The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
Over the past decade,large-scale pre-trained autoregressive and diffusion models rejuvenated the field of text-guided image generation.However,these models require enormous datasets and parameters,and their multi-step...Over the past decade,large-scale pre-trained autoregressive and diffusion models rejuvenated the field of text-guided image generation.However,these models require enormous datasets and parameters,and their multi-step generation processes are often inefficient and difficult to control.To address these challenges,we propose CAFE-GAN,a CLIP-Projected GAN with Attention-Aware Generation and Multi-Scale Discrimination,which incorporates a pretrained CLIP model along with several key architectural innovations.First,we embed a coordinate attention mechanism into the generator to capture long-range dependencies and enhance feature representation.Second,we introduce a trainable linear projection layer after the CLIP text encoder,which aligns textual embeddings with the generator’s semantic space.Third,we design a multi-scale discriminator that leverages pre-trained visual features and integrates a feature regularization strategy,thereby improving training stability and discrimination performance.Experiments on the CUB and COCO datasets demonstrate that CAFE-GAN outperforms existing text-to-image generation methods,achieving lower Fréchet Inception Distance(FID)scores and generating images with superior visual quality and semantic fidelity,with FID scores of 9.84 and 5.62 on the CUB and COCO datasets,respectively,surpassing current state-of-the-art text-to-image models by varying degrees.These findings offer valuable insights for future research on efficient,controllable text-to-image synthesis.展开更多
Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural ...Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.展开更多
Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressi...Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.展开更多
Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.You...Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.展开更多
In wind power generation system the grid-connected inverter is an important section for energy conversion and transmission, of which the performance has a direct influence on the entire wind power generation system. T...In wind power generation system the grid-connected inverter is an important section for energy conversion and transmission, of which the performance has a direct influence on the entire wind power generation system. The mathematical model of the grid-connected inverter is deduced firstly. Then, the space vector pulse width modulation （SVPWM） is analyzed. The power factor can be controlled close to unity, leading or lagging, which is realized based on H-type current controller and grid voltage vector-oriented control. The control strategy is verified by the simulation and experimental results with a good sinusoidal current, a small harmonic component and a fast dynamic response.展开更多
Islanding detection is an essential function for safety and reliability in grid-connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them may fail under mult...Islanding detection is an essential function for safety and reliability in grid-connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them may fail under multi-source configurations, or they may produce important power quality degradation which gets worse with increasing DG penetration. This paper presents an active islanding detection algorithm for Voltage Source Inverter (VSI) based multi-source DG systems. The proposed method is based on the Voltage Positive Feedback (VPF) theory to generate a limited active power perturbation. Theoretical analyses were performed and simulations by MATLAB /Simulink /SimPowerSystems were used to evaluate the algorithm’s performance and its advantages concerning the time response and the effects on power quality, which turned out to be negligible. The algorithm performance was tested under critical conditions: load with unity power factor, load with high quality factor, and load matching DER’s powers.展开更多
A quasi resonant pulse width modulation（PWM） inverter is used in a solar power system to convert the solar panel and battery charger＇s direct current（DC） output to alternating current（AC）.Although much has been...A quasi resonant pulse width modulation（PWM） inverter is used in a solar power system to convert the solar panel and battery charger＇s direct current（DC） output to alternating current（AC）.Although much has been published about DC to AC PWM inverters,none of the previous work has shown modeling and simulation results for DC to AC inverters.In this study,we suggest a new topology for a quasi resonant PWM inverter.Experimental results are also presented.展开更多
100-W class power storage systems were developed, which comprised spherical Si solar cells, a maximum power point tracking charge control-ler, a lithium-ion battery, and one of two different types of direct current (D...100-W class power storage systems were developed, which comprised spherical Si solar cells, a maximum power point tracking charge control-ler, a lithium-ion battery, and one of two different types of direct current (DC)-alter- nating current (AC) converters. One inverter used SiC met-al-oxide-semicon-ductor field-effect transistors (MOSFETs) as switching devices while the other used Si MOSFETs. In these 100-W class inverters, the ON resistance was considered to have little influence on the efficiency. Nevertheless, the SiC-based inverter exhibited an approximately 3% higher DC-AC conversion efficiency than the Si-based inverter. Power loss analysis indicated that the higher efficiency resulted predominantly from lower switching and reverse recovery losses in the SiC MOSFETs compared with in the Si MOSFETs.展开更多
During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in unc...During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.展开更多
The paper introduces an inverter system designed for segmented diagonalMHD generator.The characteristics and composition of the MHD inverter is analysed.And its control structure and function are presented.
Complementary inverter is the basic unit for logic circuits,but the inverters based on full oxide thin-film transistors(TFTs)are still very limited.The next challenge is to realize complementary inverters using homoge...Complementary inverter is the basic unit for logic circuits,but the inverters based on full oxide thin-film transistors(TFTs)are still very limited.The next challenge is to realize complementary inverters using homogeneous oxide semiconduc-tors.Herein,we propose the design of complementary inverter based on full ZnO TFTs.Li-N dual-doped ZnO(ZnO:(Li,N))acts as the p-type channel and Al-doped ZnO(ZnO:Al)serves as the n-type channel for fabrication of TFTs,and then the complemen-tary inverter is produced with p-and n-type ZnO TFTs.The homogeneous ZnO-based complementary inverter has typical volt-age transfer characteristics with the voltage gain of 13.34 at the supply voltage of 40 V.This work may open the door for the development of oxide complementary inverters for logic circuits.展开更多
With the development of high-frequency and highvoltagetraction machines(TM)incorporating hairpin windings(HW)and SiC inverters for electric vehicles(EV),both theinterturn voltage stress and temperature within HW are r...With the development of high-frequency and highvoltagetraction machines(TM)incorporating hairpin windings(HW)and SiC inverters for electric vehicles(EV),both theinterturn voltage stress and temperature within HW are rising,increasing the risk of partial discharge(PD),and presentingsignificant challenges to insulation safety.Therefore,this paperaddresses this issue and proposes potential solutions.Firstly,thepaper examines an 8-pole,48-slot,6-layer HW TM to highlightthe unique characteristics of this winding structure,and explainsthe uneven distribution of interturn voltage stress andtemperature.Subsequently,a high-frequency equivalent circuitmodel of the HW TM prototype is developed.The error ofsimulation and experiment is only 5.7%,which proves theaccuracy of the model.Then,an improved HW scheme isproposed to lower the maximum voltage stress by 29.3%.Furthermore,the temperature distribution of HW TM isanalyzed to facilitate a detailed examination of the impact oftemperature on insulation PD.Finally,the partial dischargeinception voltage(PDIV)of interturn insulation,consideringtemperature effects,is calculated and verified throughexperiment.The paper proposes a reliability-oriented designmethod and process for HW TM.It demonstrates that thereliability-oriented design can achieve PD-free performance inthe design stage of HW.展开更多
Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have de...Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have developed a vertical hydroponic breeding system integrated with light-emitting diodes(LEDs)light-ing in a closed plant factory(PF),which significantly accelerates rice growth and generation advance-ment.The results show that indica rice can be harvested as early as after 63 days of cultivation,a 50%reduction compared with field cultivation,enabling the annual harvesting of 5-6 generations within the PF.A hyperspectral imaging(HSI)system and attenuated total reflectance infrared(ATR-IR)spec-troscopy were further employed to characterize the chemical composition of the PF-and field-cultivated rice.Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)and gas chromatography-mass spectrometry(GC-MS)revealed that,com-pared with the field-cultivated rice,the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites,such as isovitexin,succinic acid,and methylillicinone F.Overall,this study reveals the unique metabolic profile of PF-cultivated rice and high-lights the potential of PFs to accelerate the breeding of crops such as rice,offering an innovative agricul-tural strategy to support food security in the face of global population growth and climate change.展开更多
Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,th...Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.展开更多
The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of user...The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.展开更多
To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a b...To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a benchmark scramjet performance evaluation model.Based on the test data of typical flying point of Mach 7 with the altitude of 29 km,the reliability of the model was verified.The deviations of parameters such as the to⁃tal pressure loss of combustor between the model and the test data were analyzed.Furtherly,an analytical method for post-combustion magnetohydrodynamic power generation was established;by embedding the above method into the overall performance evaluation model,performance prediction considering the power generation effect was realized.Finally,based on the above model,variety regulations of the inlet and the outlet parameters of the power generation channel and performance parameters including the engine specific impulse and the unit thrust under different enthalpy extraction ratios and load factors were analyzed.It could be concluded that the model can reliably predict the variations of key parameters.As the value of the load factor increases,the value of the conduc⁃tivity required to reach the specified enthalpy extraction ratio first decreases and then increases,which is approxi⁃mately parabolic.In order to reduce the demand for the gas conductivity for MHD power generation,the load fac⁃tor should be around 0.5.When the load factor is 0.4 and the magnetic induction intensity is 2.5 T,if the enthalpy extraction ratio reaches 0.5%,the engine specific impulse performance reduces about 3.58%.展开更多
The generation of optical vortices from nonlinear photonic crystals(NPCs)with spatially modulated second-order nonlinearity offers a promising approach to extend the working wavelength and topological charge of vortex...The generation of optical vortices from nonlinear photonic crystals(NPCs)with spatially modulated second-order nonlinearity offers a promising approach to extend the working wavelength and topological charge of vortex beams for various applications.In this work,the second harmonic(SH)optical vortex beams generated from nonlinear fork gratings under Gaussian beam illumination are numerically investigated.The far-field intensity and phase distributions,as well as the orbital angular momentum(OAM)spectra of the SH beams,are analyzed for different structural topological charges and diffraction orders.Results reveal that higher-order diffraction and larger structural topological charges lead to angular interference patterns and non-uniform intensity distributions,deviating from the standard vortex profile.To optimize the SH vortex quality,the effects of the fundamental wave beam waist,crystal thickness,and grating duty cycle are explored.It is shown that increasing the beam waist can effectively suppress diffraction order interference and improve the beam’s quality.This study provides theoretical guidance for enhancing the performance of nonlinear optical devices based on NPCs.展开更多
The ability to generate high pressures in a large-volume press(LVP)is crucial for the study of matter under extreme conditions.Here,we have achieved ultrahigh pressures of and 50 GPa,respectively,at room temperature a...The ability to generate high pressures in a large-volume press(LVP)is crucial for the study of matter under extreme conditions.Here,we have achieved ultrahigh pressures of and 50 GPa,respectively,at room temperature and a high temperature of 1900 K∼60within a millimeter-sized sample volume in a Kawai-type LVP(KLVP)using hard tungsten carbide(WC)and newly designed assem-blies.The introduction of electroconductive polycrystalline boron-doped diamond and dense alumina wrapped with Cu foils into a large conventional cell assembly enables the detection of resistance variations in the Fe_(2)O_(3) pressure standard upon compression.The efficiency of pressure generation in the newly developed cell assembly equipped with conventional ZK10F WC anvils is significantly higher than that of conventional assemblies with some ultrahard or tapered WC anvils.Our study has enabled the routine gener-ation of pressures exceeding 50 GPa within a millimeter-sized sample chamber that have been inaccessible with traditional KLVPs.This advance in high-pressure technology not only breaks a record for pressure generation in traditional KLVPs,but also opens up new avenues for exploration of the properties of the Earth’s deep interior and for the synthesis of novel materials at extreme high pressures.展开更多
The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation...The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation,focusing on their demonstrated potential to enhance production efficiency through automation and personalization.Despite these benefits,it is crucial to acknowledge the substantial initial computational investments required for training and deploying these models.We conduct an in-depth survey of cutting-edge generative AI technologies,encompassing models such as Stable Diffusion and GPT,and appraise pivotal large-scale datasets alongside quantifiable evaluation metrics.Review of the surveyed literature indicates the achievement of considerable maturity in the capacity of AI models to synthesize high-quality,aesthetically compelling anime visual images from textual prompts,alongside discernible progress in the generation of coherent narratives.However,achieving perfect long-form consistency,mitigating artifacts like flickering in video sequences,and enabling fine-grained artistic control remain critical ongoing challenges.Building upon these advancements,research efforts have increasingly pivoted towards the synthesis of higher-dimensional content,such as video and three-dimensional assets,with recent studies demonstrating significant progress in this burgeoning field.Nevertheless,formidable challenges endure amidst these advancements.Foremost among these are the substantial computational exigencies requisite for training and deploying these sophisticated models,particularly pronounced in the realm of high-dimensional generation such as video synthesis.Additional persistent hurdles include maintaining spatial-temporal consistency across complex scenes and mitigating ethical considerations surrounding bias and the preservation of human creative autonomy.This research underscores the transformative potential and inherent complexities of AI-driven synergy within the creative industries.We posit that future research should be dedicated to the synergistic fusion of diffusion and autoregressive models,the integration of multimodal inputs,and the balanced consideration of ethical implications,particularly regarding bias and the preservation of human creative autonomy,thereby establishing a robust foundation for the advancement of anime creation and the broader landscape of AI-driven content generation.展开更多
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
文摘Over the past decade,large-scale pre-trained autoregressive and diffusion models rejuvenated the field of text-guided image generation.However,these models require enormous datasets and parameters,and their multi-step generation processes are often inefficient and difficult to control.To address these challenges,we propose CAFE-GAN,a CLIP-Projected GAN with Attention-Aware Generation and Multi-Scale Discrimination,which incorporates a pretrained CLIP model along with several key architectural innovations.First,we embed a coordinate attention mechanism into the generator to capture long-range dependencies and enhance feature representation.Second,we introduce a trainable linear projection layer after the CLIP text encoder,which aligns textual embeddings with the generator’s semantic space.Third,we design a multi-scale discriminator that leverages pre-trained visual features and integrates a feature regularization strategy,thereby improving training stability and discrimination performance.Experiments on the CUB and COCO datasets demonstrate that CAFE-GAN outperforms existing text-to-image generation methods,achieving lower Fréchet Inception Distance(FID)scores and generating images with superior visual quality and semantic fidelity,with FID scores of 9.84 and 5.62 on the CUB and COCO datasets,respectively,surpassing current state-of-the-art text-to-image models by varying degrees.These findings offer valuable insights for future research on efficient,controllable text-to-image synthesis.
基金supported by the National Key Research and Development Program of China(2023YFF0906502)the Postgraduate Research and Innovation Project of Hunan Province under Grant(CX20240473).
文摘Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.
文摘Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.
文摘Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.
基金supported by Delta Power Electronic Science and Education Development in 2007 (Grant No.DRES2007002)
文摘In wind power generation system the grid-connected inverter is an important section for energy conversion and transmission, of which the performance has a direct influence on the entire wind power generation system. The mathematical model of the grid-connected inverter is deduced firstly. Then, the space vector pulse width modulation （SVPWM） is analyzed. The power factor can be controlled close to unity, leading or lagging, which is realized based on H-type current controller and grid voltage vector-oriented control. The control strategy is verified by the simulation and experimental results with a good sinusoidal current, a small harmonic component and a fast dynamic response.
文摘Islanding detection is an essential function for safety and reliability in grid-connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them may fail under multi-source configurations, or they may produce important power quality degradation which gets worse with increasing DG penetration. This paper presents an active islanding detection algorithm for Voltage Source Inverter (VSI) based multi-source DG systems. The proposed method is based on the Voltage Positive Feedback (VPF) theory to generate a limited active power perturbation. Theoretical analyses were performed and simulations by MATLAB /Simulink /SimPowerSystems were used to evaluate the algorithm’s performance and its advantages concerning the time response and the effects on power quality, which turned out to be negligible. The algorithm performance was tested under critical conditions: load with unity power factor, load with high quality factor, and load matching DER’s powers.
基金supported by the Ming Chuan University Internal Research Fund
文摘A quasi resonant pulse width modulation（PWM） inverter is used in a solar power system to convert the solar panel and battery charger＇s direct current（DC） output to alternating current（AC）.Although much has been published about DC to AC PWM inverters,none of the previous work has shown modeling and simulation results for DC to AC inverters.In this study,we suggest a new topology for a quasi resonant PWM inverter.Experimental results are also presented.
文摘100-W class power storage systems were developed, which comprised spherical Si solar cells, a maximum power point tracking charge control-ler, a lithium-ion battery, and one of two different types of direct current (DC)-alter- nating current (AC) converters. One inverter used SiC met-al-oxide-semicon-ductor field-effect transistors (MOSFETs) as switching devices while the other used Si MOSFETs. In these 100-W class inverters, the ON resistance was considered to have little influence on the efficiency. Nevertheless, the SiC-based inverter exhibited an approximately 3% higher DC-AC conversion efficiency than the Si-based inverter. Power loss analysis indicated that the higher efficiency resulted predominantly from lower switching and reverse recovery losses in the SiC MOSFETs compared with in the Si MOSFETs.
基金This article was supported by the general project“Research on Wind and Photovoltaic Fault Characteristics and Practical Short Circuit Calculation Model”(521820200097)of Jiangxi Electric Power Company.
文摘During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.
文摘The paper introduces an inverter system designed for segmented diagonalMHD generator.The characteristics and composition of the MHD inverter is analysed.And its control structure and function are presented.
基金supported by Zhejiang Provincial Natural Science Foundation of China(No.LZ24E020001).
文摘Complementary inverter is the basic unit for logic circuits,but the inverters based on full oxide thin-film transistors(TFTs)are still very limited.The next challenge is to realize complementary inverters using homogeneous oxide semiconduc-tors.Herein,we propose the design of complementary inverter based on full ZnO TFTs.Li-N dual-doped ZnO(ZnO:(Li,N))acts as the p-type channel and Al-doped ZnO(ZnO:Al)serves as the n-type channel for fabrication of TFTs,and then the complemen-tary inverter is produced with p-and n-type ZnO TFTs.The homogeneous ZnO-based complementary inverter has typical volt-age transfer characteristics with the voltage gain of 13.34 at the supply voltage of 40 V.This work may open the door for the development of oxide complementary inverters for logic circuits.
基金supported by the Project of National Natural Science Foundation of China under Grant 52407060 and 52422704supported by Liaoning Province science and technology plan doctoral project under Grant 2023-BSBA-255.
文摘With the development of high-frequency and highvoltagetraction machines(TM)incorporating hairpin windings(HW)and SiC inverters for electric vehicles(EV),both theinterturn voltage stress and temperature within HW are rising,increasing the risk of partial discharge(PD),and presentingsignificant challenges to insulation safety.Therefore,this paperaddresses this issue and proposes potential solutions.Firstly,thepaper examines an 8-pole,48-slot,6-layer HW TM to highlightthe unique characteristics of this winding structure,and explainsthe uneven distribution of interturn voltage stress andtemperature.Subsequently,a high-frequency equivalent circuitmodel of the HW TM prototype is developed.The error ofsimulation and experiment is only 5.7%,which proves theaccuracy of the model.Then,an improved HW scheme isproposed to lower the maximum voltage stress by 29.3%.Furthermore,the temperature distribution of HW TM isanalyzed to facilitate a detailed examination of the impact oftemperature on insulation PD.Finally,the partial dischargeinception voltage(PDIV)of interturn insulation,consideringtemperature effects,is calculated and verified throughexperiment.The paper proposes a reliability-oriented designmethod and process for HW TM.It demonstrates that thereliability-oriented design can achieve PD-free performance inthe design stage of HW.
基金supported by the National Key Research and Development Program(2023YFF1001500)the Local Financial Funds of National Agricultural Science and Technology Center,Chengdu(NASC2022KR02,NASC2023TD08,NASC2021ST08,NASC2021PC04,NASC2022KR07,NASC2022KR06,and NASC2023ST04)+2 种基金the Agricultural Science and Technology Innova-tion Program(ASTIP-34-IUA-01,ASTIP-34-IUA-02,ASTIP-IUA-2023003,and ASTIP2024-34-IUA-09)the Central Public-interest Scientific Institution Basal Research Fund(Y2023YJ07 and SZ202403)the Sichuan Science and Technology Program(2023YFN003,2024NSFC1261,2023YFQ0100,and 2023ZYD0089).
文摘Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have developed a vertical hydroponic breeding system integrated with light-emitting diodes(LEDs)light-ing in a closed plant factory(PF),which significantly accelerates rice growth and generation advance-ment.The results show that indica rice can be harvested as early as after 63 days of cultivation,a 50%reduction compared with field cultivation,enabling the annual harvesting of 5-6 generations within the PF.A hyperspectral imaging(HSI)system and attenuated total reflectance infrared(ATR-IR)spec-troscopy were further employed to characterize the chemical composition of the PF-and field-cultivated rice.Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)and gas chromatography-mass spectrometry(GC-MS)revealed that,com-pared with the field-cultivated rice,the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites,such as isovitexin,succinic acid,and methylillicinone F.Overall,this study reveals the unique metabolic profile of PF-cultivated rice and high-lights the potential of PFs to accelerate the breeding of crops such as rice,offering an innovative agricul-tural strategy to support food security in the face of global population growth and climate change.
基金received funding from the Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1633)2023 University Student Innovation and Entrepreneurship Training Program(202311463009Z)+1 种基金Changzhou Science and Technology Support Project(CE20235045)Open Project of Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology(2021JSSPD12).
文摘Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.
基金funding from King Saud University through Researchers Supporting Project number(RSP2024R387),King Saud University,Riyadh,Saudi Arabia.
文摘The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.
文摘To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a benchmark scramjet performance evaluation model.Based on the test data of typical flying point of Mach 7 with the altitude of 29 km,the reliability of the model was verified.The deviations of parameters such as the to⁃tal pressure loss of combustor between the model and the test data were analyzed.Furtherly,an analytical method for post-combustion magnetohydrodynamic power generation was established;by embedding the above method into the overall performance evaluation model,performance prediction considering the power generation effect was realized.Finally,based on the above model,variety regulations of the inlet and the outlet parameters of the power generation channel and performance parameters including the engine specific impulse and the unit thrust under different enthalpy extraction ratios and load factors were analyzed.It could be concluded that the model can reliably predict the variations of key parameters.As the value of the load factor increases,the value of the conduc⁃tivity required to reach the specified enthalpy extraction ratio first decreases and then increases,which is approxi⁃mately parabolic.In order to reduce the demand for the gas conductivity for MHD power generation,the load fac⁃tor should be around 0.5.When the load factor is 0.4 and the magnetic induction intensity is 2.5 T,if the enthalpy extraction ratio reaches 0.5%,the engine specific impulse performance reduces about 3.58%.
基金supported by the National Nat-ural Science Foundation of China(Nos.12192251,12174185,92163216,and 62288101).
文摘The generation of optical vortices from nonlinear photonic crystals(NPCs)with spatially modulated second-order nonlinearity offers a promising approach to extend the working wavelength and topological charge of vortex beams for various applications.In this work,the second harmonic(SH)optical vortex beams generated from nonlinear fork gratings under Gaussian beam illumination are numerically investigated.The far-field intensity and phase distributions,as well as the orbital angular momentum(OAM)spectra of the SH beams,are analyzed for different structural topological charges and diffraction orders.Results reveal that higher-order diffraction and larger structural topological charges lead to angular interference patterns and non-uniform intensity distributions,deviating from the standard vortex profile.To optimize the SH vortex quality,the effects of the fundamental wave beam waist,crystal thickness,and grating duty cycle are explored.It is shown that increasing the beam waist can effectively suppress diffraction order interference and improve the beam’s quality.This study provides theoretical guidance for enhancing the performance of nonlinear optical devices based on NPCs.
基金supported by the National Key R&D Program of China(Grant No.2023YFA1406200)the National Natural Science Foundation of China(Grant Nos.42272041 and 52302043)+2 种基金the National Natural Science Foundation of China(Grant No.U23A20561)the Jilin University High-level Innovation Team Foundation(Grant No.2021TD–05)the Shanghai Synchrotron Radiation Facility(Grant Nos.2024-SSRF-PT-510031 and 505511).
文摘The ability to generate high pressures in a large-volume press(LVP)is crucial for the study of matter under extreme conditions.Here,we have achieved ultrahigh pressures of and 50 GPa,respectively,at room temperature and a high temperature of 1900 K∼60within a millimeter-sized sample volume in a Kawai-type LVP(KLVP)using hard tungsten carbide(WC)and newly designed assem-blies.The introduction of electroconductive polycrystalline boron-doped diamond and dense alumina wrapped with Cu foils into a large conventional cell assembly enables the detection of resistance variations in the Fe_(2)O_(3) pressure standard upon compression.The efficiency of pressure generation in the newly developed cell assembly equipped with conventional ZK10F WC anvils is significantly higher than that of conventional assemblies with some ultrahard or tapered WC anvils.Our study has enabled the routine gener-ation of pressures exceeding 50 GPa within a millimeter-sized sample chamber that have been inaccessible with traditional KLVPs.This advance in high-pressure technology not only breaks a record for pressure generation in traditional KLVPs,but also opens up new avenues for exploration of the properties of the Earth’s deep interior and for the synthesis of novel materials at extreme high pressures.
基金supported by the National Natural Science Foundation of China(Grant No.62202210).
文摘The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation,focusing on their demonstrated potential to enhance production efficiency through automation and personalization.Despite these benefits,it is crucial to acknowledge the substantial initial computational investments required for training and deploying these models.We conduct an in-depth survey of cutting-edge generative AI technologies,encompassing models such as Stable Diffusion and GPT,and appraise pivotal large-scale datasets alongside quantifiable evaluation metrics.Review of the surveyed literature indicates the achievement of considerable maturity in the capacity of AI models to synthesize high-quality,aesthetically compelling anime visual images from textual prompts,alongside discernible progress in the generation of coherent narratives.However,achieving perfect long-form consistency,mitigating artifacts like flickering in video sequences,and enabling fine-grained artistic control remain critical ongoing challenges.Building upon these advancements,research efforts have increasingly pivoted towards the synthesis of higher-dimensional content,such as video and three-dimensional assets,with recent studies demonstrating significant progress in this burgeoning field.Nevertheless,formidable challenges endure amidst these advancements.Foremost among these are the substantial computational exigencies requisite for training and deploying these sophisticated models,particularly pronounced in the realm of high-dimensional generation such as video synthesis.Additional persistent hurdles include maintaining spatial-temporal consistency across complex scenes and mitigating ethical considerations surrounding bias and the preservation of human creative autonomy.This research underscores the transformative potential and inherent complexities of AI-driven synergy within the creative industries.We posit that future research should be dedicated to the synergistic fusion of diffusion and autoregressive models,the integration of multimodal inputs,and the balanced consideration of ethical implications,particularly regarding bias and the preservation of human creative autonomy,thereby establishing a robust foundation for the advancement of anime creation and the broader landscape of AI-driven content generation.
