An optical lattice clock based on 87Sr is built at National Institute of Metrology (NIM) of China. The systematic frequency shifts of the clock are evaluated with a total uncertainty of 2.3×10-16. To measure it...An optical lattice clock based on 87Sr is built at National Institute of Metrology (NIM) of China. The systematic frequency shifts of the clock are evaluated with a total uncertainty of 2.3×10-16. To measure its absolute frequency with respect to NIM's cesium fountain clock NIM5, the frequency of a flywheel H-maser of NIM5 is transferred to the Sr laboratory through a 50-kin-long fiber. reference frequency of this H-maser, is used for the optical this Sr clock is measured to be 429228004229873.7(1.4)Hz. A fiber optical frequency comb, phase-locked to the frequency measurement. The absolute frequency of展开更多
With the implementation of new-generation launch vehicles,space stations,lunar and deep space exploration,etc.,the development of spacecraft structures will face new challenges. In order to reduce the spacecraft weigh...With the implementation of new-generation launch vehicles,space stations,lunar and deep space exploration,etc.,the development of spacecraft structures will face new challenges. In order to reduce the spacecraft weight and increase the payload,composite material structures will be widely used. It is difficult to evaluate the strength and life of composite materials due to their complex mechanism and various phenomena in damage and failure.Meanwhile,the structures of composite materials used in spacecrafts will bear complex loads,including the coupling loads of tension,pressure,bending,shear,and torsion. Static loads,thermal loads,and vibration loads may occur at the same time,which asks for verification requirements to ensure the structure safety. Therefore,it is necessary to carry out a systematic multi-level experimental study. In this paper,the building block approach (BBA) is used to investigate the multilevel composite material structures for spacecrafts. The advanced measurement technology is adopted based on digital image correlation (DIC) and piezoelectric and optical fiber sensors to measure the composite material structure deformation. The virtual experiment technology is applied to provide sufficient and reliable data for the evaluation of the composite material structures of spacecrafts.展开更多
JT SQE system is a software quality and measurement system. Its design was based on the Chinese national standards of software product evaluation and quality characteristics. The JT SQE system consists of two parts...JT SQE system is a software quality and measurement system. Its design was based on the Chinese national standards of software product evaluation and quality characteristics. The JT SQE system consists of two parts. One is the model for software quality measurement, which is of hierarchical structure. The other is the process of requirements definition, measurement and rating. The system is a feasible model for software quality evaluation and measurement, and it has the advantage of a friendly user interface, simple operation, ease of revision and maintenance, and expansible measurements.展开更多
Objective To study the mechanism of myocardial dielectric property changes in radio frequency during hypothermic preservation and explore myocardial viability evaluative method. Methods Hybrid young pigs ( 20 - 30 kg)...Objective To study the mechanism of myocardial dielectric property changes in radio frequency during hypothermic preservation and explore myocardial viability evaluative method. Methods Hybrid young pigs ( 20 - 30 kg) were used in the experiment. Heart arrest was in-展开更多
Heart disease prognosis(HDP)is a difficult undertaking that requires knowledge and expertise to predict early on.Heart failure is on the rise as a result of today’s lifestyle.The healthcare business generates a vast ...Heart disease prognosis(HDP)is a difficult undertaking that requires knowledge and expertise to predict early on.Heart failure is on the rise as a result of today’s lifestyle.The healthcare business generates a vast volume of patient records,which are challenging to manage manually.When it comes to data mining and machine learning,having a huge volume of data is crucial for getting meaningful information.Several methods for predictingHDhave been used by researchers over the last few decades,but the fundamental concern remains the uncertainty factor in the output data,aswell as the need to decrease the error rate and enhance the accuracy of HDP assessment measures.However,in order to discover the optimal HDP solution,this study compares multiple classification algorithms utilizing two separate heart disease datasets from the Kaggle repository and the University of California,Irvine(UCI)machine learning repository.In a comparative analysis,Mean Absolute Error(MAE),Relative Absolute Error(RAE),precision,recall,fmeasure,and accuracy are used to evaluate Linear Regression(LR),Decision Tree(J48),Naive Bayes(NB),Artificial Neural Network(ANN),Simple Cart(SC),Bagging,Decision Stump(DS),AdaBoost,Rep Tree(REPT),and Support Vector Machine(SVM).Overall,the SVM classifier surpasses other classifiers in terms of increasing accuracy and decreasing error rate,with RAE of 33.2631 andMAEof 0.165,the precision of 0.841,recall of 0.835,f-measure of 0.833,and accuracy of 83.49 percent for the dataset gathered from UCI.The SC improves accuracy and reduces the error rate for the Kaggle dataset,which is 3.30%for RAE,0.016 percent for MAE,0.984%for precision,0.984 percent for recall,0.984 percent for f-measure,and 98.44%for accuracy.展开更多
This article attempts to investigate the measure effect of rubble roadbed engineering in permafrost regions of Qinghai-Tibet Plateau. As a case study, Chaidaer-Muli Railway is used to evaluate the measure effect of ru...This article attempts to investigate the measure effect of rubble roadbed engineering in permafrost regions of Qinghai-Tibet Plateau. As a case study, Chaidaer-Muli Railway is used to evaluate the measure effect of rubble roadbed engineering in permafrost regions. The AHP(Analytic Hierarchy Process) method is thus employed to establish the evaluation indicator system. The evaluation factor is selected by analyzing the mutual relation between the permafrost environment and roadbed engineering. Thus, a hierarchical structure model is established based on the selected evaluation indices. Each factor is weighted to determine the status in the evaluation system, and grading standards are built for providing a basis for the evaluation. Then, the fuzzy mathematical method is introduced to evaluate the measure effect of rubble roadbed engineering in permafrost regions along the Chadaer-Muli Railway. Results show that most of the permafrost roadbed is in a preferable condition(b) along the Chaidaer-Muli Railway due to rubble engineering measures. This proportion reaches to 86.1%. The proportion in good(a), general(c) and poor states(d) are 0.0%, 7.5% and 6.4%, respectively, in all the evaluation sections along the Chaidaer-Muli Railway. Ground-temperature monitoring results are generally consistent with AHP-FUZZY evaluation results. This means that the AHP-FUZZY method can be applied to evaluate the effect of rubble roadbed engineering measures in permafrost regions. The effect evaluation of engineering measures will provide timely and effective feedback information for further engineering design. The series of engineering measures will more effectively protect permafrost stability.展开更多
Electroless nickel(EN)plating can give rise to the severe galvanic corrosion of the magnesium(Mg)alloy matrix,owing to its nobler electrochemical potential than Mg alloy.To hinder the formation of galvanic couple,an i...Electroless nickel(EN)plating can give rise to the severe galvanic corrosion of the magnesium(Mg)alloy matrix,owing to its nobler electrochemical potential than Mg alloy.To hinder the formation of galvanic couple,an intermediate phosphate conversion coating(PCC)layer is introduced between the EN layer and the Mg alloy matrix.Since the ceramic-like PCC layer cannot be catalyzed,a low-cost Ag-activation technique is used to process the PCC layer before electroless plating.The cross-section morphology and element distribution of the PCC-EN composite coating indicate that the PCC intermediate layer can effectively separate the Mg alloy from the EN layer.Moreover,the results of electrochemical tests suggest that the PCC-EN composite coating has a better corrosion resistance in comparison with the EN coating and AZ91D Mg alloy.展开更多
Based on human perception and machine learning methods,this study proposes a measurable method for evaluating visual comfort in underground spaces.First,a comfort evaluation index based on the characteristics of human...Based on human perception and machine learning methods,this study proposes a measurable method for evaluating visual comfort in underground spaces.First,a comfort evaluation index based on the characteristics of human visual perception is proposed,and color features and segmentation extraction methods for intelligent methods are given.Then,using probability statistics and machine learning methods,a multi-class intelligent sorting and classification algorithm for ranking visual comfort levels is constructed and a comparison is made of the suitability of different intelligent methods for evaluating visual comfort.The random forest algorithm is then selected as the most effective measurable intelligent evaluation algorithm for underground spaces.Finally,the proposed method is compared to intelligent methods employed by previous research,and a case study,the Wujiaochang underground space in Shanghai,China,is applied as the background.Results show that the proposed method can effectively improve the quantification and refinement of human perception and evaluation of comfort in underground spaces;this method will also be useful in computer-aided generative design in the future.展开更多
An objective visual performance evaluation with visual evoked potential (VEP) measurements was first inte- grated into an adaptive optics (AO) system. The optical and neural limits to vision can be bypassed throug...An objective visual performance evaluation with visual evoked potential (VEP) measurements was first inte- grated into an adaptive optics (AO) system. The optical and neural limits to vision can be bypassed through this system. Visual performance can be measured electrophysiologically with VEP, which reflects the objective func- tion from the retina to the primary visual cortex. The VEP ts without and with AO correction were preliminarily carried out using this system, demonstrating the great potential of this system in the objective visual performance evaluation. The new system will provide the necessary technique and equipment support for the further study of human visual function.展开更多
The large number of new bug reports received in bug repositories of software systems makes their management a challenging task.Handling these reports manually is time consuming,and often results in delaying the resolu...The large number of new bug reports received in bug repositories of software systems makes their management a challenging task.Handling these reports manually is time consuming,and often results in delaying the resolution of important bugs.To address this issue,a recommender may be developed which automatically prioritizes the new bug reports.In this paper,we propose and evaluate a classification based approach to build such a recommender.We use the Na¨ ve Bayes and Support Vector Machine (SVM) classifiers,and present a comparison to evaluate which classifier performs better in terms of accuracy.Since a bug report contains both categorical and text features,another evaluation we perform is to determine the combination of features that better determines the priority of a bug.To evaluate the bug priority recommender,we use precision and recall measures and also propose two new measures,Nearest False Negatives (NFN) and Nearest False Positives (NFP),which provide insight into the results produced by precision and recall.Our findings are that the results of SVM are better than the Na¨ ve Bayes algorithm for text features,whereas for categorical features,Na¨ ve Bayes performance is better than SVM.The highest accuracy is achieved with SVM when categorical and text features are combined for training.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 91336212 and 91436104
文摘An optical lattice clock based on 87Sr is built at National Institute of Metrology (NIM) of China. The systematic frequency shifts of the clock are evaluated with a total uncertainty of 2.3×10-16. To measure its absolute frequency with respect to NIM's cesium fountain clock NIM5, the frequency of a flywheel H-maser of NIM5 is transferred to the Sr laboratory through a 50-kin-long fiber. reference frequency of this H-maser, is used for the optical this Sr clock is measured to be 429228004229873.7(1.4)Hz. A fiber optical frequency comb, phase-locked to the frequency measurement. The absolute frequency of
文摘With the implementation of new-generation launch vehicles,space stations,lunar and deep space exploration,etc.,the development of spacecraft structures will face new challenges. In order to reduce the spacecraft weight and increase the payload,composite material structures will be widely used. It is difficult to evaluate the strength and life of composite materials due to their complex mechanism and various phenomena in damage and failure.Meanwhile,the structures of composite materials used in spacecrafts will bear complex loads,including the coupling loads of tension,pressure,bending,shear,and torsion. Static loads,thermal loads,and vibration loads may occur at the same time,which asks for verification requirements to ensure the structure safety. Therefore,it is necessary to carry out a systematic multi-level experimental study. In this paper,the building block approach (BBA) is used to investigate the multilevel composite material structures for spacecrafts. The advanced measurement technology is adopted based on digital image correlation (DIC) and piezoelectric and optical fiber sensors to measure the composite material structure deformation. The virtual experiment technology is applied to provide sufficient and reliable data for the evaluation of the composite material structures of spacecrafts.
文摘JT SQE system is a software quality and measurement system. Its design was based on the Chinese national standards of software product evaluation and quality characteristics. The JT SQE system consists of two parts. One is the model for software quality measurement, which is of hierarchical structure. The other is the process of requirements definition, measurement and rating. The system is a feasible model for software quality evaluation and measurement, and it has the advantage of a friendly user interface, simple operation, ease of revision and maintenance, and expansible measurements.
文摘Objective To study the mechanism of myocardial dielectric property changes in radio frequency during hypothermic preservation and explore myocardial viability evaluative method. Methods Hybrid young pigs ( 20 - 30 kg) were used in the experiment. Heart arrest was in-
基金Authors would like to acknowledge the support of the Deputy for Research and Innovation-Ministry of Education,Kingdom of Saudi Arabia for this research at Najran University,Kingdom of Saudi Arabia.
文摘Heart disease prognosis(HDP)is a difficult undertaking that requires knowledge and expertise to predict early on.Heart failure is on the rise as a result of today’s lifestyle.The healthcare business generates a vast volume of patient records,which are challenging to manage manually.When it comes to data mining and machine learning,having a huge volume of data is crucial for getting meaningful information.Several methods for predictingHDhave been used by researchers over the last few decades,but the fundamental concern remains the uncertainty factor in the output data,aswell as the need to decrease the error rate and enhance the accuracy of HDP assessment measures.However,in order to discover the optimal HDP solution,this study compares multiple classification algorithms utilizing two separate heart disease datasets from the Kaggle repository and the University of California,Irvine(UCI)machine learning repository.In a comparative analysis,Mean Absolute Error(MAE),Relative Absolute Error(RAE),precision,recall,fmeasure,and accuracy are used to evaluate Linear Regression(LR),Decision Tree(J48),Naive Bayes(NB),Artificial Neural Network(ANN),Simple Cart(SC),Bagging,Decision Stump(DS),AdaBoost,Rep Tree(REPT),and Support Vector Machine(SVM).Overall,the SVM classifier surpasses other classifiers in terms of increasing accuracy and decreasing error rate,with RAE of 33.2631 andMAEof 0.165,the precision of 0.841,recall of 0.835,f-measure of 0.833,and accuracy of 83.49 percent for the dataset gathered from UCI.The SC improves accuracy and reduces the error rate for the Kaggle dataset,which is 3.30%for RAE,0.016 percent for MAE,0.984%for precision,0.984 percent for recall,0.984 percent for f-measure,and 98.44%for accuracy.
基金supported by the National Natural Science Foundation of China (Nos. 41501079 and 91647103)the self-determined Project Funded by State Key Laboratory of Frozen Soil Engineering (No. SKLFSE-ZQ-43)the Foundation for Excellent Youth Scholars of NIEER, CAS
文摘This article attempts to investigate the measure effect of rubble roadbed engineering in permafrost regions of Qinghai-Tibet Plateau. As a case study, Chaidaer-Muli Railway is used to evaluate the measure effect of rubble roadbed engineering in permafrost regions. The AHP(Analytic Hierarchy Process) method is thus employed to establish the evaluation indicator system. The evaluation factor is selected by analyzing the mutual relation between the permafrost environment and roadbed engineering. Thus, a hierarchical structure model is established based on the selected evaluation indices. Each factor is weighted to determine the status in the evaluation system, and grading standards are built for providing a basis for the evaluation. Then, the fuzzy mathematical method is introduced to evaluate the measure effect of rubble roadbed engineering in permafrost regions along the Chadaer-Muli Railway. Results show that most of the permafrost roadbed is in a preferable condition(b) along the Chaidaer-Muli Railway due to rubble engineering measures. This proportion reaches to 86.1%. The proportion in good(a), general(c) and poor states(d) are 0.0%, 7.5% and 6.4%, respectively, in all the evaluation sections along the Chaidaer-Muli Railway. Ground-temperature monitoring results are generally consistent with AHP-FUZZY evaluation results. This means that the AHP-FUZZY method can be applied to evaluate the effect of rubble roadbed engineering measures in permafrost regions. The effect evaluation of engineering measures will provide timely and effective feedback information for further engineering design. The series of engineering measures will more effectively protect permafrost stability.
基金the National Natural Science Foundation of China(Nos.51771050 and 51531007)the Liaoning Revitalization Talents Program of China(No.XLYC2002071)the Shanghai Aerospace Science and Technology Innovation Fund of China(No.SAST2020-046)。
文摘Electroless nickel(EN)plating can give rise to the severe galvanic corrosion of the magnesium(Mg)alloy matrix,owing to its nobler electrochemical potential than Mg alloy.To hinder the formation of galvanic couple,an intermediate phosphate conversion coating(PCC)layer is introduced between the EN layer and the Mg alloy matrix.Since the ceramic-like PCC layer cannot be catalyzed,a low-cost Ag-activation technique is used to process the PCC layer before electroless plating.The cross-section morphology and element distribution of the PCC-EN composite coating indicate that the PCC intermediate layer can effectively separate the Mg alloy from the EN layer.Moreover,the results of electrochemical tests suggest that the PCC-EN composite coating has a better corrosion resistance in comparison with the EN coating and AZ91D Mg alloy.
基金supported by the National Key Special Project(2018YFC0808702)National Natural Science Foundation of China(52038008)Shanghai Science and Technology Commission Innovation Action Plan(20dz1202406).
文摘Based on human perception and machine learning methods,this study proposes a measurable method for evaluating visual comfort in underground spaces.First,a comfort evaluation index based on the characteristics of human visual perception is proposed,and color features and segmentation extraction methods for intelligent methods are given.Then,using probability statistics and machine learning methods,a multi-class intelligent sorting and classification algorithm for ranking visual comfort levels is constructed and a comparison is made of the suitability of different intelligent methods for evaluating visual comfort.The random forest algorithm is then selected as the most effective measurable intelligent evaluation algorithm for underground spaces.Finally,the proposed method is compared to intelligent methods employed by previous research,and a case study,the Wujiaochang underground space in Shanghai,China,is applied as the background.Results show that the proposed method can effectively improve the quantification and refinement of human perception and evaluation of comfort in underground spaces;this method will also be useful in computer-aided generative design in the future.
基金supported by the National Natural Science Foundation of China (No. 61378064)the National High Technology Research and Development Program of China (No. 2015AA020510)
文摘An objective visual performance evaluation with visual evoked potential (VEP) measurements was first inte- grated into an adaptive optics (AO) system. The optical and neural limits to vision can be bypassed through this system. Visual performance can be measured electrophysiologically with VEP, which reflects the objective func- tion from the retina to the primary visual cortex. The VEP ts without and with AO correction were preliminarily carried out using this system, demonstrating the great potential of this system in the objective visual performance evaluation. The new system will provide the necessary technique and equipment support for the further study of human visual function.
基金The paper is based on the word under the Chinese Academy of Social Sciences major research projict "Strdy of the Interaction of Industrialization , Industrialization and Industrial Modernization"
文摘The large number of new bug reports received in bug repositories of software systems makes their management a challenging task.Handling these reports manually is time consuming,and often results in delaying the resolution of important bugs.To address this issue,a recommender may be developed which automatically prioritizes the new bug reports.In this paper,we propose and evaluate a classification based approach to build such a recommender.We use the Na¨ ve Bayes and Support Vector Machine (SVM) classifiers,and present a comparison to evaluate which classifier performs better in terms of accuracy.Since a bug report contains both categorical and text features,another evaluation we perform is to determine the combination of features that better determines the priority of a bug.To evaluate the bug priority recommender,we use precision and recall measures and also propose two new measures,Nearest False Negatives (NFN) and Nearest False Positives (NFP),which provide insight into the results produced by precision and recall.Our findings are that the results of SVM are better than the Na¨ ve Bayes algorithm for text features,whereas for categorical features,Na¨ ve Bayes performance is better than SVM.The highest accuracy is achieved with SVM when categorical and text features are combined for training.