scholarly journals Forecasting algorithm of tourism service trade based on PSO-optimized hybrid RVM model

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiaoying Dong ◽  
Xuanjun Chen
Keyword(s):  
Search Algorithm ◽  
Principal Component ◽  
Average Error ◽  
Prediction Errors ◽  
Service Trade ◽  
Total Import ◽  
Forecast Result ◽  
Import And Export ◽  
Tourism Service ◽  
The Impact

AbstractAs a comprehensive form of trade, tourism service trade has had a profound impact on the economies of various countries. This research mainly discusses the tourism service trade forecasting algorithm based on the PSO-optimized hybrid RVM model. This study extracts 8 indicators including gross national product, total fixed asset investment, total import and export, China's import and export tariff rate, the exchange rate of renminbi to the US dollar, and the global economic growth rate. The same as the impact indicators of tourism service trade, but there is a certain degree of redundancy and correlation in these indicators. In order to measure the correlation between the evaluation indicators, the autocorrelation evaluation function in MATLAB is used, and the principal component analysis method is used to extract the principal components that can represent the indicators in a larger percentage. In order to improve the prediction accuracy of the RVM model, based on the adaptive construction model structure and initial model weights, the PSO algorithm is used to optimize the RVM model weights. The optimization process takes the minimum error of the RVM model as the algorithm search target, and each represents the RVM model. The algorithm finds the value and threshold of the optimal RVM model through the particle swarm tracking search algorithm and then uses the original RVM model and the optimized RVM prediction respectively total amount of tourism service trade in City A, and compares the prediction errors of the single RVM method and the PSO-optimized RVM method, and analyzes the degree of model prediction error reduction after the PSO model optimizes the RVM model. According to the forecast result, the relative average error of 2020 is 5.7%, and the forecast result is relatively accurate. This research is helpful to provide scientific reference for my country's tourism service trade.

A comparison among approaches for recommending learning objects through collaborative filtering algorithms

2017 ◽  
Vol 51 (1) ◽  
pp. 35-51
Author(s):  
Henrique Lemos dos Santos ◽  
Cristian Cechinel ◽  
Ricardo Matsumura Araújo
Keyword(s):  
Collaborative Filtering ◽  
Learning Objects ◽  
Learning Goals ◽  
Average Error ◽  
Neighborhood Size ◽  
Relevant Parameter ◽  
Prediction Errors ◽  
Content Type ◽  
User Coverage ◽  
The Impact

Purpose The purpose of this paper is to present the results of a comparison among three different approaches for recommending learning objects (LO) inside a repository. The comparison focuses not only on prediction errors but also on the coverage of each tested configuration. Design/methodology/approach The authors compared the offline evaluation by using pure collaborative filtering (CF) algorithms with two other different combinations of pre-processed data. The first approach for pre-processing data consisted of clustering users according to their disciplines resemblance, while the second approach consisted of clustering LO according to their textual similarity regarding title and description. The three methods were compared with respect to the mean average error between predicted values and real values. Moreover, we evaluated the impact of the number of clusters and neighborhood size on the user-coverage. Findings Clustering LO has improved the prediction error measure with a small loss on user-coverage when compared to the pure CF approach. On the other hand, the approach of clustering users failed in both the error and in user-space coverage. It also became clear that the neighborhood size is the most relevant parameter to determine how large the coverage will be. Research limitations The methods proposed here were not yet evaluated in a real-world scenario, with real users opinions about the recommendations and their respective learning goals. Future work is still required to evaluate users opinions. Originality/value This research provides evidence toward new recommendation methods directed toward LO repositories.

The Impact of Shariah Governance and Corporate Governance on the Risk Management Practices: Evidence from Local and Foreign Islamic Banks in Malaysia

2018 ◽  
Vol 15 (2) ◽  
pp. 1-20
Author(s):  
Sabri Embi ◽  
Zurina Shafii
Keyword(s):  
Risk Management ◽  
Corporate Governance ◽  
Management Practices ◽  
Principal Component ◽  
T Test ◽  
The Body ◽  
Primary Data ◽  
Islamic Banks ◽  
Shariah Governance ◽  
The Impact

The purpose of this study is to examine the impact of Shariah governance and corporate governance (CG) on the risk management practices (RMPs) of local Islamic banks and foreign Islamic banks operating in Malaysia. The Shariah governance comprises the Shariah review (SR) and Shariah audit (SA) variables. The study also evaluates the level of RMPs, CG, SR, and SA between these two type of banks. With the aid of SPSS version 20, the items for RMPs, CG, SR, and SA were subjected to principal component analysis (PCA). From the PCA, one component or factor was extracted each for the CG, SR, and RMPs while another two factors were extracted for the SA. Primary data was collected using a self-administered survey questionnaire. The questionnaire covers four aspects ; CG, SR, SA, and RMPs. The data received from the 300 usable questionnaires were subjected to correlation and regression analyses as well as an independent t-test. The result of correlation analysis shows that all the four variables have large positive correlations with each other indicating a strong and significant relationship between them. From the regression analysis undertaken, CG, SR, and SA together explained 52.3 percent of the RMPs and CG emerged as the most influential variable that impacts the RMPs. The independent t-test carried out shows that there were significant differences in the CG and SA between the local and foreign Islamic banks. However, there were no significant differences between the two types of the bank in relation to SR and RMPs. The study has contributed to the body of knowledge and is beneficial to academicians, industry players, regulators, and other stakeholders.

Tracking the Transmission Channels of Fiscal Deficit and Food Inflation Linkages: A Structural VAR Approach

2020 ◽  
pp. 165-172
Keyword(s):  
Positive Impact ◽  
Structural Var ◽  
Fiscal Deficit ◽  
Agricultural Industry ◽  
Vector Autoregressive ◽  
Transmission Channels ◽  
Government Deficit ◽  
Import And Export ◽  
The Impact ◽  
Food Inflation

This empirical analysis aspired to unearth the transmission channels of fiscal deficit and food inflation linkages in the Indian perspective by reasonably exerting the data for 1991 to 2017. The precise results of structural vector autoregressive (SVAR) analysis proffered that there were three different mechanisms of transmission such as consumption, general inflation, and import channels that led to food inflation in response to the high fiscal deficit. The first channel revealed that government deficit spending had a positive impact on income which further led to food inflation through surging the household consumption expenditure. It was concluded that fiscal deficit passed through general inflation finally leading to a food price surge in the economy and seemed to work as cost-push inflation for the food and agricultural industry. The outcome also revealed that the impact of fiscal deficit passed to food inflation through external linkages such as import and export.

Evaluation of the Aging Behavior of High Density Polyethylene in Thermal Oxidative Environment by Principal Component Analysis

2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo
Keyword(s):  
Principal Component Analysis ◽  
Impact Strength ◽  
High Density Polyethylene ◽  
Tensile Modulus ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Aging Behavior ◽  
Data Set ◽  
The Impact

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.

scholarly journals Inheritable testicular metabolic memory of high-fat diet causes transgenerational sperm defects in mice

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Luís Crisóstomo ◽  
Ivana Jarak ◽  
Luís P. Rato ◽  
João F. Raposo ◽  
Rachel L. Batterham ◽  
...  
Keyword(s):  
Sperm Quality ◽  
Feeding Habits ◽  
Reproductive Function ◽  
Principal Component ◽  
Testicular Tissue ◽  
Sperm Parameters ◽  
Metabolic Memory ◽  
High Fat ◽  
And Function ◽  
The Impact

AbstractThe consumption of energy-dense diets has contributed to an increase in the prevalence of obesity and its comorbidities worldwide. The adoption of unhealthy feeding habits often occurs at early age, prompting the early onset of metabolic disease with unknown consequences for reproductive function later in life. Recently, evidence has emerged regarding the intergenerational and transgenerational effects of high-fat diets (HFD) on sperm parameters and testicular metabolism. Hereby, we study the impact of high-fat feeding male mice (F0) on the testicular metabolome and function of their sons (F1) and grandsons (F2). Testicular content of metabolites related to insulin resistance, cell membrane remodeling, nutritional support and antioxidative stress (leucine, acetate, glycine, glutamine, inosine) were altered in sons and grandsons of mice fed with HFD, comparing to descendants of chow-fed mice. Sperm counts were lower in the grandsons of mice fed with HFD, even if transient. Sperm quality was correlated to testicular metabolite content in all generations. Principal Component Analysis of sperm parameters and testicular metabolites revealed an HFD-related phenotype, especially in the diet-challenged generation and their grandsons. Ancestral HFD, even if transient, causes transgenerational “inherited metabolic memory” in the testicular tissue, characterized by changes in testicular metabolome and function.

scholarly journals The Effect of Fat Content and Fatty Acids Composition on Color and Textural Properties of Butter

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4565
Author(s):  
Sergiu Pădureţ
Keyword(s):  
Fatty Acids ◽  
Principal Component ◽  
Textural Properties ◽  
Fat Content ◽  
Fatty Acids Composition ◽  
Color Parameter ◽  
Butter Fat ◽  
Composition Variation ◽  
Texture Parameters ◽  
The Impact

The textural properties of butter are influenced by its fat content and implicitly by the fatty acids composition. The impact of butter’s chemical composition variation was studied in accordance with texture and color properties. From 37 fatty acids examined, only 18 were quantified in the analyzed butter fat samples, and approximately 69.120% were saturated, 25.482% were monounsaturated, and 5.301% were polyunsaturated. The butter samples’ viscosity ranged between 0.24 and 2.12 N, while the adhesiveness ranged between 0.286 to 18.19 N·mm. The principal component analysis (PCA) separated the butter samples based on texture parameters, fatty acids concentration, and fat content, which were in contrast with water content. Of the measured color parameters, the yellowness b* color parameter is a relevant indicator that differentiated the analyzed sample into seven statistical groups; the ANOVA statistics highlighted this difference at a level of p < 0.001.

scholarly journals Exploring Residents’ Perceptions of the Socio-Cultural Benefits of Tourism Development in the Mountain Area

Societies ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 83
Author(s):  
Iulia C. Muresan ◽  
Rezhen Harun ◽  
Felix H. Arion ◽  
Ava Omar Fatah ◽  
Diana E. Dumitras
Keyword(s):  
Positive Attitude ◽  
Statistical Tests ◽  
Tourism Development ◽  
Principal Component ◽  
Local Communities ◽  
Three Dimensions ◽  
Development Economic ◽  
Mountain Area ◽  
Sustainable Tourism Development ◽  
The Impact

Development of tourism affected the socio-cultural environment of many destinations. Previous studies have focused more on analyzing the impact of tourism on all three dimensions of sustainable development (economic, environment and socio-cultural); therefore, the present paper examines tourism development’s impact with regard to the socio-cultural benefits that enhance sustainable tourism development. A survey based on a questionnaire was employed in June 2018 in a mountain village in Cluj County, Romania. The collected data were analyzed using principal component analysis, and several statistical tests were conducted. The results indicated that the respondents have a positive attitude towards tourism development and socio-cultural perceived benefits. Older people and those running a business tend to perceive more positively the benefits of tourism development. The findings of the research could contribute to future development strategies, as it is well known that supporting local communities influences the success of tourism destination.

scholarly journals Grill Workers Exposure to Polycyclic Aromatic Hydrocarbons: Levels and Excretion Profiles of the Urinary Biomarkers

2020 ◽  
Vol 18 (1) ◽  
pp. 230
Author(s):  
Marta Oliveira ◽  
Sílvia Capelas ◽  
Cristina Delerue-Matos ◽  
Simone Morais
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
High Performance ◽  
Principal Component ◽  
Fold Increase ◽  
Urinary Biomarkers ◽  
Analysis Model ◽  
Exposed Workers ◽  
Polycyclic Aromatic ◽  
The Impact

Grilling activities release large amounts of hazardous pollutants, but information on restaurant grill workers’ exposure to polycyclic aromatic hydrocarbons (PAHs) is almost inexistent. This study assessed the impact of grilling emissions on total workers’ exposure to PAHs by evaluating the concentrations of six urinary biomarkers of exposure (OHPAHs): naphthalene, acenaphthene, fluorene, phenanthrene, pyrene, and benzo(a)pyrene. Individual levels and excretion profiles of urinary OHPAHs were determined during working and nonworking periods. Urinary OHPAHs were quantified by high-performance liquid-chromatography with fluorescence detection. Levels of total OHPAHs (∑OHPAHs) were significantly increased (about nine times; p ≤ 0.001) during working comparatively with nonworking days. Urinary 1-hydroxynaphthalene + 1-hydroxyacenapthene and 2-hydroxyfluorene presented the highest increments (ca. 23- and 6-fold increase, respectively), followed by 1-hydroxyphenanthrene (ca. 2.3 times) and 1-hydroxypyrene (ca. 1.8 times). Additionally, 1-hydroxypyrene levels were higher than the benchmark, 0.5 µmol/mol creatinine, in 5% of exposed workers. Moreover, 3-hydroxybenzo(a)pyrene, biomarker of exposure to carcinogenic PAHs, was detected in 13% of exposed workers. Individual excretion profiles showed a cumulative increase in ∑OHPAHs during consecutive working days. A principal component analysis model partially discriminated workers’ exposure during working and nonworking periods showing the impact of grilling activities. Urinary OHPAHs were increased in grill workers during working days.

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