Support vector machines are originally designed for binary classification. How to effectively extend it for multi-class classification is still an on-going research issue. In this paper, we consider kernel machines wh...Support vector machines are originally designed for binary classification. How to effectively extend it for multi-class classification is still an on-going research issue. In this paper, we consider kernel machines which are natural extensions of multi-category support vector machines originally proposed by Crammer and Singer. Based on the algorithm stability, we obtain the generalization error bounds for the kernel machines proposed in the paper.展开更多
In this paper, the complete convergence theorems for Sung’s type weighted sums of END random variables and PNQD random variables with general moment conditions are obtained. The theorems extend the related known work...In this paper, the complete convergence theorems for Sung’s type weighted sums of END random variables and PNQD random variables with general moment conditions are obtained. The theorems extend the related known works in the literature.展开更多
BACKGROUND Currently,very few studies have examined the analgesic effectiveness and safety of dexmedetomidine-assisted intravenous-inhalation combined general anesthesia in laparoscopic minimally invasive surgery for ...BACKGROUND Currently,very few studies have examined the analgesic effectiveness and safety of dexmedetomidine-assisted intravenous-inhalation combined general anesthesia in laparoscopic minimally invasive surgery for inguinal hernia.AIM To investigate the analgesic effect and safety of dexmedetomidine-assisted intravenous-inhalation combined general anesthesia in laparoscopic minimally invasive surgery for inguinal hernia.METHODS In this retrospective study,94 patients scheduled for laparoscopic minimally invasive surgery for inguinal hernia,admitted to Yiwu Central Hospital between May 2022 and May 2023,were divided into a control group(inhalation combined general anesthesia)and a treatment group(dexmedetomidine-assisted intrave-nous-inhalation combined general anesthesia).Perioperative indicators,analgesic effect,preoperative and postoperative 24-hours blood pressure(BP)and heart rate(HR),stress indicators,immune function levels,and adverse reactions were com-pared between the two groups.RESULTS Baseline data,including age,hernia location,place of residence,weight,monthly income,education level,and underlying diseases,were not significantly different between the two groups,indicating comparability(P>0.05).No significant difference was found in operation time and anesthesia time between the two groups(P>0.05).However,the treatment group exhibited a shorter postoperative urinary catheter removal time and hospital stay than the control group(P<0.05).Preoperatively,no significant differences were found in the visual analog scale(VAS)scores between the two groups(P>0.05).However,at 12,18,and 24 hours postoper-atively,the treatment group had significantly lower VAS scores than the control group(P<0.05).Although no significant differences in preoperative hemodynamic indicators were found between the two groups(P>0.05),both groups experienced some extent of changes in postoperative HR,diastolic BP(DBP),and systolic BP(SBP).Nevertheless,the treatment group showed smaller changes in HR,DBP,and SBP than the control group(P<0.05).Preoperative immune function indicators showed no significant differences between the two groups(P>0.05).However,postoperatively,the treatment group demonstrated higher levels of CD3+,CD4+,and CD4+/CD8+and lower levels of CD8+than the control group(P<0.05).The rates of adverse reactions were 6.38%and 23.40%in the treatment and control groups,respectively,revealing a significant difference(χ2=5.371,P=0.020).CONCLUSION Dexmedetomidine-assisted intravenous-inhalation combined general anesthesia can promote early recovery of patients undergoing laparoscopic minimally invasive surgery for inguinal hernia.It ensures stable blood flow,improves postoperative analgesic effects,reduces postoperative pain intensity,alleviates stress response,improves immune function,facilitates anesthesia recovery,and enhances safety.展开更多
Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN model...Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.展开更多
Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases.Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field,yet issues like limited t...Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases.Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field,yet issues like limited training data,imbalance data distribution,and inadequate feature extraction persist,hindering both the segmentation performance and optimal model generalization.Addressing these critical issues,the DEFFA-Unet is proposed featuring an additional encoder to process domain-invariant pre-processed inputs,thereby improving both richer feature encoding and enhanced model generalization.A feature filtering fusion module is developed to ensure the precise feature filtering and robust hybrid feature fusion.In response to the task-specific need for higher precision where false positives are very costly,traditional skip connections are replaced with the attention-guided feature reconstructing fusion module.Additionally,innovative data augmentation and balancing methods are proposed to counter data scarcity and distribution imbalance,further boosting the robustness and generalization of the model.With a comprehensive suite of evaluation metrics,extensive validations on four benchmark datasets(DRIVE,CHASEDB1,STARE,and HRF)and an SLO dataset(IOSTAR),demonstrate the proposed method’s superiority over both baseline and state-of-the-art models.Particularly the proposed method significantly outperforms the compared methods in cross-validation model generalization.展开更多
This study analyzes the evolution and dynamics of intensity oscillations in coronal sunspots and their surroundings using multi-wavelength image data from the Atmospheric Imaging Assembly(AIA)and Helioseismic and Magn...This study analyzes the evolution and dynamics of intensity oscillations in coronal sunspots and their surroundings using multi-wavelength image data from the Atmospheric Imaging Assembly(AIA)and Helioseismic and Magnetic Imager(HMI)on board the Solar Dynamics Observatory(SDO).Intensity time series were extracted and analyzed from consecutive macropixels along thin coronal loop paths originating in a quiet sunspot.Fourier and wavelet analyses of corrected intensity time series reveal dominant 3 and 5 minute oscillations.Signals were filtered using the Fourier and inverse transforms to isolate narrow bands around the dominant oscillation periods.Diagrams and time-distance maps of intensity time series were plotted for Fourierfiltered AIA 131A,171A,193A,and 211A channels,along with SDO/HMI magnetograms and dopplergrams at 6173A.The plots clearly show propagating oscillations with amplitude modulation(AM)across all macropixels along selected coronal paths in nearly all AIA and HMI channels.The phase speeds of the filtered oscillations,measured via slope calculations in time-distance maps,indicate that the intensity disturbances are slow magneto-acoustic waves.These results suggest that AM likely arises from the superposition of counterpropagating waves with slightly different frequencies(beta-like phenomena)due to Doppler shifts from background plasma flow along loop paths.Validating this hypothesis could establish AM's significance in solar coronal seismology for determining background plasma flow speed,the source of long-period oscillations,and coronal plasma heating mechanisms.展开更多
The US 2024 general election ended with the Republican Party winning the presidential, House and Senate elections at the same time. In the presidential election, the Republican Party not only won more popular votes in...The US 2024 general election ended with the Republican Party winning the presidential, House and Senate elections at the same time. In the presidential election, the Republican Party not only won more popular votes in over 90% counties than in the 2020 general election, but also won seven highly contested swing States with greater edges. This also marks the first time since 2004 that the Republican Party has won a relative majority of popular votes in the presidential election.展开更多
In winter,the weather is usually cold and everything seems a bit dull.Butthe sun in winter is special.When the sun shines brightly in the clear blue sky,it brings warm(1)to thecold world.The golden sunlight spreads he...In winter,the weather is usually cold and everything seems a bit dull.Butthe sun in winter is special.When the sun shines brightly in the clear blue sky,it brings warm(1)to thecold world.The golden sunlight spreads here and there and it makes the whitesnow shine like diamonds.Although the trees are usually bare in winter,but(2)they look beautiful with the sunlight falling on them.展开更多
Strengthening cybersecurity education for college students holds significant importance in achieving the strategic goal of building China into a cyber power.This article begins by discussing the significance and neces...Strengthening cybersecurity education for college students holds significant importance in achieving the strategic goal of building China into a cyber power.This article begins by discussing the significance and necessity of implementing cybersecurity education for university students.Drawing on disciplinary characteristics and student learning analysis,it presents a comprehensive construction process and countermeasures for a general cybersecurity education course,covering aspects such as teaching content development,teaching resource creation,and pedagogical approaches.The aim is to provide reference and guidance for other universities in developing general cybersecurity education courses.展开更多
Digital twin shows broad application prospects in the aerospace field.This paper introduces a generalized satellite digital twin system in detail.With the innovative design concepts of modularization,generalization an...Digital twin shows broad application prospects in the aerospace field.This paper introduces a generalized satellite digital twin system in detail.With the innovative design concepts of modularization,generalization and modeling,on the one hand,the system has successfully achieved the reuse of software modules among different satellite models;on the other hand,it has achieved the reuse of software modules between the digital twin and the testing system,significantly improving the development efficiency of the digital twin system.The paper elaborates on the technical architecture and application fields of this digital twin system,and further prospects its future development.At the same time,through a real inorbit case,the engineering value of the digital twin system is strongly demonstrated.展开更多
The phenomenon of fear memory generalization can be defined as the expansion of an individual's originally specific fear responses to a similar yet genuinely harmless stimulus or situation subsequent to the occurr...The phenomenon of fear memory generalization can be defined as the expansion of an individual's originally specific fear responses to a similar yet genuinely harmless stimulus or situation subsequent to the occurrence of a traumatic event[1].Fear generalization within the normal range represents an adaptive evolutionary mechanism to facilitate prompt reactions to potential threats and to enhance the likelihood of survival.展开更多
The challenge of enhancing the generalization capacity of reinforcement learning(RL)agents remains a formidable obstacle.Existing RL methods,despite achieving superhuman performance on certain benchmarks,often struggl...The challenge of enhancing the generalization capacity of reinforcement learning(RL)agents remains a formidable obstacle.Existing RL methods,despite achieving superhuman performance on certain benchmarks,often struggle with this aspect.A potential reason is that the benchmarks used for training and evaluation may not adequately offer a diverse set of transferable tasks.Although recent studies have developed bench-marking environments to address this shortcoming,they typically fall short in providing tasks that both ensure a solid foundation for generalization and exhibit significant variability.To overcome these limitations,this work introduces the concept that‘objects are composed of more fundamental components’in environment design,as implemented in the proposed environment called summon the magic(StM).This environment generates tasks where objects are derived from extensible and shareable basic components,facilitating strategy reuse and enhancing generalization.Furthermore,two new metrics,adaptation sensitivity range(ASR)and parameter correlation coefficient(PCC),are proposed to better capture and evaluate the generalization process of RL agents.Experimental results show that increasing the number of basic components of the object reduces the proximal policy optimization(PPO)agent’s training-testing gap by 60.9%(in episode reward),significantly alleviating overfitting.Additionally,linear variations in other environmental factors,such as the training monster set proportion and the total number of basic components,uniformly decrease the gap by at least 32.1%.These results highlight StM’s effectiveness in benchmarking and probing the generalization capabilities of RL algorithms.展开更多
基金Supported in part by the Specialized Research Fund for the Doctoral Program of Higher Education under grant 20060512001.
文摘Support vector machines are originally designed for binary classification. How to effectively extend it for multi-class classification is still an on-going research issue. In this paper, we consider kernel machines which are natural extensions of multi-category support vector machines originally proposed by Crammer and Singer. Based on the algorithm stability, we obtain the generalization error bounds for the kernel machines proposed in the paper.
基金Supported by the Natural Science Foundation of Hunan Province(Grant No.2018JJ4024)the Science and Technology Plan Project of Hengyang City(Grant No.2018KJ129)
文摘In this paper, the complete convergence theorems for Sung’s type weighted sums of END random variables and PNQD random variables with general moment conditions are obtained. The theorems extend the related known works in the literature.
文摘BACKGROUND Currently,very few studies have examined the analgesic effectiveness and safety of dexmedetomidine-assisted intravenous-inhalation combined general anesthesia in laparoscopic minimally invasive surgery for inguinal hernia.AIM To investigate the analgesic effect and safety of dexmedetomidine-assisted intravenous-inhalation combined general anesthesia in laparoscopic minimally invasive surgery for inguinal hernia.METHODS In this retrospective study,94 patients scheduled for laparoscopic minimally invasive surgery for inguinal hernia,admitted to Yiwu Central Hospital between May 2022 and May 2023,were divided into a control group(inhalation combined general anesthesia)and a treatment group(dexmedetomidine-assisted intrave-nous-inhalation combined general anesthesia).Perioperative indicators,analgesic effect,preoperative and postoperative 24-hours blood pressure(BP)and heart rate(HR),stress indicators,immune function levels,and adverse reactions were com-pared between the two groups.RESULTS Baseline data,including age,hernia location,place of residence,weight,monthly income,education level,and underlying diseases,were not significantly different between the two groups,indicating comparability(P>0.05).No significant difference was found in operation time and anesthesia time between the two groups(P>0.05).However,the treatment group exhibited a shorter postoperative urinary catheter removal time and hospital stay than the control group(P<0.05).Preoperatively,no significant differences were found in the visual analog scale(VAS)scores between the two groups(P>0.05).However,at 12,18,and 24 hours postoper-atively,the treatment group had significantly lower VAS scores than the control group(P<0.05).Although no significant differences in preoperative hemodynamic indicators were found between the two groups(P>0.05),both groups experienced some extent of changes in postoperative HR,diastolic BP(DBP),and systolic BP(SBP).Nevertheless,the treatment group showed smaller changes in HR,DBP,and SBP than the control group(P<0.05).Preoperative immune function indicators showed no significant differences between the two groups(P>0.05).However,postoperatively,the treatment group demonstrated higher levels of CD3+,CD4+,and CD4+/CD8+and lower levels of CD8+than the control group(P<0.05).The rates of adverse reactions were 6.38%and 23.40%in the treatment and control groups,respectively,revealing a significant difference(χ2=5.371,P=0.020).CONCLUSION Dexmedetomidine-assisted intravenous-inhalation combined general anesthesia can promote early recovery of patients undergoing laparoscopic minimally invasive surgery for inguinal hernia.It ensures stable blood flow,improves postoperative analgesic effects,reduces postoperative pain intensity,alleviates stress response,improves immune function,facilitates anesthesia recovery,and enhances safety.
基金funded by Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),Faculty of Engineering and IT,University of Technology Sydney.Moreover,Ongoing Research Funding Program(ORF-2025-14)King Saud University,Riyadh,Saudi Arabia,under Project ORF-2025-。
文摘Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.
文摘Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases.Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field,yet issues like limited training data,imbalance data distribution,and inadequate feature extraction persist,hindering both the segmentation performance and optimal model generalization.Addressing these critical issues,the DEFFA-Unet is proposed featuring an additional encoder to process domain-invariant pre-processed inputs,thereby improving both richer feature encoding and enhanced model generalization.A feature filtering fusion module is developed to ensure the precise feature filtering and robust hybrid feature fusion.In response to the task-specific need for higher precision where false positives are very costly,traditional skip connections are replaced with the attention-guided feature reconstructing fusion module.Additionally,innovative data augmentation and balancing methods are proposed to counter data scarcity and distribution imbalance,further boosting the robustness and generalization of the model.With a comprehensive suite of evaluation metrics,extensive validations on four benchmark datasets(DRIVE,CHASEDB1,STARE,and HRF)and an SLO dataset(IOSTAR),demonstrate the proposed method’s superiority over both baseline and state-of-the-art models.Particularly the proposed method significantly outperforms the compared methods in cross-validation model generalization.
文摘This study analyzes the evolution and dynamics of intensity oscillations in coronal sunspots and their surroundings using multi-wavelength image data from the Atmospheric Imaging Assembly(AIA)and Helioseismic and Magnetic Imager(HMI)on board the Solar Dynamics Observatory(SDO).Intensity time series were extracted and analyzed from consecutive macropixels along thin coronal loop paths originating in a quiet sunspot.Fourier and wavelet analyses of corrected intensity time series reveal dominant 3 and 5 minute oscillations.Signals were filtered using the Fourier and inverse transforms to isolate narrow bands around the dominant oscillation periods.Diagrams and time-distance maps of intensity time series were plotted for Fourierfiltered AIA 131A,171A,193A,and 211A channels,along with SDO/HMI magnetograms and dopplergrams at 6173A.The plots clearly show propagating oscillations with amplitude modulation(AM)across all macropixels along selected coronal paths in nearly all AIA and HMI channels.The phase speeds of the filtered oscillations,measured via slope calculations in time-distance maps,indicate that the intensity disturbances are slow magneto-acoustic waves.These results suggest that AM likely arises from the superposition of counterpropagating waves with slightly different frequencies(beta-like phenomena)due to Doppler shifts from background plasma flow along loop paths.Validating this hypothesis could establish AM's significance in solar coronal seismology for determining background plasma flow speed,the source of long-period oscillations,and coronal plasma heating mechanisms.
文摘The US 2024 general election ended with the Republican Party winning the presidential, House and Senate elections at the same time. In the presidential election, the Republican Party not only won more popular votes in over 90% counties than in the 2020 general election, but also won seven highly contested swing States with greater edges. This also marks the first time since 2004 that the Republican Party has won a relative majority of popular votes in the presidential election.
文摘In winter,the weather is usually cold and everything seems a bit dull.Butthe sun in winter is special.When the sun shines brightly in the clear blue sky,it brings warm(1)to thecold world.The golden sunlight spreads here and there and it makes the whitesnow shine like diamonds.Although the trees are usually bare in winter,but(2)they look beautiful with the sunlight falling on them.
基金supported in part by the 2024 Core General Education Course Construction Project of Beijing Union University,titled“Cybersecurity:Exploring the World of White Hat Hackers”the 2025 Educational Science Research Project of Beijing Union University(JK202514)+1 种基金the General Project of Science and Technology Program of Beijing Municipal Education Commission under Grant KM201911417011the Academic Research Projects of Beijing Union University(ZK30202407).
文摘Strengthening cybersecurity education for college students holds significant importance in achieving the strategic goal of building China into a cyber power.This article begins by discussing the significance and necessity of implementing cybersecurity education for university students.Drawing on disciplinary characteristics and student learning analysis,it presents a comprehensive construction process and countermeasures for a general cybersecurity education course,covering aspects such as teaching content development,teaching resource creation,and pedagogical approaches.The aim is to provide reference and guidance for other universities in developing general cybersecurity education courses.
文摘Digital twin shows broad application prospects in the aerospace field.This paper introduces a generalized satellite digital twin system in detail.With the innovative design concepts of modularization,generalization and modeling,on the one hand,the system has successfully achieved the reuse of software modules among different satellite models;on the other hand,it has achieved the reuse of software modules between the digital twin and the testing system,significantly improving the development efficiency of the digital twin system.The paper elaborates on the technical architecture and application fields of this digital twin system,and further prospects its future development.At the same time,through a real inorbit case,the engineering value of the digital twin system is strongly demonstrated.
基金supported by the Shandong Provincial Natural Science Foundation(ZR2022QH144).
文摘The phenomenon of fear memory generalization can be defined as the expansion of an individual's originally specific fear responses to a similar yet genuinely harmless stimulus or situation subsequent to the occurrence of a traumatic event[1].Fear generalization within the normal range represents an adaptive evolutionary mechanism to facilitate prompt reactions to potential threats and to enhance the likelihood of survival.
基金Supported by the National Key R&D Program of China(No.2023YFB4502200)the National Natural Science Foundation of China(No.U22A2028,61925208,62222214,62341411,62102398,62102399,U20A20227,62302478,62302482,62302483,62302480,62302481)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB0660300,XDB0660301,XDB0660302)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(No.YSBR-029)the Youth Innovation Promotion Association of Chinese Academy of Sciences and Xplore Prize.
文摘The challenge of enhancing the generalization capacity of reinforcement learning(RL)agents remains a formidable obstacle.Existing RL methods,despite achieving superhuman performance on certain benchmarks,often struggle with this aspect.A potential reason is that the benchmarks used for training and evaluation may not adequately offer a diverse set of transferable tasks.Although recent studies have developed bench-marking environments to address this shortcoming,they typically fall short in providing tasks that both ensure a solid foundation for generalization and exhibit significant variability.To overcome these limitations,this work introduces the concept that‘objects are composed of more fundamental components’in environment design,as implemented in the proposed environment called summon the magic(StM).This environment generates tasks where objects are derived from extensible and shareable basic components,facilitating strategy reuse and enhancing generalization.Furthermore,two new metrics,adaptation sensitivity range(ASR)and parameter correlation coefficient(PCC),are proposed to better capture and evaluate the generalization process of RL agents.Experimental results show that increasing the number of basic components of the object reduces the proximal policy optimization(PPO)agent’s training-testing gap by 60.9%(in episode reward),significantly alleviating overfitting.Additionally,linear variations in other environmental factors,such as the training monster set proportion and the total number of basic components,uniformly decrease the gap by at least 32.1%.These results highlight StM’s effectiveness in benchmarking and probing the generalization capabilities of RL algorithms.
