The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use w...The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use with chronic diseases, this study explored the association between different levels of PA and annual hospital service use and expenditure for inpatients with coronary heart disease (CHD) in China. We analyzed PA information from the first follow-up survey (2013) of the Dongfeng-Tongji cohort study of 1460 CHD inpatients. We examined factors such as PA exercise volume and years of PA and their associations with the number of inpatient visits, number of hospital days, and inpatient costs and total medical costs. We found that the number of hospital days and the number of inpatient visits were negatively associated with intensity of PA level. Similarly, total inpatient and outpatient costs declined when the PA exercise volume levels increased. Furthermore, there were also significant associations between the number of hospital days, inpatient costs or total medical costs and levels of PA years. This study provides the first empirical evidence about the effects of the intensity and years of PA on hospital service use and expenditure of CHD in China. It suggests that the patients' PA, especially the vigorous PA, should be promoted widely to the public and patients in order to relieve the financial burden of CHD.展开更多
Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sec...Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sectional survey in China to provide strong data support for research development in various fields and a more comprehensive and systematic understanding of the physical and mental health status of the public.Method:The study was conducted from June 20,2022 to August 31,2022,using stratified sampling and quota sampling methods,a total of 148 cities,202 districts and counties,390 townships/towns/sub-districts,and 780 communities/villages(excluding Hong Kong,Macao,and Taiwan)from 23 provinces,5 autonomous regions,and 4 municipalities directly under the central government in China were selected.The questionnaire was distributed one-on-one and face-to-face to the public by trained investigators,and the questionnaire included eight aspects:personal basic information,personal health status,family basic information,social environment in which they were located,psychological level scale,behavioral level scale,other scales,and attitude towards social hot issues.Data analysis will be performed after questionnaire return.Results:Data collection is ongoing.These findings will support physical and mental health research and strategy development in China and even globally,guiding policy-makers and health care organizations to reform their programs to ensure the best interests of residents and their families.展开更多
This study proposes a new generation network based on transformers and guided by the music theory to produce high-quality music work.In this study,the decoding block of the transformer is used to learn the internal in...This study proposes a new generation network based on transformers and guided by the music theory to produce high-quality music work.In this study,the decoding block of the transformer is used to learn the internal information of single-track music,and cross-track transformers are used to learn the information amongst the tracks of different musical instruments.A reward network based on the music theory is proposed,which optimizes the global and local loss objective functions while training and discriminating the network so that the reward network can provide a reliable adjustment method for the generation of the network.The method of combining the reward network and cross entropy loss is used to guide the training of the generator and produce high-quality music work.Compared with other multi-track music generation models,the experimental results verify the validity of the model.展开更多
With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human interaction.Traditional emotional dialogue systems usually use an e...With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human interaction.Traditional emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate responses.However,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the response.We propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional dictionary.Different from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer structure.Then,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and emotion.The content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features respectively.Moreover,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the model.Experimental results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.展开更多
Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recomm...Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recommendation.Meanwhile,diversity is an important metric for evaluating news recommendation algorithms,as users tend to reject excessive homogeneous information in their recommendation lists.However,recommendation models themselves lack diversity awareness,making it challenging to achieve a good balance between the accuracy and diversity of news recommendations.In this paper,we propose a news recommendation algorithm that achieves good performance in both accuracy and diversity.Unlike most existing works that solely optimize accuracy or employ more features to meet diversity,the proposed algorithm leverages the diversity-aware capability of the model.First,we introduce an augmented user model to fully capture user intent and the behavioral guidance they might undergo as a result.Specifically,we focus on the relationship between the original clicked news and the augmented clicked news.Moreover,we propose an effective adversarial training method for diversity(AT4D),which is a pluggable component that can enhance both the accuracy and diversity of news recommendation results.Extensive experiments on real-world datasets confirm the efficacy of the proposed algorithm in improving both the accuracy and diversity of news recommendations.展开更多
The method of terahertz(THz)resonance with a high-quality(high-Q)factor offers a vital physical mechanism for metasurface sensors and other high-Q factor applications.However,it is challenging to excite the resonance ...The method of terahertz(THz)resonance with a high-quality(high-Q)factor offers a vital physical mechanism for metasurface sensors and other high-Q factor applications.However,it is challenging to excite the resonance with a high-Q factor in metasurfaces with proper sensitivity as well as figure of merit(FOM)values.Here,an all-dielectric metasurface composed of two asymmetrical rectangular blocks is suggested.Quartz and silicon are the materials applied for the substrate and cuboids respectively.The distinct resonance governed by bound states in the continuum(BIC)is excited by forming an asymmetric cluster by a novel hybrid method of cutting and moving the cuboids.The investigation focuses on analyzing the transmission spectra of the metasurface under different variations in structural parameters and the loss of silicon refractive index.When the proposed defective metasurface serves as a transmittance sensor,it shows a Q factor of 1.08×10^(4)and achieves an FOM up to 4.8×10^(6),which is obtained under the asymmetric parameter equalling 1μm.Simultaneously,the proposed defective metasurface is sensitive to small changes in refractive index.When the thickness of the analyte is 180μm,the sensitivity reaches a maximum value of 578 GHz/RIU.Hence,the proposed defective metasurface exhibits an extensive number of possible applications in the filters,biomedical diagnosis,security screening,and so on.展开更多
"Carbon neutrality movies"are movies that focus on carbon neutrality as the object of expression and dissemination.Using carbon neutrality as an element,it influences the development of the plot,reflects env..."Carbon neutrality movies"are movies that focus on carbon neutrality as the object of expression and dissemination.Using carbon neutrality as an element,it influences the development of the plot,reflects environmental changes,and focuses on climate change caused by carbon emissions.At the same time,it focuses on offsetting carbon emissions through carbon neutrality behavior,showcasing the impact of carbon neutrality.From the perspective of ecological movies,the evolution of carbon neutrality movies at three stages can be explored.The first stage is high-carbon movies that reflect the high conflict between humans and the natural environment.The second stage is low-carbon movies,reflecting humanity's pursuit of a harmonious coexistence between humans and nature,thus adopting green and low-carbon behaviors.The third stage is carbon neutrality movies,which awaken or guide the public to pay attention to carbon emissions,promote low-carbon living,guide life practice in a carbon neutrality way,and create a better life.There are three characteristics of"carbon neutrality movies",including scientific reflection on global warming,advocating energy conservation and emission reduction in daily life,and promoting clean energy in policies.展开更多
Computer-generated aesthetic patterns arewidely used as design materials in various fields. Themost common methods use fractals or dynamicalsystems as basic tools to create various patterns. Toenhance aesthetics and c...Computer-generated aesthetic patterns arewidely used as design materials in various fields. Themost common methods use fractals or dynamicalsystems as basic tools to create various patterns. Toenhance aesthetics and controllability, some researchershave introduced symmetric layouts along with thesetools. One popular strategy employs dynamical systemscompatible with symmetries that construct functionswith the desired symmetries. However, these aretypically confined to simple planar symmetries. Theother generates symmetrical patterns under theconstraints of tilings. Although it is slightly moreflexible, it is restricted to small ranges of tilingsand lacks textural variations. Thus, we proposed anew approach for generating aesthetic patterns bysymmetrizing quasi-regular patterns using general kuniformtilings. We adopted a unified strategy toconstruct invariant mappings for k-uniform tilings thatcan eliminate texture seams across the tiling edges.Furthermore, we constructed three types of symmetriesassociated with the patterns: dihedral, rotational, andreflection symmetries. The proposed method can beeasily implemented using GPU shaders and is highlyefficient and suitable for complicated tiling with regularpolygons. Experiments demonstrated the advantages of our method over state-of-the-art methods in terms offlexibility in controlling the generation of patterns withvarious parameters as well as the diversity of texturesand styles.展开更多
In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in ...In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments.Federated learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy.However,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still under-explored.In this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular IoT.The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with environments.The clients also work as forwarder nodes in information sharing among network entities.The client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking architecture.We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.展开更多
In recent years,with the continuous advancement of the intelligent process of the Internet of Vehicles(IoV),the problem of privacy leakage in IoV has become increasingly prominent.The research on the privacy protectio...In recent years,with the continuous advancement of the intelligent process of the Internet of Vehicles(IoV),the problem of privacy leakage in IoV has become increasingly prominent.The research on the privacy protection of the IoV has become the focus of the society.This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms,proposes a privacy protection system structure based on untrusted data collection server,and designs a vehicle location acquisition algorithm based on a local differential privacy and game model.The algorithm first meshes the road network space.Then,the dynamic game model is introduced into the game user location privacy protection model and the attacker location semantic inference model,thereby minimizing the possibility of exposing the regional semantic privacy of the k-location set while maximizing the availability of the service.On this basis,a statistical method is designed,which satisfies the local differential privacy of k-location sets and obtains unbiased estimation of traffic density in different regions.Finally,this paper verifies the algorithm based on the data set of mobile vehicles in Shanghai.The experimental results show that the algorithm can guarantee the user’s location privacy and location semantic privacy while satisfying the service quality requirements,and provide better privacy protection and service for the users of the IoV.展开更多
With the rapid development of cloud computing technology,cloud services have now become a new business model for information services.The cloud server provides the IT resources required by customers in a selfservice m...With the rapid development of cloud computing technology,cloud services have now become a new business model for information services.The cloud server provides the IT resources required by customers in a selfservice manner through the network,realizing business expansion and rapid innovation.However,due to the insufficient protection of data privacy,the problem of data privacy leakage in cloud storage is threatening cloud computing.To address the problem,we propose BC-PECK,a data protection scheme based on blockchain and public key searchable encryption.Firstly,all the data is protected by the encryption algorithm.The privacy data is encrypted and stored in a cloud server,while the ciphertext index is established by a public key searchable encryption scheme and stored on the blockchain.Secondly,based on the characteristics of trusted execution of smart contract technology,a control mechanism for data accessing and sharing is given.Data transaction is automatically recorded on the blockchain,which is fairer under the premise of ensuring the privacy and security of the data sharing process.Finally,we analyzed the security and fairness of the current scheme.Through the comparison with similar schemes,we have shown the advantages of the proposed scheme.展开更多
In order to further understand the mechanism of material volume change in the drying process,numerical simulations(considering or neglecting shrinkage)of heat and mass transfer during convective drying of carrot slice...In order to further understand the mechanism of material volume change in the drying process,numerical simulations(considering or neglecting shrinkage)of heat and mass transfer during convective drying of carrot slices under constant and controlled temperature and relative humidity were carried out.Simulated results were validated with experimental data.The results of the simulation show that the Quadratic model fitted well to the moisture ratio and the material temperature data trend with average relative errors of 5.9%and 8.1%,respectively.Additionally,the results of the simulation considering shrinkage show that the moisture and temperature distributions during drying are closer to the experimental data than the results of the simulation disregarding shrinkage.The material moisture content was significantly related to the shrinkage of dried tissue.Temperature and relative humidity significantly affected the volume shrinkage of carrot slices.The volume shrinkage increased with the rising of the constant temperature and the decline of relative humidity.This model can be used to provide more information on the dynamics of heat and mass transfer during drying and can also be adapted to other products and dryers devices.展开更多
Based on the static compression experiments, the compressive stress-strain curve of multi-layer corrugated boards is simplified into three sections of linear elasticity, sub-buckling going with local collapse and dens...Based on the static compression experiments, the compressive stress-strain curve of multi-layer corrugated boards is simplified into three sections of linear elasticity, sub-buckling going with local collapse and densification. By considering the structure factors of multi-layer corrugated boards, the energy absorption model is obtained and characterized by the structure factors of corrugated cell-wall. The model is standardized by the solid modulus and it is universal for corrugated structures of different basis material. In the liner-elastic section, with the increase of the load, the energy absorption per unit volume of multi-layer corrugated boards gradually increases; in the sub-buckling section going with local collapse, the compression resistance of multi-layer corrugated boards goes on under a nearly constant load, but the energy absorption per unit volume rapidly increases with the increase of the compression strain. It is shown as an ascending curve in the energy absorption diagram. In the densification section, the corrugated sandwich core has no energy absorption capability. A good consistency is achieved between theoretical and experimental energy absorption curves. In designing the cushioning package, the cushioning properties can be evaluated by the theoretical model without more experiments. The suggested method to develop the energy absorption diagram for corrugated boards can be used to characterize the cushioning properties and optimize the structures of corrugated sandwich structures.展开更多
With the increasing popularity of mobile devices and the wide adoption of mobile Apps,an increasing concern of privacy issues is raised.Privacy policy is identified as a proper medium to indicate the legal terms,such ...With the increasing popularity of mobile devices and the wide adoption of mobile Apps,an increasing concern of privacy issues is raised.Privacy policy is identified as a proper medium to indicate the legal terms,such as the general data protection regulation(GDPR),and to bind legal agreement between service providers and users.However,privacy policies are usually long and vague for end users to read and understand.It is thus important to be able to automatically analyze the document structures of privacy policies to assist user understanding.In this work we create a manually labelled corpus containing 231 privacy policies(of more than 566,000 words and 7,748 annotated paragraphs).We benchmark our data corpus with 3 document classification models and achieve more than 82%on F1-score.展开更多
Unmanned aerial vehicles(UAV)are applied widely and profoundly in various fields.Moreover,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV usage.To ensure stable communic...Unmanned aerial vehicles(UAV)are applied widely and profoundly in various fields.Moreover,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV usage.To ensure stable communication of UAVs in denial environments with substantial electromagnetic interference,a systematic solution is proposed based on a deep learning algorithm for target detection and visible light for UAV tracking.Considering the cost and computational power limitations on the hardware,the you only look once(YOLO)v4-Tiny model is used for static target detection of the UAV model.For UAV tracking,and a light tracker that can adjust the angle of emitted light and focus it on the target is used for dynamic tracking processing.Thus,achieving the primary conditions of UAV optical communication with good secrecy is also suitable for dynamic situations.The UAV tracker positions the UAV model by returning the coordinates and calculating the time delay,and then controls the spotlight to target the UAV.In order to facilitate the deployment of deep learning models on hardware devices,the lighter and more efficient model is selected after comparison.The trained model can achieve 99.25%accuracy on the test set.The dynamic target detection can reach 20 frames per second(FPS)on a computer with an MX520 graphics processing unit(GPU)and 6 GB of random access memory(RAM).Dynamic target detection on a Jetson Nano can reach 5.4 FPS.展开更多
This paper presents a method to realize compact broadband low-RCS ReflectArray(RA)antenna based on a Frequency Selective Surface(FSS)absorber and a reflective metasurface.Such an FSS absorber consists of a resistance-...This paper presents a method to realize compact broadband low-RCS ReflectArray(RA)antenna based on a Frequency Selective Surface(FSS)absorber and a reflective metasurface.Such an FSS absorber consists of a resistance-loaded lossy layer and an FSS layer,which is utilized to reach an absorption-transmission response.The bottom reflective metasurface works as a phase array,reshaping the quasi-sphere wave from the feeding antenna into the quasi-plane wave.As a demonstration,the low-RCS RA antenna is simulated,fabricated,and measured.The simulated and measured results show that the developed low-RCS RA antenna has an aperture efficiency of 42.7%and a gain of 25.4 dBi in the X band.In the meantime,it simultaneously reaches the 10 dB RCS reduction for the orthogonal polarizations at the S and C bands,corresponding to a fractal bandwidth of 120%.Specifically,the adopted patch-feeding antenna makes the RA antenna more compact than the horn-feed conventional ones.Furthermore,the proposed RA antenna uses a few layers of substrates,making it lower in cost and easier for fabrication.The proposed design may have potential application in integrated stealth communication systems.展开更多
Information dissemination and the associated change of individual behavior can significantly slow the spread of an epidemic.However,major social events which attract public attention will disturb information spread an...Information dissemination and the associated change of individual behavior can significantly slow the spread of an epidemic.However,major social events which attract public attention will disturb information spread and affect epidemic transmission in ways that have not been readily quantified.We investigate the interplay between disease spreading and diseaserelated information dissemination in a two-layer network.We employ the SIR-UAU model with a time dependent coefficient to denote information dissemination.We found that major social events are equivalent to perturbations of information dissemination in certain time intervals and will consequently weaken the effect of information dissemination,and increase prevalence of infection.Our simulation results agree well with the trends observed from real-world data sets.We found that two specific major events explain the trend of the coronavirus epidemic in the US:the online propaganda and international agenda setting of Donald Trump early in 2020 and the 2020 US Presidential Election.展开更多
Mixed reality technologies provide real-time and immersive experiences,which bring tremendous opportunities in entertainment,education,and enriched experiences that are not directly accessible owing to safety or cost....Mixed reality technologies provide real-time and immersive experiences,which bring tremendous opportunities in entertainment,education,and enriched experiences that are not directly accessible owing to safety or cost.The research in this field has been in the spotlight in the last few years as the metaverse went viral.The recently emerging omnidirectional video streams,i.e.,360°videos,provide an affordable way to capture and present dynamic real-world scenes.In the last decade,fueled by the rapid development of artificial intelligence and computational photography technologies,the research interests in mixed reality systems using 360°videos with richer and more realistic experiences are dramatically increased to unlock the true potential of the metaverse.In this survey,we cover recent research aimed at addressing the above issues in the 360°image and video processing technologies and applications for mixed reality.The survey summarizes the contributions of the recent research and describes potential future research directions about 360°media in the field of mixed reality.展开更多
With the rapid development and widespread application of the IoT,the at-tacks against IoT vulnerabilities have become more complex and diverse.Most of the previous research focused on node vulnerability and its risk a...With the rapid development and widespread application of the IoT,the at-tacks against IoT vulnerabilities have become more complex and diverse.Most of the previous research focused on node vulnerability and its risk analysis.There is little information available about the importance of the location of the node in the system.Therefore,an estimation mechanism is proposed to assess the key node of the IoT system.The estimation of the key node includes two parts:one is the utilization relationship between nodes,and the other is the impact on the system after the node is conquered.We use the node importance value and the node risk value to quantify these two parts.First,the node importance value is calculated by considering the attack path that pass through the node and the probability that the attacker will abandon the attack.Second,in addition to node vulnerabilities and the consequences of being attacked,two quantitative indicators are proposed to comprehensively assess the impact of nodes on the system security,and the node risk value is calculated based on the grey correlation analysis method.Third,the key node in the IoT system could be obtained by integrating the node importance value and risk value.Finally,the simulation experiment result shows that the presented method could find the key node of the system quickly and accurately.展开更多
With the rapid development of knowledge pal malto:wangliye@cuc.edu.cn with a large number of knowledge products when purchasing,leading to the need for an effective recommendation system.However,existing recommendatio...With the rapid development of knowledge pal malto:wangliye@cuc.edu.cn with a large number of knowledge products when purchasing,leading to the need for an effective recommendation system.However,existing recommendation systems cannot accurately and adequately represent paid knowledge products with implicit but specialized features and sparse interactive histories,and thus are deemed not suitable for such products.In this paper,we propose a novel recommendation system for knowledge products,the core of which is the designed customer oriented representation of knowledge products.Specifically,we utilize customer activity information on the free knowledge sharing platform as the knowl-edge document for each customer of paid knowledge products,to extract customer knowledge background and preference.Then,a deep learning based model Doc2vec is adopted to transfer knowledge documents to customer knowledge background vectors.Such vectors of a particular paid knowledge product are further aggregated to a product-level vector for customer-oriented product representation,based on which two recommendation results are generated with product ratings and similarities of paid knowledge prod-ucts,respectively.Extensive comparative experiments are conducted to demonstrate the ffectiveness of the proposed system for the representation and recommendation of paid knowledge products.This paper will contribute to the literature of knowledge payment and recommendation systems,as well as provide practical implications for the information service and the operation of knowledge products on knowledge payment platforms.展开更多
文摘The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use with chronic diseases, this study explored the association between different levels of PA and annual hospital service use and expenditure for inpatients with coronary heart disease (CHD) in China. We analyzed PA information from the first follow-up survey (2013) of the Dongfeng-Tongji cohort study of 1460 CHD inpatients. We examined factors such as PA exercise volume and years of PA and their associations with the number of inpatient visits, number of hospital days, and inpatient costs and total medical costs. We found that the number of hospital days and the number of inpatient visits were negatively associated with intensity of PA level. Similarly, total inpatient and outpatient costs declined when the PA exercise volume levels increased. Furthermore, there were also significant associations between the number of hospital days, inpatient costs or total medical costs and levels of PA years. This study provides the first empirical evidence about the effects of the intensity and years of PA on hospital service use and expenditure of CHD in China. It suggests that the patients' PA, especially the vigorous PA, should be promoted widely to the public and patients in order to relieve the financial burden of CHD.
文摘Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sectional survey in China to provide strong data support for research development in various fields and a more comprehensive and systematic understanding of the physical and mental health status of the public.Method:The study was conducted from June 20,2022 to August 31,2022,using stratified sampling and quota sampling methods,a total of 148 cities,202 districts and counties,390 townships/towns/sub-districts,and 780 communities/villages(excluding Hong Kong,Macao,and Taiwan)from 23 provinces,5 autonomous regions,and 4 municipalities directly under the central government in China were selected.The questionnaire was distributed one-on-one and face-to-face to the public by trained investigators,and the questionnaire included eight aspects:personal basic information,personal health status,family basic information,social environment in which they were located,psychological level scale,behavioral level scale,other scales,and attitude towards social hot issues.Data analysis will be performed after questionnaire return.Results:Data collection is ongoing.These findings will support physical and mental health research and strategy development in China and even globally,guiding policy-makers and health care organizations to reform their programs to ensure the best interests of residents and their families.
基金the research project funded by the National Natural Science Foundation of China(Grant No.61631016 and 61901421)the National Key R&D Program of China(Grant No.2018YFB1403903)supported by the Fundamental Research Funds for the Central Universities(Grant No.CUC210B011).
文摘This study proposes a new generation network based on transformers and guided by the music theory to produce high-quality music work.In this study,the decoding block of the transformer is used to learn the internal information of single-track music,and cross-track transformers are used to learn the information amongst the tracks of different musical instruments.A reward network based on the music theory is proposed,which optimizes the global and local loss objective functions while training and discriminating the network so that the reward network can provide a reliable adjustment method for the generation of the network.The method of combining the reward network and cross entropy loss is used to guide the training of the generator and produce high-quality music work.Compared with other multi-track music generation models,the experimental results verify the validity of the model.
基金Fundamental Research Funds for the Central Universities of China,Grant/Award Number:CUC220B009National Natural Science Foundation of China,Grant/Award Numbers:62207029,62271454,72274182。
文摘With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human interaction.Traditional emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate responses.However,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the response.We propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional dictionary.Different from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer structure.Then,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and emotion.The content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features respectively.Moreover,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the model.Experimental results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.
基金This research was funded by Beijing Municipal Social Science Foundation(23YTB031)the Fundamental Research Funds for the Central Universities(CUC23ZDTJ005).
文摘Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recommendation.Meanwhile,diversity is an important metric for evaluating news recommendation algorithms,as users tend to reject excessive homogeneous information in their recommendation lists.However,recommendation models themselves lack diversity awareness,making it challenging to achieve a good balance between the accuracy and diversity of news recommendations.In this paper,we propose a news recommendation algorithm that achieves good performance in both accuracy and diversity.Unlike most existing works that solely optimize accuracy or employ more features to meet diversity,the proposed algorithm leverages the diversity-aware capability of the model.First,we introduce an augmented user model to fully capture user intent and the behavioral guidance they might undergo as a result.Specifically,we focus on the relationship between the original clicked news and the augmented clicked news.Moreover,we propose an effective adversarial training method for diversity(AT4D),which is a pluggable component that can enhance both the accuracy and diversity of news recommendation results.Extensive experiments on real-world datasets confirm the efficacy of the proposed algorithm in improving both the accuracy and diversity of news recommendations.
基金the Key Research and Development Program of Ningxia Province,China(2021BEB04068)。
文摘The method of terahertz(THz)resonance with a high-quality(high-Q)factor offers a vital physical mechanism for metasurface sensors and other high-Q factor applications.However,it is challenging to excite the resonance with a high-Q factor in metasurfaces with proper sensitivity as well as figure of merit(FOM)values.Here,an all-dielectric metasurface composed of two asymmetrical rectangular blocks is suggested.Quartz and silicon are the materials applied for the substrate and cuboids respectively.The distinct resonance governed by bound states in the continuum(BIC)is excited by forming an asymmetric cluster by a novel hybrid method of cutting and moving the cuboids.The investigation focuses on analyzing the transmission spectra of the metasurface under different variations in structural parameters and the loss of silicon refractive index.When the proposed defective metasurface serves as a transmittance sensor,it shows a Q factor of 1.08×10^(4)and achieves an FOM up to 4.8×10^(6),which is obtained under the asymmetric parameter equalling 1μm.Simultaneously,the proposed defective metasurface is sensitive to small changes in refractive index.When the thickness of the analyte is 180μm,the sensitivity reaches a maximum value of 578 GHz/RIU.Hence,the proposed defective metasurface exhibits an extensive number of possible applications in the filters,biomedical diagnosis,security screening,and so on.
文摘"Carbon neutrality movies"are movies that focus on carbon neutrality as the object of expression and dissemination.Using carbon neutrality as an element,it influences the development of the plot,reflects environmental changes,and focuses on climate change caused by carbon emissions.At the same time,it focuses on offsetting carbon emissions through carbon neutrality behavior,showcasing the impact of carbon neutrality.From the perspective of ecological movies,the evolution of carbon neutrality movies at three stages can be explored.The first stage is high-carbon movies that reflect the high conflict between humans and the natural environment.The second stage is low-carbon movies,reflecting humanity's pursuit of a harmonious coexistence between humans and nature,thus adopting green and low-carbon behaviors.The third stage is carbon neutrality movies,which awaken or guide the public to pay attention to carbon emissions,promote low-carbon living,guide life practice in a carbon neutrality way,and create a better life.There are three characteristics of"carbon neutrality movies",including scientific reflection on global warming,advocating energy conservation and emission reduction in daily life,and promoting clean energy in policies.
基金supported by the Key R&D Programs of Zhejiang Province(Nos.2023C01224 and 2022C01220)the National Natural Science Foundation of China(No.61702458)+1 种基金Yun Zhang was partially supported by Zhejiang Province Public Welfare Technology Application Research(No.LGG22F020009)Key Lab of Film and TV Media Technology of Zhejiang Province(No.2020E10015).
文摘Computer-generated aesthetic patterns arewidely used as design materials in various fields. Themost common methods use fractals or dynamicalsystems as basic tools to create various patterns. Toenhance aesthetics and controllability, some researchershave introduced symmetric layouts along with thesetools. One popular strategy employs dynamical systemscompatible with symmetries that construct functionswith the desired symmetries. However, these aretypically confined to simple planar symmetries. Theother generates symmetrical patterns under theconstraints of tilings. Although it is slightly moreflexible, it is restricted to small ranges of tilingsand lacks textural variations. Thus, we proposed anew approach for generating aesthetic patterns bysymmetrizing quasi-regular patterns using general kuniformtilings. We adopted a unified strategy toconstruct invariant mappings for k-uniform tilings thatcan eliminate texture seams across the tiling edges.Furthermore, we constructed three types of symmetriesassociated with the patterns: dihedral, rotational, andreflection symmetries. The proposed method can beeasily implemented using GPU shaders and is highlyefficient and suitable for complicated tiling with regularpolygons. Experiments demonstrated the advantages of our method over state-of-the-art methods in terms offlexibility in controlling the generation of patterns withvarious parameters as well as the diversity of texturesand styles.
基金This research was supported in part by the National Natural Science Foundation of China under Grant No.62062031 and 61877053in part by Inner Mongolia natural science foundation grant number 2019MS06035,and Inner Mongolia Science and Technology Major Project,China+1 种基金in part by ROIS NII Open Collaborative Research 21S0601in part by JSPS KAKENHI grant numbers 18KK0279,19H04093,20H00592,and 21H03424.
文摘In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments.Federated learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy.However,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still under-explored.In this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular IoT.The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with environments.The clients also work as forwarder nodes in information sharing among network entities.The client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking architecture.We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.
基金This work is supported by Major Scientific and Technological Special Project of Guizhou Province(20183001)Research on the education mode for complicate skill students in new media with cross specialty integration(22150117092)+2 种基金Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ014)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ019)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ022).
文摘In recent years,with the continuous advancement of the intelligent process of the Internet of Vehicles(IoV),the problem of privacy leakage in IoV has become increasingly prominent.The research on the privacy protection of the IoV has become the focus of the society.This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms,proposes a privacy protection system structure based on untrusted data collection server,and designs a vehicle location acquisition algorithm based on a local differential privacy and game model.The algorithm first meshes the road network space.Then,the dynamic game model is introduced into the game user location privacy protection model and the attacker location semantic inference model,thereby minimizing the possibility of exposing the regional semantic privacy of the k-location set while maximizing the availability of the service.On this basis,a statistical method is designed,which satisfies the local differential privacy of k-location sets and obtains unbiased estimation of traffic density in different regions.Finally,this paper verifies the algorithm based on the data set of mobile vehicles in Shanghai.The experimental results show that the algorithm can guarantee the user’s location privacy and location semantic privacy while satisfying the service quality requirements,and provide better privacy protection and service for the users of the IoV.
基金This work is supported by the NSFC(Grant Nos.92046001,61671087,61962009)the Fundamental Research Funds for the Central Universities(Grant No.2019XDA02)+7 种基金the Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(Grant Nos.2018BDKFJJ018,2019BDKFJJ010,2019BDKFJJ014)the High-quality and Cutting-edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China),the Open Research Project of the State Key Laboratory of Media Convergence and Communication,Communication University of China,China(Grant No.SKLMCC2020KF006)Inner Mongolia Major science and technology projects(2019ZD025)Baotou Kundulun District Science and technology plan project(YF2020013)Inner Mongolia discipline inspection and supervision big data laboratory open project fund(IMDBD2020020)the Natural Science Foundation of Inner Mongolia(2021MS0602)Huawei Technologies Co.Ltd(No.YBN2020085019)the Scientific Research Foundation of North China University of Technology。
文摘With the rapid development of cloud computing technology,cloud services have now become a new business model for information services.The cloud server provides the IT resources required by customers in a selfservice manner through the network,realizing business expansion and rapid innovation.However,due to the insufficient protection of data privacy,the problem of data privacy leakage in cloud storage is threatening cloud computing.To address the problem,we propose BC-PECK,a data protection scheme based on blockchain and public key searchable encryption.Firstly,all the data is protected by the encryption algorithm.The privacy data is encrypted and stored in a cloud server,while the ciphertext index is established by a public key searchable encryption scheme and stored on the blockchain.Secondly,based on the characteristics of trusted execution of smart contract technology,a control mechanism for data accessing and sharing is given.Data transaction is automatically recorded on the blockchain,which is fairer under the premise of ensuring the privacy and security of the data sharing process.Finally,we analyzed the security and fairness of the current scheme.Through the comparison with similar schemes,we have shown the advantages of the proposed scheme.
基金supported by Earmarked Fund for China Agriculture Research System(CARS-21).
文摘In order to further understand the mechanism of material volume change in the drying process,numerical simulations(considering or neglecting shrinkage)of heat and mass transfer during convective drying of carrot slices under constant and controlled temperature and relative humidity were carried out.Simulated results were validated with experimental data.The results of the simulation show that the Quadratic model fitted well to the moisture ratio and the material temperature data trend with average relative errors of 5.9%and 8.1%,respectively.Additionally,the results of the simulation considering shrinkage show that the moisture and temperature distributions during drying are closer to the experimental data than the results of the simulation disregarding shrinkage.The material moisture content was significantly related to the shrinkage of dried tissue.Temperature and relative humidity significantly affected the volume shrinkage of carrot slices.The volume shrinkage increased with the rising of the constant temperature and the decline of relative humidity.This model can be used to provide more information on the dynamics of heat and mass transfer during drying and can also be adapted to other products and dryers devices.
基金Funded by the National Natural Science Foundation of China (No.50905120)
文摘Based on the static compression experiments, the compressive stress-strain curve of multi-layer corrugated boards is simplified into three sections of linear elasticity, sub-buckling going with local collapse and densification. By considering the structure factors of multi-layer corrugated boards, the energy absorption model is obtained and characterized by the structure factors of corrugated cell-wall. The model is standardized by the solid modulus and it is universal for corrugated structures of different basis material. In the liner-elastic section, with the increase of the load, the energy absorption per unit volume of multi-layer corrugated boards gradually increases; in the sub-buckling section going with local collapse, the compression resistance of multi-layer corrugated boards goes on under a nearly constant load, but the energy absorption per unit volume rapidly increases with the increase of the compression strain. It is shown as an ascending curve in the energy absorption diagram. In the densification section, the corrugated sandwich core has no energy absorption capability. A good consistency is achieved between theoretical and experimental energy absorption curves. In designing the cushioning package, the cushioning properties can be evaluated by the theoretical model without more experiments. The suggested method to develop the energy absorption diagram for corrugated boards can be used to characterize the cushioning properties and optimize the structures of corrugated sandwich structures.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.61802275 and U1836214)the Innovation fund of Tianjin University(2020XRG-0022).
文摘With the increasing popularity of mobile devices and the wide adoption of mobile Apps,an increasing concern of privacy issues is raised.Privacy policy is identified as a proper medium to indicate the legal terms,such as the general data protection regulation(GDPR),and to bind legal agreement between service providers and users.However,privacy policies are usually long and vague for end users to read and understand.It is thus important to be able to automatically analyze the document structures of privacy policies to assist user understanding.In this work we create a manually labelled corpus containing 231 privacy policies(of more than 566,000 words and 7,748 annotated paragraphs).We benchmark our data corpus with 3 document classification models and achieve more than 82%on F1-score.
文摘Unmanned aerial vehicles(UAV)are applied widely and profoundly in various fields.Moreover,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV usage.To ensure stable communication of UAVs in denial environments with substantial electromagnetic interference,a systematic solution is proposed based on a deep learning algorithm for target detection and visible light for UAV tracking.Considering the cost and computational power limitations on the hardware,the you only look once(YOLO)v4-Tiny model is used for static target detection of the UAV model.For UAV tracking,and a light tracker that can adjust the angle of emitted light and focus it on the target is used for dynamic tracking processing.Thus,achieving the primary conditions of UAV optical communication with good secrecy is also suitable for dynamic situations.The UAV tracker positions the UAV model by returning the coordinates and calculating the time delay,and then controls the spotlight to target the UAV.In order to facilitate the deployment of deep learning models on hardware devices,the lighter and more efficient model is selected after comparison.The trained model can achieve 99.25%accuracy on the test set.The dynamic target detection can reach 20 frames per second(FPS)on a computer with an MX520 graphics processing unit(GPU)and 6 GB of random access memory(RAM).Dynamic target detection on a Jetson Nano can reach 5.4 FPS.
基金supported by the China Postdoctoral Science Foundation(No.2021M693712)the National Natural Science Foundation of China(Nos.62205038 and 62031006)the Chongqing Postdoctoral Science Foundation(Special Funding),China(No.XmT20200020).
文摘This paper presents a method to realize compact broadband low-RCS ReflectArray(RA)antenna based on a Frequency Selective Surface(FSS)absorber and a reflective metasurface.Such an FSS absorber consists of a resistance-loaded lossy layer and an FSS layer,which is utilized to reach an absorption-transmission response.The bottom reflective metasurface works as a phase array,reshaping the quasi-sphere wave from the feeding antenna into the quasi-plane wave.As a demonstration,the low-RCS RA antenna is simulated,fabricated,and measured.The simulated and measured results show that the developed low-RCS RA antenna has an aperture efficiency of 42.7%and a gain of 25.4 dBi in the X band.In the meantime,it simultaneously reaches the 10 dB RCS reduction for the orthogonal polarizations at the S and C bands,corresponding to a fractal bandwidth of 120%.Specifically,the adopted patch-feeding antenna makes the RA antenna more compact than the horn-feed conventional ones.Furthermore,the proposed RA antenna uses a few layers of substrates,making it lower in cost and easier for fabrication.The proposed design may have potential application in integrated stealth communication systems.
基金supported by the National Natural Science Foundation of China(61803047)Major Project of the National Social Science Foundation of China(19ZDA149 and 19ZDA324)+1 种基金Fundamental Research Funds for the Central Universities(14370119 and 14390110)supported by ARC Discovery Project(DP20010296)
文摘Information dissemination and the associated change of individual behavior can significantly slow the spread of an epidemic.However,major social events which attract public attention will disturb information spread and affect epidemic transmission in ways that have not been readily quantified.We investigate the interplay between disease spreading and diseaserelated information dissemination in a two-layer network.We employ the SIR-UAU model with a time dependent coefficient to denote information dissemination.We found that major social events are equivalent to perturbations of information dissemination in certain time intervals and will consequently weaken the effect of information dissemination,and increase prevalence of infection.Our simulation results agree well with the trends observed from real-world data sets.We found that two specific major events explain the trend of the coronavirus epidemic in the US:the online propaganda and international agenda setting of Donald Trump early in 2020 and the 2020 US Presidential Election.
基金supported by the Marsden Fund Council managed by Royal Society of New Zealand under Grant Nos.MFP-20-VUW-180 and UOO1724Zhejiang Province Public Welfare Technology Application Research under Grant No.LGG22F020009the Key Lab of Film and TV Media Technology of Zhejiang Province of China under Grant No.2020E10015.
文摘Mixed reality technologies provide real-time and immersive experiences,which bring tremendous opportunities in entertainment,education,and enriched experiences that are not directly accessible owing to safety or cost.The research in this field has been in the spotlight in the last few years as the metaverse went viral.The recently emerging omnidirectional video streams,i.e.,360°videos,provide an affordable way to capture and present dynamic real-world scenes.In the last decade,fueled by the rapid development of artificial intelligence and computational photography technologies,the research interests in mixed reality systems using 360°videos with richer and more realistic experiences are dramatically increased to unlock the true potential of the metaverse.In this survey,we cover recent research aimed at addressing the above issues in the 360°image and video processing technologies and applications for mixed reality.The survey summarizes the contributions of the recent research and describes potential future research directions about 360°media in the field of mixed reality.
基金This work is supported by the National Key R&D Program of China(2017YFB0802703)Major Scientific and Technological Special Project of Guizhou Province(20183001)+2 种基金Open Foundation of Guizhou Provincial Key VOLUME XX,2019 Laboratory of Public Big Data(2018BDKFJJ014)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ019)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ022).
文摘With the rapid development and widespread application of the IoT,the at-tacks against IoT vulnerabilities have become more complex and diverse.Most of the previous research focused on node vulnerability and its risk analysis.There is little information available about the importance of the location of the node in the system.Therefore,an estimation mechanism is proposed to assess the key node of the IoT system.The estimation of the key node includes two parts:one is the utilization relationship between nodes,and the other is the impact on the system after the node is conquered.We use the node importance value and the node risk value to quantify these two parts.First,the node importance value is calculated by considering the attack path that pass through the node and the probability that the attacker will abandon the attack.Second,in addition to node vulnerabilities and the consequences of being attacked,two quantitative indicators are proposed to comprehensively assess the impact of nodes on the system security,and the node risk value is calculated based on the grey correlation analysis method.Third,the key node in the IoT system could be obtained by integrating the node importance value and risk value.Finally,the simulation experiment result shows that the presented method could find the key node of the system quickly and accurately.
基金This work is supported by the National Natural Science Foundation of China under Grant Nos.71772177,72072177,72202221the Open Research Project of the State Key Laboratory of Media Convergence and Communication,Communication University of China under Grant No.SKLMCC2021KF005the"Double First-Class"Major(Key)lconic Project of Bejjing Foreign Studies University(Study on the globalization risk in post epidemic period:From the perspective of financial s-curity and business risk under Grant No.2022SYLZD001),and the Fundamental Resea rch Funds for the Central Universities.
文摘With the rapid development of knowledge pal malto:wangliye@cuc.edu.cn with a large number of knowledge products when purchasing,leading to the need for an effective recommendation system.However,existing recommendation systems cannot accurately and adequately represent paid knowledge products with implicit but specialized features and sparse interactive histories,and thus are deemed not suitable for such products.In this paper,we propose a novel recommendation system for knowledge products,the core of which is the designed customer oriented representation of knowledge products.Specifically,we utilize customer activity information on the free knowledge sharing platform as the knowl-edge document for each customer of paid knowledge products,to extract customer knowledge background and preference.Then,a deep learning based model Doc2vec is adopted to transfer knowledge documents to customer knowledge background vectors.Such vectors of a particular paid knowledge product are further aggregated to a product-level vector for customer-oriented product representation,based on which two recommendation results are generated with product ratings and similarities of paid knowledge prod-ucts,respectively.Extensive comparative experiments are conducted to demonstrate the ffectiveness of the proposed system for the representation and recommendation of paid knowledge products.This paper will contribute to the literature of knowledge payment and recommendation systems,as well as provide practical implications for the information service and the operation of knowledge products on knowledge payment platforms.
