In a telemedicine diagnosis system,the emergence of 3D imaging enables doctors to make clearer judgments,and its accuracy also directly affects doctors’diagnosis of the disease.In order to ensure the safe transmissio...In a telemedicine diagnosis system,the emergence of 3D imaging enables doctors to make clearer judgments,and its accuracy also directly affects doctors’diagnosis of the disease.In order to ensure the safe transmission and storage of medical data,a 3D medical watermarking algorithm based on wavelet transform is proposed in this paper.The proposed algorithm employs the principal component analysis(PCA)transform to reduce the data dimension,which can minimize the error between the extracted components and the original data in the mean square sense.Especially,this algorithm helps to create a bacterial foraging model based on particle swarm optimization(BF-PSO),by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding,thereby achieving the optimal balance between embedding capacity and imperceptibility.A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.展开更多
The leakage of medical audio data in telemedicine seriously violates the privacy of patients.In order to avoid the leakage of patient information in telemedicine,a two-stage reversible robust audio watermarking algori...The leakage of medical audio data in telemedicine seriously violates the privacy of patients.In order to avoid the leakage of patient information in telemedicine,a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data.The scheme decomposes the medical audio into two independent embedding domains,embeds the robust watermark and the reversible watermark into the two domains respectively.In order to ensure the audio quality,the Hurst exponent is used to find a suitable position for watermark embedding.Due to the independence of the two embedding domains,the embedding of the second-stage reversible watermark will not affect the first-stage watermark,so the robustness of the first-stage watermark can be well maintained.In the second stage,the correlation between the sampling points in the medical audio is used to modify the hidden bits of the histogram to reduce the modification of the medical audio and reduce the distortion caused by reversible embedding.Simulation experiments show that this scheme has strong robustness against signal processing operations such as MP3 compression of 48 db,additive white Gaussian noise(AWGN)of 20 db,low-pass filtering,resampling,re-quantization and other attacks,and has good imperceptibility.展开更多
With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and ...With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.展开更多
The 21st century is the age of information when information becomes an important strategic resource. The information obtaining, processing and security guarantee capability are playing critical roles in comprehensive ...The 21st century is the age of information when information becomes an important strategic resource. The information obtaining, processing and security guarantee capability are playing critical roles in comprehensive national power, and information security is related to the national security and social stability. Therefore, we should take measures to ensure the information security of our country. In recent years, momentous accomplishments have been obtained with the rapid development of information security technology. There are extensive theories about information security and technology. However, due to the limitation of length, this article mainly focuses on the research and development of cryptology, trusted computing, security of network, and information hiding, etc.展开更多
In this paper, we propose a balanced multi-label propagation algorithm （BMLPA） for overlapping community detection in social networks. As well as its fast speed, another important advantage of our method is good sta...In this paper, we propose a balanced multi-label propagation algorithm （BMLPA） for overlapping community detection in social networks. As well as its fast speed, another important advantage of our method is good stability, which other multi-label propagation algorithms, such as COPRA, lack. In BMLPA, we propose a new update strategy, which requires that community identifiers of one vertex should have balanced belonging coefficients. The advantage of this strategy is that it allows vertices to belong to any number of communities without a global limit on the largest number of community memberships, which is needed for COPRA. Also, we propose a fast method to generate ＂rough cores＂, which can be used to initialize labels for multi-label propagation algorithms, and are able to improve the quality and stability of results. Experimental results on synthetic and real social networks show that BMLPA is very efficient and effective for uncovering overlapping communities.展开更多
Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important r...Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.展开更多
Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms...Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.Photonic accelerators are designed to accelerate specific categories of computing in the optical domain,especially matrix multiplication,to address the growing demand for computing resources and capacity.Photonic matrix multiplication has much potential to expand the domain of telecommunication,and artificial intelligence benefiting from its superior performance.Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors.In this review,we first introduce the methods of photonic matrix multiplication,mainly including the plane light conversion method,Mach–Zehnder interferometer method and wavelength division multiplexing method.We also summarize the developmental milestones of photonic matrix multiplication and the related applications.Then,we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years.Finally,we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.展开更多
The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implem...The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle.展开更多
Multi-label learning deals with problems where each example is represented by a single instance while being associated with multiple class labels simultaneously. Binary relevance is arguably the most intuitive solutio...Multi-label learning deals with problems where each example is represented by a single instance while being associated with multiple class labels simultaneously. Binary relevance is arguably the most intuitive solution for learning from multi-label examples. It works by decomposing the multi-label learning task into a number of independent binary learning tasks （one per class label）. In view of its potential weakness in ignoring correlations between labels, many correlation-enabling extensions to binary relevance have been proposed in the past decade. In this paper, we aim to review the state of the art of binary relevance from three perspectives. First, basic settings for multi-label learning and binary relevance solutions are briefly summarized. Second, representative strategies to provide binary relevance with label correlation exploitation abilities are discussed. Third, some of our recent studies on binary relevance aimed at issues other than label correlation exploitation are introduced. As a conclusion, we provide suggestions on future research directions.展开更多
The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment innovation.Insulating material,as the core of electrical power equipm...The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment innovation.Insulating material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and opportunities.The goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first discussed.The engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are investigated.Insulating materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being discussed.In the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material level.It is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality rules.The authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.展开更多
Research on two-dimensional(2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since ...Research on two-dimensional(2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since the mechanical exfoliation of graphene in 2004. Starting from graphene, 2D materials now have become a big family with numerous members and diverse categories. The unique structural features and physicochemical properties of 2D materials make them one class of the most appealing candidates for a wide range of potential applications. In particular, we have seen some major breakthroughs made in the field of 2D materials in last five years not only in developing novel synthetic methods and exploring new structures/properties but also in identifying innovative applications and pushing forward commercialisation. In this review, we provide a critical summary on the recent progress made in the field of 2D materials with a particular focus on last five years. After a brief backgroundintroduction, we first discuss the major synthetic methods for 2D materials, including the mechanical exfoliation, liquid exfoliation, vapor phase deposition, and wet-chemical synthesis as well as phase engineering of 2D materials belonging to the field of phase engineering of nanomaterials(PEN). We then introduce the superconducting/optical/magnetic properties and chirality of 2D materials along with newly emerging magic angle 2D superlattices. Following that, the promising applications of 2D materials in electronics, optoelectronics, catalysis, energy storage, solar cells, biomedicine, sensors, environments, etc. are described sequentially. Thereafter, we present the theoretic calculations and simulations of 2D materials. Finally, after concluding the current progress, we provide some personal discussions on the existing challenges and future outlooks in this rapidly developing field.展开更多
A class of quasi-cubic B-spline base functions by trigonometric polynomials are established which inherit properties similar to those of cubic B-spline bases. The corresponding curves with a shape parameter a, defined...A class of quasi-cubic B-spline base functions by trigonometric polynomials are established which inherit properties similar to those of cubic B-spline bases. The corresponding curves with a shape parameter a, defined by the introduced base functions, include the B-spline curves and can approximate the B-spline curves from both sides. The curves can be adjusted easily by using the shape parameter a, where dpi（a,t） is linear with respect to da for the fixed t. With the shape parameter chosen properly, the defined curves can be used to precisely represent straight line segments, parabola segments, circular arcs and some transcendental curves, and the corresponding tensor product surfaces can also represent spherical surfaces, cylindrical surfaces and some transcendental surfaces exactly. By abandoning positive property, this paper proposes a new C^2 continuous blended interpolation spline based on piecewise trigonometric polynomials associated with a sequence of local parameters. Illustration showed that the curves and surfaces constructed by the blended spline can be adjusted easily and freely. The blended interpolation spline curves can be shape-preserving with proper local parameters since these local parameters can be considered to be the magnification ratio to the length of tangent vectors at the interpolating points. The idea is extended to produce blended spline surfaces.展开更多
Clinical manifestations of symptoms play a crucial role in the diagnosis and appropriate treatment of diseases and are considered one of the main clinical features for contemporary disease taxonomy(i.e.,international ...Clinical manifestations of symptoms play a crucial role in the diagnosis and appropriate treatment of diseases and are considered one of the main clinical features for contemporary disease taxonomy(i.e.,international classification of diseases,ICD)[1].Deep investigation on molecular connections among symptoms is one of the key tasks for developing a disease-specific knowledge network and thus promoting the refinement of disease taxonomy toward precision medicine[2].展开更多
Vehicle re-identification(ReID)aims to retrieve the target vehicle in an extensive image gallery through its appearances from various views in the cross-camera scenario.It has gradually become a core technology of int...Vehicle re-identification(ReID)aims to retrieve the target vehicle in an extensive image gallery through its appearances from various views in the cross-camera scenario.It has gradually become a core technology of intelligent transportation system.Most existing vehicle re-identification models adopt the joint learning of global and local features.However,they directly use the extracted global features,resulting in insufficient feature expression.Moreover,local features are primarily obtained through advanced annotation and complex attention mechanisms,which require additional costs.To solve this issue,a multi-feature learning model with enhanced local attention for vehicle re-identification(MFELA)is proposed in this paper.The model consists of global and local branches.The global branch utilizes both middle and highlevel semantic features of ResNet50 to enhance the global representation capability.In addition,multi-scale pooling operations are used to obtain multiscale information.While the local branch utilizes the proposed Region Batch Dropblock(RBD),which encourages the model to learn discriminative features for different local regions and simultaneously drops corresponding same areas randomly in a batch during training to enhance the attention to local regions.Then features from both branches are combined to provide a more comprehensive and distinctive feature representation.Extensive experiments on VeRi-776 and VehicleID datasets prove that our method has excellent performance.展开更多
DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in...DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.展开更多
Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framew...Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human drivers.Moreover, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.展开更多
Driven by their potential applications, vectorial optical fields with spatially inhomogeneous states of polarization within the cross section have drawn significant attention recently. This work intends to review some...Driven by their potential applications, vectorial optical fields with spatially inhomogeneous states of polarization within the cross section have drawn significant attention recently. This work intends to review some of the latest development of this rapidly growing field of optics and offer a general overview of the current status of this field in a few areas. Mathematical descriptions of generalized vectorial optical fields are provided along with several special examples. A time-reversal methodology for the creation of a wide variety of exotic optical focal fields with prescribed characteristics within the focal volume is presented. Recently developed methods for the generation of vectorial optical fields that utilize fiber lasers,digital lasers, vectorial optical field generator, metasurfaces or photoalignment liquid crystals are summarized. The interactions of these vectorial optical fields with various micro-and nano-structures are presented and the prospects of their potential applications are discussed. The connection of vectorial optical fields with higher dimensionality in quantum information is summarized.展开更多
Acute ischemic stroke （AIS）, as the third leading cause of death worldwide, is characterized by its high incidence, mortality rate, high incurred disability rate, and frequent reoccurrence. The neuroprotective effec...Acute ischemic stroke （AIS）, as the third leading cause of death worldwide, is characterized by its high incidence, mortality rate, high incurred disability rate, and frequent reoccurrence. The neuroprotective effects of Ginkgo biloba extract （GBE） against several cerebral diseases have been reported in previous studies, but the underlying mechanisms of action are still unclear. Using a novel in vitro rat cortical capillary endothelial cell- astrocyte-neuron network model, we investigated the neuroprotective effects of GBE and one of its important constituents, Ginkgolide B （GB）, against oxygenglucose deprivation/reoxygenation and glucose （OGD/R） injury. In this model, rat cortical capillary endothelial cells, astrocytes, and neurons were cocultured so that they could be synchronously observed in the same system. Pretreatment with GBE or GB increased the neuron cell viability, ameliorated cell injury, and inhibited the cell apoptotic rate through Bax and Bcl-2 expression regulation after OGD/R injury. Furthermore, GBE or GB pretreatment enhanced the transendothelial electrical resistance of capillary endothelial monolayers, reduced the endothelial permeability coefficients for sodium fluorescein （Na-F）, and increased the expression levels of tight junction proteins, namely, ZO-1 and occludin, in endothelial cells. Results demonstrated the preventive effects of GBE on neuronal cell death and enhancement of the function of brain capillary endothelial monolayers after OGD/R injury in vitro; thus, GBE could be used as an effective neuroprotective agent for AIS/reperfusion, with GB as one of its significant constituents.展开更多
Batteries have been widely applied in many high-power applications,such as electric vehicles(EVs)and hybrid electric vehicles,where a suitable battery management system(BMS)is vital in ensuring safe and reliable opera...Batteries have been widely applied in many high-power applications,such as electric vehicles(EVs)and hybrid electric vehicles,where a suitable battery management system(BMS)is vital in ensuring safe and reliable operation of batteries.This paper aims to give a brief review on several key technologies of BMS,including battery modelling,state estimation and battery charging.First,popular battery types used in EVs are surveyed,followed by the introduction of key technologies used in BMS.Various battery models,including the electric model,thermal model and coupled electro-thermal model are reviewed.Then,battery state estimations for the state of charge,state of health and internal temperature are comprehensively surveyed.Finally,several key and traditional battery charging approaches with associated optimization methods are discussed.展开更多
High-speed polarization management is highly desirable for many applications,such as remote sensing,telecommunication,and medical diagnosis.However,most of the approaches for polarization management rely on bulky opti...High-speed polarization management is highly desirable for many applications,such as remote sensing,telecommunication,and medical diagnosis.However,most of the approaches for polarization management rely on bulky optical components that are slow to respond,cumbersome to use,and sometimes with high drive voltages.Here,we overcome these limitations by harnessing photonic integrated circuits based on thin-film lithium niobate platform.We successfully realize a portfolio of thin-film lithium niobate devices for essential polarization management functionalities,including arbitrary polarization generation,fast polarization measurement,polarization scrambling,and automatic polarization control.The present devices feature ultra-fast control speeds,low drive voltages,low optical losses and compact footprints.Using these devices,we achieve high fidelity polarization generation with a polarization extinction ratio up to 41.9 dB and fast polarization scrambling with a scrambling rate up to 65 Mrad s−1,both of which are best results in integrated optics.We also demonstrate the endless polarization state tracking operation in our devices.The demonstrated devices unlock a drastically new level of performance and scales in polarization management devices,leading to a paradigm shift in polarization management.展开更多
基金supported,in part,by the Natural Science Foundation of Jiangsu Province under grant numbers BK20201136,BK20191401in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘In a telemedicine diagnosis system,the emergence of 3D imaging enables doctors to make clearer judgments,and its accuracy also directly affects doctors’diagnosis of the disease.In order to ensure the safe transmission and storage of medical data,a 3D medical watermarking algorithm based on wavelet transform is proposed in this paper.The proposed algorithm employs the principal component analysis(PCA)transform to reduce the data dimension,which can minimize the error between the extracted components and the original data in the mean square sense.Especially,this algorithm helps to create a bacterial foraging model based on particle swarm optimization(BF-PSO),by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding,thereby achieving the optimal balance between embedding capacity and imperceptibility.A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.
基金This work was supported,in part,by the Natural Science Foundation of Jiangsu Province under Grant Numbers BK20201136,BK20191401in part,by the National Nature Science Foundation of China under Grant Numbers 61502240,61502096,61304205,61773219in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.Conflicts of Interest:The aut。
文摘The leakage of medical audio data in telemedicine seriously violates the privacy of patients.In order to avoid the leakage of patient information in telemedicine,a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data.The scheme decomposes the medical audio into two independent embedding domains,embeds the robust watermark and the reversible watermark into the two domains respectively.In order to ensure the audio quality,the Hurst exponent is used to find a suitable position for watermark embedding.Due to the independence of the two embedding domains,the embedding of the second-stage reversible watermark will not affect the first-stage watermark,so the robustness of the first-stage watermark can be well maintained.In the second stage,the correlation between the sampling points in the medical audio is used to modify the hidden bits of the histogram to reduce the modification of the medical audio and reduce the distortion caused by reversible embedding.Simulation experiments show that this scheme has strong robustness against signal processing operations such as MP3 compression of 48 db,additive white Gaussian noise(AWGN)of 20 db,low-pass filtering,resampling,re-quantization and other attacks,and has good imperceptibility.
基金Supported by National Natural Science Foundation of China(Grant No.51405241,51505234,51575283)
文摘With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.
基金the National Natural Science Foundation of China(Grant Nos.60373087,60673071and 60572155)the National High-Tech Development 863 Progranm of China(Grant No.2006AA01Z442)
文摘The 21st century is the age of information when information becomes an important strategic resource. The information obtaining, processing and security guarantee capability are playing critical roles in comprehensive national power, and information security is related to the national security and social stability. Therefore, we should take measures to ensure the information security of our country. In recent years, momentous accomplishments have been obtained with the rapid development of information security technology. There are extensive theories about information security and technology. However, due to the limitation of length, this article mainly focuses on the research and development of cryptology, trusted computing, security of network, and information hiding, etc.
基金supported by the Fundamental Research Funds for the Central Universities of Chinathe National Natural Science Foundation of China under Grant No. 60905029the Natural Science Foundation of Beijing of China under Grant No. 4112046
文摘In this paper, we propose a balanced multi-label propagation algorithm （BMLPA） for overlapping community detection in social networks. As well as its fast speed, another important advantage of our method is good stability, which other multi-label propagation algorithms, such as COPRA, lack. In BMLPA, we propose a new update strategy, which requires that community identifiers of one vertex should have balanced belonging coefficients. The advantage of this strategy is that it allows vertices to belong to any number of communities without a global limit on the largest number of community memberships, which is needed for COPRA. Also, we propose a fast method to generate ＂rough cores＂, which can be used to initialize labels for multi-label propagation algorithms, and are able to improve the quality and stability of results. Experimental results on synthetic and real social networks show that BMLPA is very efficient and effective for uncovering overlapping communities.
基金supported in part by the National Natural Science Foundation of China(61573147,91520201,61625303,61522302,61761130080)Guangzhou Research Collaborative Innovation Projects(2014Y2-00507)+2 种基金Guangdong Science and Technology Research Collaborative Innovation Projects(20138010102010,20148090901056,20158020214003)Guangdong Science and Technology Plan Project(Application Technology Research Foundation)(2015B020233006)National High-Tech Research and De-velopment Program of China(863 Program)(2015AA042303)
文摘Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.
基金Chaoran Huang would like to thank Alexander Tait,Bhavin Shastri and Paul Prucnal for the fruitful discussions.J.J.D.acknowledges the support of the National Key Research and Development Project of China(2018YFB2201901)the National Natural Science Foundation of China(61805090,62075075).
文摘Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.Photonic accelerators are designed to accelerate specific categories of computing in the optical domain,especially matrix multiplication,to address the growing demand for computing resources and capacity.Photonic matrix multiplication has much potential to expand the domain of telecommunication,and artificial intelligence benefiting from its superior performance.Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors.In this review,we first introduce the methods of photonic matrix multiplication,mainly including the plane light conversion method,Mach–Zehnder interferometer method and wavelength division multiplexing method.We also summarize the developmental milestones of photonic matrix multiplication and the related applications.Then,we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years.Finally,we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.
基金The work of A.Jacobsen,C.Evelo,M.Thompson,R.Cornet,R.Kaliyaperuma and M.Roos is supported by funding from the European Union’s Horizon 2020 research and innovation program under the EJP RD COFUND-EJP N°825575.The work of A.Jacobsen,C.Evelo,C.Goble,M.Thompson,N.Juty,R.Hooft,M.Roos,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista is supported by funding from ELIXIR EXCELERATE,H2020 grant agreement number 676559.R.Hooft was further funded by NL NWO NRGWI.obrug.2018.009.N.Juty and C.Goble were funded by CORBEL(H2020 grant agreement 654248)N.Juty,C.Goble,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista were funded by FAIRplus(IMI grant agreement 802750)+12 种基金N.Juty,C.Goble,M.Thompson,M.Roos,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista were funded by EOSClife H2020-EU(grant agreement number 824087)C.Goble was funded by DMMCore(BBSRC BB/M013189/)M.Thompson,M.Roos received funding from NWO(VWData 400.17.605)S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista have been funded by grants awarded to S-A.Sansone from the UK BBSRC and Research Councils(BB/L024101/1,BB/L005069/1)EU(H2020-EU 634107H2020-EU 654241,IMI(IMPRiND 116060)NIH Data Common Fund,and from the Wellcome Trust(ISA-InterMine 212930/Z/18/ZFAIRsharing 208381/A/17/Z)The work of A.Waagmeester has been funded by grant award number GM089820 from the National Institutes of Health.M.Kersloot was funded by the European Regional Development Fund(KVW-00163).The work of N.Meyers was funded by the National Science Foundation(OAC 1839030)The work of M.D.Wilkinson is funded by Isaac Peral/Marie Curie cofund with the Universidad Politecnica de Madrid and the Ministerio de Economia y Competitividad grant number TIN2014-55993-RMThe work of B.Magagna,E.Schultes,L.da Silva Santos and K.Jeffery is funded by the H2020-EU 824068The work of B.Magagna,E.Schultes and L.da Silva Santos is funded by the GO FAIR ISCO grant of the Dutch Ministry of Science and CultureThe work of G.Guizzardi is supported by the OCEAN Project(FUB).M.Courtot received funding from the I
文摘The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle.
基金Acknowledgements The authors would like to thank the associate editor and anonymous reviewers for their helpful comments and suggestions. This work was supported by the National Natural Science Foundation of China （Grant Nos. 61573104, 61622203）, the Natural Science Foundation of Jiangsu Province （BK20141340）, the Fundamental Research Funds for the Central Universities （2242017K40140）, and partially supported by the Collaborative Innovation Center of Novel Software Technology and Industrialization.
文摘Multi-label learning deals with problems where each example is represented by a single instance while being associated with multiple class labels simultaneously. Binary relevance is arguably the most intuitive solution for learning from multi-label examples. It works by decomposing the multi-label learning task into a number of independent binary learning tasks （one per class label）. In view of its potential weakness in ignoring correlations between labels, many correlation-enabling extensions to binary relevance have been proposed in the past decade. In this paper, we aim to review the state of the art of binary relevance from three perspectives. First, basic settings for multi-label learning and binary relevance solutions are briefly summarized. Second, representative strategies to provide binary relevance with label correlation exploitation abilities are discussed. Third, some of our recent studies on binary relevance aimed at issues other than label correlation exploitation are introduced. As a conclusion, we provide suggestions on future research directions.
文摘The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment innovation.Insulating material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and opportunities.The goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first discussed.The engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are investigated.Insulating materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being discussed.In the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material level.It is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality rules.The authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.
文摘Research on two-dimensional(2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since the mechanical exfoliation of graphene in 2004. Starting from graphene, 2D materials now have become a big family with numerous members and diverse categories. The unique structural features and physicochemical properties of 2D materials make them one class of the most appealing candidates for a wide range of potential applications. In particular, we have seen some major breakthroughs made in the field of 2D materials in last five years not only in developing novel synthetic methods and exploring new structures/properties but also in identifying innovative applications and pushing forward commercialisation. In this review, we provide a critical summary on the recent progress made in the field of 2D materials with a particular focus on last five years. After a brief backgroundintroduction, we first discuss the major synthetic methods for 2D materials, including the mechanical exfoliation, liquid exfoliation, vapor phase deposition, and wet-chemical synthesis as well as phase engineering of 2D materials belonging to the field of phase engineering of nanomaterials(PEN). We then introduce the superconducting/optical/magnetic properties and chirality of 2D materials along with newly emerging magic angle 2D superlattices. Following that, the promising applications of 2D materials in electronics, optoelectronics, catalysis, energy storage, solar cells, biomedicine, sensors, environments, etc. are described sequentially. Thereafter, we present the theoretic calculations and simulations of 2D materials. Finally, after concluding the current progress, we provide some personal discussions on the existing challenges and future outlooks in this rapidly developing field.
基金Project supported by the National Natural Science Foundation of China (Nos. 10171026 and 60473114), the Research Funds forYoung Innovation Group, Education Department of Anhui Prov-ince (No. 2005TD03) and the Natural Science Foundation of An-hui Provincial Education Department (No. 2006KJ252B), China
文摘A class of quasi-cubic B-spline base functions by trigonometric polynomials are established which inherit properties similar to those of cubic B-spline bases. The corresponding curves with a shape parameter a, defined by the introduced base functions, include the B-spline curves and can approximate the B-spline curves from both sides. The curves can be adjusted easily by using the shape parameter a, where dpi（a,t） is linear with respect to da for the fixed t. With the shape parameter chosen properly, the defined curves can be used to precisely represent straight line segments, parabola segments, circular arcs and some transcendental curves, and the corresponding tensor product surfaces can also represent spherical surfaces, cylindrical surfaces and some transcendental surfaces exactly. By abandoning positive property, this paper proposes a new C^2 continuous blended interpolation spline based on piecewise trigonometric polynomials associated with a sequence of local parameters. Illustration showed that the curves and surfaces constructed by the blended spline can be adjusted easily and freely. The blended interpolation spline curves can be shape-preserving with proper local parameters since these local parameters can be considered to be the magnification ratio to the length of tangent vectors at the interpolating points. The idea is extended to produce blended spline surfaces.
基金supported by the National Natural Science Foundation of China(81830111,82030122,82174533,and 81774201)National Key Research and Development Program of China(2018YFC1705201)+2 种基金Innovation Project of China Academy of Chinese Medical Sciences(CI2021A04907)Youth Innovation Team of Shaanxi Universities and Shaanxi Provincial Science and Technology Department Project(2016SF-378)Fundamental Research Funds for the Central Public Welfare Research Institutes(ZXKT17058 and ZZ13-YQ-095)。
文摘Clinical manifestations of symptoms play a crucial role in the diagnosis and appropriate treatment of diseases and are considered one of the main clinical features for contemporary disease taxonomy(i.e.,international classification of diseases,ICD)[1].Deep investigation on molecular connections among symptoms is one of the key tasks for developing a disease-specific knowledge network and thus promoting the refinement of disease taxonomy toward precision medicine[2].
基金This work was supported,in part,by the National Nature Science Foundation of China under Grant Numbers 61502240,61502096,61304205,61773219in part,by the Natural Science Foundation of Jiangsu Province under grant numbers BK20201136,BK20191401+1 种基金in part,by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant Numbers SJCX21_0363in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘Vehicle re-identification(ReID)aims to retrieve the target vehicle in an extensive image gallery through its appearances from various views in the cross-camera scenario.It has gradually become a core technology of intelligent transportation system.Most existing vehicle re-identification models adopt the joint learning of global and local features.However,they directly use the extracted global features,resulting in insufficient feature expression.Moreover,local features are primarily obtained through advanced annotation and complex attention mechanisms,which require additional costs.To solve this issue,a multi-feature learning model with enhanced local attention for vehicle re-identification(MFELA)is proposed in this paper.The model consists of global and local branches.The global branch utilizes both middle and highlevel semantic features of ResNet50 to enhance the global representation capability.In addition,multi-scale pooling operations are used to obtain multiscale information.While the local branch utilizes the proposed Region Batch Dropblock(RBD),which encourages the model to learn discriminative features for different local regions and simultaneously drops corresponding same areas randomly in a batch during training to enhance the attention to local regions.Then features from both branches are combined to provide a more comprehensive and distinctive feature representation.Extensive experiments on VeRi-776 and VehicleID datasets prove that our method has excellent performance.
基金the National Natural Science Foundation of China(62271485,61903363,U1811463,62103411,62203250)the Science and Technology Development Fund of Macao SAR(0093/2023/RIA2,0050/2020/A1)。
文摘DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.
基金supported in part by the National Natural Science Foundation of China (61773414,61806076)Hubei Provincial Natural Science Foundation of China (2018CFB158)
文摘Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human drivers.Moreover, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.
基金support provided through the Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learningalso partially supported by the National Natural Science Foundation of China(91438108 and 61505062)the Chinese Scholarship Council for supporting their study at the University of Dayton through the Joint Training PhD Program and Visiting Scholar Program
文摘Driven by their potential applications, vectorial optical fields with spatially inhomogeneous states of polarization within the cross section have drawn significant attention recently. This work intends to review some of the latest development of this rapidly growing field of optics and offer a general overview of the current status of this field in a few areas. Mathematical descriptions of generalized vectorial optical fields are provided along with several special examples. A time-reversal methodology for the creation of a wide variety of exotic optical focal fields with prescribed characteristics within the focal volume is presented. Recently developed methods for the generation of vectorial optical fields that utilize fiber lasers,digital lasers, vectorial optical field generator, metasurfaces or photoalignment liquid crystals are summarized. The interactions of these vectorial optical fields with various micro-and nano-structures are presented and the prospects of their potential applications are discussed. The connection of vectorial optical fields with higher dimensionality in quantum information is summarized.
文摘Acute ischemic stroke （AIS）, as the third leading cause of death worldwide, is characterized by its high incidence, mortality rate, high incurred disability rate, and frequent reoccurrence. The neuroprotective effects of Ginkgo biloba extract （GBE） against several cerebral diseases have been reported in previous studies, but the underlying mechanisms of action are still unclear. Using a novel in vitro rat cortical capillary endothelial cell- astrocyte-neuron network model, we investigated the neuroprotective effects of GBE and one of its important constituents, Ginkgolide B （GB）, against oxygenglucose deprivation/reoxygenation and glucose （OGD/R） injury. In this model, rat cortical capillary endothelial cells, astrocytes, and neurons were cocultured so that they could be synchronously observed in the same system. Pretreatment with GBE or GB increased the neuron cell viability, ameliorated cell injury, and inhibited the cell apoptotic rate through Bax and Bcl-2 expression regulation after OGD/R injury. Furthermore, GBE or GB pretreatment enhanced the transendothelial electrical resistance of capillary endothelial monolayers, reduced the endothelial permeability coefficients for sodium fluorescein （Na-F）, and increased the expression levels of tight junction proteins, namely, ZO-1 and occludin, in endothelial cells. Results demonstrated the preventive effects of GBE on neuronal cell death and enhancement of the function of brain capillary endothelial monolayers after OGD/R injury in vitro; thus, GBE could be used as an effective neuroprotective agent for AIS/reperfusion, with GB as one of its significant constituents.
文摘Batteries have been widely applied in many high-power applications,such as electric vehicles(EVs)and hybrid electric vehicles,where a suitable battery management system(BMS)is vital in ensuring safe and reliable operation of batteries.This paper aims to give a brief review on several key technologies of BMS,including battery modelling,state estimation and battery charging.First,popular battery types used in EVs are surveyed,followed by the introduction of key technologies used in BMS.Various battery models,including the electric model,thermal model and coupled electro-thermal model are reviewed.Then,battery state estimations for the state of charge,state of health and internal temperature are comprehensively surveyed.Finally,several key and traditional battery charging approaches with associated optimization methods are discussed.
基金supported by the National Key Research and Development Program of China(2019YFB1803900 and 2019YFA0705000)National Natural Science Foundation of China(11690031 and 11761131001)+2 种基金Key R&D Program of Guangdong Province(2018B030329001)Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program(2017BT01X121)Key-Area Research and Development Program of Guangdong Province(2019B121204003).
文摘High-speed polarization management is highly desirable for many applications,such as remote sensing,telecommunication,and medical diagnosis.However,most of the approaches for polarization management rely on bulky optical components that are slow to respond,cumbersome to use,and sometimes with high drive voltages.Here,we overcome these limitations by harnessing photonic integrated circuits based on thin-film lithium niobate platform.We successfully realize a portfolio of thin-film lithium niobate devices for essential polarization management functionalities,including arbitrary polarization generation,fast polarization measurement,polarization scrambling,and automatic polarization control.The present devices feature ultra-fast control speeds,low drive voltages,low optical losses and compact footprints.Using these devices,we achieve high fidelity polarization generation with a polarization extinction ratio up to 41.9 dB and fast polarization scrambling with a scrambling rate up to 65 Mrad s−1,both of which are best results in integrated optics.We also demonstrate the endless polarization state tracking operation in our devices.The demonstrated devices unlock a drastically new level of performance and scales in polarization management devices,leading to a paradigm shift in polarization management.
