The effects of socio-demographics, land use characteristics and trip attributes on the commute mode choice are studied with a nested logit （NL） model. Based on the random utility maximum theory, the NL model is form...The effects of socio-demographics, land use characteristics and trip attributes on the commute mode choice are studied with a nested logit （NL） model. Based on the random utility maximum theory, the NL model is formulated. The analysis is carried out in the main area of Nanjing. Direct and cross elasticities are calculated to analyze the effects of travel time and travel cost on the selection of travel mode choice. The results reveal that the non-motorized travel modes are more attractive in the areas with higher housing and employment accessibility and car owners are found to be more likely to commute to work by car. The bus and subway choice probabilities are more sensitive to changes in travel times than to changes in travel costs. In conclusion, a comprehensive public transit system and effective integration of land use and transportation policies help to relieve the traffic congestion levels caused by the increasing urban sprawl.展开更多
An improved Gaussian mixture model （GMM）- based clustering method is proposed for the difficult case where the true distribution of data is against the assumed GMM. First, an improved model selection criterion, the ...An improved Gaussian mixture model （GMM）- based clustering method is proposed for the difficult case where the true distribution of data is against the assumed GMM. First, an improved model selection criterion, the completed likelihood minimum message length criterion, is derived. It can measure both the goodness-of-fit of the candidate GMM to the data and the goodness-of-partition of the data. Secondly, by utilizing the proposed criterion as the clustering objective function, an improved expectation- maximization （EM） algorithm is developed, which can avoid poor local optimal solutions compared to the standard EM algorithm for estimating the model parameters. The experimental results demonstrate that the proposed method can rectify the over-fitting tendency of representative GMM-based clustering approaches and can robustly provide more accurate clustering results.展开更多
Flotation is a complex multifaceted process that is widely used for the separation of finely ground minerals. The theory of froth flotation is complex and is not completely understood. This fact has been brought many ...Flotation is a complex multifaceted process that is widely used for the separation of finely ground minerals. The theory of froth flotation is complex and is not completely understood. This fact has been brought many monitoring challenges in a coal processing plant. To solve those challenges, it is important to understand the effect of different parameters on the fine particle separation, and control flotation performance for a particular system. This study is going to indicate the effect of various parameters （particle Characteristics and hydrodynamic conditions） on coal flotation responses （flotation rate constant and recovery） by different modeling techniques. A comprehensive coal flotation database was prepared for the statistical and soft computing methods. Statistical factors were used for variable selections. Results were in a good agreement with recent theoretical flotation investigations. Computational models accurately can estimate flotation rate constant and coal recovery （correlation coefficient 0.85, and 0.99, respectively）. According to the results, it can be concluded that the soft computing models can overcome the complexity of process and be used as an expert system to control, and optimize parameters of coal flotation process.展开更多
Although, researchers in the ATC field have done a wide range of work based on SVM, almost all existing approaches utilize an empirical model of selection algorithms. Their attempts to model automatic selection in pra...Although, researchers in the ATC field have done a wide range of work based on SVM, almost all existing approaches utilize an empirical model of selection algorithms. Their attempts to model automatic selection in practical, large-scale, text classification systems have been limited. In this paper, we propose a new model selection algorithm that utilizes the DDAG learning architecture. This architecture derives a new large-scale text classifier with very good performance. Experimental results show that the proposed algorithm has good efficiency and the necessary generalization capability while handling large-scale multi-class text classification tasks.展开更多
Beneficiation of coal of -4.76 mm + 3 mm size fraction was investigated in a laboratory model Denver jig.Process variables were studied to analyze their effect on the performance of jig in terms of yield and ash conte...Beneficiation of coal of -4.76 mm + 3 mm size fraction was investigated in a laboratory model Denver jig.Process variables were studied to analyze their effect on the performance of jig in terms of yield and ash content of clean coal. Three-factor three-level Box-Behnken design of experiments with response surface methodology(RSM) was employed to understand the performance behavior of jig. From the study, the bed height was found to be the most significant parameter affecting the yield and ash content of clean coal. It was possible to reduce the ash content from 24.32% in feed to an ash content of 16.55% in clean coal at 2 L/min water flow rate and 10 min jigging time. Influence of operating variables of the jig on responses was presented and discussed in 3D surface plots. The developed model was found to be significant within the range of parameters under investigation with correlation of co-efficient values as 0.99(yield) and 0.98(ash).展开更多
Using autocorrelation information of the pseudorange errors generated by se- lective availability (SA) frequency dithering, we have constructed a simple first order stochas- tic model for SA effects. This model has be...Using autocorrelation information of the pseudorange errors generated by se- lective availability (SA) frequency dithering, we have constructed a simple first order stochas- tic model for SA effects. This model has been used in a Kalman filter to account for the stochastic behavior of SA dithering in estimating satellite clock information in wide area dif- ferential GPS. We have obtained fifteen percent improvement in the user positioning using the correlation information on the satellite clock information in a Kalman filter, when comparing the results obtained using a regular least square estimation.展开更多
The paper describes information technologies （IT） role in organization---especially its influence on organizational structure. Article concerns the importance of analyzing IT acceptance, while describing IT in organ...The paper describes information technologies （IT） role in organization---especially its influence on organizational structure. Article concerns the importance of analyzing IT acceptance, while describing IT in organization and points out that inadequate variable choice may influence validity of IT analysis. First part of the article describes both variables analyzed in presented research--IT dissemination and IT acceptance. It also presents how in theory IT can influence organizational structure. The main part of the article describes empirical studies conducted in order to verify if the influence of IT on the organizational structure exists. First, the main goal and methodology of the empirical studies are presented. Variables used to assess IT and organizational structure in organizations are discussed. Then, there is a description of research results--statistical correlation between analyzed variables and regression models is shown. Conclusion of the article is that IT can influence organizational structure, but the most important factor ensuring this influence is the actual use of IT by employees of the organization--their access to IT is not enough.展开更多
On the basis of the float-and-sink analysis and the timed-release analysis, a new theoretical floatability curve of coal has been advanced. By means of fitting to a lot of data, a model of theoretical floatability cur...On the basis of the float-and-sink analysis and the timed-release analysis, a new theoretical floatability curve of coal has been advanced. By means of fitting to a lot of data, a model of theoretical floatability curve has been set up. The characteristics of curve and how to achieve standardization were discussed.展开更多
A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The pre...A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The predicted data are used to draw washability curves and to provide a rapid evaluation of the effect from heavy medium induced separation.Thirty-one production shifts worth of fast float/sink data and the corresponding quick ash data are used to verify the model.The results show a small error with an arithmetic average of 0.53 and an absolute average error of 1.50.This indicates that this model has high precision.The theoretical yield from the washability curves is 76.47% for the monthly comprehensive data and 81.31% using the model data.This is for a desired cleaned coal ash of 9%.The relative error between these two is 6.33%,which is small and indicates that the predicted data can be used to rapidly evaluate the separation effect of gravity separation equipment.展开更多
We propose a two-step variable selection procedure for censored quantile regression with high dimensional predictors. To account for censoring data in high dimensional case, we employ effective dimension reduction and...We propose a two-step variable selection procedure for censored quantile regression with high dimensional predictors. To account for censoring data in high dimensional case, we employ effective dimension reduction and the ideas of informative subset idea. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. Simulation study and real data analysis are conducted to evaluate the finite sample performance of the proposed approach.展开更多
基金The National Natural Science Foundation of China(No.50908051)
文摘The effects of socio-demographics, land use characteristics and trip attributes on the commute mode choice are studied with a nested logit （NL） model. Based on the random utility maximum theory, the NL model is formulated. The analysis is carried out in the main area of Nanjing. Direct and cross elasticities are calculated to analyze the effects of travel time and travel cost on the selection of travel mode choice. The results reveal that the non-motorized travel modes are more attractive in the areas with higher housing and employment accessibility and car owners are found to be more likely to commute to work by car. The bus and subway choice probabilities are more sensitive to changes in travel times than to changes in travel costs. In conclusion, a comprehensive public transit system and effective integration of land use and transportation policies help to relieve the traffic congestion levels caused by the increasing urban sprawl.
基金The National Natural Science Foundation of China(No.61105048,60972165)the Doctoral Fund of Ministry of Education of China(No.20110092120034)+2 种基金the Natural Science Foundation of Jiangsu Province(No.BK2010240)the Technology Foundation for Selected Overseas Chinese Scholar,Ministry of Human Resources and Social Security of China(No.6722000008)the Open Fund of Jiangsu Province Key Laboratory for Remote Measuring and Control(No.YCCK201005)
文摘An improved Gaussian mixture model （GMM）- based clustering method is proposed for the difficult case where the true distribution of data is against the assumed GMM. First, an improved model selection criterion, the completed likelihood minimum message length criterion, is derived. It can measure both the goodness-of-fit of the candidate GMM to the data and the goodness-of-partition of the data. Secondly, by utilizing the proposed criterion as the clustering objective function, an improved expectation- maximization （EM） algorithm is developed, which can avoid poor local optimal solutions compared to the standard EM algorithm for estimating the model parameters. The experimental results demonstrate that the proposed method can rectify the over-fitting tendency of representative GMM-based clustering approaches and can robustly provide more accurate clustering results.
文摘Flotation is a complex multifaceted process that is widely used for the separation of finely ground minerals. The theory of froth flotation is complex and is not completely understood. This fact has been brought many monitoring challenges in a coal processing plant. To solve those challenges, it is important to understand the effect of different parameters on the fine particle separation, and control flotation performance for a particular system. This study is going to indicate the effect of various parameters （particle Characteristics and hydrodynamic conditions） on coal flotation responses （flotation rate constant and recovery） by different modeling techniques. A comprehensive coal flotation database was prepared for the statistical and soft computing methods. Statistical factors were used for variable selections. Results were in a good agreement with recent theoretical flotation investigations. Computational models accurately can estimate flotation rate constant and coal recovery （correlation coefficient 0.85, and 0.99, respectively）. According to the results, it can be concluded that the soft computing models can overcome the complexity of process and be used as an expert system to control, and optimize parameters of coal flotation process.
文摘Although, researchers in the ATC field have done a wide range of work based on SVM, almost all existing approaches utilize an empirical model of selection algorithms. Their attempts to model automatic selection in practical, large-scale, text classification systems have been limited. In this paper, we propose a new model selection algorithm that utilizes the DDAG learning architecture. This architecture derives a new large-scale text classifier with very good performance. Experimental results show that the proposed algorithm has good efficiency and the necessary generalization capability while handling large-scale multi-class text classification tasks.
文摘Beneficiation of coal of -4.76 mm + 3 mm size fraction was investigated in a laboratory model Denver jig.Process variables were studied to analyze their effect on the performance of jig in terms of yield and ash content of clean coal. Three-factor three-level Box-Behnken design of experiments with response surface methodology(RSM) was employed to understand the performance behavior of jig. From the study, the bed height was found to be the most significant parameter affecting the yield and ash content of clean coal. It was possible to reduce the ash content from 24.32% in feed to an ash content of 16.55% in clean coal at 2 L/min water flow rate and 10 min jigging time. Influence of operating variables of the jig on responses was presented and discussed in 3D surface plots. The developed model was found to be significant within the range of parameters under investigation with correlation of co-efficient values as 0.99(yield) and 0.98(ash).
基金Project Supported by the Hong Kong Polytechnic University Research Grand(No. 353/392
文摘Using autocorrelation information of the pseudorange errors generated by se- lective availability (SA) frequency dithering, we have constructed a simple first order stochas- tic model for SA effects. This model has been used in a Kalman filter to account for the stochastic behavior of SA dithering in estimating satellite clock information in wide area dif- ferential GPS. We have obtained fifteen percent improvement in the user positioning using the correlation information on the satellite clock information in a Kalman filter, when comparing the results obtained using a regular least square estimation.
文摘The paper describes information technologies （IT） role in organization---especially its influence on organizational structure. Article concerns the importance of analyzing IT acceptance, while describing IT in organization and points out that inadequate variable choice may influence validity of IT analysis. First part of the article describes both variables analyzed in presented research--IT dissemination and IT acceptance. It also presents how in theory IT can influence organizational structure. The main part of the article describes empirical studies conducted in order to verify if the influence of IT on the organizational structure exists. First, the main goal and methodology of the empirical studies are presented. Variables used to assess IT and organizational structure in organizations are discussed. Then, there is a description of research results--statistical correlation between analyzed variables and regression models is shown. Conclusion of the article is that IT can influence organizational structure, but the most important factor ensuring this influence is the actual use of IT by employees of the organization--their access to IT is not enough.
文摘On the basis of the float-and-sink analysis and the timed-release analysis, a new theoretical floatability curve of coal has been advanced. By means of fitting to a lot of data, a model of theoretical floatability curve has been set up. The characteristics of curve and how to achieve standardization were discussed.
基金National Natural Science Foundation of China (No. 51174202)Doctoral Fund of Ministry of Education of China (No. 20100095110013)
文摘A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The predicted data are used to draw washability curves and to provide a rapid evaluation of the effect from heavy medium induced separation.Thirty-one production shifts worth of fast float/sink data and the corresponding quick ash data are used to verify the model.The results show a small error with an arithmetic average of 0.53 and an absolute average error of 1.50.This indicates that this model has high precision.The theoretical yield from the washability curves is 76.47% for the monthly comprehensive data and 81.31% using the model data.This is for a desired cleaned coal ash of 9%.The relative error between these two is 6.33%,which is small and indicates that the predicted data can be used to rapidly evaluate the separation effect of gravity separation equipment.
基金supported by National Natural Science Foundation of China (Grant Nos. 11401383, 11301391 and 11271080)
文摘We propose a two-step variable selection procedure for censored quantile regression with high dimensional predictors. To account for censoring data in high dimensional case, we employ effective dimension reduction and the ideas of informative subset idea. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. Simulation study and real data analysis are conducted to evaluate the finite sample performance of the proposed approach.
