In this paper,the sentiment classification method of multimodal adversarial autoencoder is studied.This paper includes the introduction of the multimodal adversarial autoencoder emotion classification method and the e...In this paper,the sentiment classification method of multimodal adversarial autoencoder is studied.This paper includes the introduction of the multimodal adversarial autoencoder emotion classification method and the experiment of the emotion classification method based on the encoder.The experimental analysis shows that the encoder has higher precision than other encoders in emotion classification.It is hoped that this analysis can provide some reference for the emotion classification under the current intelligent algorithm mode.展开更多
Considerable studies have been carried out on fault diagnosis of gears, with most of them concentrated on conventional vibration analysis. However, besides the complexity of gear dynamics, the diagnosis results in ter...Considerable studies have been carried out on fault diagnosis of gears, with most of them concentrated on conventional vibration analysis. However, besides the complexity of gear dynamics, the diagnosis results in terms of vibration signal are easily misjudged owing to the interference of sensor position or other components. In this paper, an alternative gearbox fault detection method based on the instantaneous rotational speed is proposed because of its advantages over vibration analysis. Depending on the timer/counter-based method for the pulse signal of the optical encoder, the varying rotational speed can be obtained e ectively. Owing to the coupling and meshing of gears in transmission, the excitations are the same for the instantaneous rotational speed of the input and output shafts. Thus, the di erential signal of instantaneous rotational speeds can be adopted to eliminate the e ect of the interference excitations and extract the associated feature of the localized fault e ectively. With the experiments on multistage gearbox test system, the di erential signal of instantaneous speeds is compared with other signals. It is proved that localized faults in the gearbox generate small angular speed fluctuations, which are measurable with an optical encoder. Using the di erential signal of instantaneous speeds, the fault characteristics are extracted in the spectrum where the deterministic frequency component and its harmonics corresponding to crack fault characteristics are displayed clearly.展开更多
Low cost and miniaturized rotary encoders are important in automatic and precise production. Presented here is a code called Single Track Cyclic Gray Code (STCGC) that is an image etched on a single circular track of ...Low cost and miniaturized rotary encoders are important in automatic and precise production. Presented here is a code called Single Track Cyclic Gray Code (STCGC) that is an image etched on a single circular track of a rotary encoder disk read by a group of even spread reading heads to provide a unique codeword for every angular position and features such that every two adjacent words differ in exactly one component, thus avoiding coarse error. The existing construction or combination methods are helpful but not sufficient in determining the period of the STCGC of large word length and the theoretical approach needs further development to extend the word length. Three principles, such as the seed combination, short code removal and ergodicity examination were put forward that suffice determination of the optimal period for such absolute rotary encoders using STCGC with even spread heads. The optimal periods of STCGC in 3 through 29 bit length were determined and listed.展开更多
Background Conditional relative survival(CRS),the probability of survival given that an individual has already survived a certain period post-diagnosis,is a more clinically relevant measure for long-term survival than...Background Conditional relative survival(CRS),the probability of survival given that an individual has already survived a certain period post-diagnosis,is a more clinically relevant measure for long-term survival than standard relative survival(RS).This study aims to evaluate the 5-year CRS among adolescent and young adult(AYA)breast cancer patients by age,tumor stage,and receptor subtype to guide disclosure periods for insurance.Methods Data of all females aged 18–39 years and diagnosed with invasive breast cancer between 2003 and 2021(n=13,075)were obtained from The Netherlands Cancer Registry(NCR).The five-year CRS was calculated annually up to 10 years post-diagnosis using a hybrid analysis approach.Results For the total AYA breast cancer study population the 5-year CRS exceeded 90%from diagnosis and increased beyond 95%7 years post-diagnosis.Patients aged 18–24 reached 95%9 years post-diagnosis,those aged 25–29 after 5 years,and those aged 30–34 and 35–39 after 8 years.For stage I,the 5-year CRS reached 95%from diagnosis,for stage II after 6 years,while the 5-year CRS for stages III and IV did not reach the 95%threshold during the 10-year follow-up.Triple-negative tumors exceeded 95%after 4 years,human epidermal growth factor receptor 2(HER2)positive tumors after 6 years,while hormone receptor(HR)positive tumors did not reach 95%.Conclusion Excess mortality among AYA breast cancer patients tends to be little(CRS 90%–95%)from diagnosis and becomes minimal(CRS>95%)over time compared to the general population.These results can enhance expectation management and inform policymakers,suggesting a shorter disclosure period.展开更多
High-performance terahertz(THz)logic gate devices are crucial components for signal processing and modulation,playing a significant role in the application of THz communication and imaging.Here,we propose a THz broadb...High-performance terahertz(THz)logic gate devices are crucial components for signal processing and modulation,playing a significant role in the application of THz communication and imaging.Here,we propose a THz broadband NOR logic encoder based on a graphene-metal hybrid metasurface.The unit structure consists of two symmetrical dual-gap metal split-ring resonators(DSRRs)arranged in a staggered configuration,with graphene strips embedded in their gaps.The NOR logic gate metadevice is controlled by the bias voltages independently applied to the two electrodes.Experiments show that when the bias voltages are applied to both electrodes,the metadevice achieves the NOR logic gate within a 0.52 THz bandwidth,with an average modulation depth above 80%.The experimental results match well with theoretical simulations.Additionally,the strong near-field coupling induced by the staggered DSRRs causes redshift at both LC resonance and dipole resonance.This phenomenon was demonstrated by coupled mode theory.Besides,we analyze the surface current distribution at resonances and propose four equivalent circuit models to elucidate the physical mechanisms of modulation under distinct loaded voltage conditions.The results not only advance modulation and logic gate designs for THz communication but also demonstrate significant potential applications in 6G networks,THz imaging,and radar systems.展开更多
Frame-Semantic Parsing(FSP)aims to extract frame-semantic structures from text.The task usually involves three subtasks sequentially:Target Identification(TI),Frame Identification(FI),and Frame Semantic Role Labeling(...Frame-Semantic Parsing(FSP)aims to extract frame-semantic structures from text.The task usually involves three subtasks sequentially:Target Identification(TI),Frame Identification(FI),and Frame Semantic Role Labeling(FSRL).The three subtasks are closely related while most previous studies model them individually,encountering error propagation and running efficiency problems.Recently,an end-to-end graphbased model is proposed to jointly process three subtasks in one model.However,it still encounters three problems:insufficient semantic modeling between targets and arguments,span missing,and lacking knowledge incorporation of FrameNet.To address the mentioned problems,this paper presents an End-to-end FSP model with Table Encoder(EFSP-TE),which models FSP as two semantically dependent region classification problems and extracts frame-semantic structures from sentences in a one-step manner.Specifically,EFSP-TE incorporates lexical unit knowledge into context encoder via saliency embedding,and develops an effective table representation learning method based on Biaffine network and multi-layer ResNetstyle-CNNs(Convolutional Neural Networks),which can fully exploit word-to-word interactions and capture the information of various levels of semantic relations between targets and arguments.In addition,it adopts two separate region-based modules to obtain potential targets and arguments,followed by two interactive classification modules to predict the frames and roles for the potential targets and arguments.Experiments on two public benchmarks show that the proposed approach achieves state-of-the-art performance in end-to-end setting.展开更多
This study proposes an efficient traffic classification model to address the growing threat of distributed denial-of-service(DDoS)attacks in 5th generation technology standard(5G)slicing networks.The proposed method u...This study proposes an efficient traffic classification model to address the growing threat of distributed denial-of-service(DDoS)attacks in 5th generation technology standard(5G)slicing networks.The proposed method utilizes an ensemble of encoder components from multiple autoencoders to compress and extract latent representations from high-dimensional traffic data.These representations are then used as input for a support vector machine(SVM)-based metadata classifier,enabling precise detection of attack traffic.This architecture is designed to achieve both high detection accuracy and training efficiency,while adapting flexibly to the diverse service requirements and complexity of 5G network slicing.The model was evaluated using the DDoS Datasets 2022,collected in a simulated 5G slicing environment.Experiments were conducted under both class-balanced and class-imbalanced conditions.In the balanced setting,the model achieved an accuracy of 89.33%,an F1-score of 88.23%,and an Area Under the Curve(AUC)of 89.45%.In the imbalanced setting(attack:normal 7:3),the model maintained strong robustness,=achieving a recall of 100%and an F1-score of 90.91%,demonstrating its effectiveness in diverse real-world scenarios.Compared to existing AI-based detection methods,the proposed model showed higher precision,better handling of class imbalance,and strong generalization performance.Moreover,its modular structure is well-suited for deployment in containerized network function(NF)environments,making it a practical solution for real-world 5G infrastructure.These results highlight the potential of the proposed approach to enhance both the security and operational resilience of 5G slicing networks.展开更多
The research on ocean dynamics information plays a crucial role in understanding ocean phenomena, assessing marine environmental impacts, and guiding engineering designs. The Doppler information observed by radars ref...The research on ocean dynamics information plays a crucial role in understanding ocean phenomena, assessing marine environmental impacts, and guiding engineering designs. The Doppler information observed by radars reflects sea surface dynamics, to which ocean waves make important contributions. Low-incidence-angle real aperture radar(RAR)demonstrates great potential for independently observing vectorial Doppler information on the ocean surface. To systematically characterize and accurately estimate the wave-induced Doppler frequency shift(WVF) from lowincidence-angle RAR, this study conducts comprehensive influencing factor analysis and establishes sea-stateparameterized WVF models. First, a simulated WVF dataset is generated under a rotating low-incidence-angle RAR.The feature parameters of WVF are then determined by analysing contributing factors including wind waves, swells,and sea state parameters. Furthermore, two WVF models(WVF_Ku P9 with 9 inputs and WVF_Ku P4 with 4 inputs) are constructed by the Transformer encoder for different application scenarios. Both models achieve high accuracy for WVF estimation with root mean square errors(RMSE) of 1.874 Hz and 2.716 Hz, respectively. The reliability and superiority of the proposed models are validated through comparisons with the Ka DOP, which is a typical geophysical model function(GMF). The findings in this paper advance the understanding of WVF characteristics and generation mechanisms. The proposed estimation models can provide reliable estimates, offering critical references for lowincidence-angle RAR applications such as ocean surface current retrieval.展开更多
文摘In this paper,the sentiment classification method of multimodal adversarial autoencoder is studied.This paper includes the introduction of the multimodal adversarial autoencoder emotion classification method and the experiment of the emotion classification method based on the encoder.The experimental analysis shows that the encoder has higher precision than other encoders in emotion classification.It is hoped that this analysis can provide some reference for the emotion classification under the current intelligent algorithm mode.
基金supported by the National Natural Science Foundation of China(1127105011371183+2 种基金61403036)the Science and Technology Development Foundation of CAEP(2013A04030202013B0403068)
基金Supported by National Natural Science Foundation of China(Grant No.51575438)China Postdoctoral Science Foundation(Grant Nos.2017M623159,2018T111046)Shaanxi Provincial Postdoctoral Science Foundation of China(Grant No.2017BSHEDZZ68)
文摘Considerable studies have been carried out on fault diagnosis of gears, with most of them concentrated on conventional vibration analysis. However, besides the complexity of gear dynamics, the diagnosis results in terms of vibration signal are easily misjudged owing to the interference of sensor position or other components. In this paper, an alternative gearbox fault detection method based on the instantaneous rotational speed is proposed because of its advantages over vibration analysis. Depending on the timer/counter-based method for the pulse signal of the optical encoder, the varying rotational speed can be obtained e ectively. Owing to the coupling and meshing of gears in transmission, the excitations are the same for the instantaneous rotational speed of the input and output shafts. Thus, the di erential signal of instantaneous rotational speeds can be adopted to eliminate the e ect of the interference excitations and extract the associated feature of the localized fault e ectively. With the experiments on multistage gearbox test system, the di erential signal of instantaneous speeds is compared with other signals. It is proved that localized faults in the gearbox generate small angular speed fluctuations, which are measurable with an optical encoder. Using the di erential signal of instantaneous speeds, the fault characteristics are extracted in the spectrum where the deterministic frequency component and its harmonics corresponding to crack fault characteristics are displayed clearly.
基金Project(JX2004J0170) supported by the Foundation of Beijing Jiaotong University, China
文摘Low cost and miniaturized rotary encoders are important in automatic and precise production. Presented here is a code called Single Track Cyclic Gray Code (STCGC) that is an image etched on a single circular track of a rotary encoder disk read by a group of even spread reading heads to provide a unique codeword for every angular position and features such that every two adjacent words differ in exactly one component, thus avoiding coarse error. The existing construction or combination methods are helpful but not sufficient in determining the period of the STCGC of large word length and the theoretical approach needs further development to extend the word length. Three principles, such as the seed combination, short code removal and ergodicity examination were put forward that suffice determination of the optimal period for such absolute rotary encoders using STCGC with even spread heads. The optimal periods of STCGC in 3 through 29 bit length were determined and listed.
基金supported by The Netherlands Organization for Scientific Research VIDI(grant number:198.007).
文摘Background Conditional relative survival(CRS),the probability of survival given that an individual has already survived a certain period post-diagnosis,is a more clinically relevant measure for long-term survival than standard relative survival(RS).This study aims to evaluate the 5-year CRS among adolescent and young adult(AYA)breast cancer patients by age,tumor stage,and receptor subtype to guide disclosure periods for insurance.Methods Data of all females aged 18–39 years and diagnosed with invasive breast cancer between 2003 and 2021(n=13,075)were obtained from The Netherlands Cancer Registry(NCR).The five-year CRS was calculated annually up to 10 years post-diagnosis using a hybrid analysis approach.Results For the total AYA breast cancer study population the 5-year CRS exceeded 90%from diagnosis and increased beyond 95%7 years post-diagnosis.Patients aged 18–24 reached 95%9 years post-diagnosis,those aged 25–29 after 5 years,and those aged 30–34 and 35–39 after 8 years.For stage I,the 5-year CRS reached 95%from diagnosis,for stage II after 6 years,while the 5-year CRS for stages III and IV did not reach the 95%threshold during the 10-year follow-up.Triple-negative tumors exceeded 95%after 4 years,human epidermal growth factor receptor 2(HER2)positive tumors after 6 years,while hormone receptor(HR)positive tumors did not reach 95%.Conclusion Excess mortality among AYA breast cancer patients tends to be little(CRS 90%–95%)from diagnosis and becomes minimal(CRS>95%)over time compared to the general population.These results can enhance expectation management and inform policymakers,suggesting a shorter disclosure period.
基金supported by the National Natural Science Foundation of China(Grant Nos.62005058 and 62365006)the Natural Science Foundation of Guangxi,China(Grant No.2020GXNSFBA238012)+2 种基金the China Postdoctoral Science Foundation(Grant No.2020M683726)the Innovation Project of Guangxi Graduate Education(Grant Nos.YCSW2024345 and YCBZ2025157)the Guangxi Key Laboratory of Automatic Detecting Technology and Instruments(Grant No.YQ24101).
文摘High-performance terahertz(THz)logic gate devices are crucial components for signal processing and modulation,playing a significant role in the application of THz communication and imaging.Here,we propose a THz broadband NOR logic encoder based on a graphene-metal hybrid metasurface.The unit structure consists of two symmetrical dual-gap metal split-ring resonators(DSRRs)arranged in a staggered configuration,with graphene strips embedded in their gaps.The NOR logic gate metadevice is controlled by the bias voltages independently applied to the two electrodes.Experiments show that when the bias voltages are applied to both electrodes,the metadevice achieves the NOR logic gate within a 0.52 THz bandwidth,with an average modulation depth above 80%.The experimental results match well with theoretical simulations.Additionally,the strong near-field coupling induced by the staggered DSRRs causes redshift at both LC resonance and dipole resonance.This phenomenon was demonstrated by coupled mode theory.Besides,we analyze the surface current distribution at resonances and propose four equivalent circuit models to elucidate the physical mechanisms of modulation under distinct loaded voltage conditions.The results not only advance modulation and logic gate designs for THz communication but also demonstrate significant potential applications in 6G networks,THz imaging,and radar systems.
基金supported by the Science and Technology Cooperation and Exchange Special Project of Shanxi Province(No.202204041101016)the Basic Research Program of Shanxi Province(No.202203021211286)+2 种基金the Four“Batches”Innovation Project of Invigorating Medical through Science and Technology of Shanxi Province(No.2022XM01)the Research Fund of Guangxi Key Lab of Multi-source Information Mining Security(No.MIMS22-10)the Foundation of Shanxi Vocational University of Engineering Science and Technology(No.KJ202203).
文摘Frame-Semantic Parsing(FSP)aims to extract frame-semantic structures from text.The task usually involves three subtasks sequentially:Target Identification(TI),Frame Identification(FI),and Frame Semantic Role Labeling(FSRL).The three subtasks are closely related while most previous studies model them individually,encountering error propagation and running efficiency problems.Recently,an end-to-end graphbased model is proposed to jointly process three subtasks in one model.However,it still encounters three problems:insufficient semantic modeling between targets and arguments,span missing,and lacking knowledge incorporation of FrameNet.To address the mentioned problems,this paper presents an End-to-end FSP model with Table Encoder(EFSP-TE),which models FSP as two semantically dependent region classification problems and extracts frame-semantic structures from sentences in a one-step manner.Specifically,EFSP-TE incorporates lexical unit knowledge into context encoder via saliency embedding,and develops an effective table representation learning method based on Biaffine network and multi-layer ResNetstyle-CNNs(Convolutional Neural Networks),which can fully exploit word-to-word interactions and capture the information of various levels of semantic relations between targets and arguments.In addition,it adopts two separate region-based modules to obtain potential targets and arguments,followed by two interactive classification modules to predict the frames and roles for the potential targets and arguments.Experiments on two public benchmarks show that the proposed approach achieves state-of-the-art performance in end-to-end setting.
基金supported by an Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korean government(MSIT)(RS-2024-00438156,Development of Security Resilience Technology Based on Network Slicing Services in a 5G Specialized Network).
文摘This study proposes an efficient traffic classification model to address the growing threat of distributed denial-of-service(DDoS)attacks in 5th generation technology standard(5G)slicing networks.The proposed method utilizes an ensemble of encoder components from multiple autoencoders to compress and extract latent representations from high-dimensional traffic data.These representations are then used as input for a support vector machine(SVM)-based metadata classifier,enabling precise detection of attack traffic.This architecture is designed to achieve both high detection accuracy and training efficiency,while adapting flexibly to the diverse service requirements and complexity of 5G network slicing.The model was evaluated using the DDoS Datasets 2022,collected in a simulated 5G slicing environment.Experiments were conducted under both class-balanced and class-imbalanced conditions.In the balanced setting,the model achieved an accuracy of 89.33%,an F1-score of 88.23%,and an Area Under the Curve(AUC)of 89.45%.In the imbalanced setting(attack:normal 7:3),the model maintained strong robustness,=achieving a recall of 100%and an F1-score of 90.91%,demonstrating its effectiveness in diverse real-world scenarios.Compared to existing AI-based detection methods,the proposed model showed higher precision,better handling of class imbalance,and strong generalization performance.Moreover,its modular structure is well-suited for deployment in containerized network function(NF)environments,making it a practical solution for real-world 5G infrastructure.These results highlight the potential of the proposed approach to enhance both the security and operational resilience of 5G slicing networks.
基金The National Natural Science Foundation of China under contract No. 42274159the Project supported by Key Laboratory of Space Ocean Remote Sensing and Application,MNR under contract No.2023CFO016。
文摘The research on ocean dynamics information plays a crucial role in understanding ocean phenomena, assessing marine environmental impacts, and guiding engineering designs. The Doppler information observed by radars reflects sea surface dynamics, to which ocean waves make important contributions. Low-incidence-angle real aperture radar(RAR)demonstrates great potential for independently observing vectorial Doppler information on the ocean surface. To systematically characterize and accurately estimate the wave-induced Doppler frequency shift(WVF) from lowincidence-angle RAR, this study conducts comprehensive influencing factor analysis and establishes sea-stateparameterized WVF models. First, a simulated WVF dataset is generated under a rotating low-incidence-angle RAR.The feature parameters of WVF are then determined by analysing contributing factors including wind waves, swells,and sea state parameters. Furthermore, two WVF models(WVF_Ku P9 with 9 inputs and WVF_Ku P4 with 4 inputs) are constructed by the Transformer encoder for different application scenarios. Both models achieve high accuracy for WVF estimation with root mean square errors(RMSE) of 1.874 Hz and 2.716 Hz, respectively. The reliability and superiority of the proposed models are validated through comparisons with the Ka DOP, which is a typical geophysical model function(GMF). The findings in this paper advance the understanding of WVF characteristics and generation mechanisms. The proposed estimation models can provide reliable estimates, offering critical references for lowincidence-angle RAR applications such as ocean surface current retrieval.
