Layered manganese dioxide(δ-MnO_(2))is a promising cathode material for aqueous zinc-ion batteries(AZIBs)due to its high theoretical capacity,high operating voltage,and low cost.However,its practical application face...Layered manganese dioxide(δ-MnO_(2))is a promising cathode material for aqueous zinc-ion batteries(AZIBs)due to its high theoretical capacity,high operating voltage,and low cost.However,its practical application faces challenges,such as low electronic conductivity,sluggish diffusion kinetics,and severe dissolution of Mn^(2+).In this study,we developed a δ-MnO_(2) coated with a 2-methylimidazole(δ-MnO_(2)@2-ML)hybrid cathode.Density functional theory(DFT)calculations indicate that 2-ML can be integrated into δ-MnO_(2) through both pre-intercalation and surface coating,with thermodynamically favorable outcomes.This modification expands the interlayer spacing of δ-MnO_(2) and generates Mn-N bonds on the surface,enhancing Zn^(2+)accommodation and diffusion kinetics as well as stabilizing surface Mn sites.The experimentally prepared δ-MnO_(2)@2-ML cathode,as predicted by DFT,features both 2-ML pre-intercalation and surface coating,providing more zinc-ion insertion sites and improved structural stability.Furthermore,X-ray diffraction shows the expanded interlayer spacing,which effectively buffers local electrostatic interactions,leading to an enhanced Zn^(2+)diffusion rate.Consequently,the optimized cathode(δ-MnO_(2)@2-ML)presents improved electrochemical performance and stability,and the fabricated AZIBs exhibit a high specific capacity(309.5mAh/g at 0.1 A/g),superior multiplicative performance(137.6mAh/g at 1 A/g),and impressive capacity retention(80%after 1350 cycles at 1 A/g).These results surpass the performance of most manganese-based and vanadium-based cathode materials reported to date.This dual-modulation strategy,combining interlayer engineering and interface optimization,offers a straightforward and scalable approach,potentially advancing the commercial viability of low-cost,high-performance AZIBs.展开更多
Theoretically,blue phosphorescent materials are capable of achieving 100%internal quantum effi-ciency.Nevertheless,the mutual constraints among efficiency,color purity,and stability remain one of the key bottlenecks i...Theoretically,blue phosphorescent materials are capable of achieving 100%internal quantum effi-ciency.Nevertheless,the mutual constraints among efficiency,color purity,and stability remain one of the key bottlenecks in the industrialization of organic light-emitting diodes(OLEDs).In addition,the design and application of host materials also exert a significant impact on the overall performance of blue light-emitting de-vices.To address this issue,this study constructs a series of host materials with high triplet energy levels by designing different connection modes,based on 9-phenylcarbazole and benzimidazole units.Through a combi-nation of theoretical and experimental approaches,the correlation between the chemical structure and perfor-mance has been unraveled.It is found that the designed and synthesized blue phosphorescent bipolar host ma-terials based on different biphenyl linking sites,i.e.,9-(3'-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1'-bi-phenyl]-3-yl)-9H-carbazole(mCzmBI),9-(2'-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1'-biphenyl]-3-yl)-9H-carbazole(mCzoBI)and 9-(3'-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1'-biphenyl]-2-yl)-9H-carbazole(oCzmBI).The three compounds have a similar triplet energy level of 2.70 eV,accompanied with the glass transition temperatures of 92℃,103℃,and 93℃respectively.mCzmBI,mCzoBI and oCzmBI are regioiso-mers,but differ in the linking sites of carbazole and benzimidazole on the biphenyl linker.This difference in linking positions enables effective regulation of the host materials’properties.Constructed with the blue phos-phorescent material bis(4,6-difluorophenylpyridinato-N,C2)picolinatoiridium(Ⅲ)(FIrpic)as the vip,the influence of the three hosts on device performance is clarified.Overall,the device using mCzmBI,a host linked by biphenyl at double meta-positions,achieved a maximum current efficiency of 24.9 cd·A^(-1)and a max-imum external quantum efficiency exceeding 12.8%,it also demonstrates low efficiency roll-off under highbrightness conditions.This work offers an effective strategy to the development of high-efficiency blue phospho-rescent hosts.展开更多
Two tetrasubstituted carbazole derivatives TBICz and TOXDCz have been designed and synthesized,which possess the twist skeletons and exhibit excellent thermal and morphological stabilities.Utilizing these novel compou...Two tetrasubstituted carbazole derivatives TBICz and TOXDCz have been designed and synthesized,which possess the twist skeletons and exhibit excellent thermal and morphological stabilities.Utilizing these novel compounds as host material,high efficiency solution-processed green phosphorescent organic light-emitting diodes(PhOLEDs)have been achieved.The high triplet energies of TBICz and TOXDCz ensure efficient energy transfer from the host to the phosphor and triplet exciton confinement on the phosphor.Solution-processable green phospho⁃rescent devices employing Ir(ppy)3 as vip and the two tetrasubstituted carbazole derivatives as hosts exhibit high ef⁃ficiencies.The best EL performance is achieved for the TBICz-based device,with a maximum current efficiency of 27.3 cd/A,a maximum power efficiency of 15.9 lm/W,and a maximum external quantum efficiency of 7.8%,which provides more host material options for solution-processed OLEDs.展开更多
Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security.The performance of existing CNN-based methods is limited by the pun...Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security.The performance of existing CNN-based methods is limited by the puny generalization of learned features and deficiency of the finger vein image training data.Considering the concerns of existing methods,in this work,a simplified deep transfer learning-based framework for finger-vein recognition is developed using an EfficientNet model of deep learning with a self-attention mechanism.Data augmentation using various geometrical methods is employed to address the problem of training data shortage required for a deep learning model.The proposed model is tested using K-fold cross-validation on three publicly available datasets:HKPU,FVUSM,and SDUMLA.Also,the developed network is compared with other modern deep nets to check its effectiveness.In addition,a comparison of the proposed method with other existing Finger vein recognition(FVR)methods is also done.The experimental results exhibited superior recognition accuracy of the proposed method compared to other existing methods.In addition,the developed method proves to be more effective and less sophisticated at extracting robust features.The proposed EffAttenNet achieves an accuracy of 98.14%on HKPU,99.03%on FVUSM,and 99.50%on SDUMLA databases.展开更多
The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation system.However,its characteristics are defined by its highly nonlinear dynamics and instability.Furthermore,the u...The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation system.However,its characteristics are defined by its highly nonlinear dynamics and instability.Furthermore,the uncertainties in the dynamics of an electromagnetic levitation system make the controller design more difficult.Therefore,it is necessary to design a robust control law that will ensure the system’s stability in the presence of these uncertainties.In this framework,the dynamics of an electromagnetic levitation system are addressed in terms of matched and unmatched uncertainties.The robust control problem is translated into the optimal control problem,where the uncertainties of the electromagnetic levitation system are directly reflected in the cost function.The optimal control method is used to solve the robust control problem.The solution to the optimal control problem for the electromagnetic levitation system is indeed a solution to the robust control problem of the electromagnetic levitation system under matched and unmatched uncertainties.The simulation and experimental results demonstrate the performance of the designed control scheme.The performance indices such as integral absolute error(IAE),integral square error(ISE),integral time absolute error(ITAE),and integral time square error(ITSE)are compared for both uncertainties to showcase the robustness of the designed control scheme.展开更多
1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become ...1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.展开更多
In digital signal processing,image enhancement or image denoising are challenging task to preserve pixel quality.There are several approaches from conventional to deep learning that are used to resolve such issues.But...In digital signal processing,image enhancement or image denoising are challenging task to preserve pixel quality.There are several approaches from conventional to deep learning that are used to resolve such issues.But they still face challenges in terms of computational requirements,overfitting and generalization issues,etc.To resolve such issues,optimization algorithms provide greater control and transparency in designing digital filters for image enhancement and denoising.Therefore,this paper presented a novel denoising approach for medical applications using an Optimized Learning⁃based Multi⁃level discrete Wavelet Cascaded Convolutional Neural Network(OLMWCNN).In this approach,the optimal filter parameters are identified to preserve the image quality after denoising.The performance and efficiency of the OLMWCNN filter are evaluated,demonstrating significant progress in denoising medical images while overcoming the limitations of conventional methods.展开更多
Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study ...Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.展开更多
The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the ...The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency domain.Despite being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.展开更多
In recent years,Speech Emotion Recognition(SER)has developed into an essential instrument for interpreting human emotions from auditory data.The proposed research focuses on the development of a SER system employing d...In recent years,Speech Emotion Recognition(SER)has developed into an essential instrument for interpreting human emotions from auditory data.The proposed research focuses on the development of a SER system employing deep learning and multiple datasets containing samples of emotive speech.The primary objective of this research endeavor is to investigate the utilization of Convolutional Neural Networks(CNNs)in the process of sound feature extraction.Stretching,pitch manipulation,and noise injection are a few of the techniques utilized in this study to improve the data quality.Feature extraction methods including Zero Crossing Rate,Chroma_stft,Mel⁃scale Frequency Cepstral Coefficients(MFCC),Root Mean Square(RMS),and Mel⁃Spectogram are used to train a model.By using these techniques,audio signals can be transformed into recognized features that can be utilized to train the model.Ultimately,the study produces a thorough evaluation of the models performance.When this method was applied,the model achieved an impressive accuracy of 94.57%on the test dataset.The proposed work was also validated on the EMO⁃BD and IEMOCAP datasets.These consist of further data augmentation,feature engineering,and hyperparameter optimization.By following these development paths,SER systems will be able to be implemented in real⁃world scenarios with greater accuracy and resilience.展开更多
Background:A major side effect of diabetes is diabetic retinopathy(DR),which can cause irreparable blindness if left untreated.Because of the additional psychological and social strains,controlling comorbidities like ...Background:A major side effect of diabetes is diabetic retinopathy(DR),which can cause irreparable blindness if left untreated.Because of the additional psychological and social strains,controlling comorbidities like DR becomes crucial for cancer patients,particularly those receiving treatments like chemotherapy.Both the patient and their caretakers may have severe effects from vision impairment,including increased anxiety,depression,and a lower quality of life.One can reduce these psychological pressures by facilitating prompt intervention,early identification,and categorization of DR.Methods:This work uses a metaheuristic optimization technique to offer a sophisticated,automated categorization system for DR.The system combines Attention AlexNet with an Improved Nutcracker Optimizer,which optimizes the weights and hyperparameters of deep learning models to improve classification accuracy.Results:The approach achieves high classification accuracy of 99.43%and enhanced precision and recall when tested on two popular image datasets,APTOS-2019 and EyePacs.Conclusions:By addressing the technological improvement in DR detection,this work contributes to the multidisciplinary approach of psycho-oncology and helps lessen the psychological distress that cancer patients experience when they lose their eyesight.Ultimately,it supports the general well-being and mental health of people facing diabetes-related problems and cancer by highlighting the significance of incorporating cutting-edge machine learning technologies into clinical practice.展开更多
This study investigates a metal laser direct-writing additive manufacturing process for potential in-space applications.The feasibility of stable deposition under various gravitational conditions—specifically at angl...This study investigates a metal laser direct-writing additive manufacturing process for potential in-space applications.The feasibility of stable deposition under various gravitational conditions—specifically at angles of 0°,90°,and 180°between the deposition direction and gravitational acceleration,and under zero-gravity—is demonstrated.The analysis reveals that a stable metal deposition layer can be formed under different gravity conditions by establishing a strong liquid bridge connection with the substrate;however,the direction of gravitational acceleration significantly affects the cross-sectional morphology of the deposition layer.By comparing different parameters,it is found that the best cross-sectional morphology can be obtained when the wire feeding speed is 120 mm/min and the ratio to the moving speed is 1.0.Notably,a higher wire feeding rate correlates with an increased temperature gradient within the heat-affected zone.On this basis,a thin-walled cylindrical piece printed at a 90°angle between the deposition gravity directions exhibits an outer surface cylindricity of 0.294mm,a size deviation range of-0.168 mm to 0.126 mm,a maximum size deviation of 0.168 mm on the outer surface,and a surface roughness of less than 8.142μm.The results indicate that this process produces printed parts with high surface quality and geometric accuracy.Tensile tests on the printed parts demonstrate that they possess excellent mechanical properties.This study provides valuable insights and a meaningful exploration of future in-orbit metal manufacturing.展开更多
The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, w...The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.展开更多
In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions ...In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions between barbers and customers,BaOA captures two key processes:the customer’s selection of a hairstyle and the detailed refinement during the haircut.These processes are translated into a mathematical framework that forms the foundation of BaOA,consisting of two critical phases:exploration,representing the creative selection process,and exploitation,which focuses on refining details for optimization.The performance of BaOA is evaluated using 52 standard benchmark functions,including unimodal,high-dimensional multimodal,fixed-dimensional multimodal,and the Congress on Evolutionary Computation(CEC)2017 test suite.This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively,resulting in high-quality solutions.A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance,as it consistently delivers better results across most benchmark functions.To validate its real-world applicability,BaOA is tested on four engineering design problems,illustrating its capability to address practical challenges with remarkable efficiency.The results confirm BaOA’s versatility and reliability as an optimization tool.This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems,providing a foundation for future research and applications in diverse scientific and engineering domains.展开更多
Nanotechnology has been gradually penetrated into the field of asphalt modification. Seemingly magic effects of nanomaterials have now been brought to improve the performance of asphalt. To demonstrate many of the pro...Nanotechnology has been gradually penetrated into the field of asphalt modification. Seemingly magic effects of nanomaterials have now been brought to improve the performance of asphalt. To demonstrate many of the prospective applications, researchers have conducted a series of positive and effective efforts dealing with the preparation of modified asphalt to demonstrate the mechanism of modification and the resultant improvement in performance. In this review, various nanomaterials used in asphalt modification are initially presented, followed by the methods employed to modify the asphalt with these materials and finally the effects of nanomaterials on the performance of base asphalt are presented and the modification mechanisms are discussed. Based on the current research results, the influence of preparation process parameters on the compatibility of every phase in the modified asphalt and the stability of the modified asphalt system are described. Finally, the development trend of the topic field is projected.展开更多
The present research on involute spline cold roll-beating forming is mainly about the principles and motion relations of cold roll-beating,the theory of roller design,and the stress and strain field analysis of cold r...The present research on involute spline cold roll-beating forming is mainly about the principles and motion relations of cold roll-beating,the theory of roller design,and the stress and strain field analysis of cold roll-beating,etc.However,the research on law of metal flow in the forming process of involute spline cold roll-beating is rare.According to the principle of involute spline cold roll-beating,the contact model between the rollers and the spline shaft blank in the process of cold roll-beating forming is established,and the theoretical analysis of metal flow in the cold roll-beating deforming region is proceeded.A finite element model of the spline cold roll-beating process is established,the formation mechanism of the involute spline tooth profile in cold roll-beating forming process is studied,and the node flow tracks of the deformation area are analyzed.The experimental research on the metal flow of cold roll-beating spline is conducted,and the metallographic structure variation,grain characteristics and metal flow line of the different tooth profile area are analyzed.The experimental results show that the particle flow directions of the deformable bodies in cold roll-beating deformation area are determined by the minimum moving resistance.There are five types of metal flow rules of the deforming region in the process of cold roll-beating forming.The characteristics of involute spline cold roll-beating forming are given,and the forming mechanism of involute spline cold roll-beating is revealed.This paper researches the law of metal flow in the forming process of involute spline cold roll-beating,which provides theoretical supports for solving the tooth profile forming quality problem.展开更多
A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant no...A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant nonlinearity exist in the volume control electro-hydraulic servo system,the ILC(iterative learning control) method is applied to tracking the displacement curve of the hydraulic press slider.In order to improve the convergence speed and precision of ILC,a fuzzy ILC algorithm that utilizes the fuzzy strategy to adaptively adjust the iterative learning gains is put forward.The simulation and experimental researches are carried out to investigate the convergence speed and precision of the fuzzy ILC for hydraulic press slider position tracking.The results show that the fuzzy ILC can raise the iterative learning speed enormously,and realize the tracking control of slider displacement curve with rapid response speed and high control precision.In experiment,the maximum tracking error 0.02 V is achieved through 12 iterations only.展开更多
Because the result of the MB fractal model contradicts with the classical contact mechanics, a revised elastoplastic contact model of a single asperity is developed based on fractal theory. The critical areas of a sin...Because the result of the MB fractal model contradicts with the classical contact mechanics, a revised elastoplastic contact model of a single asperity is developed based on fractal theory. The critical areas of a single asperity are scale dependent, with an increase in the contact load and contact area, a transition from elastic, elastoplastic to full plastic deformation takes place in this order. In considering the size distribution function, analytic expression between the total contact load and the real contact area on the contact surface is obtained. The elastic, elastoplastic and full plastic contact load are obtained by the critical elastic contact area of the biggest asperity and maximun contact area of a single asperity. The results show that a rough surface is firstly in elastic deformation. As the load increases, elastoplastic or full plastic deformation takes place. For constant characteristic length scale G, the slope of load-area relation is proportional to fractal dimension D. For constant fractal dimension D, the slope of load-area relation is inversely proportional to G. For constant D and G, the slope of load-area relation is inversely proportional to property of the material ~b, namely with the same load, the material of rough surface is softer, and the total contact area is larger. The contact mechanics model provides a foundation for study of the friction, wear and seal performance of rough surfaces.展开更多
基金supported by the the National Natural Science Foundation of China(52203303)the Shenzhen Science and Technology Program(SGDX20211123151002003 and GJHZ20220913142812025)+1 种基金the International Partnership Program of the Chinese Academy of Sciences(321GJHZ2023189FN)the SIAT International Joint Lab(E5G108).
文摘Layered manganese dioxide(δ-MnO_(2))is a promising cathode material for aqueous zinc-ion batteries(AZIBs)due to its high theoretical capacity,high operating voltage,and low cost.However,its practical application faces challenges,such as low electronic conductivity,sluggish diffusion kinetics,and severe dissolution of Mn^(2+).In this study,we developed a δ-MnO_(2) coated with a 2-methylimidazole(δ-MnO_(2)@2-ML)hybrid cathode.Density functional theory(DFT)calculations indicate that 2-ML can be integrated into δ-MnO_(2) through both pre-intercalation and surface coating,with thermodynamically favorable outcomes.This modification expands the interlayer spacing of δ-MnO_(2) and generates Mn-N bonds on the surface,enhancing Zn^(2+)accommodation and diffusion kinetics as well as stabilizing surface Mn sites.The experimentally prepared δ-MnO_(2)@2-ML cathode,as predicted by DFT,features both 2-ML pre-intercalation and surface coating,providing more zinc-ion insertion sites and improved structural stability.Furthermore,X-ray diffraction shows the expanded interlayer spacing,which effectively buffers local electrostatic interactions,leading to an enhanced Zn^(2+)diffusion rate.Consequently,the optimized cathode(δ-MnO_(2)@2-ML)presents improved electrochemical performance and stability,and the fabricated AZIBs exhibit a high specific capacity(309.5mAh/g at 0.1 A/g),superior multiplicative performance(137.6mAh/g at 1 A/g),and impressive capacity retention(80%after 1350 cycles at 1 A/g).These results surpass the performance of most manganese-based and vanadium-based cathode materials reported to date.This dual-modulation strategy,combining interlayer engineering and interface optimization,offers a straightforward and scalable approach,potentially advancing the commercial viability of low-cost,high-performance AZIBs.
文摘Theoretically,blue phosphorescent materials are capable of achieving 100%internal quantum effi-ciency.Nevertheless,the mutual constraints among efficiency,color purity,and stability remain one of the key bottlenecks in the industrialization of organic light-emitting diodes(OLEDs).In addition,the design and application of host materials also exert a significant impact on the overall performance of blue light-emitting de-vices.To address this issue,this study constructs a series of host materials with high triplet energy levels by designing different connection modes,based on 9-phenylcarbazole and benzimidazole units.Through a combi-nation of theoretical and experimental approaches,the correlation between the chemical structure and perfor-mance has been unraveled.It is found that the designed and synthesized blue phosphorescent bipolar host ma-terials based on different biphenyl linking sites,i.e.,9-(3'-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1'-bi-phenyl]-3-yl)-9H-carbazole(mCzmBI),9-(2'-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1'-biphenyl]-3-yl)-9H-carbazole(mCzoBI)and 9-(3'-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1'-biphenyl]-2-yl)-9H-carbazole(oCzmBI).The three compounds have a similar triplet energy level of 2.70 eV,accompanied with the glass transition temperatures of 92℃,103℃,and 93℃respectively.mCzmBI,mCzoBI and oCzmBI are regioiso-mers,but differ in the linking sites of carbazole and benzimidazole on the biphenyl linker.This difference in linking positions enables effective regulation of the host materials’properties.Constructed with the blue phos-phorescent material bis(4,6-difluorophenylpyridinato-N,C2)picolinatoiridium(Ⅲ)(FIrpic)as the vip,the influence of the three hosts on device performance is clarified.Overall,the device using mCzmBI,a host linked by biphenyl at double meta-positions,achieved a maximum current efficiency of 24.9 cd·A^(-1)and a max-imum external quantum efficiency exceeding 12.8%,it also demonstrates low efficiency roll-off under highbrightness conditions.This work offers an effective strategy to the development of high-efficiency blue phospho-rescent hosts.
文摘Two tetrasubstituted carbazole derivatives TBICz and TOXDCz have been designed and synthesized,which possess the twist skeletons and exhibit excellent thermal and morphological stabilities.Utilizing these novel compounds as host material,high efficiency solution-processed green phosphorescent organic light-emitting diodes(PhOLEDs)have been achieved.The high triplet energies of TBICz and TOXDCz ensure efficient energy transfer from the host to the phosphor and triplet exciton confinement on the phosphor.Solution-processable green phospho⁃rescent devices employing Ir(ppy)3 as vip and the two tetrasubstituted carbazole derivatives as hosts exhibit high ef⁃ficiencies.The best EL performance is achieved for the TBICz-based device,with a maximum current efficiency of 27.3 cd/A,a maximum power efficiency of 15.9 lm/W,and a maximum external quantum efficiency of 7.8%,which provides more host material options for solution-processed OLEDs.
文摘Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security.The performance of existing CNN-based methods is limited by the puny generalization of learned features and deficiency of the finger vein image training data.Considering the concerns of existing methods,in this work,a simplified deep transfer learning-based framework for finger-vein recognition is developed using an EfficientNet model of deep learning with a self-attention mechanism.Data augmentation using various geometrical methods is employed to address the problem of training data shortage required for a deep learning model.The proposed model is tested using K-fold cross-validation on three publicly available datasets:HKPU,FVUSM,and SDUMLA.Also,the developed network is compared with other modern deep nets to check its effectiveness.In addition,a comparison of the proposed method with other existing Finger vein recognition(FVR)methods is also done.The experimental results exhibited superior recognition accuracy of the proposed method compared to other existing methods.In addition,the developed method proves to be more effective and less sophisticated at extracting robust features.The proposed EffAttenNet achieves an accuracy of 98.14%on HKPU,99.03%on FVUSM,and 99.50%on SDUMLA databases.
文摘The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation system.However,its characteristics are defined by its highly nonlinear dynamics and instability.Furthermore,the uncertainties in the dynamics of an electromagnetic levitation system make the controller design more difficult.Therefore,it is necessary to design a robust control law that will ensure the system’s stability in the presence of these uncertainties.In this framework,the dynamics of an electromagnetic levitation system are addressed in terms of matched and unmatched uncertainties.The robust control problem is translated into the optimal control problem,where the uncertainties of the electromagnetic levitation system are directly reflected in the cost function.The optimal control method is used to solve the robust control problem.The solution to the optimal control problem for the electromagnetic levitation system is indeed a solution to the robust control problem of the electromagnetic levitation system under matched and unmatched uncertainties.The simulation and experimental results demonstrate the performance of the designed control scheme.The performance indices such as integral absolute error(IAE),integral square error(ISE),integral time absolute error(ITAE),and integral time square error(ITSE)are compared for both uncertainties to showcase the robustness of the designed control scheme.
基金supported by the National Level Project of China (No. 2020-JCJQ-ZQ-059)。
文摘1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.
文摘In digital signal processing,image enhancement or image denoising are challenging task to preserve pixel quality.There are several approaches from conventional to deep learning that are used to resolve such issues.But they still face challenges in terms of computational requirements,overfitting and generalization issues,etc.To resolve such issues,optimization algorithms provide greater control and transparency in designing digital filters for image enhancement and denoising.Therefore,this paper presented a novel denoising approach for medical applications using an Optimized Learning⁃based Multi⁃level discrete Wavelet Cascaded Convolutional Neural Network(OLMWCNN).In this approach,the optimal filter parameters are identified to preserve the image quality after denoising.The performance and efficiency of the OLMWCNN filter are evaluated,demonstrating significant progress in denoising medical images while overcoming the limitations of conventional methods.
文摘Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.
基金supported by National Natural Science Foundation of China(52375530,52075132)Natural Science Foundation of Heilongjiang Province(YQ2022E025)+4 种基金State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment(Guangdong University of Technology)(JMDZ202312)Fundamental Research Funds for the Central Universities(HIT.OCEF.2024034)China Postdoctoral Science Foundation(2019M651278,2020T130155)Heilongjiang Province Postdoctoral Science Foundation(LBH-Z19066)Space Drive and Manipulation Mechanism Laboratory of BICE and National Key Laboratory of Space Intelligent Control,No BICE-SDMM-2024-01
文摘The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency domain.Despite being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.
文摘In recent years,Speech Emotion Recognition(SER)has developed into an essential instrument for interpreting human emotions from auditory data.The proposed research focuses on the development of a SER system employing deep learning and multiple datasets containing samples of emotive speech.The primary objective of this research endeavor is to investigate the utilization of Convolutional Neural Networks(CNNs)in the process of sound feature extraction.Stretching,pitch manipulation,and noise injection are a few of the techniques utilized in this study to improve the data quality.Feature extraction methods including Zero Crossing Rate,Chroma_stft,Mel⁃scale Frequency Cepstral Coefficients(MFCC),Root Mean Square(RMS),and Mel⁃Spectogram are used to train a model.By using these techniques,audio signals can be transformed into recognized features that can be utilized to train the model.Ultimately,the study produces a thorough evaluation of the models performance.When this method was applied,the model achieved an impressive accuracy of 94.57%on the test dataset.The proposed work was also validated on the EMO⁃BD and IEMOCAP datasets.These consist of further data augmentation,feature engineering,and hyperparameter optimization.By following these development paths,SER systems will be able to be implemented in real⁃world scenarios with greater accuracy and resilience.
文摘Background:A major side effect of diabetes is diabetic retinopathy(DR),which can cause irreparable blindness if left untreated.Because of the additional psychological and social strains,controlling comorbidities like DR becomes crucial for cancer patients,particularly those receiving treatments like chemotherapy.Both the patient and their caretakers may have severe effects from vision impairment,including increased anxiety,depression,and a lower quality of life.One can reduce these psychological pressures by facilitating prompt intervention,early identification,and categorization of DR.Methods:This work uses a metaheuristic optimization technique to offer a sophisticated,automated categorization system for DR.The system combines Attention AlexNet with an Improved Nutcracker Optimizer,which optimizes the weights and hyperparameters of deep learning models to improve classification accuracy.Results:The approach achieves high classification accuracy of 99.43%and enhanced precision and recall when tested on two popular image datasets,APTOS-2019 and EyePacs.Conclusions:By addressing the technological improvement in DR detection,this work contributes to the multidisciplinary approach of psycho-oncology and helps lessen the psychological distress that cancer patients experience when they lose their eyesight.Ultimately,it supports the general well-being and mental health of people facing diabetes-related problems and cancer by highlighting the significance of incorporating cutting-edge machine learning technologies into clinical practice.
文摘This study investigates a metal laser direct-writing additive manufacturing process for potential in-space applications.The feasibility of stable deposition under various gravitational conditions—specifically at angles of 0°,90°,and 180°between the deposition direction and gravitational acceleration,and under zero-gravity—is demonstrated.The analysis reveals that a stable metal deposition layer can be formed under different gravity conditions by establishing a strong liquid bridge connection with the substrate;however,the direction of gravitational acceleration significantly affects the cross-sectional morphology of the deposition layer.By comparing different parameters,it is found that the best cross-sectional morphology can be obtained when the wire feeding speed is 120 mm/min and the ratio to the moving speed is 1.0.Notably,a higher wire feeding rate correlates with an increased temperature gradient within the heat-affected zone.On this basis,a thin-walled cylindrical piece printed at a 90°angle between the deposition gravity directions exhibits an outer surface cylindricity of 0.294mm,a size deviation range of-0.168 mm to 0.126 mm,a maximum size deviation of 0.168 mm on the outer surface,and a surface roughness of less than 8.142μm.The results indicate that this process produces printed parts with high surface quality and geometric accuracy.Tensile tests on the printed parts demonstrate that they possess excellent mechanical properties.This study provides valuable insights and a meaningful exploration of future in-orbit metal manufacturing.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61971345 and 52107174)。
文摘The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.
文摘In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions between barbers and customers,BaOA captures two key processes:the customer’s selection of a hairstyle and the detailed refinement during the haircut.These processes are translated into a mathematical framework that forms the foundation of BaOA,consisting of two critical phases:exploration,representing the creative selection process,and exploitation,which focuses on refining details for optimization.The performance of BaOA is evaluated using 52 standard benchmark functions,including unimodal,high-dimensional multimodal,fixed-dimensional multimodal,and the Congress on Evolutionary Computation(CEC)2017 test suite.This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively,resulting in high-quality solutions.A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance,as it consistently delivers better results across most benchmark functions.To validate its real-world applicability,BaOA is tested on four engineering design problems,illustrating its capability to address practical challenges with remarkable efficiency.The results confirm BaOA’s versatility and reliability as an optimization tool.This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems,providing a foundation for future research and applications in diverse scientific and engineering domains.
基金the financial supports from the National Natural Science Foundation of China(Grant Nos. 51002118 and 51172180)Program for New Century Excellent Talents in University of Ministry of Education of China(Grant No.NCET-12-1045)Shaanxi Programs for Outstanding Youth Project(2011)
文摘Nanotechnology has been gradually penetrated into the field of asphalt modification. Seemingly magic effects of nanomaterials have now been brought to improve the performance of asphalt. To demonstrate many of the prospective applications, researchers have conducted a series of positive and effective efforts dealing with the preparation of modified asphalt to demonstrate the mechanism of modification and the resultant improvement in performance. In this review, various nanomaterials used in asphalt modification are initially presented, followed by the methods employed to modify the asphalt with these materials and finally the effects of nanomaterials on the performance of base asphalt are presented and the modification mechanisms are discussed. Based on the current research results, the influence of preparation process parameters on the compatibility of every phase in the modified asphalt and the stability of the modified asphalt system are described. Finally, the development trend of the topic field is projected.
基金supported by National Natural Science Foundation of China(Grant Nos.5107512450975229)Doctoral Foundation of Henan University of Science and Technology of China(Grant No.09001331)
文摘The present research on involute spline cold roll-beating forming is mainly about the principles and motion relations of cold roll-beating,the theory of roller design,and the stress and strain field analysis of cold roll-beating,etc.However,the research on law of metal flow in the forming process of involute spline cold roll-beating is rare.According to the principle of involute spline cold roll-beating,the contact model between the rollers and the spline shaft blank in the process of cold roll-beating forming is established,and the theoretical analysis of metal flow in the cold roll-beating deforming region is proceeded.A finite element model of the spline cold roll-beating process is established,the formation mechanism of the involute spline tooth profile in cold roll-beating forming process is studied,and the node flow tracks of the deformation area are analyzed.The experimental research on the metal flow of cold roll-beating spline is conducted,and the metallographic structure variation,grain characteristics and metal flow line of the different tooth profile area are analyzed.The experimental results show that the particle flow directions of the deformable bodies in cold roll-beating deformation area are determined by the minimum moving resistance.There are five types of metal flow rules of the deforming region in the process of cold roll-beating forming.The characteristics of involute spline cold roll-beating forming are given,and the forming mechanism of involute spline cold roll-beating is revealed.This paper researches the law of metal flow in the forming process of involute spline cold roll-beating,which provides theoretical supports for solving the tooth profile forming quality problem.
基金Project(2007AA04Z144) supported by the National High-Tech Research and Development Program of ChinaProject(2007421119) supported by the China Postdoctoral Science Foundation
文摘A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant nonlinearity exist in the volume control electro-hydraulic servo system,the ILC(iterative learning control) method is applied to tracking the displacement curve of the hydraulic press slider.In order to improve the convergence speed and precision of ILC,a fuzzy ILC algorithm that utilizes the fuzzy strategy to adaptively adjust the iterative learning gains is put forward.The simulation and experimental researches are carried out to investigate the convergence speed and precision of the fuzzy ILC for hydraulic press slider position tracking.The results show that the fuzzy ILC can raise the iterative learning speed enormously,and realize the tracking control of slider displacement curve with rapid response speed and high control precision.In experiment,the maximum tracking error 0.02 V is achieved through 12 iterations only.
基金Supported by National Natural Science Foundation of China(Grant Nos.51105304,51475364)Shaanxi Provincial Natural Science Basic Research Plan of China(Grant No.2015JM5212)
文摘Because the result of the MB fractal model contradicts with the classical contact mechanics, a revised elastoplastic contact model of a single asperity is developed based on fractal theory. The critical areas of a single asperity are scale dependent, with an increase in the contact load and contact area, a transition from elastic, elastoplastic to full plastic deformation takes place in this order. In considering the size distribution function, analytic expression between the total contact load and the real contact area on the contact surface is obtained. The elastic, elastoplastic and full plastic contact load are obtained by the critical elastic contact area of the biggest asperity and maximun contact area of a single asperity. The results show that a rough surface is firstly in elastic deformation. As the load increases, elastoplastic or full plastic deformation takes place. For constant characteristic length scale G, the slope of load-area relation is proportional to fractal dimension D. For constant fractal dimension D, the slope of load-area relation is inversely proportional to G. For constant D and G, the slope of load-area relation is inversely proportional to property of the material ~b, namely with the same load, the material of rough surface is softer, and the total contact area is larger. The contact mechanics model provides a foundation for study of the friction, wear and seal performance of rough surfaces.
