The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on regression analysis indicates...The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on regression analysis indicates its importance as a statistical method that helps researchers understand relationships between variables and make predictions based on data. The inclusion of multiple disciplines, such as health sciences, social sciences, environmental studies, economics, engineering, clinical psychology, social psychology, developmental psychology, cognitive psychology, and education highlights the interdisciplinary relevance of regression analysis. This breadth suggests that the findings and methodologies discussed in the paper may have wide applications, benefiting various sectors by enhancing the quality of research outcomes. The mention of “methodologies and data analysis techniques” indicates that the paper will likely delve into specific statistical approaches, offering a comprehensive examination of how regression analysis is applied in real-world scenarios. This nuance is essential, as it demonstrates the research’s commitment to not only presenting theoretical insights but also practical applications. Furthermore, the abstract states that regression analysis “enhances the validity of findings” and “informs data-driven decision-making.” This assertion underlines the critical role that robust statistical methods play in ensuring that research conclusions are reliable and applicable. The ability of regression analysis to provide clarity and support informed decisions makes it a valuable tool in both academic and professional settings. The abstract effectively outlines the paper’s exploration of regression analysis in various fields, underscoring its importance in enhancing research validity and facilitating informed decision-making. The interdisciplinary nature of the research broadens its appeal and emphasizes the need for rigorous statistical approaches in addressing complex issues across different domains.展开更多
In the new era,the impact of emerging productive forces has permeated every sector of industry.As the core production factor of these forces,data plays a pivotal role in industrial transformation and social developmen...In the new era,the impact of emerging productive forces has permeated every sector of industry.As the core production factor of these forces,data plays a pivotal role in industrial transformation and social development.Consequently,many domestic universities have introduced majors or courses related to big data.Among these,the Big Data Management and Applications major stands out for its interdisciplinary approach and emphasis on practical skills.However,as an emerging field,it has not yet accumulated a robust foundation in teaching theory and practice.Current instructional practices face issues such as unclear training objectives,inconsistent teaching methods and course content,insufficient integration of practical components,and a shortage of qualified faculty-factors that hinder both the development of the major and the overall quality of education.Taking the statistics course within the Big Data Management and Applications major as an example,this paper examines the challenges faced by statistics education in the context of emerging productive forces and proposes corresponding improvement measures.By introducing innovative teaching concepts and strategies,the teaching system for professional courses is optimized,and authentic classroom scenarios are recreated through illustrative examples.Questionnaire surveys and statistical analyses of data collected before and after the teaching reforms indicate that the curriculum changes effectively enhance instructional outcomes,promote the development of the major,and improve the quality of talent cultivation.展开更多
随着锂电池领域论文数量的激增和研究主题的日益丰富,准确监测该领域的发展趋势和把握最新研究动向变得日益复杂。通过运用大数据和机器学习技术,采用BERTopic主题模型对Web of Science数据库中的18万余篇锂电池论文进行文本分析,绘制...随着锂电池领域论文数量的激增和研究主题的日益丰富,准确监测该领域的发展趋势和把握最新研究动向变得日益复杂。通过运用大数据和机器学习技术,采用BERTopic主题模型对Web of Science数据库中的18万余篇锂电池论文进行文本分析,绘制了锂电池领域的主题图,识别了新兴研究主题和高被引主题。结果表明,锂电池研究活动正显著加速,锂硫电池、锂枝晶生长抑制、电池回收和金属回收等新兴主题快速发展,而材料研究如二硫化钼纳米材料、氧化铁电极材料则具有显著的高学术影响力。研究还探讨了《锂电池百篇论文点评系列》对当前锂电池研究主题的监测情况,该系列对多数科学技术主题有良好覆盖。本研究为锂电池领域的主题监测提供了新方法,为政策制定和技术研发提供了情报支持,并为“锂电池百篇论文点评”系列的后续研究提供了参考。展开更多
Objective: To explore the application effect of CBL combined with rain classroom teaching method in medical statistics courses. Methods: The undergraduate students of medical imaging technology in 2019 and 2020 in a u...Objective: To explore the application effect of CBL combined with rain classroom teaching method in medical statistics courses. Methods: The undergraduate students of medical imaging technology in 2019 and 2020 in a university were selected as the research objects. A cluster sampling method was used to select 79 undergraduate students from 2019 in the control group and 75 undergraduate students from 2020 in the experimental group. Traditional teaching method and CBL combined with rain classroom teaching method was used in the control group and experimental group respectively. The final examination scores of the two groups were compared. In experimental group, the correlation between the average score in the rain classroom and the final examination score was tested, and the teaching effect was evaluated. Results: The average score of final examination in experimental group and control group was 79.13 ± 10.32 points and 71.54 ± 14.752 points, respectively, which had a statistically significant difference (Z = 2.586, P = 0.012);the final examination scores of the students in the experimental group were positively correlated with the average scores of the rain classroom (r = 0.372, P = 0.001), and the proportion of satisfaction in the experimental group was 94.7%. Conclusion: The CBL combined with rain classroom teaching method can improve the teaching effectiveness of medical statistics courses.展开更多
The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typica...The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typically random and unpredictable. Some people use the lottery terminal randomly generates numbers for them, some players choose numbers that hold personal significance to them, such as birthdays, anniversaries, or other important dates, some enthusiasts have turned to statistical analysis as a means to analyze past winning numbers identify patterns or frequencies. In this paper, we use order statistics to estimate the probability of specific order of numbers or number combinations being drawn in future drawings.展开更多
In today's world where everything is interconnected, air-space-ground integrated networks have become a current research hotspot due to their characteristics of high, long and wide area coverage. Given the constan...In today's world where everything is interconnected, air-space-ground integrated networks have become a current research hotspot due to their characteristics of high, long and wide area coverage. Given the constantly changing and dynamic characteristics of air and space networks, along with the sheer number and complexity of access nodes involved, the process of rapid networking presents substantial challenges. In order to achieve rapid and dynamic networking of air-space-ground integrated networks, this paper focuses on the study of methods for large-scale nodes to randomly access satellites. This paper utilizes a cross-layer design methodology to enhance the access success probability by jointly optimizing the physical layer and medium access control(MAC) layer aspects. Load statistics priority random access(LSPRA) technology is proposed.Experiments show that when the number of nodes is greater than 1 000, this method can also ensure stable access performance, providing ideas for the design of air-space-ground integrated network access systems.展开更多
The Bureau of Statistics has demonstrated a forward-looking strategic approach in its economic census.By leveraging dual innovations in technology and management,and incorporating modern technologies such as big data,...The Bureau of Statistics has demonstrated a forward-looking strategic approach in its economic census.By leveraging dual innovations in technology and management,and incorporating modern technologies such as big data,cloud computing,and the Internet of Things,it has deepened the reform of the census methodology.Additionally,the Bureau has built a multi-dimensional collaborative network that enhances international cooperation,departmental coordination,and public participation.This approach not only addresses the limitations of traditional statistical methods in a complex economic environment but also improves data quality and census efficiency,providing an accurate and reliable foundation for national economic decision-making.展开更多
To cultivate talents with an exploratory spirit and practical skills in the era of information technology,it is imperative to reform teaching methods and approaches.In the teaching process of the Probability and Stati...To cultivate talents with an exploratory spirit and practical skills in the era of information technology,it is imperative to reform teaching methods and approaches.In the teaching process of the Probability and Statistics course,an application-oriented blended teaching model combining problem-based learning and small private online course was explored.By organizing and implementing online and offline teaching activities based on problem-based learning,a multidimensional process-oriented learning assessment system was established.Practice has shown that this model can effectively enhance classroom teaching effectiveness,benefiting the improvement of students’overall skills and mathematical literacy.展开更多
With the rapid development of higher education in China,colleges and universities are facing new challenges and impacts in talent training.Probability Theory and Mathematical Statistics is one of the important courses...With the rapid development of higher education in China,colleges and universities are facing new challenges and impacts in talent training.Probability Theory and Mathematical Statistics is one of the important courses in higher education for science and engineering majors and economics and management majors.Its critical role in cultivating students’thinking skills and improving their problem-solving skills is self-evident.Course ideological and political education construction is an important link in college talent training work.Combining ideological and political education with course teaching can help students establish correct value concepts and play a certain role in improving their comprehensive ability and quality.At present,the construction of ideological and political education in the Probability Theory and Mathematical Statistics course still faces some problems,mainly manifested in the lack of attention paid by teachers to course ideological and political education,insufficient exploitation of ideological and political elements,and the simplification of ideological and political education implementation methods.In order to comprehensively deepen the construction of course ideological and political education in line with the actual needs of Probability Theory and Mathematical Statistics course teaching,we should strengthen the construction of teacher teams,improve teachers’ability to carry out course ideological and political education,integrate educational resources,develop educational resources for ideological and political education,and innovate teaching methods to improve the overall effect of ideological and political education integration.展开更多
目的/意义探究近十年(2014-2023年)医学人工智能领域的研究主题及其发展趋势,为相关研究决策提供参考。方法/过程从PubMed和Web of Science数据库中获取2014-2023年医学人工智能相关文献题录152398条,使用BERTopic模型挖掘文献的研究主...目的/意义探究近十年(2014-2023年)医学人工智能领域的研究主题及其发展趋势,为相关研究决策提供参考。方法/过程从PubMed和Web of Science数据库中获取2014-2023年医学人工智能相关文献题录152398条,使用BERTopic模型挖掘文献的研究主题,并依据文献信息逻辑增长规律,划分医学人工智能发展阶段,进而分析研究主题的演化特征。结果/结论医学人工智能领域包含生物信息分析、外科手术机器人、医学影像分析等22个主要研究方向。深度学习技术突破、医疗需求增长以及突发公共卫生事件等多重因素共同推动医学人工智能研究的持续扩展和深化。近年来生成式人工智能为医学人工智能领域研究注入新的活力。展开更多
In this study,the gradients of Total Electron Content(TEC)for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations,time periods within a day,and satellite directions...In this study,the gradients of Total Electron Content(TEC)for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations,time periods within a day,and satellite directions.Annual medians of these gradients for quiet days are computed as templates.The metric distances(L2N)and Symmetric Kullback-Leibler Distances(SKLD)are obtained between the templates and the daily gradient series.The grouped histograms are fitted to the prospective Probability Density Functions(PDF).The method is applied to the Slant Total Electron Content(STEC)estimates from the Turkish National Permanent GPS Network(TNPGN-Active)for 2015.The highest gradients are observed in the east-west axis with a maximum of 25 mm/km during a geomagnetic storm.The maximum differences from the gradient templates occur for neighboring stations within100-130 km distance away from each other,during night hours,and for regions bordering the Black Sea and the Mediterranean in the northeast and southeast of Turkey.The empirical PDFs of the stationpair gradients are predominantly Weibull-distributed.The mean values of Weibull PDFs in all station groups are between 1.2 and 1.8 mm/km,with an increase during noon and afternoon hours.The standard deviations of the gradient PDFs generally increase during night hours.The algorithm will form a basis for quantifying the stochastic variations of the spatial rate of change of TEC trends in midlatitude regions,thus supplementing reliable and accurate regional monitoring of ionospheric variability.展开更多
Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome th...Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.展开更多
Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a ...Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.展开更多
[目的/意义]旨在为在线教育的发展提供参考。[方法/过程]检索Web of Science(WoS)核心数据库关于在线教育的文献(保留摘要以Excel格式导出),运用BERTopic模型进行热点主题抽取,进而对在线教育领域主题进行分析。[结果/结论]BERTopic模...[目的/意义]旨在为在线教育的发展提供参考。[方法/过程]检索Web of Science(WoS)核心数据库关于在线教育的文献(保留摘要以Excel格式导出),运用BERTopic模型进行热点主题抽取,进而对在线教育领域主题进行分析。[结果/结论]BERTopic模型自动生成145个主题(未经干扰),经过归纳和筛选共得到四个主题,即主题1在线教育底层技术研究、主题2在线教学研究、主题3创造思维培养以及主题4在线学习研究。目前元宇宙的出现促进了在线教育的发展,给在线教育提供了沉浸式的学习环境。同时,在线教育促进了学生的个性化发展,在一定程度上弥补了教育不公平。展开更多
Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and ideal...Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.展开更多
文摘The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on regression analysis indicates its importance as a statistical method that helps researchers understand relationships between variables and make predictions based on data. The inclusion of multiple disciplines, such as health sciences, social sciences, environmental studies, economics, engineering, clinical psychology, social psychology, developmental psychology, cognitive psychology, and education highlights the interdisciplinary relevance of regression analysis. This breadth suggests that the findings and methodologies discussed in the paper may have wide applications, benefiting various sectors by enhancing the quality of research outcomes. The mention of “methodologies and data analysis techniques” indicates that the paper will likely delve into specific statistical approaches, offering a comprehensive examination of how regression analysis is applied in real-world scenarios. This nuance is essential, as it demonstrates the research’s commitment to not only presenting theoretical insights but also practical applications. Furthermore, the abstract states that regression analysis “enhances the validity of findings” and “informs data-driven decision-making.” This assertion underlines the critical role that robust statistical methods play in ensuring that research conclusions are reliable and applicable. The ability of regression analysis to provide clarity and support informed decisions makes it a valuable tool in both academic and professional settings. The abstract effectively outlines the paper’s exploration of regression analysis in various fields, underscoring its importance in enhancing research validity and facilitating informed decision-making. The interdisciplinary nature of the research broadens its appeal and emphasizes the need for rigorous statistical approaches in addressing complex issues across different domains.
文摘In the new era,the impact of emerging productive forces has permeated every sector of industry.As the core production factor of these forces,data plays a pivotal role in industrial transformation and social development.Consequently,many domestic universities have introduced majors or courses related to big data.Among these,the Big Data Management and Applications major stands out for its interdisciplinary approach and emphasis on practical skills.However,as an emerging field,it has not yet accumulated a robust foundation in teaching theory and practice.Current instructional practices face issues such as unclear training objectives,inconsistent teaching methods and course content,insufficient integration of practical components,and a shortage of qualified faculty-factors that hinder both the development of the major and the overall quality of education.Taking the statistics course within the Big Data Management and Applications major as an example,this paper examines the challenges faced by statistics education in the context of emerging productive forces and proposes corresponding improvement measures.By introducing innovative teaching concepts and strategies,the teaching system for professional courses is optimized,and authentic classroom scenarios are recreated through illustrative examples.Questionnaire surveys and statistical analyses of data collected before and after the teaching reforms indicate that the curriculum changes effectively enhance instructional outcomes,promote the development of the major,and improve the quality of talent cultivation.
文摘随着锂电池领域论文数量的激增和研究主题的日益丰富,准确监测该领域的发展趋势和把握最新研究动向变得日益复杂。通过运用大数据和机器学习技术,采用BERTopic主题模型对Web of Science数据库中的18万余篇锂电池论文进行文本分析,绘制了锂电池领域的主题图,识别了新兴研究主题和高被引主题。结果表明,锂电池研究活动正显著加速,锂硫电池、锂枝晶生长抑制、电池回收和金属回收等新兴主题快速发展,而材料研究如二硫化钼纳米材料、氧化铁电极材料则具有显著的高学术影响力。研究还探讨了《锂电池百篇论文点评系列》对当前锂电池研究主题的监测情况,该系列对多数科学技术主题有良好覆盖。本研究为锂电池领域的主题监测提供了新方法,为政策制定和技术研发提供了情报支持,并为“锂电池百篇论文点评”系列的后续研究提供了参考。
文摘Objective: To explore the application effect of CBL combined with rain classroom teaching method in medical statistics courses. Methods: The undergraduate students of medical imaging technology in 2019 and 2020 in a university were selected as the research objects. A cluster sampling method was used to select 79 undergraduate students from 2019 in the control group and 75 undergraduate students from 2020 in the experimental group. Traditional teaching method and CBL combined with rain classroom teaching method was used in the control group and experimental group respectively. The final examination scores of the two groups were compared. In experimental group, the correlation between the average score in the rain classroom and the final examination score was tested, and the teaching effect was evaluated. Results: The average score of final examination in experimental group and control group was 79.13 ± 10.32 points and 71.54 ± 14.752 points, respectively, which had a statistically significant difference (Z = 2.586, P = 0.012);the final examination scores of the students in the experimental group were positively correlated with the average scores of the rain classroom (r = 0.372, P = 0.001), and the proportion of satisfaction in the experimental group was 94.7%. Conclusion: The CBL combined with rain classroom teaching method can improve the teaching effectiveness of medical statistics courses.
文摘The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typically random and unpredictable. Some people use the lottery terminal randomly generates numbers for them, some players choose numbers that hold personal significance to them, such as birthdays, anniversaries, or other important dates, some enthusiasts have turned to statistical analysis as a means to analyze past winning numbers identify patterns or frequencies. In this paper, we use order statistics to estimate the probability of specific order of numbers or number combinations being drawn in future drawings.
基金supported by the National Natural Science Foundation of China (No. 62027801)。
文摘In today's world where everything is interconnected, air-space-ground integrated networks have become a current research hotspot due to their characteristics of high, long and wide area coverage. Given the constantly changing and dynamic characteristics of air and space networks, along with the sheer number and complexity of access nodes involved, the process of rapid networking presents substantial challenges. In order to achieve rapid and dynamic networking of air-space-ground integrated networks, this paper focuses on the study of methods for large-scale nodes to randomly access satellites. This paper utilizes a cross-layer design methodology to enhance the access success probability by jointly optimizing the physical layer and medium access control(MAC) layer aspects. Load statistics priority random access(LSPRA) technology is proposed.Experiments show that when the number of nodes is greater than 1 000, this method can also ensure stable access performance, providing ideas for the design of air-space-ground integrated network access systems.
文摘The Bureau of Statistics has demonstrated a forward-looking strategic approach in its economic census.By leveraging dual innovations in technology and management,and incorporating modern technologies such as big data,cloud computing,and the Internet of Things,it has deepened the reform of the census methodology.Additionally,the Bureau has built a multi-dimensional collaborative network that enhances international cooperation,departmental coordination,and public participation.This approach not only addresses the limitations of traditional statistical methods in a complex economic environment but also improves data quality and census efficiency,providing an accurate and reliable foundation for national economic decision-making.
基金2023 Quality Engineering Project of Guangzhou City Polytechnic“Research on Process Assessment Mode of‘Probability Theory and Mathematical Statistics’Course Based on Application Ability Cultivation”(JY230140)2024 Quality Engineering Project of Guangzhou City Polytechnic“Exploration and Practice of Teaching Model Based on PBL+SPOC+Flipped Classroom in‘Probability Theory and Mathematical Statistics’”(J1124030)。
文摘To cultivate talents with an exploratory spirit and practical skills in the era of information technology,it is imperative to reform teaching methods and approaches.In the teaching process of the Probability and Statistics course,an application-oriented blended teaching model combining problem-based learning and small private online course was explored.By organizing and implementing online and offline teaching activities based on problem-based learning,a multidimensional process-oriented learning assessment system was established.Practice has shown that this model can effectively enhance classroom teaching effectiveness,benefiting the improvement of students’overall skills and mathematical literacy.
基金2023 General Project of Philosophy and Social Science Research in Universities of Jiangsu Province“Exploration and Practice of Mixed Teaching Model Oriented by Curriculum Ideology and Politics in the Course of Probability Theory and Mathematical Statistics”(2023SJYB1499)。
文摘With the rapid development of higher education in China,colleges and universities are facing new challenges and impacts in talent training.Probability Theory and Mathematical Statistics is one of the important courses in higher education for science and engineering majors and economics and management majors.Its critical role in cultivating students’thinking skills and improving their problem-solving skills is self-evident.Course ideological and political education construction is an important link in college talent training work.Combining ideological and political education with course teaching can help students establish correct value concepts and play a certain role in improving their comprehensive ability and quality.At present,the construction of ideological and political education in the Probability Theory and Mathematical Statistics course still faces some problems,mainly manifested in the lack of attention paid by teachers to course ideological and political education,insufficient exploitation of ideological and political elements,and the simplification of ideological and political education implementation methods.In order to comprehensively deepen the construction of course ideological and political education in line with the actual needs of Probability Theory and Mathematical Statistics course teaching,we should strengthen the construction of teacher teams,improve teachers’ability to carry out course ideological and political education,integrate educational resources,develop educational resources for ideological and political education,and innovate teaching methods to improve the overall effect of ideological and political education integration.
文摘目的/意义探究近十年(2014-2023年)医学人工智能领域的研究主题及其发展趋势,为相关研究决策提供参考。方法/过程从PubMed和Web of Science数据库中获取2014-2023年医学人工智能相关文献题录152398条,使用BERTopic模型挖掘文献的研究主题,并依据文献信息逻辑增长规律,划分医学人工智能发展阶段,进而分析研究主题的演化特征。结果/结论医学人工智能领域包含生物信息分析、外科手术机器人、医学影像分析等22个主要研究方向。深度学习技术突破、医疗需求增长以及突发公共卫生事件等多重因素共同推动医学人工智能研究的持续扩展和深化。近年来生成式人工智能为医学人工智能领域研究注入新的活力。
基金supported by TUBITAK 112E568,114E092,and 115E915 projectsTNPGN-Active RINEX data set is available to the IONOLAB group for the TUBITAK 109E055 project。
文摘In this study,the gradients of Total Electron Content(TEC)for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations,time periods within a day,and satellite directions.Annual medians of these gradients for quiet days are computed as templates.The metric distances(L2N)and Symmetric Kullback-Leibler Distances(SKLD)are obtained between the templates and the daily gradient series.The grouped histograms are fitted to the prospective Probability Density Functions(PDF).The method is applied to the Slant Total Electron Content(STEC)estimates from the Turkish National Permanent GPS Network(TNPGN-Active)for 2015.The highest gradients are observed in the east-west axis with a maximum of 25 mm/km during a geomagnetic storm.The maximum differences from the gradient templates occur for neighboring stations within100-130 km distance away from each other,during night hours,and for regions bordering the Black Sea and the Mediterranean in the northeast and southeast of Turkey.The empirical PDFs of the stationpair gradients are predominantly Weibull-distributed.The mean values of Weibull PDFs in all station groups are between 1.2 and 1.8 mm/km,with an increase during noon and afternoon hours.The standard deviations of the gradient PDFs generally increase during night hours.The algorithm will form a basis for quantifying the stochastic variations of the spatial rate of change of TEC trends in midlatitude regions,thus supplementing reliable and accurate regional monitoring of ionospheric variability.
基金partially funded by the National Natural Science Foundation of China(U2142205)the Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)+1 种基金the Special Fund for Forecasters of China Meteorological Administration(CMAYBY2020-094)the Graduate Student Research and Innovation Program of Central South University(2023ZZTS0347)。
文摘Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.
基金Project(52274096)supported by the National Natural Science Foundation of ChinaProject(WS2023A03)supported by the State Key Laboratory Cultivation Base for Gas Geology and Gas Control,China。
文摘Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.
文摘[目的/意义]旨在为在线教育的发展提供参考。[方法/过程]检索Web of Science(WoS)核心数据库关于在线教育的文献(保留摘要以Excel格式导出),运用BERTopic模型进行热点主题抽取,进而对在线教育领域主题进行分析。[结果/结论]BERTopic模型自动生成145个主题(未经干扰),经过归纳和筛选共得到四个主题,即主题1在线教育底层技术研究、主题2在线教学研究、主题3创造思维培养以及主题4在线学习研究。目前元宇宙的出现促进了在线教育的发展,给在线教育提供了沉浸式的学习环境。同时,在线教育促进了学生的个性化发展,在一定程度上弥补了教育不公平。
基金supported by the National Science and Technology Major Project(No.2011 ZX05007-006)the 973 Program of China(No.2013CB228604)the Major Project of Petrochina(No.2014B-0610)
文摘Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.
