assessment of Cardiac Wall Motion Abnormalities: Comparison Study

Left ventricular(LV)dysfunction is mainly assessed by global contractile indices such as ejection fraction and LV Volumes in cardiac MRI.While these indices give information about the presence or not of LV alteration,they are not able to identify the location and the size of such alteration.The aim of this study is to compare the performance of three parametric imaging techniques used in cardiac MRI for the regional quantification of cardiac dysfunction.The proposed approaches were evaluated on 20 patients with myocardial infarction and 20 subjects with normal function.Three parametric images approaches:covariance analysis,parametric images based on Hilbert transform and those based on the monogenic signal were evaluated using cine-MRI frames acquired in three planes of views.The results show that parametric images generated from the monogenic signal were superior in term of sensitivity(89.69%),specificity(86.51%)and accuracy(89.06%)to those based on covariance analysis and Hilbert transform in the detection of contractile dysfunction related to myocardial infarction.Therefore,the parametric image based on the monogenic signal is likely to provide additional regional indices about LV dysfunction and it may be used in clinical practice as a tool for the analysis of the myocardial alterations.

Geometric precision evaluation methodology of multiple reference station network algorithms

To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.

Closed-loop deep neural network optimal control algorithm and error analysis for powered landing under uncertainties

Real-time guidance is critical for the vertical recovery of rockets.However,traditional sequential convex optimization algorithms suffer from shortcomings in terms of their poor real-time performance.This work focuses on applying the deep learning-based closedloop guidance algorithm and error propagation analysis for powered landing,thereby significantly improving the real-time performance.First,a controller consisting of two deep neural networks is constructed to map the thrust direction and magnitude of the rocket according to the state variables.Thereafter,the analytical transition relationships between different uncertainty sources and the state propagation error in a single guidance period are analyzed by adopting linear covariance analysis.Finally,the accuracy of the proposed methods is verified via a comparison with the indirect method and Monte Carlo simulations.Compared with the traditional sequential convex optimization algorithm,our method reduces the computation time from 75 ms to less than 1 ms.Therefore,it shows potential for online applications.

Factors Related to LGBT Recognition for University Students and Employed Adults

Background: The aim of this study was to investigate Japanese students and employed adults’ characteristic features, and sexual situation, and to find the correlated factors of lesbian, gay, bisexual, transgender (LGBT) recognition in order to obtain suggestions for improved relationships with sexual minorities in a diversifying society. Methods: This quantitative cross-sectional descriptive correlational study occurred during 2018 to 2019 when 2210 questionnaires were distributed to a purposive sample of eligible participants. A total of 1534 completed questionnaires (69.4%) were returned, of which 1439 (65.1%) were suitable for analyses. The survey included respondents’ 1) characteristics, 2) sexual situation, and 3) LGBT recognition scale. Data were analyzed with descriptive statistics, factor analysis, reliability analysis, and structural equation modeling. SPSS ver. 26.0 (SPSS, Chicago, IL, USA) was used for data analysis at a 5% significance level. Results: The LGBT recognition score was significantly affected by suffering from gender identity (standardized partial regression coefficient: β = 0.17, p < 0.001), age (β = −0.19, p < 0.001), learning about LGBT experience (β = 0.29, p < 0.001), experience of disclosure from LGBT person (β = 0.14, p < 0.001), sexual problems with intimate relationship (β = 0.07, p < 0.001), and diversity penetration (β = 0.14, p < 0.05). Conclusions: Suffering from gender identity, learning about LGBT experience, experience of disclosure from LGBT person, sexual problem with intimate relationship, and diversity penetration had a positive effect, whereas age had negative effects on the LGBT recognition score.

Decomposition Method of Genetic Correlation Coefficient Based on NC Ⅱ Mating Design

There are different degrees of correlation between crop traits. The phenotypic correlation is decomposed into genetic and environmental correlation in quantitative genetics. In this paper,according to stochastic model of variance and covariance analysis,we calculate different genetic components,bring up a decomposition method of genetic correlation coefficient based on NC II mating design,and use examples to show analytic steps and interpret results.

Measurement of neutron capture cross section on^(71)Ga at 2.15 and 3.19 MeV and uncertainty propagation and covariance analysis

The cross section values of the^(71)Ga(n,γ)^(72)Ga reaction are measured,which are 9.14±0.81 mb and 5.74±0.50 mb at 2.15 and 3.19 MeV,respectively.The detailed uncertainty propagation and covariance analysis are also given.The^(7)Li(p,n)^(7)Be reaction was used to generate the neutrons,and the neutron flux was normalized using the^(115)In(n,n′)^(115)In^(m)monitor reaction.The measured cross section data are compared with the data available in the EXFOR database,the data obtained using nuclear reaction model codes EMPIRE-3.2 and TALYS-1.95,and also the evaluated nuclear data from ENDF/B-VIII.0 and JEFF-3.1/A.The comparison shows that our result at 3.19 MeV is in good agreement with those of EMPIRE-3.2 and JEFF-3.1/A.Since there are no other measurements available at3.19 MeV,our data could not be compared with literature data at 3.19 MeV,but they are consistent with the cross section values available at 2.98±0.26 and 3.0±0.1 MeV.Our result at 2.15 MeV is slightly higher than the literature value available in EXFOR,evaluated value,and theoretically predicted result.

Covariance analysis of periodic and quasi-periodic orbits around Phobos with applications to the Martian Moons eXploration mission

Understanding the internal composition of a celestial body is fundamental for formulating theories regarding its origin.Deep knowledge of the distribution of mass under the body’s crust can be achieved by analyzing its moments of inertia and gravity field.In this regard,the two moons of the Martian system have not yet been closely studied and continue to pose questions regarding their origin to the space community;thus,they deserve further characterization.The Martian Moons eXploration mission will be the first of its kind to sample and study Phobos over a prolonged period.This study aims to demonstrate that the adoption of periodic and quasi-periodic retrograde trajectories would be beneficial for the scientific value of the mission.Here,a covariance analysis was implemented to compare the estimation of high-order gravitational field coefficients from different orbital geometries and for different sets of processed observables.It was shown that the adoption of low-altitude non-planar quasi-satellite orbits would help to refine the knowledge of the moon’s libration angle and gravitational field.

Measurement of the(n,2n)reaction cross-sections of iodine and cesium induced by D-T neutrons with covariance analysis

The cross-sections of the 127I(n,2n)126I and 133Cs(n,2n)132Cs reactions at neutron energies of 13.83±0.05,14.33±0.10,and 14.79±0.10 MeV were measured relative to the 93Nb(n,2n)92mNb reaction using the activation technique in combination with off-lineγ-ray spectrometry.A neutron beam was generated from the T(d,n)4He reaction using the K-400 neutron generator at the China Academy of Engineering Physics.Considering the correlations between different attributes,detailed uncertainty propagation was performed using covariance analysis,and the cross-sections were reported with their uncertainties and correlation matrix.The uncertainty of the measurement cross-sections ranged from 4.84 to 5.90%,which is lower than previous experimental data.Furthermore,the theoretical excitation functions of the 127I(n,2n)126I and 133Cs(n,2n)132Cs reactions were calculated using the TALYS-1.95 and EMPIRE-3.2.3 codes.Then,the experimentally determined cross-sections were analyzed by comparing them with literature data available in the EXFOR database and evaluated nuclear data in the ENDF/B-VIII.0,JEFF-3.3,JENDL-5,BROND-3.1,CENDL-3.2,and TENDL-2021 databases.Compared with the values previously reported in the 13.8-14.8 MeV energy region,the precision of the results obtained in this study was greatly improved.The current experimental results with thorough uncertainties and covariance information are critical for verifying the reliability of the theoretical model and improving the quality of the nuclear database.

COVARIANCE STRUCTURAL ANALYSIS WITH POLYTOMOUS VARIABLES IN SEVERAL POPULATIONS

In this paper, covariance structures with polytomous variables in several populations are analyzed. A computationally efficient multistage procedure is proposed to estimate the thresholds and the covariance structure parameters.Statistical properties of the estimators are derived, and a computer program is implemented to obtain the solution. An artificial example is presented to illustrate the method.

14.77 MeV neutron-induced nuclear reaction cross sections for zinc,yttrium,and molybdenum targets

The cross sections for neutron-induced nuclear reactions on natural zinc, yttrium, and molybdenum targets were measured at a neutron energy of 14.77 ± 0.17 MeV using the activation technique, offline gamma-ray spectrometry, and a detailed covariance analysis. The uncertainty in the statistical model calculations of cross sections for the (n, 2n), (n, p), (n, α), and (n, γ) reactions with natural zinc, yttrium, and molybdenum at neutron energies from 13 to 17 MeV was calculated using the TALYS-1.96 nuclear code. The measured cross sections of the present study were compared with the experimental cross sections reported in the EXFOR database, the cross sections were calculated with the TALYS-1.96 and EMPIRE-3.2.3 nuclear codes and the evaluated nuclear data from the TENDL-2019, JENDL-5, and ENDF/B-VIII.0 libraries.

New cross-section measurements for the (n, 2n), (n, p), and (n, a) reactions on bromine in the 14 MeV region with detailed uncertainty quantification

Measurement of the cross-sections of the ^(79)Br(n,2n)^(78)Br,^(81)Br(n,p)^(81)mSe,^(81)Br(n,α)^(78)As,and ^(79)Br(n,α)^(76)As reactions was performed at specific neutron energies,precisely,13.5±0.2,14.1±0.2,14.4±0.2,and 14.8±0.2 MeV,relative to the standard ^(93)Nb(n,2n)^(92)mNb and ^(27)Al(n,α)^(24)Na reference reactions using offlineγ-ray spectrometry and neutron activation.Monoenergetic neutrons were generated at the China Academy of Engineering Physics via a ^(3)H(d,n)^(4)He reaction using the K-400 Neutron Generator equipped with a solid ^(3)H-Ti based target.The activity of the reaction produce was obtained using a high-purity germanium detector.The cross-sections of the(n,2n),(n,p),and(n,α)reactions on the bromine isotopes were measured in the 13–15 MeV neutron energy range.The covariance analysis approach was employed for a thorough inspection of any uncertainties within the measured cross-section data.A discussion and comparison of the observed outcome were carried out with previously published data,especially with the results of the JENDL-4.0,JEFF-3.3,TENDL-2019,and ENDF/B-VIII.0 data libraries,along with the theoretical excitation function curve derived by employing the TALYS-1.95 program.Improved cross-section restrictions for the investigated processes in the 13–15 MeV neutron energy range will be obtained using the current findings,which will help to raise the caliber of associated databases.Furthermore,the parameters of relevant nuclear reaction models can be verified using this data.

Perception of people for the risk of Tianwan nuclear power plant

A questionnaire survey of residents’risk perceptions related to Taiwan nuclear power plant in China was carried out to explore the determining factors that affect individual risk perception.This study proposed to pursue a more comprehensive understanding of factors that affected individual risk perception to nuclear power plants.Covariance structure analysis was conducted using risk perceptions of nuclear power as dependent variable and including interest and knowledge levels of nuclear power,acceptability,benefit perception,trust in nuclear power operation,and trust in government as independent variables.The use of the hypothesis of Elaboration likelihood model(ELM)was also proposed.The results showed that persons with higher levels of interest and knowledge of nuclear power had their own perceptions of risk closely associated with acceptability and potential benefits of nuclear power.In contrast,persons with no interest in and knowledge of nuclear power would have risk perceptions related to their trust in nuclear operation and the government,which partially supported the ELM hypothesis.All these results indicated that the government in China plays an important role in rational risk perceptions,and well-designed communication of risks will help the public to be involved in risk management and improve people’s rational acceptance of risk.