Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are i...Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.展开更多
Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on chang...Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on changes of flow regime characteristics remained rare.This study detects temporal changes in 16 flow regime metrics from five main components(i.e.,magnitude,frequency of events,variability,duration,and timing),and evaluates the effects of observation uncertainty on trends of flow regime metrics by adopting a normal distribution error model and using uncertainty width,significant change rate of slopes,coefficient of variation,and degree of deviation.The daily runoff series from 1971 to 2020 at five hydrological stations(i.e.,Huangheyan,Tangnaihai,and Lanzhou in the Yellow River Source Region,Xianyang in the Weihe River Catchment,and Heishiguan in the Yiluo River Catchment)in the water conservation zone of Yellow River are collected for our study.Results showed that:(1)Flow regimes showed significant increases in the low flow magnitude,and significant decreases in the high and average flow magnitude,variability and duration at all the five stations.The magnitude,variability and duration metrics decreased significantly,and the frequency metrics increased significantly at Heishiguan.The low flow magnitude and timing metrics increased significantly,while the high flow magnitude,frequency and variability metrics decreased significantly at Xianyang.The low flow magnitude and high flow timing metrics increased significantly,while the low flow frequency,high flow magnitude and variability metrics decreased significantly in the Yellow River Source Region.(2)Observation uncertainty remarkably impacted the changes of 28.75% of total flow regime metrics at all the stations.The trends of 11.25% of total metrics changed from significance to insignificance,while those of 17.5% of total metrics changed from insignificance to significance.For the rest metrics,the trends remained the same,i.e.,significant(18.75%)and insignificant(52.50%)trends.(3)Observation uncertainty had the greatest impacts on the frequency metrics,especially at Xianyang,followed by duration,variability,timing and magnitude metrics.展开更多
With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distributi...With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.展开更多
A new milling methodology with the equivalent normal curvature milling model machining freeform surfaces is proposed based on the normal curvature theorems on differential geometry. Moreover, a specialized whirlwind m...A new milling methodology with the equivalent normal curvature milling model machining freeform surfaces is proposed based on the normal curvature theorems on differential geometry. Moreover, a specialized whirlwind milling tool and a 5-axis CNC horizontal milling machine are introduced. This new milling model can efficiently enlarge the material removal volume at the tip of the whirlwind milling tool and improve the producing capacity. The machining strategy of this model is to regulate the orientation of the whirlwind milling tool relatively to the principal directions of the workpiece surface at the point of contact, so as to create a full match with collision avoidance between the workpiece surface and the symmetric rotational surface of the milling tool. The practical results show that this new milling model is an effective method in machining complex three- dimensional surfaces. This model has a good improvement on finishing machining time and scallop height in machining the freeform surfaces over other milling processes. Some actual examples for manufacturing the freeform surfaces with this new model are given.展开更多
Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcom...Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.展开更多
A low-viscosity emulsion of crude oil in water can be believed to be the bulk of a flow regime in a pipeline.To differentiate which crude oil would and which would not counter the blockage of flow due to gas hydrate f...A low-viscosity emulsion of crude oil in water can be believed to be the bulk of a flow regime in a pipeline.To differentiate which crude oil would and which would not counter the blockage of flow due to gas hydrate formation in flow channels,varying amount of crude oil in water emulsion without any other extraneous additives has undergone methane gas hydrate formation in an autoclave cell.Crude oil was able to thermodynamically inhibit the gas hydrate formation as observed from its hydrate stability zone.The normalized rate of hydrate formation in the emulsion has been calculated from an illustrative chemical affinity model,which showed a decrease in the methane consumption（decreased normalized rate constant） with an increase in the oil content in the emulsion.Fourier transform infrared spectroscopy（FTIR） of the emulsion and characteristic properties of the crude oil have been used to find the chemical component that could be pivotal in selfinhibitory characteristic of the crude oil collected from Ankleshwar,India,against a situation of clogged flow due to formation of gas hydrate and establish flow assurance.展开更多
In this paper, we consider the risk assessment problem under multi-levels and multiple mixture subpopulations. Our result is the generalization of the results of [1-5].1 Finite Mixture Normal ModelsIn dose-response s...In this paper, we consider the risk assessment problem under multi-levels and multiple mixture subpopulations. Our result is the generalization of the results of [1-5].1 Finite Mixture Normal ModelsIn dose-response studies, a class of phenomena that frequently occur are that experimental subjects (e.g., mice) may have different responses like ’none, mild, severe’ after a toxicant experiment, or ’getting worse, no change, getting better’ after a medical treatment, etc. These phenomena have attracted the attention of many researchers in recent years. Finite展开更多
Extensive studies based on partition curve of gravity separation have been investigated. All created models are merely used to simulate density distribution at the same size fraction. However, they cannot be used to p...Extensive studies based on partition curve of gravity separation have been investigated. All created models are merely used to simulate density distribution at the same size fraction. However, they cannot be used to predictive distribution of materials depending on compound feature of density and size. According to this situation, an improved model of partition curve based on accumulation normal distribution, which was distinguished from conventional model of accumulation normal distribution for partition curve, was proposed in this paper. It could simulate density distribution at different size fractions by using the density-size compound index and conflating the partition curves at different size fractions as one partition curve. The feasibility of three compound indexes, including mass index, settlement index and transformation index, were investigated. Specific forms of the improved model were also proposed. It is found that transformation index leads to the best fitting results, while the fitting error is only 1.75 according to the fitting partition curve.展开更多
Mathematical models for burden descending process have been applied to obtain whole burden structures in blast furnace,whereas the accuracy of those burden descent models has not been sufficiently investigated.Special...Mathematical models for burden descending process have been applied to obtain whole burden structures in blast furnace,whereas the accuracy of those burden descent models has not been sufficiently investigated.Special evaluation method based on timeline burden profiles was established to quantitatively evaluate the error between experimental and modeled burden structures.Four existing burden descent models were utilized to describe the burden structure of a 1/20 scaled warm blast furnace.Input modeling conditions including initial burden profile,descending volumes in each time interval,and normalized descending velocity distribution were determined via special image processing technology.Modeled burden structures were evaluated combined with the published experimental data.It is found that all the models caught the main profile of the burden structure.Furthermore,the improved nonuniform descent model（Model IV）shows the highest level of precision especially when burden descends with unstable velocity distribution tendency.Meanwhile,the traditional nonuniform descent model（Model III）may also be desirable to model the burden descending process when the burden descending velocity presents a linear tendency.Finally,the uniform descent model（Model I）might be the first option for roughly predicting burden structure.展开更多
We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forwa...We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forward scattering dominates. At the same time, this model provides an efficiency gain of an order of magnitude or more over two-way coupled-mode models. This model can be applied to three-dimensional range-dependent problems with a slowly varying bathymetry or internal waves. A numerical example of the latter is demonstrated in this work. Comparisons of both accuracy and efficiency between the present model and a benchmark model are also provided.展开更多
An artificial immune system was modelled with self/non-self selection to overcome abnormity in a mobile robot demo. The immune modelling includes the innate immune modelling and the adaptive immune modelling. The self...An artificial immune system was modelled with self/non-self selection to overcome abnormity in a mobile robot demo. The immune modelling includes the innate immune modelling and the adaptive immune modelling. The self/non-self selection includes detection and recognition, and the self/non-self detection is based on the normal model of the demo. After the detection, the non-self recognition is based on learning unknown non-self for the adaptive immunization. The learning was designed on the neural network or on the learning mechanism from examples. The last step is elimination of all the non-self and failover of the demo. The immunization of the mobile robot demo is programmed with Java to test effectiveness of the approach. Some worms infected the mobile robot demo, and caused the abnormity. The results of the immunization simulations show that the immune program can detect 100% worms, recognize all known Worms and most unknown worms, and eliminate the worms. Moreover, the damaged files of the mobile robot demo can all be repaired through the normal model and immunization. Therefore, the immune modelling of the mobile robot demo is effective and programmable in some anti-worms and abnormity detection applications.展开更多
The stretchable sensor wrapped around a foldable airfoil or embedded inside of it has great potential for use in the monitoring of the structural status of the foldable airfoil.The design methodology is important to t...The stretchable sensor wrapped around a foldable airfoil or embedded inside of it has great potential for use in the monitoring of the structural status of the foldable airfoil.The design methodology is important to the development of the stretchable sensor for status monitoring on the foldable airfoil.According to the requirement of mechanical flexibility of the sensor,the combined use of a layered flexible structural formation and a strain isolation layer is implemented.An analytical higher-order model is proposed to predict the stresses of the strain-isolation layer based on the shear-lag model for the safe design of the flexible and stretchable sensors.The normal stress and shear stress equations in the constructed structure of the sensors are obtained by the proposed model.The stress distribution in the structure is investigated when bending load is applied to the structures.The numerical results show that the proposed model can predict the variation of normal stress and shear stress along the thickness of the strain-isolation（polydimethylsiloxane）layer accurately.The results by the proposed model are in good agreement with the finite element method,in which the normal stress is variable while the shear stress is invariable along the thickness direction of strain-isolation layer.The high-order model is proposed to predict the stresses of the layered structure of the flexible and stretchable sensor for monitoring the status of the foldable airfoil.展开更多
To cope with multi-directional transmission coupling,spreading, amplification, and chain reaction of risks during multiproject parallel construction of warships, a risk transmission evaluation method is proposed, whic...To cope with multi-directional transmission coupling,spreading, amplification, and chain reaction of risks during multiproject parallel construction of warships, a risk transmission evaluation method is proposed, which integrates an intuitionistic cloud model with a fuzzy cognitive map. By virtue of expectancy Ex, entropy En, and hyper entropy He, the risk fuzziness and randomness of the knowledge of experts are organically combined to develop a method for converting bi-linguistic variable decision-making information into the quantitative information of the intuitionistic normal cloud(INC) model. Subsequently, the threshold function and weighted summation operation in the traditional fuzzy cognitive map is converted into the INC ordered weighted averaging operator to create the risk transmission model based on the intuitionistic fuzzy cognitive map(IFCM) and the algorithm for solving it. Subsequently, the risk influence sequencing method based on INC and the risk rating method based on nearness are proposed on the basis of Monte Carlo simulation in order to realize the mutual conversion of the qualitative and quantitative information in the risk evaluation results.Example analysis is presented to verify the effectiveness and practicality of the methods.展开更多
Leakage is one of the most important reasons for failure of hydraulic systems.The accurate positioning of leakage is of great significance to ensure the safe and reliable operation of hydraulic systems.For early stage...Leakage is one of the most important reasons for failure of hydraulic systems.The accurate positioning of leakage is of great significance to ensure the safe and reliable operation of hydraulic systems.For early stage of leakage,the pressure of the hydraulic circuit does not change obviously and therefore cannot be monitored by pressure sensors.Meanwhile,the pressure of the hydraulic circuit changes frequently due to the influence of load and state of the switch,which further reduces the accuracy of leakage localization.In the work,a novel Bayesian networks(BNs)-based data-driven early leakage localization approach for multi-valve systems is proposed.Wavelet transform is used for signal noise reduction and BNs-based leak localization model is used to identify the location of leakage.A normalization model is developed to improve the robustness of the leakage localization model.A hydraulic system with eight valves is used to demonstrate the application of the proposed early micro-leakage detection and localization approach.展开更多
Infrared absorption spectra of gaseous CH2Cl2 in the regions of 1200-12000 cm^-1 were measured using a Bruker IFS 120HR Fourier transform spectrometer in conjunction with a nmltipass cell. 47 vibrational levels of ove...Infrared absorption spectra of gaseous CH2Cl2 in the regions of 1200-12000 cm^-1 were measured using a Bruker IFS 120HR Fourier transform spectrometer in conjunction with a nmltipass cell. 47 vibrational levels of overtone and combinational spectral lines of the CH stretching （v1, v6）, bending （v2）, and rocking （v8） modes were analyzed and assigned. Utilizing the normal mode model and considering the coupling among CH stretching, bending and rocking vibrations, values of the harmonic frequency wi, the anharmonic constant xij, and the coefficients of Fermi and the Darling-Dennison resonances of v1, v6, v2 and v8 modes were also determined from experimental spectral data with nonlinear least-square fitting. These spectral constants reproduced the experimental levels very well. These results showed that Fermi resonance between CH stretching and rocking vibrations （kiss=-254.63 cm^-1） is stronger than that between CH stretching and bending vibrations （k122 = 54.87 cm^-1 ）; and that Darling-Dennison resonances between CH stretching and bending vibrations （k166=-215.28 cm^-1） is also much stronger than that between CH bending and rocking vibrations （k2288=5.72 cm^-1）.展开更多
There is no reasonable scientific basis for selecting the excellent teachers of the school’s courses.To solve the practical problem,we firstly give a series of normalization models for defining the key attributes of ...There is no reasonable scientific basis for selecting the excellent teachers of the school’s courses.To solve the practical problem,we firstly give a series of normalization models for defining the key attributes of teachers’professional foundation,course difficulty coefficient,and comprehensive evaluation of teaching.Then,we define a partial weight function to calculate the key attributes,and obtain the partial recommendation values.Next,we construct a highly sparse Teaching Recommendation Factorization Machines(TRFMs)model,which takes the 5-tuples relation including teacher,course,teachers’professional foundation,course difficulty,teaching evaluation as the feature vector,and take partial recommendation value as the recommendation label.Finally,we design a novel Top-N excellent teacher recommendation algorithm based on TRFMs by course classification on the highly sparse dataset.Experimental results show that the proposed TRFMs and recommendation algorithm can accurately realize the recommendation of excellent teachers on a highly sparse historical teaching dataset.The recommendation accuracy is superior to that of the three-dimensional tensor decomposition model algorithm which also solves sparse datasets.The proposed method can be used as a new recommendation method applied to the teaching arrangements in all kinds of schools,which can effectively improve the teaching quality.展开更多
A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment group than others. Finite mixture models have traditionally been used to d...A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment group than others. Finite mixture models have traditionally been used to describe the distribution of responses in treated subjects for such studies. In this paper, we first study the mixture normal model with multi-levels and multiple mixture sub-populations under each level, with particular attention being given to the model in which the proportions of susceptibility are related to dose levels, then we use EM-algorithm to find the maximum likelihood estimators of model parameters. Our results are generalizations of the existing results. Finally, we illustrate realistic significance of the above extension based on a set of real dose-response data.展开更多
Medical insurance service, the important part of national healthcare supporting system with a history dating back more than 100 years ago, remains a global challenge because of its high rates of compensation and diffi...Medical insurance service, the important part of national healthcare supporting system with a history dating back more than 100 years ago, remains a global challenge because of its high rates of compensation and difficulty in risk control. When developing the diabetes related, hospitalization insurance, we found that the risk loss of the diabetic inpatients does not follow a symmetrical unimodal distribution： in fact, it is hard to describe its risk loses distribution with a single probability distribution model. Therefore, we put forward a risk measurement method based on a mixed normal distributions model for medical insurance of inpatients with diabetes.展开更多
Background Monitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat.Traditional ground-based sampling ...Background Monitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat.Traditional ground-based sampling methods have been widely used and provide valuable information;however,they are time-consuming,labor-intensive,and limited in their ability to capture larger extents of the spatial and temporal dynamics of rangeland ecosystems.Drones provide a solution to collect data to larger extents than field-based methods and with higher-resolution than traditional remote sensing platforms.Our objectives were to(1)assess the accuracy of vegetation cover height in grasses using drones,(2)quantify the spatial distribution of vegetation cover height in grazed and non-grazed pastures during the dormant(fall-winter)and growing seasons(spring-summer),and(3)evaluate the spatial distribution of vegetation cover height as a proxy for northern bobwhite(Colinusvirginianus)habitat in South Texas.We achieved this by very fine scale drone-derived imagery and using class level landscape metrics to assess vegetation cover height configuration.Results Estimated heights from drone imagery had a significant relationship with the field height measurements in September(r2=0.83;growing season)and February(r^(2)=0.77;dormant season).Growing season pasture maintained residual landscape habitat configuration adequate for bobwhites throughout the fall and winter of 2022-2023 following grazing.Dormant season pasture had an increase in bare ground cover,and a shift from many large patches of tall herbaceous cover(40-120 cm)to few large patches of low herbaceous cover(5-30 cm)(p<0.05).Conclusions Drones provided high-resolution imagery that allowed us to assess the spatial and temporal changes of vertical herbaceous vegetation structure in a semi-arid rangeland subject to grazing.This study shows how drone imagery can be beneficial for wildlife conservation and management by providing insights into changes in fine-scale vegetation spatial and temporal heterogeneity from livestock grazing.展开更多
基金the National Natural Science Foundation of China under contract Nos 42090043 and 41876074the National Basic Research Program(973 Program)of China under contract No.2014CB441502.
文摘Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.
基金National Key Research and Development Program of China,No.2021YFC3201102National Natural Science Foundation of China,No.42071041,No.42171047。
文摘Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on changes of flow regime characteristics remained rare.This study detects temporal changes in 16 flow regime metrics from five main components(i.e.,magnitude,frequency of events,variability,duration,and timing),and evaluates the effects of observation uncertainty on trends of flow regime metrics by adopting a normal distribution error model and using uncertainty width,significant change rate of slopes,coefficient of variation,and degree of deviation.The daily runoff series from 1971 to 2020 at five hydrological stations(i.e.,Huangheyan,Tangnaihai,and Lanzhou in the Yellow River Source Region,Xianyang in the Weihe River Catchment,and Heishiguan in the Yiluo River Catchment)in the water conservation zone of Yellow River are collected for our study.Results showed that:(1)Flow regimes showed significant increases in the low flow magnitude,and significant decreases in the high and average flow magnitude,variability and duration at all the five stations.The magnitude,variability and duration metrics decreased significantly,and the frequency metrics increased significantly at Heishiguan.The low flow magnitude and timing metrics increased significantly,while the high flow magnitude,frequency and variability metrics decreased significantly at Xianyang.The low flow magnitude and high flow timing metrics increased significantly,while the low flow frequency,high flow magnitude and variability metrics decreased significantly in the Yellow River Source Region.(2)Observation uncertainty remarkably impacted the changes of 28.75% of total flow regime metrics at all the stations.The trends of 11.25% of total metrics changed from significance to insignificance,while those of 17.5% of total metrics changed from insignificance to significance.For the rest metrics,the trends remained the same,i.e.,significant(18.75%)and insignificant(52.50%)trends.(3)Observation uncertainty had the greatest impacts on the frequency metrics,especially at Xianyang,followed by duration,variability,timing and magnitude metrics.
基金supported by the State Grid Corporation of China(KJ21-1-56).
文摘With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.
基金China Postdoctoral Science Foundation(No.2005037348)Science and Technology Research Program of Hubei Province,Ministry of Education,China(No.D200612003)
文摘A new milling methodology with the equivalent normal curvature milling model machining freeform surfaces is proposed based on the normal curvature theorems on differential geometry. Moreover, a specialized whirlwind milling tool and a 5-axis CNC horizontal milling machine are introduced. This new milling model can efficiently enlarge the material removal volume at the tip of the whirlwind milling tool and improve the producing capacity. The machining strategy of this model is to regulate the orientation of the whirlwind milling tool relatively to the principal directions of the workpiece surface at the point of contact, so as to create a full match with collision avoidance between the workpiece surface and the symmetric rotational surface of the milling tool. The practical results show that this new milling model is an effective method in machining complex three- dimensional surfaces. This model has a good improvement on finishing machining time and scallop height in machining the freeform surfaces over other milling processes. Some actual examples for manufacturing the freeform surfaces with this new model are given.
基金Supported by the National Natural Science Foundation of China(11261025,11201412)the Natural Science Foundation of Yunnan Province(2011FB016)the Program for Middle-aged Backbone Teacher,Yunnan University
文摘Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.
基金the financial assistance provided by University Grants Commission, New Delhi, India, under Special Assistance Program (SAP) to the Department of Petroleum Engineering, Indian School of Mines, Dhanbad, India
文摘A low-viscosity emulsion of crude oil in water can be believed to be the bulk of a flow regime in a pipeline.To differentiate which crude oil would and which would not counter the blockage of flow due to gas hydrate formation in flow channels,varying amount of crude oil in water emulsion without any other extraneous additives has undergone methane gas hydrate formation in an autoclave cell.Crude oil was able to thermodynamically inhibit the gas hydrate formation as observed from its hydrate stability zone.The normalized rate of hydrate formation in the emulsion has been calculated from an illustrative chemical affinity model,which showed a decrease in the methane consumption（decreased normalized rate constant） with an increase in the oil content in the emulsion.Fourier transform infrared spectroscopy（FTIR） of the emulsion and characteristic properties of the crude oil have been used to find the chemical component that could be pivotal in selfinhibitory characteristic of the crude oil collected from Ankleshwar,India,against a situation of clogged flow due to formation of gas hydrate and establish flow assurance.
文摘In this paper, we consider the risk assessment problem under multi-levels and multiple mixture subpopulations. Our result is the generalization of the results of [1-5].1 Finite Mixture Normal ModelsIn dose-response studies, a class of phenomena that frequently occur are that experimental subjects (e.g., mice) may have different responses like ’none, mild, severe’ after a toxicant experiment, or ’getting worse, no change, getting better’ after a medical treatment, etc. These phenomena have attracted the attention of many researchers in recent years. Finite
基金the financial support from the National Natural Science Foundation of China (No. 51221462)
文摘Extensive studies based on partition curve of gravity separation have been investigated. All created models are merely used to simulate density distribution at the same size fraction. However, they cannot be used to predictive distribution of materials depending on compound feature of density and size. According to this situation, an improved model of partition curve based on accumulation normal distribution, which was distinguished from conventional model of accumulation normal distribution for partition curve, was proposed in this paper. It could simulate density distribution at different size fractions by using the density-size compound index and conflating the partition curves at different size fractions as one partition curve. The feasibility of three compound indexes, including mass index, settlement index and transformation index, were investigated. Specific forms of the improved model were also proposed. It is found that transformation index leads to the best fitting results, while the fitting error is only 1.75 according to the fitting partition curve.
基金Item Sponsored by National Natural Science Foundation of China(61290325)
文摘Mathematical models for burden descending process have been applied to obtain whole burden structures in blast furnace,whereas the accuracy of those burden descent models has not been sufficiently investigated.Special evaluation method based on timeline burden profiles was established to quantitatively evaluate the error between experimental and modeled burden structures.Four existing burden descent models were utilized to describe the burden structure of a 1/20 scaled warm blast furnace.Input modeling conditions including initial burden profile,descending volumes in each time interval,and normalized descending velocity distribution were determined via special image processing technology.Modeled burden structures were evaluated combined with the published experimental data.It is found that all the models caught the main profile of the burden structure.Furthermore,the improved nonuniform descent model（Model IV）shows the highest level of precision especially when burden descends with unstable velocity distribution tendency.Meanwhile,the traditional nonuniform descent model（Model III）may also be desirable to model the burden descending process when the burden descending velocity presents a linear tendency.Finally,the uniform descent model（Model I）might be the first option for roughly predicting burden structure.
基金Supported by the National Natural Science Foundation of China under Grant No 11774374the Natural Science Foundation of Shandong Province of China under Grant No ZR2016AL10
文摘We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forward scattering dominates. At the same time, this model provides an efficiency gain of an order of magnitude or more over two-way coupled-mode models. This model can be applied to three-dimensional range-dependent problems with a slowly varying bathymetry or internal waves. A numerical example of the latter is demonstrated in this work. Comparisons of both accuracy and efficiency between the present model and a benchmark model are also provided.
基金Projects(60234030, 60404021) supported by the National Natural Science Foundation of China project(040125) supported by the Doctoral Research Grant of Central South University
文摘An artificial immune system was modelled with self/non-self selection to overcome abnormity in a mobile robot demo. The immune modelling includes the innate immune modelling and the adaptive immune modelling. The self/non-self selection includes detection and recognition, and the self/non-self detection is based on the normal model of the demo. After the detection, the non-self recognition is based on learning unknown non-self for the adaptive immunization. The learning was designed on the neural network or on the learning mechanism from examples. The last step is elimination of all the non-self and failover of the demo. The immunization of the mobile robot demo is programmed with Java to test effectiveness of the approach. Some worms infected the mobile robot demo, and caused the abnormity. The results of the immunization simulations show that the immune program can detect 100% worms, recognize all known Worms and most unknown worms, and eliminate the worms. Moreover, the damaged files of the mobile robot demo can all be repaired through the normal model and immunization. Therefore, the immune modelling of the mobile robot demo is effective and programmable in some anti-worms and abnormity detection applications.
基金Supported by National Natural Science Foundation of China(Grant No.51075327)Open Project of State Key Laboratory for Strength and Vibration of Mechanical Structures of China(Grant No.SV2014-KF-08)Shaanxi Provincial Natural Science Foundation of China(Grant No.2014JM2-5082)
文摘The stretchable sensor wrapped around a foldable airfoil or embedded inside of it has great potential for use in the monitoring of the structural status of the foldable airfoil.The design methodology is important to the development of the stretchable sensor for status monitoring on the foldable airfoil.According to the requirement of mechanical flexibility of the sensor,the combined use of a layered flexible structural formation and a strain isolation layer is implemented.An analytical higher-order model is proposed to predict the stresses of the strain-isolation layer based on the shear-lag model for the safe design of the flexible and stretchable sensors.The normal stress and shear stress equations in the constructed structure of the sensors are obtained by the proposed model.The stress distribution in the structure is investigated when bending load is applied to the structures.The numerical results show that the proposed model can predict the variation of normal stress and shear stress along the thickness of the strain-isolation（polydimethylsiloxane）layer accurately.The results by the proposed model are in good agreement with the finite element method,in which the normal stress is variable while the shear stress is invariable along the thickness direction of strain-isolation layer.The high-order model is proposed to predict the stresses of the layered structure of the flexible and stretchable sensor for monitoring the status of the foldable airfoil.
基金supported by the National Natural Science Foundation of China(71501183).
文摘To cope with multi-directional transmission coupling,spreading, amplification, and chain reaction of risks during multiproject parallel construction of warships, a risk transmission evaluation method is proposed, which integrates an intuitionistic cloud model with a fuzzy cognitive map. By virtue of expectancy Ex, entropy En, and hyper entropy He, the risk fuzziness and randomness of the knowledge of experts are organically combined to develop a method for converting bi-linguistic variable decision-making information into the quantitative information of the intuitionistic normal cloud(INC) model. Subsequently, the threshold function and weighted summation operation in the traditional fuzzy cognitive map is converted into the INC ordered weighted averaging operator to create the risk transmission model based on the intuitionistic fuzzy cognitive map(IFCM) and the algorithm for solving it. Subsequently, the risk influence sequencing method based on INC and the risk rating method based on nearness are proposed on the basis of Monte Carlo simulation in order to realize the mutual conversion of the qualitative and quantitative information in the risk evaluation results.Example analysis is presented to verify the effectiveness and practicality of the methods.
基金Project(51779267)supported by the National Natural Science Foundation of ChinaProject(2019YFE0105100)supported by the National Key Research and Development Program of China+2 种基金Project(tsqn201909063)supported by the Taishan Scholars Project,ChinaProject(20CX02301A)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2019KJB016)supported by the Science and Technology Support Plan for Youth Innovation of Universities in Shandong Province,China。
文摘Leakage is one of the most important reasons for failure of hydraulic systems.The accurate positioning of leakage is of great significance to ensure the safe and reliable operation of hydraulic systems.For early stage of leakage,the pressure of the hydraulic circuit does not change obviously and therefore cannot be monitored by pressure sensors.Meanwhile,the pressure of the hydraulic circuit changes frequently due to the influence of load and state of the switch,which further reduces the accuracy of leakage localization.In the work,a novel Bayesian networks(BNs)-based data-driven early leakage localization approach for multi-valve systems is proposed.Wavelet transform is used for signal noise reduction and BNs-based leak localization model is used to identify the location of leakage.A normalization model is developed to improve the robustness of the leakage localization model.A hydraulic system with eight valves is used to demonstrate the application of the proposed early micro-leakage detection and localization approach.
基金This work was supported by National Natural Science Foundation of China （Grant No. 10274077, 20103007 and 29703007）. The authors would like to thank Wei Chu, Yong-qiang Xu and Guo-sheng Cheng for their kind help.
文摘Infrared absorption spectra of gaseous CH2Cl2 in the regions of 1200-12000 cm^-1 were measured using a Bruker IFS 120HR Fourier transform spectrometer in conjunction with a nmltipass cell. 47 vibrational levels of overtone and combinational spectral lines of the CH stretching （v1, v6）, bending （v2）, and rocking （v8） modes were analyzed and assigned. Utilizing the normal mode model and considering the coupling among CH stretching, bending and rocking vibrations, values of the harmonic frequency wi, the anharmonic constant xij, and the coefficients of Fermi and the Darling-Dennison resonances of v1, v6, v2 and v8 modes were also determined from experimental spectral data with nonlinear least-square fitting. These spectral constants reproduced the experimental levels very well. These results showed that Fermi resonance between CH stretching and rocking vibrations （kiss=-254.63 cm^-1） is stronger than that between CH stretching and bending vibrations （k122 = 54.87 cm^-1 ）; and that Darling-Dennison resonances between CH stretching and bending vibrations （k166=-215.28 cm^-1） is also much stronger than that between CH bending and rocking vibrations （k2288=5.72 cm^-1）.
基金This work was supported by the Planning Subject for the 13th Five-Year Plan of Hunan Provincial Educational Sciences under Grant XJK17BXX006,author D.Y,http://ghkt.hntky.com/.
文摘There is no reasonable scientific basis for selecting the excellent teachers of the school’s courses.To solve the practical problem,we firstly give a series of normalization models for defining the key attributes of teachers’professional foundation,course difficulty coefficient,and comprehensive evaluation of teaching.Then,we define a partial weight function to calculate the key attributes,and obtain the partial recommendation values.Next,we construct a highly sparse Teaching Recommendation Factorization Machines(TRFMs)model,which takes the 5-tuples relation including teacher,course,teachers’professional foundation,course difficulty,teaching evaluation as the feature vector,and take partial recommendation value as the recommendation label.Finally,we design a novel Top-N excellent teacher recommendation algorithm based on TRFMs by course classification on the highly sparse dataset.Experimental results show that the proposed TRFMs and recommendation algorithm can accurately realize the recommendation of excellent teachers on a highly sparse historical teaching dataset.The recommendation accuracy is superior to that of the three-dimensional tensor decomposition model algorithm which also solves sparse datasets.The proposed method can be used as a new recommendation method applied to the teaching arrangements in all kinds of schools,which can effectively improve the teaching quality.
基金Supported by the National Natural Science Foundation of China (No. 10571073)Specialized Research Fund for the Doctoral Program of Higher Education (No. 20070183023)Program for New Century Excellent Talents in University, Scientific Research Fund of Jilin University (No. 200810024)
文摘A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment group than others. Finite mixture models have traditionally been used to describe the distribution of responses in treated subjects for such studies. In this paper, we first study the mixture normal model with multi-levels and multiple mixture sub-populations under each level, with particular attention being given to the model in which the proportions of susceptibility are related to dose levels, then we use EM-algorithm to find the maximum likelihood estimators of model parameters. Our results are generalizations of the existing results. Finally, we illustrate realistic significance of the above extension based on a set of real dose-response data.
基金This study was granted by Guangdong Province Medical Science Research Fund (No. A2002255)
文摘Medical insurance service, the important part of national healthcare supporting system with a history dating back more than 100 years ago, remains a global challenge because of its high rates of compensation and difficulty in risk control. When developing the diabetes related, hospitalization insurance, we found that the risk loss of the diabetic inpatients does not follow a symmetrical unimodal distribution： in fact, it is hard to describe its risk loses distribution with a single probability distribution model. Therefore, we put forward a risk measurement method based on a mixed normal distributions model for medical insurance of inpatients with diabetes.
基金supported by the Hildebrand Foundation,Ken Leonard Fund for Livestock Interactions Research,Harvey Weil Foundation,Comision Nacional de Ciencia y Tecnologia(CONACYT),Houston Safari Club,South Texas Quail Coalition Chapter,Hill Country Quail Coalition,and R.Stacy from Houston,TX.
文摘Background Monitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat.Traditional ground-based sampling methods have been widely used and provide valuable information;however,they are time-consuming,labor-intensive,and limited in their ability to capture larger extents of the spatial and temporal dynamics of rangeland ecosystems.Drones provide a solution to collect data to larger extents than field-based methods and with higher-resolution than traditional remote sensing platforms.Our objectives were to(1)assess the accuracy of vegetation cover height in grasses using drones,(2)quantify the spatial distribution of vegetation cover height in grazed and non-grazed pastures during the dormant(fall-winter)and growing seasons(spring-summer),and(3)evaluate the spatial distribution of vegetation cover height as a proxy for northern bobwhite(Colinusvirginianus)habitat in South Texas.We achieved this by very fine scale drone-derived imagery and using class level landscape metrics to assess vegetation cover height configuration.Results Estimated heights from drone imagery had a significant relationship with the field height measurements in September(r2=0.83;growing season)and February(r^(2)=0.77;dormant season).Growing season pasture maintained residual landscape habitat configuration adequate for bobwhites throughout the fall and winter of 2022-2023 following grazing.Dormant season pasture had an increase in bare ground cover,and a shift from many large patches of tall herbaceous cover(40-120 cm)to few large patches of low herbaceous cover(5-30 cm)(p<0.05).Conclusions Drones provided high-resolution imagery that allowed us to assess the spatial and temporal changes of vertical herbaceous vegetation structure in a semi-arid rangeland subject to grazing.This study shows how drone imagery can be beneficial for wildlife conservation and management by providing insights into changes in fine-scale vegetation spatial and temporal heterogeneity from livestock grazing.
