This paper discussed the current of works on computerisation of all problems related to mining subsidence, including the time factor,carried out in the Division of Mining Geodesy of Technical University of Silesia, Po...This paper discussed the current of works on computerisation of all problems related to mining subsidence, including the time factor,carried out in the Division of Mining Geodesy of Technical University of Silesia, Poland. First, the formulas implemented in the programs were presented. These formulas considerably increase the description accuracy of final deformations by taking into uncaved strip along extraction rib (extraction margin). They also improve the deformation description of areas located far from the extraction place. Then, the research results aiming to improving the description of deformation with time were introduced. Finally, the Windows based version of the program for the creation of mining geological opinions were presented in the form accepted by Mining Offices of Poland.展开更多
Existing algorithms of news recommendations lack in depth analysis of news texts and timeliness. To address these issues, an algorithm for news recommendations based on time factor and word embedding(TFWE) was propose...Existing algorithms of news recommendations lack in depth analysis of news texts and timeliness. To address these issues, an algorithm for news recommendations based on time factor and word embedding(TFWE) was proposed to improve the interpretability and precision of news recommendations. First, TFWE used term frequency-inverse document frequency(TF-IDF) to extract news feature words and used the bidirectional encoder representations from transformers(BERT) pre-training model to convert the feature words into vector representations. By calculating the distance between the vectors, TFWE analyzed the semantic similarity to construct a user interest model. Second, considering the timeliness of news, a method of calculating news popularity by integrating time factors into the similarity calculation was proposed. Finally, TFWE combined the similarity of news content with the similarity of collaborative filtering(CF) and recommended some news with higher rankings to users. In addition, results of the experiments on real dataset showed that TFWE significantly improved precision, recall, and F1 score compared to the classic hybrid recommendation algorithm.展开更多
The Collaborative Filtering(CF) recommendation algorithm, one of the most popular algorithms in Recommendation Systems(RS), mainly includes memory-based and model-based methods. When performing rating prediction using...The Collaborative Filtering(CF) recommendation algorithm, one of the most popular algorithms in Recommendation Systems(RS), mainly includes memory-based and model-based methods. When performing rating prediction using a memory-based method, the approach used to measure the similarity between users or items can significantly influence the recommendation performance. Traditional CFs suffer from data sparsity when making recommendations based on a rating matrix, and cannot effectively capture changes in user interest. In this paper, we propose an improved hybrid collaborative filtering algorithm based on tags and a time factor(TTHybridCF), which fully utilizes tag information that characterizes users and items. This algorithm utilizes both tag and rating information to calculate the similarity between users or items. In addition, we introduce a time weighting factor to measure user interest, which changes over time. Our experimental results show that our method alleviates the sparsity problem and demonstrates promising prediction accuracy.展开更多
Relaxation time spectra （RTS） derived from time domain induced polarization data （TDIP） are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio （SNR）, th...Relaxation time spectra （RTS） derived from time domain induced polarization data （TDIP） are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio （SNR）, the inversion accuracy of the traditional singular value decomposition （SVD） inversion method reduces with a decrease of SNR. In order to enhance the inversion accuracy and improve robustness of the inversion method to the SNR, an improved inversion method, based on damping factor and spectrum component residual correction, is proposed in this study. The numerical inversion results show that the oscillation of the RTS derived from the SVD method increased with a decrease of SNR, which makes it impossible to get accurate inversion components. However, the SNR has little influence on inversion components of the improved method, and the RTS has high inversion accuracy and robustness. Moreover, RTS derived from core sample data is basically in accord with the pore-size distribution curve, and the RTS derived from the actual induced polarization logging data is smooth and continuous, which indicates that the improved method is practicable.展开更多
Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smar...Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.展开更多
Based on the Gauss linear frequency modulated wavelet transform, a new characteristic index is presented, namely time frequency energy attenuation factor which can reflect the difference features of waveform in earthq...Based on the Gauss linear frequency modulated wavelet transform, a new characteristic index is presented, namely time frequency energy attenuation factor which can reflect the difference features of waveform in earthquake focus mechanism, wave traveling path and its attenuation characteristics in focal area or near field. In order to test its validity, we select the natural earthquakes and explosion or collapse events whose focus mechanisms vary obviously,and some natural earthquakes located at the same site or in a very small area. The study indicates that the time frequency energy attenuation factors of the natural earthquakes are obviously different with that of explosion or collapse events, and the change of the time frequency energy attenuation factors is relatively stable for the earthquakes under the normal seismicity background. Using the above mentioned method, it is expected to offer a useful criterion for strong earthquake prediction by continuous earthquake observation.展开更多
Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effectiv...Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.展开更多
Time-resolved Kerr rotation spectroscopy is used to determine the sign of the g factor of carriers in a semiconductor material, with the help of a rotatable magnetic field in the plane of the sample. The spin precessi...Time-resolved Kerr rotation spectroscopy is used to determine the sign of the g factor of carriers in a semiconductor material, with the help of a rotatable magnetic field in the plane of the sample. The spin precession signal of carriers at a fixed time delay is measured as a function of the orientation of the magnetic field with a fixed strength B. The signal has a sine-like form and its phase determines the sign of the g factor of carriers. As a natural extension of previous methods to measure the （time-resolved） photoluminescence or time-resolved Kerr rotation signal as a function of the magnetic field strength with a fixed orientation, such a method gives the correct sign of the g factor of electrons in GaAs. Furthermore, the sign of carriers in a （Ga, Mn）As magnetic semiconductor is also found to be negative.展开更多
Cost and time overrun are the key troubles of any improvement ventures. These troubles are inflicting the terrible end result in the development of kingdom monetary improvement and thriving. To overcome these problems...Cost and time overrun are the key troubles of any improvement ventures. These troubles are inflicting the terrible end result in the development of kingdom monetary improvement and thriving. To overcome these problems, the?paper examines predominant impact on elements causing the mission postponement and cost. A poll review was led for the situation study embracing various information-gathering procedures. The discoveries from the contextual investigation uncovered that the most persuasive factors in Malaysia:?1) contractor’s inappropriate arranging, 2) poor site the board, 3) deficient contractual worker experience,?are the most powerful factors. This paper has likewise broken down the normal and least effective of the postpone variables causing task deferral and cost overrun in Malaysia. It likewise infers that there are various measures as per the idea of deferring components to decrease the effect on task postponement and cost overruns in the development industry.?There are significant factors in the control of time overrun that would be actual thought related to know and tackle in great impact to improvement rate which may additionally no capacity that be recovered. Thirty (30) massive development extensions in Malaysia were exceptional coping with time overrun at some stage in development. Out of 30 undertakings, 17 (56.67%) ventures had been introduced by using 1100 days’ time overrun, 5 (16.67%) extensions in the middle of a hundred and one to 200 days, 5 (16.67%) ventures?201 to 300 days while three (10%) ventures have been deferred for timeframe over 300 days.展开更多
Martens proposed a highly efficient and simply formed DFT algorithm——RCFA,whose efficien-cy is comparable with that of WFTA or that of PFA,and whose structure is similar to that of FFT.Theauthors have proved that,in...Martens proposed a highly efficient and simply formed DFT algorithm——RCFA,whose efficien-cy is comparable with that of WFTA or that of PFA,and whose structure is similar to that of FFT.Theauthors have proved that,in the case of radix 2,the RCFA is exactly equivalent to the twiddle factor mergedfrequency-decimal FFT algorithm.The twiddle factor merged time-decimal FFT algorithm is providedin this paper.Thus,in any case,the FFT algorithm used currently can be replaced by the more efficientalgorithm——the twiddle factor merged FFT algorithm,with exactly the same external property and thesimilar internal structure.Also in this paper,the software for implementing the twiddle factor merged FFTalgorithm(TMFFT)is provided.展开更多
Bus safety is a matter of great importance in many developing countries, with driving behaviors among bus drivers identified as a primary factor contributing to accidents. This concern is particularly amplified in mix...Bus safety is a matter of great importance in many developing countries, with driving behaviors among bus drivers identified as a primary factor contributing to accidents. This concern is particularly amplified in mixed traffic flow (MTF) environments with time pressure (TP). However, there is a lack of sufficient research exploring the relationships among these factors. This study consists of two papers that aim to investigate the impact of MTF environments with TP on the driving behaviors of bus drivers. While the first paper focuses on violated driving behaviors, this particular paper delves into mistake-prone driving behaviors (MDB). To collect data on MDB, as well as perceptions of MTF and TP, a questionnaire survey was implemented among bus drivers. Factor analyses were employed to create new measurements for validating MDB in MTF environments. The study utilized partial correlation and linear regression analyses with the Bayesian Model Averaging (BMA) method to explore the relationships between MDB and MTF/TP. The results revealed a modified scale for MDB. Two MTF factors and two TP factors were found to be significantly associated with MDB. A high presence of motorcycles and dangerous interactions among vehicles were not found to be associated with MDB among bus drivers. However, bus drivers who perceived motorcyclists as aggressive, considered road users’ traffic habits as unsafe, and perceived bus routes’ punctuality and organization as very strict were more likely to exhibit MDB. Moreover, the results from the three MDB predictive models demonstrated a positive impact of bus route organization on MDB among bus drivers. The study also examined various relationships between the socio-demographic characteristics of bus drivers and MDB. These findings are of practical significance in developing interventions aimed at reducing MDB among bus drivers operating in MTF environments with TP.展开更多
Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuz...Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.展开更多
文摘This paper discussed the current of works on computerisation of all problems related to mining subsidence, including the time factor,carried out in the Division of Mining Geodesy of Technical University of Silesia, Poland. First, the formulas implemented in the programs were presented. These formulas considerably increase the description accuracy of final deformations by taking into uncaved strip along extraction rib (extraction margin). They also improve the deformation description of areas located far from the extraction place. Then, the research results aiming to improving the description of deformation with time were introduced. Finally, the Windows based version of the program for the creation of mining geological opinions were presented in the form accepted by Mining Offices of Poland.
基金supported by the Research Program of the Basic Scientific Research of National Defense of China (JCKY2019210B005, JCKY2018204B025, and JCKY2017204B011)the Key Scientific Project Program of National Defense of China (ZQ2019D20401 )+2 种基金the Open Program of National Engineering Laboratory for Modeling and Emulation in E-Government (MEL-20-02 )the Foundation Strengthening Project of China (2019JCJZZD13300 )the Jiangsu Postgraduate Research and Innovation Program (KYCX20_0824)。
文摘Existing algorithms of news recommendations lack in depth analysis of news texts and timeliness. To address these issues, an algorithm for news recommendations based on time factor and word embedding(TFWE) was proposed to improve the interpretability and precision of news recommendations. First, TFWE used term frequency-inverse document frequency(TF-IDF) to extract news feature words and used the bidirectional encoder representations from transformers(BERT) pre-training model to convert the feature words into vector representations. By calculating the distance between the vectors, TFWE analyzed the semantic similarity to construct a user interest model. Second, considering the timeliness of news, a method of calculating news popularity by integrating time factors into the similarity calculation was proposed. Finally, TFWE combined the similarity of news content with the similarity of collaborative filtering(CF) and recommended some news with higher rankings to users. In addition, results of the experiments on real dataset showed that TFWE significantly improved precision, recall, and F1 score compared to the classic hybrid recommendation algorithm.
基金supported by the National Natural Science Foundation of China (Nos. 61432008 and 61272222)
文摘The Collaborative Filtering(CF) recommendation algorithm, one of the most popular algorithms in Recommendation Systems(RS), mainly includes memory-based and model-based methods. When performing rating prediction using a memory-based method, the approach used to measure the similarity between users or items can significantly influence the recommendation performance. Traditional CFs suffer from data sparsity when making recommendations based on a rating matrix, and cannot effectively capture changes in user interest. In this paper, we propose an improved hybrid collaborative filtering algorithm based on tags and a time factor(TTHybridCF), which fully utilizes tag information that characterizes users and items. This algorithm utilizes both tag and rating information to calculate the similarity between users or items. In addition, we introduce a time weighting factor to measure user interest, which changes over time. Our experimental results show that our method alleviates the sparsity problem and demonstrates promising prediction accuracy.
基金supported by a project from the Youth Science Foundation of the National Natural Science Foundation of China (11104089)
文摘Relaxation time spectra （RTS） derived from time domain induced polarization data （TDIP） are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio （SNR）, the inversion accuracy of the traditional singular value decomposition （SVD） inversion method reduces with a decrease of SNR. In order to enhance the inversion accuracy and improve robustness of the inversion method to the SNR, an improved inversion method, based on damping factor and spectrum component residual correction, is proposed in this study. The numerical inversion results show that the oscillation of the RTS derived from the SVD method increased with a decrease of SNR, which makes it impossible to get accurate inversion components. However, the SNR has little influence on inversion components of the improved method, and the RTS has high inversion accuracy and robustness. Moreover, RTS derived from core sample data is basically in accord with the pore-size distribution curve, and the RTS derived from the actual induced polarization logging data is smooth and continuous, which indicates that the improved method is practicable.
基金Supported by Shaanxi Provincial Overall Innovation Project of Science and Technology,China(Grant No.2013KTCQ01-06)
文摘Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.
文摘Based on the Gauss linear frequency modulated wavelet transform, a new characteristic index is presented, namely time frequency energy attenuation factor which can reflect the difference features of waveform in earthquake focus mechanism, wave traveling path and its attenuation characteristics in focal area or near field. In order to test its validity, we select the natural earthquakes and explosion or collapse events whose focus mechanisms vary obviously,and some natural earthquakes located at the same site or in a very small area. The study indicates that the time frequency energy attenuation factors of the natural earthquakes are obviously different with that of explosion or collapse events, and the change of the time frequency energy attenuation factors is relatively stable for the earthquakes under the normal seismicity background. Using the above mentioned method, it is expected to offer a useful criterion for strong earthquake prediction by continuous earthquake observation.
基金Supported by Humanities and Social Sciences Fund of the Ministry of Education(12YJC790094)Tianjin Philosophy and Social Science Planning Project(TJYY13-028TJLJ13-011)
文摘Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.
基金Project supported by the National Basic Research Program of China (Grant No. 2009CB929301)the National Natural Science Foundation of China (Grant No. 10911130232)
文摘Time-resolved Kerr rotation spectroscopy is used to determine the sign of the g factor of carriers in a semiconductor material, with the help of a rotatable magnetic field in the plane of the sample. The spin precession signal of carriers at a fixed time delay is measured as a function of the orientation of the magnetic field with a fixed strength B. The signal has a sine-like form and its phase determines the sign of the g factor of carriers. As a natural extension of previous methods to measure the （time-resolved） photoluminescence or time-resolved Kerr rotation signal as a function of the magnetic field strength with a fixed orientation, such a method gives the correct sign of the g factor of electrons in GaAs. Furthermore, the sign of carriers in a （Ga, Mn）As magnetic semiconductor is also found to be negative.
文摘Cost and time overrun are the key troubles of any improvement ventures. These troubles are inflicting the terrible end result in the development of kingdom monetary improvement and thriving. To overcome these problems, the?paper examines predominant impact on elements causing the mission postponement and cost. A poll review was led for the situation study embracing various information-gathering procedures. The discoveries from the contextual investigation uncovered that the most persuasive factors in Malaysia:?1) contractor’s inappropriate arranging, 2) poor site the board, 3) deficient contractual worker experience,?are the most powerful factors. This paper has likewise broken down the normal and least effective of the postpone variables causing task deferral and cost overrun in Malaysia. It likewise infers that there are various measures as per the idea of deferring components to decrease the effect on task postponement and cost overruns in the development industry.?There are significant factors in the control of time overrun that would be actual thought related to know and tackle in great impact to improvement rate which may additionally no capacity that be recovered. Thirty (30) massive development extensions in Malaysia were exceptional coping with time overrun at some stage in development. Out of 30 undertakings, 17 (56.67%) ventures had been introduced by using 1100 days’ time overrun, 5 (16.67%) extensions in the middle of a hundred and one to 200 days, 5 (16.67%) ventures?201 to 300 days while three (10%) ventures have been deferred for timeframe over 300 days.
文摘Martens proposed a highly efficient and simply formed DFT algorithm——RCFA,whose efficien-cy is comparable with that of WFTA or that of PFA,and whose structure is similar to that of FFT.Theauthors have proved that,in the case of radix 2,the RCFA is exactly equivalent to the twiddle factor mergedfrequency-decimal FFT algorithm.The twiddle factor merged time-decimal FFT algorithm is providedin this paper.Thus,in any case,the FFT algorithm used currently can be replaced by the more efficientalgorithm——the twiddle factor merged FFT algorithm,with exactly the same external property and thesimilar internal structure.Also in this paper,the software for implementing the twiddle factor merged FFTalgorithm(TMFFT)is provided.
文摘Bus safety is a matter of great importance in many developing countries, with driving behaviors among bus drivers identified as a primary factor contributing to accidents. This concern is particularly amplified in mixed traffic flow (MTF) environments with time pressure (TP). However, there is a lack of sufficient research exploring the relationships among these factors. This study consists of two papers that aim to investigate the impact of MTF environments with TP on the driving behaviors of bus drivers. While the first paper focuses on violated driving behaviors, this particular paper delves into mistake-prone driving behaviors (MDB). To collect data on MDB, as well as perceptions of MTF and TP, a questionnaire survey was implemented among bus drivers. Factor analyses were employed to create new measurements for validating MDB in MTF environments. The study utilized partial correlation and linear regression analyses with the Bayesian Model Averaging (BMA) method to explore the relationships between MDB and MTF/TP. The results revealed a modified scale for MDB. Two MTF factors and two TP factors were found to be significantly associated with MDB. A high presence of motorcycles and dangerous interactions among vehicles were not found to be associated with MDB among bus drivers. However, bus drivers who perceived motorcyclists as aggressive, considered road users’ traffic habits as unsafe, and perceived bus routes’ punctuality and organization as very strict were more likely to exhibit MDB. Moreover, the results from the three MDB predictive models demonstrated a positive impact of bus route organization on MDB among bus drivers. The study also examined various relationships between the socio-demographic characteristics of bus drivers and MDB. These findings are of practical significance in developing interventions aimed at reducing MDB among bus drivers operating in MTF environments with TP.
基金supported by the National Natural Science Foundation of China(61309022)
文摘Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.
