Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea...Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.展开更多
Wave fields in Bohai Sea from 1985 to 2004 were simulated using SWAN wave model by inputting high-resolution hindcast wind fields dataset. Comparisons of wave heights between simulation and observation show good agree...Wave fields in Bohai Sea from 1985 to 2004 were simulated using SWAN wave model by inputting high-resolution hindcast wind fields dataset. Comparisons of wave heights between simulation and observation show good agreement in general. According to the annual extreme values of simulation, this paper gives wave extreme parameters with different return-period for all computation grids in Bohai sea.展开更多
This paper is aimed at the whole Bohai Sea, as the complement and improvement of wave characteristics and extreme parameters. Wave fields were simulated in the Bohai Sea by using wave model SWAN from 1985 to 2004. The...This paper is aimed at the whole Bohai Sea, as the complement and improvement of wave characteristics and extreme parameters. Wave fields were simulated in the Bohai Sea by using wave model SWAN from 1985 to 2004. The input data based on the hindcast of high-resolution wind fields from RAMS and water level fields from POM, which have been tested and verified well. Comparisons of significant wave heights between simulation and station observations show a good agreement in general. By statistical analysis, the wave characteristics such as significant wave heights, dominant wave directions and their seasonal variations are discussed. In addition, main wave extreme parameters and directional extreme values particularly for 100-year return period are investigated.展开更多
Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machin...Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.展开更多
BACKGROUND: For many years, the extremities of stroke patients are divided into affected side and unaffected side according to clinical symptoms and body signs. Moreover, previous rehabilitation function training is d...BACKGROUND: For many years, the extremities of stroke patients are divided into affected side and unaffected side according to clinical symptoms and body signs. Moreover, previous rehabilitation function training is developed simply aiming to the dysfunction manifested by unaffected extremity. Problems of unaffected extremity are always ignored, such as left- and right- side connection dysfunction, abnormal muscular tension of unaffected side and so on. OBJECTIVE: To observe neurophysiological change characteristics of unaffected extremity of stroke patients with hemiplegia by electromyographical method. DESIGN: Case-control observation. SETTING: First Hospital, Jilin University. PARTICIPANTS: Eighty stroke patients with hemiplegia confirmed by skull CT or MRI, who firstly hospitalized in the Department of Neurology, First Hospital, Jilin University between July 2004 and March 2005, were retrieved. They were scored > 8 points in Glasgow Coma Scale and had stable vital sign. Nineteen normal persons who received healthy examination in the clinic were involved in normal control group. Following the classification criteria of Brunnstrom's Recovery Stages of Stroke (BRSS), 80 stroke patients with hemiplegia were assigned into 3 groups: BRSS Ⅰ-Ⅱ group (n =36), BRSS Ⅲ-Ⅳ group (n =23) and BRSSⅤ-Ⅵ (n =21). METHODS: F-wave parameters of median nerve of unaffected extremity were detected by electromyographical technique. The recording electrode (muscular belly of abductor pollicis brevis) and reference electrode (first finger bone) were connected with grounding electrode. Stimulating electrode was placed in the median part of wrist joint with stimulation intensity of 130% that of threshold stimulation, stimulation frequency of 2 Hz, current pulse width of 0.2 ms, time course of 5 ms and sensitivity of 2 mV. The F-wave of median nerve of affected extremity under the resting stage (static status) and that of unaffected extremity under the maximum resistant contracted state were detected in order. The amplitude and appearance percentage of F wave were recorded. MAIN OUTCOME MEASURES: Comparison of F-wave parameters of median nerve between the unaffected extremity of stroke patients with hemiplegia and the extremity of control subjects under different status. RESULTS: All the patients accomplished the detection, and all of them participated in the final analysis. ①Under dynamic status, the amplitude and appearance percentage of F wave of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group were significantly higher than those in the normal control group, respectively[(0.803 9±0.157 3) mV vs. (0.406 7±0.170 3) mV; (0.856 1±0.266 8)% vs. (0.650 0±0.197 6)%, P < 0.05]. Under static status, there were no significant differences in F-wave parameters of median nerve in the unaffected extremity of patients between BRSS Ⅰ-Ⅱ group and BRSS Ⅴ-Ⅵ group (P > 0.05). ②F-wave parameters of median nerve of unaffected extremity of patients in BRSS Ⅰ-Ⅱ group and BRSS Ⅴ-Ⅵ group under dynamic statewere higher than those under static status, without significant difference (P > 0.05), while the amplitude and appearance percentage of F wave of median nerve of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group under dynamic statewere significantly higher than those under static state[(0.803 9±0.157 3) mV vs. (0.391 7±0.131 6) mV; (0.856 1±0.266 8 )% vs.(0.639 1 ±0.259 4)%,P < 0.05]. ③ There was no significant difference in F wave parameters among groups under static state(P > 0.05). However, under dynamic status, the amplitude and appearance percentage of F wave parameters of median nerve of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group [(0.803 9±0.157 3) mV,(0.856 1±0.266 8)%] were significantly lower than those in the other two groups [(0.395 1±0.148 8),(0.437 1±0.157 6) mV;(0.612 5±0.232 8)%,(0.657 1±0.232 5)%,P < 0.05]. CONCLUSION: With the development of disease condition and the increase of muscular tension at anesthetic side, combination motor of affected extremity is caused following movement and muscular tension enhances to non-anesthetic-side. Therefore, F-wave parameters increase under dynamic status.展开更多
Traditional artificial neural networks (ANN) such as back-propagation neural networks (BPNN) provide good predictions of length-of-day (LOD). However, the determination of network topology is difficult and time ...Traditional artificial neural networks (ANN) such as back-propagation neural networks (BPNN) provide good predictions of length-of-day (LOD). However, the determination of network topology is difficult and time consuming. Therefore, we propose a new type of neural network, extreme learning machine (ELM), to improve the efficiency of LOD predictions. Earth orientation parameters (EOP) C04 time-series provides daily values from International Earth Rotation and Reference Systems Service (IERS), which serves as our database. First, the known predictable effects that can be described by functional models-such as the effects of solid earth, ocean tides, or seasonal atmospheric variations--are removed a priori from the C04 time-series. Only the residuals after the subtraction of a priori model from the observed LOD data (i.e., the irregular and quasi-periodic variations) are employed for training and predictions. The predicted LOD is the sum of a prior extrapolation model and the ELM predictions of the residuals. Different input patterns are discussed and compared to optimize the network solution. The prediction results are analyzed and compared with those obtained by other machine learning-based prediction methods, including BPNN, generalization regression neural networks (GRNN), and adaptive network-based fuzzy inference systems (ANFIS). It is shown that while achieving similar prediction accuracy, the developed method uses much less training time than other methods. Furthermore, to conduct a direct comparison with the existing prediction tech- niques, the mean-absolute-error (MAE) from the proposed method is compared with that from the EOP prediction comparison campaign (EOP PCC). The results indicate that the accuracy of the proposed method is comparable with that of the former techniques. The implementation of the proposed method is simple.展开更多
Objective To investigate the effects of different electromagnetic fields on some haematochemical parameters of circadian rhythms in Sprague-Dawley rats. Methods The study was carried out in 18 male and 18 female rats ...Objective To investigate the effects of different electromagnetic fields on some haematochemical parameters of circadian rhythms in Sprague-Dawley rats. Methods The study was carried out in 18 male and 18 female rats in good health conditions exposed to 50 Hz magnetic sinusoid fields at the intensity of 1000 μT, 100 μT, and 0 μT (control group) respectively, and in 18 male and 18 female rats in good health conditions exposed to 1.8 GHz electromagnetic fields at the intensity of 50 V/m, 25 V/m and 0 V/m (control group), respectively. Following haematochemical parameters for glucose, triglycerides, and total cholesterol were measured. Results Different effects of electromagnetic fields on circadian rhythms of both male and female rats were observed. Different changes occurred in some haematochemical parameters for glucose, triglycerides, and total cholesterol (P〈0.05). Conclusion Exposure to different electromagnetic fields is responsible for the variations of some haematochemical parameters in rats.展开更多
This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. Th...This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.展开更多
The response by the government of Tanzania to food security and poverty alleviation in the Naming’ongo area in Mbozi District has been to develop Naming’ongo irrigation scheme as well as construct a bridge across Ri...The response by the government of Tanzania to food security and poverty alleviation in the Naming’ongo area in Mbozi District has been to develop Naming’ongo irrigation scheme as well as construct a bridge across River Nkana to connect the farms and other parts of the district to facilitate a reliable transportation of the produce to the market. The Australian Water Balance Model that was calibrated by using 10 years data from a nearby sub-catchment of Mbarali. The Naming’ongo Sub-catchment was delineated form a 30 m digital elevation model. The observed rainfall was obtained from Mbozi Meteorological station. The study approximated the peak flows in River Nkana for a return period of 50 years to be slightly above 560 m3/s. This was considered to be adequate for the proposed structure. The study recommends that when undertaking human activities such as deforestation and cultivation an account for soil and environmental conservation should be considered. While it is necessary to establish a monitoring system within the catchment, the designs of future hydraulic structures should incorporate stream flow measuring facilities.展开更多
In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown u...In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown under moving extremes ranked set sampling(MERSS).Explicit mathematical expressions of these estimators and their variances are derived.Their relative efficiencies with respect to the minimum variance unbiased estimators(MVUEs)under simple random sampling(SRS)are compared for the cases of some usual distributions.The numerical results show that the BLUEs under MERSS are significantly more efficient than the MVUEs under SRS.展开更多
基金The project supported by Key Laboratory of Space Ocean Remote Sensing and Application,Ministry of Natural Resources under contract No.2023CFO016the National Natural Science Foundation of China under contract No.61931025+1 种基金the Innovation Fund Project for Graduate Student of China University of Petroleum(East China)the Fundamental Research Funds for the Central Universities under contract No.23CX04042A.
文摘Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.
基金supported by National Nature Science Foundation of China, China National Basic Research Program (Grant No. 2009CB421201)
文摘Wave fields in Bohai Sea from 1985 to 2004 were simulated using SWAN wave model by inputting high-resolution hindcast wind fields dataset. Comparisons of wave heights between simulation and observation show good agreement in general. According to the annual extreme values of simulation, this paper gives wave extreme parameters with different return-period for all computation grids in Bohai sea.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.40976005 and 40930844)
文摘This paper is aimed at the whole Bohai Sea, as the complement and improvement of wave characteristics and extreme parameters. Wave fields were simulated in the Bohai Sea by using wave model SWAN from 1985 to 2004. The input data based on the hindcast of high-resolution wind fields from RAMS and water level fields from POM, which have been tested and verified well. Comparisons of significant wave heights between simulation and station observations show a good agreement in general. By statistical analysis, the wave characteristics such as significant wave heights, dominant wave directions and their seasonal variations are discussed. In addition, main wave extreme parameters and directional extreme values particularly for 100-year return period are investigated.
文摘Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.
文摘BACKGROUND: For many years, the extremities of stroke patients are divided into affected side and unaffected side according to clinical symptoms and body signs. Moreover, previous rehabilitation function training is developed simply aiming to the dysfunction manifested by unaffected extremity. Problems of unaffected extremity are always ignored, such as left- and right- side connection dysfunction, abnormal muscular tension of unaffected side and so on. OBJECTIVE: To observe neurophysiological change characteristics of unaffected extremity of stroke patients with hemiplegia by electromyographical method. DESIGN: Case-control observation. SETTING: First Hospital, Jilin University. PARTICIPANTS: Eighty stroke patients with hemiplegia confirmed by skull CT or MRI, who firstly hospitalized in the Department of Neurology, First Hospital, Jilin University between July 2004 and March 2005, were retrieved. They were scored > 8 points in Glasgow Coma Scale and had stable vital sign. Nineteen normal persons who received healthy examination in the clinic were involved in normal control group. Following the classification criteria of Brunnstrom's Recovery Stages of Stroke (BRSS), 80 stroke patients with hemiplegia were assigned into 3 groups: BRSS Ⅰ-Ⅱ group (n =36), BRSS Ⅲ-Ⅳ group (n =23) and BRSSⅤ-Ⅵ (n =21). METHODS: F-wave parameters of median nerve of unaffected extremity were detected by electromyographical technique. The recording electrode (muscular belly of abductor pollicis brevis) and reference electrode (first finger bone) were connected with grounding electrode. Stimulating electrode was placed in the median part of wrist joint with stimulation intensity of 130% that of threshold stimulation, stimulation frequency of 2 Hz, current pulse width of 0.2 ms, time course of 5 ms and sensitivity of 2 mV. The F-wave of median nerve of affected extremity under the resting stage (static status) and that of unaffected extremity under the maximum resistant contracted state were detected in order. The amplitude and appearance percentage of F wave were recorded. MAIN OUTCOME MEASURES: Comparison of F-wave parameters of median nerve between the unaffected extremity of stroke patients with hemiplegia and the extremity of control subjects under different status. RESULTS: All the patients accomplished the detection, and all of them participated in the final analysis. ①Under dynamic status, the amplitude and appearance percentage of F wave of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group were significantly higher than those in the normal control group, respectively[(0.803 9±0.157 3) mV vs. (0.406 7±0.170 3) mV; (0.856 1±0.266 8)% vs. (0.650 0±0.197 6)%, P < 0.05]. Under static status, there were no significant differences in F-wave parameters of median nerve in the unaffected extremity of patients between BRSS Ⅰ-Ⅱ group and BRSS Ⅴ-Ⅵ group (P > 0.05). ②F-wave parameters of median nerve of unaffected extremity of patients in BRSS Ⅰ-Ⅱ group and BRSS Ⅴ-Ⅵ group under dynamic statewere higher than those under static status, without significant difference (P > 0.05), while the amplitude and appearance percentage of F wave of median nerve of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group under dynamic statewere significantly higher than those under static state[(0.803 9±0.157 3) mV vs. (0.391 7±0.131 6) mV; (0.856 1±0.266 8 )% vs.(0.639 1 ±0.259 4)%,P < 0.05]. ③ There was no significant difference in F wave parameters among groups under static state(P > 0.05). However, under dynamic status, the amplitude and appearance percentage of F wave parameters of median nerve of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group [(0.803 9±0.157 3) mV,(0.856 1±0.266 8)%] were significantly lower than those in the other two groups [(0.395 1±0.148 8),(0.437 1±0.157 6) mV;(0.612 5±0.232 8)%,(0.657 1±0.232 5)%,P < 0.05]. CONCLUSION: With the development of disease condition and the increase of muscular tension at anesthetic side, combination motor of affected extremity is caused following movement and muscular tension enhances to non-anesthetic-side. Therefore, F-wave parameters increase under dynamic status.
基金supported by the West Light Foundation of the Chinese Academy of Sciences
文摘Traditional artificial neural networks (ANN) such as back-propagation neural networks (BPNN) provide good predictions of length-of-day (LOD). However, the determination of network topology is difficult and time consuming. Therefore, we propose a new type of neural network, extreme learning machine (ELM), to improve the efficiency of LOD predictions. Earth orientation parameters (EOP) C04 time-series provides daily values from International Earth Rotation and Reference Systems Service (IERS), which serves as our database. First, the known predictable effects that can be described by functional models-such as the effects of solid earth, ocean tides, or seasonal atmospheric variations--are removed a priori from the C04 time-series. Only the residuals after the subtraction of a priori model from the observed LOD data (i.e., the irregular and quasi-periodic variations) are employed for training and predictions. The predicted LOD is the sum of a prior extrapolation model and the ELM predictions of the residuals. Different input patterns are discussed and compared to optimize the network solution. The prediction results are analyzed and compared with those obtained by other machine learning-based prediction methods, including BPNN, generalization regression neural networks (GRNN), and adaptive network-based fuzzy inference systems (ANFIS). It is shown that while achieving similar prediction accuracy, the developed method uses much less training time than other methods. Furthermore, to conduct a direct comparison with the existing prediction tech- niques, the mean-absolute-error (MAE) from the proposed method is compared with that from the EOP prediction comparison campaign (EOP PCC). The results indicate that the accuracy of the proposed method is comparable with that of the former techniques. The implementation of the proposed method is simple.
文摘Objective To investigate the effects of different electromagnetic fields on some haematochemical parameters of circadian rhythms in Sprague-Dawley rats. Methods The study was carried out in 18 male and 18 female rats in good health conditions exposed to 50 Hz magnetic sinusoid fields at the intensity of 1000 μT, 100 μT, and 0 μT (control group) respectively, and in 18 male and 18 female rats in good health conditions exposed to 1.8 GHz electromagnetic fields at the intensity of 50 V/m, 25 V/m and 0 V/m (control group), respectively. Following haematochemical parameters for glucose, triglycerides, and total cholesterol were measured. Results Different effects of electromagnetic fields on circadian rhythms of both male and female rats were observed. Different changes occurred in some haematochemical parameters for glucose, triglycerides, and total cholesterol (P〈0.05). Conclusion Exposure to different electromagnetic fields is responsible for the variations of some haematochemical parameters in rats.
文摘This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.
文摘The response by the government of Tanzania to food security and poverty alleviation in the Naming’ongo area in Mbozi District has been to develop Naming’ongo irrigation scheme as well as construct a bridge across River Nkana to connect the farms and other parts of the district to facilitate a reliable transportation of the produce to the market. The Australian Water Balance Model that was calibrated by using 10 years data from a nearby sub-catchment of Mbarali. The Naming’ongo Sub-catchment was delineated form a 30 m digital elevation model. The observed rainfall was obtained from Mbozi Meteorological station. The study approximated the peak flows in River Nkana for a return period of 50 years to be slightly above 560 m3/s. This was considered to be adequate for the proposed structure. The study recommends that when undertaking human activities such as deforestation and cultivation an account for soil and environmental conservation should be considered. While it is necessary to establish a monitoring system within the catchment, the designs of future hydraulic structures should incorporate stream flow measuring facilities.
基金supported by National Science Foundation of China (Grant Nos.12261036 and 11901236)Scientific Research Fund of Hunan Provincial Education Department (Grant No.21A0328)+1 种基金Provincial Natural Science Foundation of Hunan (Grant No.2022JJ30469)Young Core Teacher Foundation of Hunan Province (Grant No.[2020]43)。
文摘In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown under moving extremes ranked set sampling(MERSS).Explicit mathematical expressions of these estimators and their variances are derived.Their relative efficiencies with respect to the minimum variance unbiased estimators(MVUEs)under simple random sampling(SRS)are compared for the cases of some usual distributions.The numerical results show that the BLUEs under MERSS are significantly more efficient than the MVUEs under SRS.