An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing...An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.展开更多
Using the trial-error method, for a given wave spectrum, wave trains with different wave groupness, which is defined by the groupness factor GF have been simulated in a flume. The statistic characteristics are analyze...Using the trial-error method, for a given wave spectrum, wave trains with different wave groupness, which is defined by the groupness factor GF have been simulated in a flume. The statistic characteristics are analyzed for some of these wave trains in this paper.展开更多
A data buoy, when moored at the sea, will be influenced by different environmental factors such as wind and wave current. For this reason, the stability of a data buoy is of great importance. This paper describes the ...A data buoy, when moored at the sea, will be influenced by different environmental factors such as wind and wave current. For this reason, the stability of a data buoy is of great importance. This paper describes the analysis and calculation of the stability of a data buoy which has a weight suspended from its bottom under normal working conditions and the influence of the distance from the weight to the bottom of the buoy on the 'righting' ability of the buoy when it is capsized. The paper also provides the curves which show the influence of the size of the weight and the distance from the weight to the bottom of the buoy on the 'righting' ability of the buoy. All these are of great reference value for the design and use of a data buoy at sea and for the design of similar floating bodies. The results from calculations agree with those from the model experiment.展开更多
In this paper the theoretical analysis and calculating method for the maximal impact caused by a jet are presented and the formulas for calculation of the maximal impact of waves acting on the slope are developed. Thr...In this paper the theoretical analysis and calculating method for the maximal impact caused by a jet are presented and the formulas for calculation of the maximal impact of waves acting on the slope are developed. Through the comparison between the results of model tests with a model scale of 1:10 and those of prototype tests conducted in the same way in Big Wave Flume, Hannover, West Germany, the effects of model scale on the measurement of wave impact on slopes are described. In addition, a distribution regularity of the maximal impact pressure is also given.展开更多
In this study, the author will investigate and utilize advanced machine learning models related to two different methodologies to determine the best and most effective way to predict individuals with heart failure and...In this study, the author will investigate and utilize advanced machine learning models related to two different methodologies to determine the best and most effective way to predict individuals with heart failure and cardiovascular diseases. The first methodology involves a list of classification machine learning algorithms, and the second methodology involves the use of a deep learning algorithm known as MLP or Multilayer Perceptrons. Globally, hospitals are dealing with cases related to cardiovascular diseases and heart failure as they are major causes of death, not only for overweight individuals but also for those who do not adopt a healthy diet and lifestyle. Often, heart failures and cardiovascular diseases can be caused by many factors, including cardiomyopathy, high blood pressure, coronary heart disease, and heart inflammation [1]. Other factors, such as irregular shocks or stress, can also contribute to heart failure or a heart attack. While these events cannot be predicted, continuous data from patients’ health can help doctors predict heart failure. Therefore, this data-driven research utilizes advanced machine learning and deep learning techniques to better analyze and manipulate the data, providing doctors with informative decision-making tools regarding a person’s likelihood of experiencing heart failure. In this paper, the author employed advanced data preprocessing and cleaning techniques. Additionally, the dataset underwent testing using two different methodologies to determine the most effective machine-learning technique for producing optimal predictions. The first methodology involved employing a list of supervised classification machine learning algorithms, including Naïve Bayes (NB), KNN, logistic regression, and the SVM algorithm. The second methodology utilized a deep learning (DL) algorithm known as Multilayer Perceptrons (MLPs). This algorithm provided the author with the flexibility to experiment with different layer sizes and activation functions, such as ReLU, logistic (sigmoid), and Tanh. Both methodologies produced optimal models with high-level accuracy rates. The first methodology involves a list of supervised machine learning algorithms, including KNN, SVM, Adaboost, Logistic Regression, Naive Bayes, and Decision Tree algorithms. They achieved accuracy rates of 86%, 89%, 89%, 81%, 79%, and 99%, respectively. The author clearly explained that Decision Tree algorithm is not suitable for the dataset at hand due to overfitting issues. Therefore, it was discarded as an optimal model to be used. However, the latter methodology (Neural Network) demonstrated the most stable and optimal accuracy, achieving over 87% accuracy while adapting well to real-life situations and requiring low computing power overall. A performance assessment and evaluation were carried out based on a confusion matrix report to demonstrate feasibility and performance. The author concluded that the performance of the model in real-life situations can advance not only the medical field of science but also mathematical concepts. Additionally, the advanced preprocessing approach behind the model can provide value to the Data Science community. The model can be further developed by employing various optimization techniques to handle even larger datasets related to heart failures. Furthermore, different neural network algorithms can be tested to explore alternative approaches and yield different results.展开更多
The principle, method and mersuring equipment in studying siltaton in the Lianyun Harbor by using the γ-ray density gauge are described in this paper. From field observation and analyses, some primary principles conc...The principle, method and mersuring equipment in studying siltaton in the Lianyun Harbor by using the γ-ray density gauge are described in this paper. From field observation and analyses, some primary principles concerning the infill rate, the distribution of silt density with depth and the consolidation rate and change of the shear strength of the silt have been found out.展开更多
This paper, based on wave data measured with Type 956 Directional WAVE-TRACK Buoy System at new Dalian Port for a whole year, analyses the properties of the wave frequency spectra, and derives the formula for the freq...This paper, based on wave data measured with Type 956 Directional WAVE-TRACK Buoy System at new Dalian Port for a whole year, analyses the properties of the wave frequency spectra, and derives the formula for the frequency spectrum of wind-waves.展开更多
For load-controlled and displacement-controlled test data of piles cyclically axiallly loaded in clay, the displacement conditions are suggested for determining the shaft capacity. According to the suggested displacem...For load-controlled and displacement-controlled test data of piles cyclically axiallly loaded in clay, the displacement conditions are suggested for determining the shaft capacity. According to the suggested displacement conditions, not only the results of shaft capacity from laboratory model piles are close to those from in-situ piles, but also the results of load-controlled tests are in satisfactory agreement with those of displacement-controlled test. Moreover, based on the test data of laboratory model piles in combination with the test data published, the paper suggests the values of the normalized shaft capacity of piles under a variety of static and cyclic loading combinations.展开更多
A new type of air-ground communication application framework named FACT(framework for air-ground communication technology with weather-modification aircraft)is presented to track and command weather-modification aircr...A new type of air-ground communication application framework named FACT(framework for air-ground communication technology with weather-modification aircraft)is presented to track and command weather-modification aircraft to perform ideal cloud seeding.FACT provides a set of solutions from three perspectives,namely,onboard,onground and air-to-ground,with the core purpose of solving the problems of the rapid exchange of information,contract analysis and identifying potential seeding areas when flight plans and meteorological conditions change.On board,the observed data are processed centrally and transmitted downward through air-to-ground communication.The real-time application and sharing of aircraft detection data are strengthened on the ground,and potential areas of operation are automatically identified based on ground data.The communication between the air and the ground achieves a technical breakthrough by realizing double satellite links,adaptive data transmission and VPN channel encryption.Additionally,an application based on FACT is designed and implemented for the real-time command of weather-modified aircraft.This approach has become the key air-to-ground communication system support for more than 40 Chinese aircraft and the big data service support center of airborne data to ensure improved operation of weather-modification aircraft in China.展开更多
Mass spectrometry-based single-cell proteomics(MS-scP)is attracting tremendous attention because it is now technically feasible to quantify thousands of proteins in minute samples.Since protein amplification is still ...Mass spectrometry-based single-cell proteomics(MS-scP)is attracting tremendous attention because it is now technically feasible to quantify thousands of proteins in minute samples.Since protein amplification is still not possible,technological improvements in MS-scP focus on mini-mizing sample loss while increasing throughput,resolution,and sensitivity,as well as achieving measurement depth,accuracy,and stability comparable to bulk samples.Major advances in MS-sCP have facilitated its application in biological and even medical research.Here,we review the key advancements in MS-SCP technology and discuss the strategies of the typical proteomics workflow to improve MS-SCP analysis from single-cell isolation,sample preparation,and liquid chromatography separation to MS data acquisition and analysis.The review will provide an overall understanding of the development and applications of Ms-scP and inspire more novel ideas regarding the innovation of MS-SCPtechnology.展开更多
This scientific research report focuses on the help of neural networks in fitness promotion.The project background points out that the growth in fitness demand,rich data,technological development,and the popularity of...This scientific research report focuses on the help of neural networks in fitness promotion.The project background points out that the growth in fitness demand,rich data,technological development,and the popularity of smart devices provide conditions for the application of neural networks in fitness promotion.The project content includes learning neural network knowledge,collecting data,and querying information.Through neural networks,personalized finess plan recommendations,4 fitness effect prediction and motivation,assistance from smart fitness equipment,and fitness content recommendation and education can be achieved.The project encounters difficulties such as data collection,content organization,and language expression.Teachers provide help in data collection,content organization,and language improvement.The project gains are reflected in realizing the importance of the rigor and systematicness of scientific research,the spirit of innovative exploration,and the importance of patience and perseverance.At the same time,there is a new understanding of neural networks.Their leaming ability is strong but there are challenges in interpretability,and combining with other technologies can play a greater role.In short,this project shows the potential of neural networks in the field of fitness promotion and the gains and challenges in the scientific research process.展开更多
基金This project supported by the National High-Tech Research and Development Plan (863-804-3)
文摘An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.
文摘Using the trial-error method, for a given wave spectrum, wave trains with different wave groupness, which is defined by the groupness factor GF have been simulated in a flume. The statistic characteristics are analyzed for some of these wave trains in this paper.
文摘A data buoy, when moored at the sea, will be influenced by different environmental factors such as wind and wave current. For this reason, the stability of a data buoy is of great importance. This paper describes the analysis and calculation of the stability of a data buoy which has a weight suspended from its bottom under normal working conditions and the influence of the distance from the weight to the bottom of the buoy on the 'righting' ability of the buoy when it is capsized. The paper also provides the curves which show the influence of the size of the weight and the distance from the weight to the bottom of the buoy on the 'righting' ability of the buoy. All these are of great reference value for the design and use of a data buoy at sea and for the design of similar floating bodies. The results from calculations agree with those from the model experiment.
文摘In this paper the theoretical analysis and calculating method for the maximal impact caused by a jet are presented and the formulas for calculation of the maximal impact of waves acting on the slope are developed. Through the comparison between the results of model tests with a model scale of 1:10 and those of prototype tests conducted in the same way in Big Wave Flume, Hannover, West Germany, the effects of model scale on the measurement of wave impact on slopes are described. In addition, a distribution regularity of the maximal impact pressure is also given.
文摘In this study, the author will investigate and utilize advanced machine learning models related to two different methodologies to determine the best and most effective way to predict individuals with heart failure and cardiovascular diseases. The first methodology involves a list of classification machine learning algorithms, and the second methodology involves the use of a deep learning algorithm known as MLP or Multilayer Perceptrons. Globally, hospitals are dealing with cases related to cardiovascular diseases and heart failure as they are major causes of death, not only for overweight individuals but also for those who do not adopt a healthy diet and lifestyle. Often, heart failures and cardiovascular diseases can be caused by many factors, including cardiomyopathy, high blood pressure, coronary heart disease, and heart inflammation [1]. Other factors, such as irregular shocks or stress, can also contribute to heart failure or a heart attack. While these events cannot be predicted, continuous data from patients’ health can help doctors predict heart failure. Therefore, this data-driven research utilizes advanced machine learning and deep learning techniques to better analyze and manipulate the data, providing doctors with informative decision-making tools regarding a person’s likelihood of experiencing heart failure. In this paper, the author employed advanced data preprocessing and cleaning techniques. Additionally, the dataset underwent testing using two different methodologies to determine the most effective machine-learning technique for producing optimal predictions. The first methodology involved employing a list of supervised classification machine learning algorithms, including Naïve Bayes (NB), KNN, logistic regression, and the SVM algorithm. The second methodology utilized a deep learning (DL) algorithm known as Multilayer Perceptrons (MLPs). This algorithm provided the author with the flexibility to experiment with different layer sizes and activation functions, such as ReLU, logistic (sigmoid), and Tanh. Both methodologies produced optimal models with high-level accuracy rates. The first methodology involves a list of supervised machine learning algorithms, including KNN, SVM, Adaboost, Logistic Regression, Naive Bayes, and Decision Tree algorithms. They achieved accuracy rates of 86%, 89%, 89%, 81%, 79%, and 99%, respectively. The author clearly explained that Decision Tree algorithm is not suitable for the dataset at hand due to overfitting issues. Therefore, it was discarded as an optimal model to be used. However, the latter methodology (Neural Network) demonstrated the most stable and optimal accuracy, achieving over 87% accuracy while adapting well to real-life situations and requiring low computing power overall. A performance assessment and evaluation were carried out based on a confusion matrix report to demonstrate feasibility and performance. The author concluded that the performance of the model in real-life situations can advance not only the medical field of science but also mathematical concepts. Additionally, the advanced preprocessing approach behind the model can provide value to the Data Science community. The model can be further developed by employing various optimization techniques to handle even larger datasets related to heart failures. Furthermore, different neural network algorithms can be tested to explore alternative approaches and yield different results.
文摘The principle, method and mersuring equipment in studying siltaton in the Lianyun Harbor by using the γ-ray density gauge are described in this paper. From field observation and analyses, some primary principles concerning the infill rate, the distribution of silt density with depth and the consolidation rate and change of the shear strength of the silt have been found out.
文摘This paper, based on wave data measured with Type 956 Directional WAVE-TRACK Buoy System at new Dalian Port for a whole year, analyses the properties of the wave frequency spectra, and derives the formula for the frequency spectrum of wind-waves.
基金This project is financially sponsored by the Chinese National Natural Scinece Foundation
文摘For load-controlled and displacement-controlled test data of piles cyclically axiallly loaded in clay, the displacement conditions are suggested for determining the shaft capacity. According to the suggested displacement conditions, not only the results of shaft capacity from laboratory model piles are close to those from in-situ piles, but also the results of load-controlled tests are in satisfactory agreement with those of displacement-controlled test. Moreover, based on the test data of laboratory model piles in combination with the test data published, the paper suggests the values of the normalized shaft capacity of piles under a variety of static and cyclic loading combinations.
基金jointly funded by the National Key R&D Program of China(Grant Number 2018YFC1505702)the project of scientific research on weather modification in Northwest China,research for experimental design and application integration(RYSY201909).
文摘A new type of air-ground communication application framework named FACT(framework for air-ground communication technology with weather-modification aircraft)is presented to track and command weather-modification aircraft to perform ideal cloud seeding.FACT provides a set of solutions from three perspectives,namely,onboard,onground and air-to-ground,with the core purpose of solving the problems of the rapid exchange of information,contract analysis and identifying potential seeding areas when flight plans and meteorological conditions change.On board,the observed data are processed centrally and transmitted downward through air-to-ground communication.The real-time application and sharing of aircraft detection data are strengthened on the ground,and potential areas of operation are automatically identified based on ground data.The communication between the air and the ground achieves a technical breakthrough by realizing double satellite links,adaptive data transmission and VPN channel encryption.Additionally,an application based on FACT is designed and implemented for the real-time command of weather-modified aircraft.This approach has become the key air-to-ground communication system support for more than 40 Chinese aircraft and the big data service support center of airborne data to ensure improved operation of weather-modification aircraft in China.
基金supported by the National Natural Science Foundation of China(Grant No.32371500)the National Key R&D Program of China(Grant No.2022YFA1304500).
文摘Mass spectrometry-based single-cell proteomics(MS-scP)is attracting tremendous attention because it is now technically feasible to quantify thousands of proteins in minute samples.Since protein amplification is still not possible,technological improvements in MS-scP focus on mini-mizing sample loss while increasing throughput,resolution,and sensitivity,as well as achieving measurement depth,accuracy,and stability comparable to bulk samples.Major advances in MS-sCP have facilitated its application in biological and even medical research.Here,we review the key advancements in MS-SCP technology and discuss the strategies of the typical proteomics workflow to improve MS-SCP analysis from single-cell isolation,sample preparation,and liquid chromatography separation to MS data acquisition and analysis.The review will provide an overall understanding of the development and applications of Ms-scP and inspire more novel ideas regarding the innovation of MS-SCPtechnology.
文摘This scientific research report focuses on the help of neural networks in fitness promotion.The project background points out that the growth in fitness demand,rich data,technological development,and the popularity of smart devices provide conditions for the application of neural networks in fitness promotion.The project content includes learning neural network knowledge,collecting data,and querying information.Through neural networks,personalized finess plan recommendations,4 fitness effect prediction and motivation,assistance from smart fitness equipment,and fitness content recommendation and education can be achieved.The project encounters difficulties such as data collection,content organization,and language expression.Teachers provide help in data collection,content organization,and language improvement.The project gains are reflected in realizing the importance of the rigor and systematicness of scientific research,the spirit of innovative exploration,and the importance of patience and perseverance.At the same time,there is a new understanding of neural networks.Their leaming ability is strong but there are challenges in interpretability,and combining with other technologies can play a greater role.In short,this project shows the potential of neural networks in the field of fitness promotion and the gains and challenges in the scientific research process.
