Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteris...Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteristics play a significant role in improving the direction-of-arrival(DOA)estimation accuracy.However,most of the existing NULA geometries are primarily applicable to circular sources(CSs),while they limitedly improve the DOF and continuous virtual aperture for noncircular sources(NCSs).Toward this purpose,we present a triaddisplaced ULAs(Tdis-ULAs)configuration for NCS.The TdisULAs structure generally consists of three ULAs,which are appropriately placed.The proposed antenna array approach fully exploits the non-circular characteristics of the sources.Given the same number of elements,the Tdis-ULAs design achieves more DOF and larger hole-free co-array aperture than its sparse array competitors.Advantageously,the number of uniform DOF,optimal distribution of elements among the ULAs,and precise element positions are uniquely determined by the closed-form expressions.Moreover,the proposed array also produces a filled resulting co-array.Numerical simulations are conducted to show the performance advantages of the proposed Tdis-ULAs configuration over its counterpart designs.展开更多
Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have b...Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have been adopted as an alternative,nevertheless a major challenge is a lack of sufficient actual training images.Here we report the generation of synthetic two-dimensional materials images using StyleGAN3 to complement the dataset.DeepLabv3Plus network is trained with the synthetic images which reduces overfitting and improves recognition accuracy to over 90%.A semi-supervisory technique for labeling images is introduced to reduce manual efforts.The sharper edges recognized by this method facilitate material stacking with precise edge alignment,which benefits exploring novel properties of layered-material devices that crucially depend on the interlayer twist-angle.This feasible and efficient method allows for the rapid and high-quality manufacturing of atomically thin materials and devices.展开更多
In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tens...In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.展开更多
AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally ...AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets,and used to train,verify and test the diagnostic model of RVO.All the images were divided into four categories[normal,central retinal vein occlusion(CRVO),branch retinal vein occlusion(BRVO),and macular retinal vein occlusion(MRVO)]by three fundus disease experts.Swin Transformer was used to build the RVO diagnosis model,and different types of RVO diagnosis experiments were conducted.The model’s performance was compared to that of the experts.RESULTS:The accuracy of the model in the diagnosis of normal,CRVO,BRVO,and MRVO reached 1.000,0.978,0.957,and 0.978;the specificity reached 1.000,0.986,0.982,and 0.976;the sensitivity reached 1.000,0.955,0.917,and 1.000;the F1-Sore reached 1.000,0.9550.943,and 0.887 respectively.In addition,the area under curve of normal,CRVO,BRVO,and MRVO diagnosed by the diagnostic model were 1.000,0.900,0.959 and 0.970,respectively.The diagnostic results were highly consistent with those of fundus disease experts,and the diagnostic performance was superior.CONCLUSION:The diagnostic model developed in this study can well diagnose different types of RVO,effectively relieve the work pressure of clinicians,and provide help for the follow-up clinical diagnosis and treatment of RVO patients.展开更多
Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted drugs.To address this,this study desc...Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted drugs.To address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of cells.The GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 model.Immunofluorescence analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the model.Compared with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and genes.Moreover,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three models.In addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude mice.Immunohistochemical evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was higher.This research therefore acts as a foundation for the application of 3DP-7721 models in drug development research.展开更多
A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy...A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.展开更多
In this paper,we propose a novel deep learning(DL)-based receiver design for orthogonal frequency division multiplexing(OFDM)systems.The entire process of channel estimation,equalization,and signal detection is replac...In this paper,we propose a novel deep learning(DL)-based receiver design for orthogonal frequency division multiplexing(OFDM)systems.The entire process of channel estimation,equalization,and signal detection is replaced by a neural network(NN),and hence,the detector is called a NN detector(N^(2)D).First,an OFDM signal model is established.We analyze both temporal and spectral characteristics of OFDM signals,which are the motivation for DL.Then,the generated data based on the simulation of channel statistics is used for offline training of bi-directional long short-term memory(Bi-LSTM)NN.Especially,a discriminator(F)is added to the input of Bi-LSTM NN to look for subcarrier transmission data with optimal channel gain(OCG),which can greatly improve the performance of the detector.Finally,the trained N^(2)D is used for online recovery of OFDM symbols.The performance of the proposed N^(2)D is analyzed theoretically in terms of bit error rate(BER)by Monte Carlo simulation under different parameter scenarios.The simulation results demonstrate that the BER of N^(2)D is obviously lower than other algorithms,especially at high signal-to-noise ratios(SNRs).Meanwhile,the proposed N^(2)D is robust to the fluctuation of parameter values.展开更多
Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection.This study aimed to develop a deep learning model that can automatically classify colorect...Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection.This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologically on white-light and narrow-band imaging(NBI)colonoscopy images based on World Health Organization(WHO)and Workgroup serrAted polypS and Polyposis(WASP)classification criteria for colorectal polyps.White-light and NBI colonoscopy images of colorectal polyps exhibiting pathological results were firstly collected and classified into four categories:conventional adenoma,hyperplastic polyp,sessile serrated adenoma/polyp(SSAP)and normal,among which conventional adenoma could be further divided into three sub-categories of tubular adenoma,villous adenoma and villioustublar adenoma,subsequently the images were re-classified into six categories.In this paper,we proposed a novel convolutional neural network termed Polyp-DedNet for the four-and six-category classification tasks of colorectal polyps.Based on the existing classification network ResNet50,Polyp-DedNet adopted dilated convolution to retain more high-dimensional spatial information and an Efficient Channel Attention(ECA)module to improve the classification performance further.To eliminate gridding artifacts caused by dilated convolutions,traditional convolutional layers were used instead of the max pooling layer,and two convolutional layers with progressively decreasing dilation were added at the end of the network.Due to the inevitable imbalance of medical image data,a regularization method DropBlock and a Class-Balanced(CB)Loss were performed to prevent network overfitting.Furthermore,the 5-fold cross-validation was adopted to estimate the performance of Polyp-DedNet for the multi-classification task of colorectal polyps.Mean accuracies of the proposed Polyp-DedNet for the four-and six-category classifications of colorectal polyps were 89.91%±0.92%and 85.13%±1.10%,respectively.The metrics of precision,recall and F1-score were also improved by 1%∼2%compared to the baseline ResNet50.The proposed Polyp-DedNet presented state-of-the-art performance for colorectal polyp classifying on white-light and NBI colonoscopy images,highlighting its considerable potential as an AI-assistant system for accurate colorectal polyp diagnosis in colonoscopy.展开更多
Exploiting the source-to-relay channel phase information at the relays can increase the rate upper-bound of distributed orthogonal space-time block codes(STBC)from 2/K to 1/2,where Kis the number of relays.This techni...Exploiting the source-to-relay channel phase information at the relays can increase the rate upper-bound of distributed orthogonal space-time block codes(STBC)from 2/K to 1/2,where Kis the number of relays.This technique is known as distributed orthogonal space-time block codes with channel phase information(DOSTBC-CPI).However,the decoding delay of existing DOSTBC-CPIs is not optimal.Therefore,based on the rate of 1/2 balanced complex orthogonal design(COD),an algorithm is provided to construct a maximal rate DOSTBC-CPI with only half the decoding delay of existing DOSTBC-CPI.Simulation results show that the proposed method exhibits lower symbol error rate than the existing DOSTBC-CPIs.展开更多
This paper introduces the design and implementation of agricultural products information collection system based on Qt and ZigBee platform. It consists of three subsystems mainly based in acquisition of images, temper...This paper introduces the design and implementation of agricultural products information collection system based on Qt and ZigBee platform. It consists of three subsystems mainly based in acquisition of images, temperature and humidity values which are passed to the regional gateway. The regional gateway is equipped with embedded Linux operating system and deployed Qt runtime library. The function of transmitting the static image of agricultural products and the temperature and humidity to the regional gateway through the ZigBee Wireless Sensor Network is realized, the pH value, electrical conductivity and light intensity of the growth environment of agricultural products were measured by using Qt library combined with sensor cluster, it can store, display and query the image, electrical conductivity and other parameters in the regional gateway.展开更多
Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allo...Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allow metal halide perovskite to be employed in a wide variety of applications. This article provides a holistic review over the current progress and future prospects of metal halide perovskite materials in representative promising applications, including traditional optoelectronic devices(solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices(artificial synapses and memristors) and pressure-induced emission. This review highlights the fundamentals, the current progress and the remaining challenges for each application, aiming to provide a comprehensive overview of the development status and a navigation of future research for metal halide perovskite materials and devices.展开更多
Using the first-principles calculations, we study the structural, electronic, and magnetic properties of vanadium adsorbed MoSe_2 monolayer, and the magnetic couplings between the V adatoms at different adsorption con...Using the first-principles calculations, we study the structural, electronic, and magnetic properties of vanadium adsorbed MoSe_2 monolayer, and the magnetic couplings between the V adatoms at different adsorption concentrations. The calculations show that the V atom is chemically adsorbed on the MoSe_2 monolayer and prefers the location on the top of an Mo atom surrounded by three nearest-neighbor Se atoms. The interatomic electron transfer from the V to the nearestneighbor Se results in the polarized covalent bond with weak covalency, associated with the hybridizations of V with Se and Mo. The V adatom induces local impurity states in the middle of the band gap of pristine MoSe_2, and the peak of density of states right below the Fermi energy is associated with the V- dz^2 orbital. A single V adatom induces a magnetic moment of 5 μBthat mainly distributes on the V-3d and Mo-4d orbitals. The V adatom is in high-spin state, and its local magnetic moment is associated with the mid-gap impurity states that are mainly from the V-3d orbitals. In addition,the crystal field squashes a part of the V-4s electrons into the V-3d orbitals, which enhances the local magnetic moment.The magnetic ground states at different adsorption concentrations are calculated by generalized gradient approximations(GGA) and GGA+U with enhanced electron localization. In addition, the exchange integrals between the nearest-neighbor V adatoms at different adsorption concentrations are calculated by fitting the first-principle total energies of ferromagnetic(FM) and antiferromagnetic(AFM) states to the Heisenberg model. The calculations with GGA show that there is a transition from ferromagnetic to antiferromagnetic ground state with increasing the distance between the V adatoms. We propose an exchange mechanism based on the on-site exchange on Mo and the hybridization between Mo and V, to explain the strong ferromagnetic coupling at a short distance between the V adatoms. However, the ferromagnetic exchange mechanism is sensitive to both the increased inter-adatom distance at low concentration and the enhanced electron localization by GGA+U, which leads to antiferromagnetic ground state, where the antiferromagnetic superexchange is dominant.展开更多
The direct target of engineering education is to cultivate engineers and industry leaders with the qualifi ed skills and strong competencies. To cultivate skilled technological talents in a local engineering college, ...The direct target of engineering education is to cultivate engineers and industry leaders with the qualifi ed skills and strong competencies. To cultivate skilled technological talents in a local engineering college, the fi rst subject is to establish the discipline according to the major strategy of the local economic development requirements, so that the professional regional service function is relatively strong. Secondly, the individual work orientation and development direction are considered as well in the cultivated process. These aspects are required such as renewing education idea, strengthening the education of humanity quality, perfecting the system of continuing education, establishing the mechanism of lifelong learning.展开更多
Network information communication technology in power systems is the key to ensuring the safe and efficient operation of power grids.The network information communication technology itself has advantages in automation...Network information communication technology in power systems is the key to ensuring the safe and efficient operation of power grids.The network information communication technology itself has advantages in automation operation and information transmission,thus is widely applied to the power system.In the case of ensuring that the power system is compatible with the network information communication technology,the control of the power system can be strengthened,and the operational efficiency of the power system can be improved.This paper mainly analyzes the specific application of network information communication technology in power system.展开更多
Chirality,as the symmetric breaking of molecules,plays an essential role in physical,chemical and especially biological processes,which highlights the accurate distinction among heterochiralities as well as the precis...Chirality,as the symmetric breaking of molecules,plays an essential role in physical,chemical and especially biological processes,which highlights the accurate distinction among heterochiralities as well as the precise preparation for homochirality.To this end,the well-designed structure-specific recognizer and catalysis reactor are necessitated,respectively.However,each kind of target molecules requires a custom-made chiral partner and the dynamic disorder of spatial-orientation distribution of molecules at the ensemble level leads to an inefficient protocol.In this perspective article,we developed a universal strategy capable of realizing the chirality detection and control by the external symmetry breaking based on the alignment of the molecular frame to external stimuli.Specifically,in combination with the discussion about the relationship among the chirality(molecule),spin(electron)and polarization(photon),i.e.,the three natural symmetry breaking,single-molecule junctions were proposed to achieve a single-molecule/event-resolved detection and synthesis.The fixation of the molecular orientation and the CMOS-compatibility provide an efficient interface to achieve the external input of symmetry breaking.This perspective is believed to offer more efficient applications in accurate chirality detection and precise asymmetric synthesis via the close collaboration of chemists,physicists,materials scientists,and engineers.展开更多
Colored dissolved organic matter(CDOM)is an important optically active substance in marine environment.Its biochemical conservatism makes it an important indicator to offshore pollution process.Monitoring the content,...Colored dissolved organic matter(CDOM)is an important optically active substance in marine environment.Its biochemical conservatism makes it an important indicator to offshore pollution process.Monitoring the content,composition,and diffusion process of CDOM is a good approach to analyze the terrestrial input,optical properties,and ecological environment of offshore areas.The spatiotemporal characteristics of CDOM around the Leizhou Peninsula were analyzed based on field observation data collected in the autumn 2020 and spring 2021,and an empirical inversion model of the ag(355)(absorption coefficient at 355 nm)and spectral slope(Sg)(g stands for gelbstoff/gilvin,which is called CDOM)based on Sentinel-3A ocean and land color instrument(OLCI)images was constructed.The results show(1)the order of average ag(355)value around the Leizhou Peninsula was east coast(0.503/m)>Qiongzhou Strait(0.502/m)>west coast(0.365/m);(2)the best band combinations of CDOM inversion in spring and autumn were(B4+B11)/B3 and(B7-B1)/B6(B stands for the band of spectral images),and the final inversion results are close to the measured results,indicating that the model has good accuracy;(3)the S_(g)value of the CDOM absorption spectrum was fitted to the hyperbolicexponential model.The fitting accuracy of the model was higher than those of the exponential model and the hyperbolic model,and the best S_(g)inversion model was constructed by selecting Sg(275-295)and Sg(250-295)in spring and autumn;(4)the spatial distributions of ag(355)and S_(g)were inverted,and CDOM in the waters around the Leizhou Peninsula originated from terrestrial organic matter carried by coastal aquaculture zones and runoff in the northeast Zhanjiang and the northern Beibu Gulf.展开更多
With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central...With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central nervous system,shrinkage of brain tissue,and decline in physical function in many elderlies,making them susceptible to neurological diseases such as Alzheimer’s disease(AD),stroke,Parkinson’s and major depressive disorder(MDD).Due to the influence of these neurological diseases,the elderly have troubles such as memory loss,inability to move,falling,and getting lost,which seriously affect their quality of life.Tracking and positioning of elderly with neurological diseases and keeping track of their location in real-time are necessary and crucial in order to detect and treat dangerous and unexpected situations in time.Considering that the elderly with neurological diseases forget to wear a positioning device or have mobility problems due to carrying a positioning device,device-free positioning as a passive positioning technology that detects device-free individuals is more suitable than traditional active positioning for the home-based care of the elderly with neurological diseases.This paper provides an extensive and in-depth survey of device-free indoor positioning technology for home-based care and an in-depth analysis of the main features of current positioning systems,as well as the techniques,technologies andmethods they employ,fromthe perspective of the needs of the elderly with neurological conditions.Moreover,evaluation criteria and possible solutions of positioning techniques for the home-based care of the elderly with neurological conditions are proposed.Finally,the opportunities and challenges for the development of indoor positioning technology in 6G mobile networks for home-based care of the elderly with neurological diseases are discussed.This review has provided comprehensive and effective tracking and positioning techniques,technologies and methods for the elderly,by which we can obtain the location information of the elderly in real-time and make home-based care more comfortable and safer for the elderly with neurological diseases.展开更多
To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affect...To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.展开更多
In this study,we present characteristics of post-sunset GHz scintillation occurrence and their correlations with ionospheric parameters derived from ionosonde observations in high solar activity years(2012−2013)of sol...In this study,we present characteristics of post-sunset GHz scintillation occurrence and their correlations with ionospheric parameters derived from ionosonde observations in high solar activity years(2012−2013)of solar cycle 24 at Sanya(18.3°N,109.6°E;dip lat.:12.8°N),China.The analyzed data include the F_(2)-layer’s critical frequency(foF_(2)),peak height(h_(m)F_(2)),and minimum virtual height(h’F),as well as the scale height around the F_(2)-layer peak(H_(m)),and virtual height(h’F_(5))and true height(hF_(5))measured at 5 MHz.We have investigated relationships between the equinoctial asymmetry of these scintillations and these ionospheric parameters.In addition,we calculate the growth rates of Rayleigh−Taylor instability on the basis of the ionosonde measurements and theoretical models,respectively.We find that the equinoctial asymmetry of scintillation onset time is associated with the scale length of the vertical electron density gradient(L),which has been shown to affect the growth of Rayleigh−Taylor instability at the bottom of the F-layer.The seasonal variations of foF_(2),H_(m)and scale length of vertical electron density gradient appear to cause the seasonal variations of scintillation occurrence;the equinoctial asymmetry of scintillation occurrence rate over low latitudes appears to be related to background electron density and vertical drifts in the F-layer around time of sunset.Further study is required to explain the observed correlational weakness in low latitudes between scintillation strength,represented by the daily maximum S4,and daily maximum values of foF_(2),h_(m)F_(2),h’F,H_(m),and also the drifts.展开更多
Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice...Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice.As a result,this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller.Specifically,the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller.In this method,a risk threshold model is proposed to classify the risk level of the scenes based on the scene features,and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios.The proposed algorithm is compared to a pure model predictive controller in car-following case.According to the results,the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations,showing a good scenario adaptability with safety guaranteed.展开更多
基金supported by the National Natural Science Foundation of China(62031017,61971221)the Fundamental Research Funds for the Central Universities of China(NP2020104)。
文摘Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteristics play a significant role in improving the direction-of-arrival(DOA)estimation accuracy.However,most of the existing NULA geometries are primarily applicable to circular sources(CSs),while they limitedly improve the DOF and continuous virtual aperture for noncircular sources(NCSs).Toward this purpose,we present a triaddisplaced ULAs(Tdis-ULAs)configuration for NCS.The TdisULAs structure generally consists of three ULAs,which are appropriately placed.The proposed antenna array approach fully exploits the non-circular characteristics of the sources.Given the same number of elements,the Tdis-ULAs design achieves more DOF and larger hole-free co-array aperture than its sparse array competitors.Advantageously,the number of uniform DOF,optimal distribution of elements among the ULAs,and precise element positions are uniquely determined by the closed-form expressions.Moreover,the proposed array also produces a filled resulting co-array.Numerical simulations are conducted to show the performance advantages of the proposed Tdis-ULAs configuration over its counterpart designs.
基金Project supported by the National Key Research and Development Program of China(Grant No.2022YFB2803900)the National Natural Science Foundation of China(Grant Nos.61974075 and 61704121)+2 种基金the Natural Science Foundation of Tianjin Municipality(Grant Nos.22JCZDJC00460 and 19JCQNJC00700)Tianjin Municipal Education Commission(Grant No.2019KJ028)Fundamental Research Funds for the Central Universities(Grant No.22JCZDJC00460).
文摘Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have been adopted as an alternative,nevertheless a major challenge is a lack of sufficient actual training images.Here we report the generation of synthetic two-dimensional materials images using StyleGAN3 to complement the dataset.DeepLabv3Plus network is trained with the synthetic images which reduces overfitting and improves recognition accuracy to over 90%.A semi-supervisory technique for labeling images is introduced to reduce manual efforts.The sharper edges recognized by this method facilitate material stacking with precise edge alignment,which benefits exploring novel properties of layered-material devices that crucially depend on the interlayer twist-angle.This feasible and efficient method allows for the rapid and high-quality manufacturing of atomically thin materials and devices.
基金funded by the National Natural Science Foundation of China(Grant Number 52075361)Shanxi Province Science and Technology Major Project(Grant Number 20201102003)+3 种基金Lvliang Science and Technology Guidance Special Key R&D Project(Grant Number 2022XDHZ08)National Natural Science Foundation of China(Grant Number 51905367)Shanxi Natural Science Foundation General Project(Grant Numbers 202103021224271,202203021211201)Shanxi Province Key Research and Development Plan(Grant Number 202102020101013).
文摘In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.
基金Supported by Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties(No.SZGSP014)Sanming Project of Medicine in Shenzhen(No.SZSM202011015)Shenzhen Science and Technology Planning Project(No.KCXFZ20211020163813019).
文摘AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets,and used to train,verify and test the diagnostic model of RVO.All the images were divided into four categories[normal,central retinal vein occlusion(CRVO),branch retinal vein occlusion(BRVO),and macular retinal vein occlusion(MRVO)]by three fundus disease experts.Swin Transformer was used to build the RVO diagnosis model,and different types of RVO diagnosis experiments were conducted.The model’s performance was compared to that of the experts.RESULTS:The accuracy of the model in the diagnosis of normal,CRVO,BRVO,and MRVO reached 1.000,0.978,0.957,and 0.978;the specificity reached 1.000,0.986,0.982,and 0.976;the sensitivity reached 1.000,0.955,0.917,and 1.000;the F1-Sore reached 1.000,0.9550.943,and 0.887 respectively.In addition,the area under curve of normal,CRVO,BRVO,and MRVO diagnosed by the diagnostic model were 1.000,0.900,0.959 and 0.970,respectively.The diagnostic results were highly consistent with those of fundus disease experts,and the diagnostic performance was superior.CONCLUSION:The diagnostic model developed in this study can well diagnose different types of RVO,effectively relieve the work pressure of clinicians,and provide help for the follow-up clinical diagnosis and treatment of RVO patients.
基金supported by the National Natural Science Foundation of China(Nos.51975400 and 62031022)Shanxi Provincial Key Medical Scientific Research Project(Nos.2020XM06 and 2021XM12)+3 种基金Fundamental Research Program of Shanxi Province(No.202103021224081)Shanxi Provincial Basic Research Project(Nos.202103021221006 and 202103021223040)Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(No.2021L044)Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering(No.2022SX-TD026).
文摘Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted drugs.To address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of cells.The GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 model.Immunofluorescence analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the model.Compared with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and genes.Moreover,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three models.In addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude mice.Immunohistochemical evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was higher.This research therefore acts as a foundation for the application of 3DP-7721 models in drug development research.
文摘A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.
基金supported in part by the National Natural Science Foundation of China No.62001220the Natural Science Foundation of Jiangsu Province BK20200440the Fundamental Research Funds for the Central Universities No.1004-YAH20016,No.NT2020009。
文摘In this paper,we propose a novel deep learning(DL)-based receiver design for orthogonal frequency division multiplexing(OFDM)systems.The entire process of channel estimation,equalization,and signal detection is replaced by a neural network(NN),and hence,the detector is called a NN detector(N^(2)D).First,an OFDM signal model is established.We analyze both temporal and spectral characteristics of OFDM signals,which are the motivation for DL.Then,the generated data based on the simulation of channel statistics is used for offline training of bi-directional long short-term memory(Bi-LSTM)NN.Especially,a discriminator(F)is added to the input of Bi-LSTM NN to look for subcarrier transmission data with optimal channel gain(OCG),which can greatly improve the performance of the detector.Finally,the trained N^(2)D is used for online recovery of OFDM symbols.The performance of the proposed N^(2)D is analyzed theoretically in terms of bit error rate(BER)by Monte Carlo simulation under different parameter scenarios.The simulation results demonstrate that the BER of N^(2)D is obviously lower than other algorithms,especially at high signal-to-noise ratios(SNRs).Meanwhile,the proposed N^(2)D is robust to the fluctuation of parameter values.
基金funded by the Research Fund for Foundation of Hebei University(DXK201914)the President of Hebei University(XZJJ201914)+3 种基金the Post-graduate’s Innovation Fund Project of Hebei University(HBU2022SS003)the Special Project for Cultivating College Students’Scientific and Technological Innovation Ability in Hebei Province(22E50041D)Guangdong Basic and Applied Basic Research Foundation(2021A1515011654)the Fundamental Research Funds for the Central Universities of China(20720210117).
文摘Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection.This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologically on white-light and narrow-band imaging(NBI)colonoscopy images based on World Health Organization(WHO)and Workgroup serrAted polypS and Polyposis(WASP)classification criteria for colorectal polyps.White-light and NBI colonoscopy images of colorectal polyps exhibiting pathological results were firstly collected and classified into four categories:conventional adenoma,hyperplastic polyp,sessile serrated adenoma/polyp(SSAP)and normal,among which conventional adenoma could be further divided into three sub-categories of tubular adenoma,villous adenoma and villioustublar adenoma,subsequently the images were re-classified into six categories.In this paper,we proposed a novel convolutional neural network termed Polyp-DedNet for the four-and six-category classification tasks of colorectal polyps.Based on the existing classification network ResNet50,Polyp-DedNet adopted dilated convolution to retain more high-dimensional spatial information and an Efficient Channel Attention(ECA)module to improve the classification performance further.To eliminate gridding artifacts caused by dilated convolutions,traditional convolutional layers were used instead of the max pooling layer,and two convolutional layers with progressively decreasing dilation were added at the end of the network.Due to the inevitable imbalance of medical image data,a regularization method DropBlock and a Class-Balanced(CB)Loss were performed to prevent network overfitting.Furthermore,the 5-fold cross-validation was adopted to estimate the performance of Polyp-DedNet for the multi-classification task of colorectal polyps.Mean accuracies of the proposed Polyp-DedNet for the four-and six-category classifications of colorectal polyps were 89.91%±0.92%and 85.13%±1.10%,respectively.The metrics of precision,recall and F1-score were also improved by 1%∼2%compared to the baseline ResNet50.The proposed Polyp-DedNet presented state-of-the-art performance for colorectal polyp classifying on white-light and NBI colonoscopy images,highlighting its considerable potential as an AI-assistant system for accurate colorectal polyp diagnosis in colonoscopy.
基金supported in part by the National Natural Science Foundation of China(Nos.61271230,61472190)the National Mobile Communications Research Laboratory,Southeast University(No.2013D02)
文摘Exploiting the source-to-relay channel phase information at the relays can increase the rate upper-bound of distributed orthogonal space-time block codes(STBC)from 2/K to 1/2,where Kis the number of relays.This technique is known as distributed orthogonal space-time block codes with channel phase information(DOSTBC-CPI).However,the decoding delay of existing DOSTBC-CPIs is not optimal.Therefore,based on the rate of 1/2 balanced complex orthogonal design(COD),an algorithm is provided to construct a maximal rate DOSTBC-CPI with only half the decoding delay of existing DOSTBC-CPI.Simulation results show that the proposed method exhibits lower symbol error rate than the existing DOSTBC-CPIs.
文摘This paper introduces the design and implementation of agricultural products information collection system based on Qt and ZigBee platform. It consists of three subsystems mainly based in acquisition of images, temperature and humidity values which are passed to the regional gateway. The regional gateway is equipped with embedded Linux operating system and deployed Qt runtime library. The function of transmitting the static image of agricultural products and the temperature and humidity to the regional gateway through the ZigBee Wireless Sensor Network is realized, the pH value, electrical conductivity and light intensity of the growth environment of agricultural products were measured by using Qt library combined with sensor cluster, it can store, display and query the image, electrical conductivity and other parameters in the regional gateway.
基金the National Key Research and Development Program of China (2022YFB3803300)the open research fund of Songshan Lake Materials Laboratory (2021SLABFK02)the National Natural Science Foundation of China (21961160720)。
文摘Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allow metal halide perovskite to be employed in a wide variety of applications. This article provides a holistic review over the current progress and future prospects of metal halide perovskite materials in representative promising applications, including traditional optoelectronic devices(solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices(artificial synapses and memristors) and pressure-induced emission. This review highlights the fundamentals, the current progress and the remaining challenges for each application, aiming to provide a comprehensive overview of the development status and a navigation of future research for metal halide perovskite materials and devices.
基金Project supported by the National Basic Research Program of China(Grant No.2011CB606405)the CAEP Microsystem and THz Science and Technology Foundation,China(Grant No.CAEPMT201501)the Science Challenge Project,China(Grant No.JCKY2016212A503)
文摘Using the first-principles calculations, we study the structural, electronic, and magnetic properties of vanadium adsorbed MoSe_2 monolayer, and the magnetic couplings between the V adatoms at different adsorption concentrations. The calculations show that the V atom is chemically adsorbed on the MoSe_2 monolayer and prefers the location on the top of an Mo atom surrounded by three nearest-neighbor Se atoms. The interatomic electron transfer from the V to the nearestneighbor Se results in the polarized covalent bond with weak covalency, associated with the hybridizations of V with Se and Mo. The V adatom induces local impurity states in the middle of the band gap of pristine MoSe_2, and the peak of density of states right below the Fermi energy is associated with the V- dz^2 orbital. A single V adatom induces a magnetic moment of 5 μBthat mainly distributes on the V-3d and Mo-4d orbitals. The V adatom is in high-spin state, and its local magnetic moment is associated with the mid-gap impurity states that are mainly from the V-3d orbitals. In addition,the crystal field squashes a part of the V-4s electrons into the V-3d orbitals, which enhances the local magnetic moment.The magnetic ground states at different adsorption concentrations are calculated by generalized gradient approximations(GGA) and GGA+U with enhanced electron localization. In addition, the exchange integrals between the nearest-neighbor V adatoms at different adsorption concentrations are calculated by fitting the first-principle total energies of ferromagnetic(FM) and antiferromagnetic(AFM) states to the Heisenberg model. The calculations with GGA show that there is a transition from ferromagnetic to antiferromagnetic ground state with increasing the distance between the V adatoms. We propose an exchange mechanism based on the on-site exchange on Mo and the hybridization between Mo and V, to explain the strong ferromagnetic coupling at a short distance between the V adatoms. However, the ferromagnetic exchange mechanism is sensitive to both the increased inter-adatom distance at low concentration and the enhanced electron localization by GGA+U, which leads to antiferromagnetic ground state, where the antiferromagnetic superexchange is dominant.
文摘The direct target of engineering education is to cultivate engineers and industry leaders with the qualifi ed skills and strong competencies. To cultivate skilled technological talents in a local engineering college, the fi rst subject is to establish the discipline according to the major strategy of the local economic development requirements, so that the professional regional service function is relatively strong. Secondly, the individual work orientation and development direction are considered as well in the cultivated process. These aspects are required such as renewing education idea, strengthening the education of humanity quality, perfecting the system of continuing education, establishing the mechanism of lifelong learning.
文摘Network information communication technology in power systems is the key to ensuring the safe and efficient operation of power grids.The network information communication technology itself has advantages in automation operation and information transmission,thus is widely applied to the power system.In the case of ensuring that the power system is compatible with the network information communication technology,the control of the power system can be strengthened,and the operational efficiency of the power system can be improved.This paper mainly analyzes the specific application of network information communication technology in power system.
基金supports from the National Key R&D Program of China(2021YFA1200101 and 2022YFE0128700)the National Natural Science Foundation of China(22150013 and 21933001)+2 种基金the New Cornerstone Science Foundation through the XPLORER PRIZEthe Natural Science Foundation of Beijing(2222009)“Frontiers Science Centre for New Organic Matter”at Nankai University(63181206).
文摘Chirality,as the symmetric breaking of molecules,plays an essential role in physical,chemical and especially biological processes,which highlights the accurate distinction among heterochiralities as well as the precise preparation for homochirality.To this end,the well-designed structure-specific recognizer and catalysis reactor are necessitated,respectively.However,each kind of target molecules requires a custom-made chiral partner and the dynamic disorder of spatial-orientation distribution of molecules at the ensemble level leads to an inefficient protocol.In this perspective article,we developed a universal strategy capable of realizing the chirality detection and control by the external symmetry breaking based on the alignment of the molecular frame to external stimuli.Specifically,in combination with the discussion about the relationship among the chirality(molecule),spin(electron)and polarization(photon),i.e.,the three natural symmetry breaking,single-molecule junctions were proposed to achieve a single-molecule/event-resolved detection and synthesis.The fixation of the molecular orientation and the CMOS-compatibility provide an efficient interface to achieve the external input of symmetry breaking.This perspective is believed to offer more efficient applications in accurate chirality detection and precise asymmetric synthesis via the close collaboration of chemists,physicists,materials scientists,and engineers.
基金Supported by the Key Projects of the Guangdong Education Department(No.2019KZDXM019)the Fund of Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)(No.ZJW-2019-08)+3 种基金the High-level Marine Discipline Team Project of Guangdong Ocean University(No.002026002009)the Guangdong Graduate Academic Forum Project(No.230420003)the“First Class”Discipline Construction Platform Project in 2019 of Guangdong Ocean University(No.231419026)the Innovation Projects of Colleges and Universities in Guangdong Province(No.2021KQNCX028)。
文摘Colored dissolved organic matter(CDOM)is an important optically active substance in marine environment.Its biochemical conservatism makes it an important indicator to offshore pollution process.Monitoring the content,composition,and diffusion process of CDOM is a good approach to analyze the terrestrial input,optical properties,and ecological environment of offshore areas.The spatiotemporal characteristics of CDOM around the Leizhou Peninsula were analyzed based on field observation data collected in the autumn 2020 and spring 2021,and an empirical inversion model of the ag(355)(absorption coefficient at 355 nm)and spectral slope(Sg)(g stands for gelbstoff/gilvin,which is called CDOM)based on Sentinel-3A ocean and land color instrument(OLCI)images was constructed.The results show(1)the order of average ag(355)value around the Leizhou Peninsula was east coast(0.503/m)>Qiongzhou Strait(0.502/m)>west coast(0.365/m);(2)the best band combinations of CDOM inversion in spring and autumn were(B4+B11)/B3 and(B7-B1)/B6(B stands for the band of spectral images),and the final inversion results are close to the measured results,indicating that the model has good accuracy;(3)the S_(g)value of the CDOM absorption spectrum was fitted to the hyperbolicexponential model.The fitting accuracy of the model was higher than those of the exponential model and the hyperbolic model,and the best S_(g)inversion model was constructed by selecting Sg(275-295)and Sg(250-295)in spring and autumn;(4)the spatial distributions of ag(355)and S_(g)were inverted,and CDOM in the waters around the Leizhou Peninsula originated from terrestrial organic matter carried by coastal aquaculture zones and runoff in the northeast Zhanjiang and the northern Beibu Gulf.
基金supported by the National Natural Science Foundation of China under Grant No.61701284the Innovative Research Foundation of Qingdao under Grant No.19-6-2-1-CG+5 种基金the Elite Plan Project of Shandong University of Science and Technology under Grant No.skr21-3-B-048the Sci.&Tech.Development Fund of Shandong Province of China under Grant Nos.ZR202102230289,ZR202102250695,and ZR2019LZH001the Humanities and Social Science Research Project of the Ministry of Education under Grant No.18YJAZH017the Taishan Scholar Program of Shandong Province,the Shandong Chongqing Science and Technology Cooperation Project under Grant No.cstc2020jscx-lyjsAX0008the Sci.&Tech.Development Fund of Qingdao under Grant No.21-1-5-zlyj-1-zc,SDUST Research Fund under Grant No.2015TDJH102the Science and Technology Support Plan of Youth Innovation Team of Shandong higher School under Grant No.2019KJN024.
文摘With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central nervous system,shrinkage of brain tissue,and decline in physical function in many elderlies,making them susceptible to neurological diseases such as Alzheimer’s disease(AD),stroke,Parkinson’s and major depressive disorder(MDD).Due to the influence of these neurological diseases,the elderly have troubles such as memory loss,inability to move,falling,and getting lost,which seriously affect their quality of life.Tracking and positioning of elderly with neurological diseases and keeping track of their location in real-time are necessary and crucial in order to detect and treat dangerous and unexpected situations in time.Considering that the elderly with neurological diseases forget to wear a positioning device or have mobility problems due to carrying a positioning device,device-free positioning as a passive positioning technology that detects device-free individuals is more suitable than traditional active positioning for the home-based care of the elderly with neurological diseases.This paper provides an extensive and in-depth survey of device-free indoor positioning technology for home-based care and an in-depth analysis of the main features of current positioning systems,as well as the techniques,technologies andmethods they employ,fromthe perspective of the needs of the elderly with neurological conditions.Moreover,evaluation criteria and possible solutions of positioning techniques for the home-based care of the elderly with neurological conditions are proposed.Finally,the opportunities and challenges for the development of indoor positioning technology in 6G mobile networks for home-based care of the elderly with neurological diseases are discussed.This review has provided comprehensive and effective tracking and positioning techniques,technologies and methods for the elderly,by which we can obtain the location information of the elderly in real-time and make home-based care more comfortable and safer for the elderly with neurological diseases.
基金financially supported by the National Natural Science Foundation of China(NSFC)project(Authorization Number:61771261)。
文摘To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.
基金supported by the Fundamental Research Funds for the Central Universities,South-Central MinZu University(Grant Number:CPT22019).
文摘In this study,we present characteristics of post-sunset GHz scintillation occurrence and their correlations with ionospheric parameters derived from ionosonde observations in high solar activity years(2012−2013)of solar cycle 24 at Sanya(18.3°N,109.6°E;dip lat.:12.8°N),China.The analyzed data include the F_(2)-layer’s critical frequency(foF_(2)),peak height(h_(m)F_(2)),and minimum virtual height(h’F),as well as the scale height around the F_(2)-layer peak(H_(m)),and virtual height(h’F_(5))and true height(hF_(5))measured at 5 MHz.We have investigated relationships between the equinoctial asymmetry of these scintillations and these ionospheric parameters.In addition,we calculate the growth rates of Rayleigh−Taylor instability on the basis of the ionosonde measurements and theoretical models,respectively.We find that the equinoctial asymmetry of scintillation onset time is associated with the scale length of the vertical electron density gradient(L),which has been shown to affect the growth of Rayleigh−Taylor instability at the bottom of the F-layer.The seasonal variations of foF_(2),H_(m)and scale length of vertical electron density gradient appear to cause the seasonal variations of scintillation occurrence;the equinoctial asymmetry of scintillation occurrence rate over low latitudes appears to be related to background electron density and vertical drifts in the F-layer around time of sunset.Further study is required to explain the observed correlational weakness in low latitudes between scintillation strength,represented by the daily maximum S4,and daily maximum values of foF_(2),h_(m)F_(2),h’F,H_(m),and also the drifts.
基金Supported by National Key R&D Program of China(Grant No.2022YFB2502900)Fundamental Research Funds for the Central Universities of China,Science and Technology Commission of Shanghai Municipality of China(Grant No.21ZR1465900)Shanghai Gaofeng&Gaoyuan Project for University Academic Program Development of China.
文摘Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice.As a result,this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller.Specifically,the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller.In this method,a risk threshold model is proposed to classify the risk level of the scenes based on the scene features,and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios.The proposed algorithm is compared to a pure model predictive controller in car-following case.According to the results,the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations,showing a good scenario adaptability with safety guaranteed.