The manufacturing industry is an important pillar of the national economy.It is of vital importance to develop statistical modellings in order to quantify the relationship between potential internal drivers and the tr...The manufacturing industry is an important pillar of the national economy.It is of vital importance to develop statistical modellings in order to quantify the relationship between potential internal drivers and the trend of output values in the manufacturing industry.However,only a few statistical modellings have been established to investigate such associations.This study developed the correlation coefficient model and generalized linear model(GLM)to measure the single and interactive effects of the internal drivers on the changes of the output values.For the GLM,different predictive variables were developed to fit into the dataset,and the performance of the models were compared using fitness parameters.Furthermore,an industry survey dataset for 1,180 manufacturing enterprises in 2020 was used to validate the models.The use of the GLM combining land area,number of employees,scientific research input,and labor productivity may have a great potential to bolster capacity in monitoring and predicting the trend of output values in the manufacture industry.展开更多
The influence of non-uniqueness in selecting statistical time ranges on seismicity parameters of b value and annual mean occurrence rate ν4 is widely analyzed and studied. The studied result states that the influence...The influence of non-uniqueness in selecting statistical time ranges on seismicity parameters of b value and annual mean occurrence rate ν4 is widely analyzed and studied. The studied result states that the influence of statistical time range on the b value is generally smaller than on the annual mean rate. Owing to the exponentially functional relation between the annual mean rate and b value, the variation of b value by varying statistical time range brings about decrease or increase in the annual mean rates of each magnitude interval with power progression law. These results will exert a synthetic effect on seismic safety evaluation results in various regions in our country.展开更多
Empirical research was done interviewing face to face a sample of 2,447, 10-12 grade students in Culiacan, Sinaloa, Mexico, from the main public university high school in town. Education is seen as a tool to develop b...Empirical research was done interviewing face to face a sample of 2,447, 10-12 grade students in Culiacan, Sinaloa, Mexico, from the main public university high school in town. Education is seen as a tool to develop better citizens first, and better workers later. The objective of this research was to detect different perceptions related to values and education. Using a 13 items questionnaire, we measured： Students＇ perceptions about him/herself as part of their education role, responsibility that students show toward activities m school, perceptions about education as a tool to grow in the social ladder and as a way of social recognition, social perception about effort as an important value to self-improve and get social recognition, and to finish, perceptions about their teacher＇s performance.展开更多
Most real application processes belong to a complex nonlinear system with incomplete information. It is difficult to estimate a model by assuming that the data set is governed by a global model. Moreover, in real proc...Most real application processes belong to a complex nonlinear system with incomplete information. It is difficult to estimate a model by assuming that the data set is governed by a global model. Moreover, in real processes, the available data set is usually obtained with missing values. To overcome the shortcomings of global modeling and missing data values, a new modeling method is proposed. Firstly, an incomplete data set with missing values is partitioned into several clusters by a K-means with soft constraints （KSC） algorithm, which incorporates soft constraints to enable clustering with missing values. Then a local model based on each group is developed by using SVR algorithm, which adopts a missing value insensitive （MVI） kernel to investigate the missing value estimation problem. For each local model, its valid area is gotten as well. Simulation results prove the effectiveness of the current local model and the estimation algorithm.展开更多
In an effort to cope with the fact that functional magnetic resonance imaging (fMRI) data are spatiotemporally correlated, we propose a novel statistical method with a view to improve the detection of brain regions wi...In an effort to cope with the fact that functional magnetic resonance imaging (fMRI) data are spatiotemporally correlated, we propose a novel statistical method with a view to improve the detection of brain regions with increased neu-ronal activity in fMRI. In this method, we make use of information from neighboring voxels of a voxel, for estimation at the voxel. We examined performance of the method against the statistical parametric mapping (SPM) method using both simulated and real data. The proposed method is shown to be considerably better than the SPM in the context of receiver operating characteristics (ROC) curves.展开更多
Based on the continuous development of motion capture technology for ordinary video images, unmarked optical motion capture has become the fastest human posture recognition technology. Compared with other technical pr...Based on the continuous development of motion capture technology for ordinary video images, unmarked optical motion capture has become the fastest human posture recognition technology. Compared with other technical products, Google’s 3D human body recognition framework—Mediapipe is the most mature representative in this field. However, Mediapipe also has many defects in the detection of 3D human posture. In this paper, firstly, to solve the problem of inaccurate detection of human posture by Mediapipe, the accuracy of 2D human posture detection is improved through the speed threshold correction method for each joint;According to the problem that the monocular camera can not detect the depth Z value in the human posture data accurately, the Z value of the joint point is corrected for the human tilt angle through statistics;Then, according to the inaccurate recognition of Z value caused by large body posture, the accurate correction of Z value of human posture under different body posture is realized by normalizing the simulation proportion of each body limb;Finally, in order to solve the problem of jitter, lag problem and periodic noise in multiple frames caused by the speed change of human joints, one euro filtering and mean filtering of joint data are carried out. This paper verifies that the accuracy of 3D human posture detection based on the improved Mediapipe is more than 90% through the multi-pose recognition test for people of different heights, weights, ages and gender.展开更多
文摘The manufacturing industry is an important pillar of the national economy.It is of vital importance to develop statistical modellings in order to quantify the relationship between potential internal drivers and the trend of output values in the manufacturing industry.However,only a few statistical modellings have been established to investigate such associations.This study developed the correlation coefficient model and generalized linear model(GLM)to measure the single and interactive effects of the internal drivers on the changes of the output values.For the GLM,different predictive variables were developed to fit into the dataset,and the performance of the models were compared using fitness parameters.Furthermore,an industry survey dataset for 1,180 manufacturing enterprises in 2020 was used to validate the models.The use of the GLM combining land area,number of employees,scientific research input,and labor productivity may have a great potential to bolster capacity in monitoring and predicting the trend of output values in the manufacture industry.
基金Chinese Joint Seismological Science Foundation (100110).
文摘The influence of non-uniqueness in selecting statistical time ranges on seismicity parameters of b value and annual mean occurrence rate ν4 is widely analyzed and studied. The studied result states that the influence of statistical time range on the b value is generally smaller than on the annual mean rate. Owing to the exponentially functional relation between the annual mean rate and b value, the variation of b value by varying statistical time range brings about decrease or increase in the annual mean rates of each magnitude interval with power progression law. These results will exert a synthetic effect on seismic safety evaluation results in various regions in our country.
文摘Empirical research was done interviewing face to face a sample of 2,447, 10-12 grade students in Culiacan, Sinaloa, Mexico, from the main public university high school in town. Education is seen as a tool to develop better citizens first, and better workers later. The objective of this research was to detect different perceptions related to values and education. Using a 13 items questionnaire, we measured： Students＇ perceptions about him/herself as part of their education role, responsibility that students show toward activities m school, perceptions about education as a tool to grow in the social ladder and as a way of social recognition, social perception about effort as an important value to self-improve and get social recognition, and to finish, perceptions about their teacher＇s performance.
基金supported by Key Discipline Construction Program of Beijing Municipal Commission of Education (XK10008043)
文摘Most real application processes belong to a complex nonlinear system with incomplete information. It is difficult to estimate a model by assuming that the data set is governed by a global model. Moreover, in real processes, the available data set is usually obtained with missing values. To overcome the shortcomings of global modeling and missing data values, a new modeling method is proposed. Firstly, an incomplete data set with missing values is partitioned into several clusters by a K-means with soft constraints （KSC） algorithm, which incorporates soft constraints to enable clustering with missing values. Then a local model based on each group is developed by using SVR algorithm, which adopts a missing value insensitive （MVI） kernel to investigate the missing value estimation problem. For each local model, its valid area is gotten as well. Simulation results prove the effectiveness of the current local model and the estimation algorithm.
文摘In an effort to cope with the fact that functional magnetic resonance imaging (fMRI) data are spatiotemporally correlated, we propose a novel statistical method with a view to improve the detection of brain regions with increased neu-ronal activity in fMRI. In this method, we make use of information from neighboring voxels of a voxel, for estimation at the voxel. We examined performance of the method against the statistical parametric mapping (SPM) method using both simulated and real data. The proposed method is shown to be considerably better than the SPM in the context of receiver operating characteristics (ROC) curves.
文摘Based on the continuous development of motion capture technology for ordinary video images, unmarked optical motion capture has become the fastest human posture recognition technology. Compared with other technical products, Google’s 3D human body recognition framework—Mediapipe is the most mature representative in this field. However, Mediapipe also has many defects in the detection of 3D human posture. In this paper, firstly, to solve the problem of inaccurate detection of human posture by Mediapipe, the accuracy of 2D human posture detection is improved through the speed threshold correction method for each joint;According to the problem that the monocular camera can not detect the depth Z value in the human posture data accurately, the Z value of the joint point is corrected for the human tilt angle through statistics;Then, according to the inaccurate recognition of Z value caused by large body posture, the accurate correction of Z value of human posture under different body posture is realized by normalizing the simulation proportion of each body limb;Finally, in order to solve the problem of jitter, lag problem and periodic noise in multiple frames caused by the speed change of human joints, one euro filtering and mean filtering of joint data are carried out. This paper verifies that the accuracy of 3D human posture detection based on the improved Mediapipe is more than 90% through the multi-pose recognition test for people of different heights, weights, ages and gender.
