Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superp...Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer(WET)and orthogonal-frequency-divisionmultiplexing(OFDM)signals for wireless data transfer(WDT).The outdated channel state information(CSI)in aging channels is employed by the transmitter to shape IDET waveforms.With the constraints of transmission power and WDT requirement,the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average directcurrent(DC)among a limited number of transmission frames with the existence of carrier-frequencyoffset(CFO).For the amplitude optimisation,the original non-convex problem can be transformed into a reversed geometric programming problem,then it can be effectively solved with existing tools.As for the phase optimisation,the artificial bee colony(ABC)algorithm is invoked in order to deal with the nonconvexity.Iteration between the amplitude optimisation and phase optimisation yields our joint design.Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI.展开更多
Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted ...Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.展开更多
In unmanned aerial vehicle(UAV)-based scenarios,sensing-aided integrated data and energy networking(IDEN)systems can significantly mitigate non-line-of-sight(NLoS)propagation,thereby enhancing sensing accuracy..Howeve...In unmanned aerial vehicle(UAV)-based scenarios,sensing-aided integrated data and energy networking(IDEN)systems can significantly mitigate non-line-of-sight(NLoS)propagation,thereby enhancing sensing accuracy..However,the rapid channel variations induced by UAV mobility pose a challenge for traditional polar code construction methods,making it difficult to satisfy the stringent requirements of IDEN systems.To address this challenge,we propose a neural network(NN)-based sensing-aided IDEN framework.This system leverages sensing information to assist polar code construction while satisfying energy constraints.Furthermore,it incorporates neural networks to optimize the performance of polar codes in dynamic environments.Specifically,a sensing-aided binarized neural network(BNN)-based polar encoder is proposed for both lowlatency and high-reliability requirements,and a deep neural network(DNN)-based polar decoder is applied to match the encoder.Moreover,the corresponding training method is proposed,which focuses on the initialization design of the NNs.The simulation results show that the NN-based sensing-aided polar encoding scheme outperforms the conventional counterparts in terms of IDEN for both low-latency and high-reliability requirements.展开更多
Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as ...Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as sandstone and mudstone to undertake separate porositydepth compaction modeling. However, using just two lithologies is an oversimplification that cannot represent the compaction history. In such schemes, the precision of the compaction recovery is inadequate. To improve the precision of compaction recovery, a depth compaction model has been proposed that involves both porosity and clay content. A clastic lithological compaction unit classification method, based on clay content, has been designed to identify lithological boundaries and establish sets of compaction units. Also, on the basis of the clastic compaction unit classification, two methods of compaction recovery that integrate well and seismic data are employed to extrapolate well-based compaction information outward along seismic lines and recover the paleo-topography of the clastic strata in the region. The examples presented here show that a better understanding of paleo-geomorphology can be gained by applying the proposed compaction recovery technology.展开更多
In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The...In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.展开更多
Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data ...Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data and energy through radio frequency signals.State-of-the-art researches mostly focus on theoretical aspects.By contrast,we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle(UAV).The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals,while collecting essential information from them.Then,the UAV uploads the information to remote base stations.Our system verifies the feasibility of the DEIN in practical applications.展开更多
With the rapid development of the mobile internet and the massive deployment of the Internet of Things, mobile devices, including both the consumer electronics and the sensors, become hungrier for the energy than ever...With the rapid development of the mobile internet and the massive deployment of the Internet of Things, mobile devices, including both the consumer electronics and the sensors, become hungrier for the energy than ever before. Conventional cable based charging largely restrict the movement of the mobile devices. Wireless charging hence emerges as an essential technique for enabling our ultimate goal of charging anytime and anywhere. By efficiently exploiting the legacy of the existing communication infrastructure, we propose a nov- el data and energy integrated network （DEIN） in order to re- alise the radio frequency （RF） based wireless charging with- out degrading the information transmission. In this treatise, we focus on the implementation of the DEIN in both the theoretical and practical aspects, concerning the transceiver architecture design and the rectifier circuit design. Furthermore, we also present a Wi-Fi based testbed for demonstrating the availability of the RF based wireless charging.展开更多
This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling ...This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.展开更多
Background Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment.However,limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to...Background Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment.However,limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress.In response,our research team has embarked on the development of a specialized clinical research database for cardiology,thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors.Methods The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021.It included comprehensive data on patients'basic information,medical history,non-invasive imaging studies,laboratory test results,as well as peri-procedural information related to interventional surgeries,extracted from the Hospital Information System.Additionally,an innovative artificial intelligence(AI)-powered interactive follow-up system had been developed,ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up,thereby achieving comprehensive data management throughout the entire care continuum for highrisk patients.Results This database integrates extensive cross-sectional and longitudinal patient data,with a focus on higher-risk acute coronary syndrome patients.It achieves the integration of structured and unstructured clinical data,while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency.It creates a comprehensive patient view,thereby improving diagnostic and follow-up quality,and provides high-quality data to support clinical research.Despite limitations in unstructured data standardization and biological sample integrity,the database's development is accompanied by ongoing optimization efforts.Conclusion The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research,which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes.It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.展开更多
To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,al...To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.展开更多
The large-scale deployment of Internet of Things(IoT)technology across various aspects of daily life has significantly propelled the intelligent development of society.Among them,the integration of IoT and named data ...The large-scale deployment of Internet of Things(IoT)technology across various aspects of daily life has significantly propelled the intelligent development of society.Among them,the integration of IoT and named data networks(NDNs)reduces network complexity and provides practical directions for content-oriented network design.However,ensuring data integrity in NDN-IoT applications remains a challenging issue.Very recently,Wang et al.(Entropy,27(5),471(2025))designed a certificateless aggregate signature(CLAS)scheme for NDN-IoT environments.Wang et al.stated that their construction was provably secure under various types of security attacks.Using theoretical analysis methods,in this work,we reveal that their CLAS design fails to meet unforgeability,a core security requirement for CLAS schemes.In particular,we demonstrate that their scheme is vulnerable to amalicious public-key replacement attack,enabling an adversary to produce authentic signatures for arbitrary fraudulent messages.Therefore,Wang et al.’s design cannot achieve its goal.To address the issue,we systematically examine the root causes behind the vulnerability and propose a security-enhanced CLAS construction for NDN-IoT environments.We prove the security ofour improveddesignunder the standard security assumptionandalsoanalyze its practicalperformanceby comparing the computational and communication costs with several related works.The comparison results show the practicality of our design.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data...Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.展开更多
Blast furnace (BF) ironmaking is the most typical “black box” process, and its complexity and uncertainty bring forth great challenges for furnace condition judgment and BF operation. Rich data resources for BF iron...Blast furnace (BF) ironmaking is the most typical “black box” process, and its complexity and uncertainty bring forth great challenges for furnace condition judgment and BF operation. Rich data resources for BF ironmaking are available, and the rapid development of data science and intelligent technology will provide an effective means to solve the uncertainty problem in the BF ironmaking process. This work focused on the application of artificial intelligence technology in BF ironmaking. The current intelligent BF ironmaking technology was summarized and analyzed from five aspects. These aspects include BF data management, the analyses of time delay and correlation, the prediction of BF key variables, the evaluation of BF status, and the multi-objective intelligent optimization of BF operations. Solutions and suggestions were offered for the problems in the current progress, and some outlooks for future prospects and technological breakthroughs were added. To effectively improve the BF data quality, we comprehensively considered the data problems and the characteristics of algorithms and selected the data processing method scientifically. For analyzing important BF characteristics, the effect of the delay was eliminated to ensure an accurate logical relationship between the BF parameters and economic indicators. As for BF parameter prediction and BF status evaluation,a BF intelligence model that integrates data information and process mechanism was built to effectively achieve the accurate prediction of BF key indexes and the scientific evaluation of BF status. During the optimization of BF parameters, low risk, low cost, and high return were used as the optimization criteria, and while pursuing the optimization effect, the feasibility and site operation cost were considered comprehensively.This work will help increase the process operator’s overall awareness and understanding of intelligent BF technology. Additionally, combining big data technology with the process will improve the practicality of data models in actual production and promote the application of intelligent technology in BF ironmaking.展开更多
The karst mountainous area is an ecologically fragile region with prominent humanland contradictions.The resource-environment carrying capacity(RECC)of this region needs to be further clarified.The development of remo...The karst mountainous area is an ecologically fragile region with prominent humanland contradictions.The resource-environment carrying capacity(RECC)of this region needs to be further clarified.The development of remote sensing(RS)and geographic information system(GIS)provides data sources and processing platform for RECC monitoring.This study analyzed and established the evaluation index system of RECC by considering particularity in the karst mountainous area of Southwest China;processed multisource RS data(Sentinel-2,Aster-DEM and Landsat-8)to extract the spatial distributions of nine key indexes by GIS techniques(information classification,overlay analysis and raster calculation);proposed the methods of index integration and fuzzy comprehensive evaluation of the RECC by GIS;and took a typical area,Guangnan County in Yunnan Province of China,as an experimental area to explore the effectiveness of the indexes and methods.The results showed that:(1)The important indexes affecting the RECC of karst mountainous area are water resources,tourism resources,position resources,geographical environment and soil erosion environment.(2)Data on cultivated land,construction land,minerals,transportation,water conservancy,ecosystem services,topography,soil erosion and rocky desertification can be obtained from RS data.GIS techniques integrate the information into the RECC results.The data extraction and processing methods are feasible on evaluating RECC.(3)The RECC of Guangnan County was in the mid-carrying level in 2018.The midcarrying and low-carrying levels were the main types,accounting for more than 80.00%of the total study area.The areas with high carrying capacity were mainly distributed in the northern regions of the northwest-southeast line of the county,and other areas have a low carrying capacity comparatively.The coordination between regional resource-environment status and socioeconomic development is the key to improve RECC.This study explores the evaluation index system of RECC in karst mountainous area and the application of multisource RS data and GIS techniques in the comprehensive evaluation.The methods can be applied in related fields to provide suggestions for data/information extraction and integration,and sustainable development.展开更多
Cloud storage is one of the main application of the cloud computing.With the data services in the cloud,users is able to outsource their data to the cloud,access and share their outsourced data from the cloud server a...Cloud storage is one of the main application of the cloud computing.With the data services in the cloud,users is able to outsource their data to the cloud,access and share their outsourced data from the cloud server anywhere and anytime.However,this new paradigm of data outsourcing services also introduces new security challenges,among which is how to ensure the integrity of the outsourced data.Although the cloud storage providers commit a reliable and secure environment to users,the integrity of data can still be damaged owing to the carelessness of humans and failures of hardwares/softwares or the attacks from external adversaries.Therefore,it is of great importance for users to audit the integrity of their data outsourced to the cloud.In this paper,we first design an auditing framework for cloud storage and proposed an algebraic signature based remote data possession checking protocol,which allows a third-party to auditing the integrity of the outsourced data on behalf of the users and supports unlimited number of verifications.Then we extends our auditing protocol to support data dynamic operations,including data update,data insertion and data deletion.The analysis and experiment results demonstrate that our proposed schemes are secure and efficient.展开更多
There are two key issues in distributed intrusion detection system,that is,maintaining load balance of system and protecting data integrity.To address these issues,this paper proposes a new distributed intrusion detec...There are two key issues in distributed intrusion detection system,that is,maintaining load balance of system and protecting data integrity.To address these issues,this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation.A data allocation strategy based on capacity and workload is introduced to achieve local load balance,and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster.Moreover,data integrity is protected by using session reassemble and session partitioning.The simulation results show that the new model enjoys favorable advantages such as good load balance,higher detection rate and detection efficiency.展开更多
With the rapid development of Web, there are more and more Web databases available for users to access. At the same time, job searchers often have difficulties in first finding the right sources and then querying over...With the rapid development of Web, there are more and more Web databases available for users to access. At the same time, job searchers often have difficulties in first finding the right sources and then querying over them, providing such an integrated job search system over Web databases has become a Web application in high demand. Based on such consideration, we build a deep Web data integration system that supports unified access for users to multiple job Web sites as a job meta-search engine. In this paper, the architecture of the system is given first, and the key components in the system are introduced.展开更多
Integration between file systems and multidatabase systems is a necessary approach to support data sharing from distributed and heterogeneous data sources. We first analyses problems about data integration between fil...Integration between file systems and multidatabase systems is a necessary approach to support data sharing from distributed and heterogeneous data sources. We first analyses problems about data integration between file systems and multidatabase systems. Then, A common data model named XIDM(XML\|based Integrating Dada Model), which is XML oriented, is presented. XIDM bases on a series of XML standards, especially XML Schema, and can well describe semistructured data. So XIDM is powerfully practicable and multipurpose.展开更多
A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improv...A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improved fairness and dynamic provable data possession scheme that supports public verification and batch auditing while preserves data privacy. The rb23Tree is utilized to facilitate data dynamics. Moreover, the fairness is considered to prevent a dishonest user from accusing the cloud service provider of manipulating the data. The scheme allows a third party auditor （TPA） to verify the data integrity without learning any information about the data content during the auditing process. Furthermore, our scheme also allows batch auditing, which greatly accelerates the auditing process when there are multiple auditing requests. Security analysis and extensive experimental evaluations show that our scheme is secure and efficient.展开更多
基金financial support of Natural Science Foundation of China(No.61971102,62132004)MOST Major Research and Development Project(No.2021YFB2900204)+1 种基金Sichuan Science and Technology Program(No.2022YFH0022)Key Research and Development Program of Zhejiang Province(No.2022C01093)。
文摘Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer(WET)and orthogonal-frequency-divisionmultiplexing(OFDM)signals for wireless data transfer(WDT).The outdated channel state information(CSI)in aging channels is employed by the transmitter to shape IDET waveforms.With the constraints of transmission power and WDT requirement,the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average directcurrent(DC)among a limited number of transmission frames with the existence of carrier-frequencyoffset(CFO).For the amplitude optimisation,the original non-convex problem can be transformed into a reversed geometric programming problem,then it can be effectively solved with existing tools.As for the phase optimisation,the artificial bee colony(ABC)algorithm is invoked in order to deal with the nonconvexity.Iteration between the amplitude optimisation and phase optimisation yields our joint design.Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI.
基金supported in part by the MOST Major Research and Development Project(Grant No.2021YFB2900204)the National Natural Science Foundation of China(NSFC)(Grant No.62201123,No.62132004,No.61971102)+3 种基金China Postdoctoral Science Foundation(Grant No.2022TQ0056)in part by the financial support of the Sichuan Science and Technology Program(Grant No.2022YFH0022)Sichuan Major R&D Project(Grant No.22QYCX0168)the Municipal Government of Quzhou(Grant No.2022D031)。
文摘Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.
基金supported in part by the Natural Science Foundation of China under Grants 62132004,62531008,and 62301122in part by Jiangsu Major Project on Fundamental Research under Grant BK20243059+3 种基金in part by Gusu Innovation Project under Grant ZXL2024360in part by the High-Tech District of Suzhou City under Grant RC2025001in part by Quzhou Government under Grants 2024D007,and 2023D005in part by the Xiaomi Young Scholar Award,in part by Nanjing University-China Mobile Communications Group Co.,Ltd.Joint Institute.
文摘In unmanned aerial vehicle(UAV)-based scenarios,sensing-aided integrated data and energy networking(IDEN)systems can significantly mitigate non-line-of-sight(NLoS)propagation,thereby enhancing sensing accuracy..However,the rapid channel variations induced by UAV mobility pose a challenge for traditional polar code construction methods,making it difficult to satisfy the stringent requirements of IDEN systems.To address this challenge,we propose a neural network(NN)-based sensing-aided IDEN framework.This system leverages sensing information to assist polar code construction while satisfying energy constraints.Furthermore,it incorporates neural networks to optimize the performance of polar codes in dynamic environments.Specifically,a sensing-aided binarized neural network(BNN)-based polar encoder is proposed for both lowlatency and high-reliability requirements,and a deep neural network(DNN)-based polar decoder is applied to match the encoder.Moreover,the corresponding training method is proposed,which focuses on the initialization design of the NNs.The simulation results show that the NN-based sensing-aided polar encoding scheme outperforms the conventional counterparts in terms of IDEN for both low-latency and high-reliability requirements.
文摘Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as sandstone and mudstone to undertake separate porositydepth compaction modeling. However, using just two lithologies is an oversimplification that cannot represent the compaction history. In such schemes, the precision of the compaction recovery is inadequate. To improve the precision of compaction recovery, a depth compaction model has been proposed that involves both porosity and clay content. A clastic lithological compaction unit classification method, based on clay content, has been designed to identify lithological boundaries and establish sets of compaction units. Also, on the basis of the clastic compaction unit classification, two methods of compaction recovery that integrate well and seismic data are employed to extrapolate well-based compaction information outward along seismic lines and recover the paleo-topography of the clastic strata in the region. The examples presented here show that a better understanding of paleo-geomorphology can be gained by applying the proposed compaction recovery technology.
基金financial support of National Natural Science Foundation of China(NSFC),No.U1705263 and 61971102GF Innovative Research Programthe Sichuan Science and Technology Program,No.2019YJ0194。
文摘In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.
基金partly funded by Natural Science Foundation of China(No.61971102 and 62132004)Sichuan Science and Technology Program(No.22QYCX0168)the Municipal Government of Quzhou(Grant No.2021D003)。
文摘Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data and energy through radio frequency signals.State-of-the-art researches mostly focus on theoretical aspects.By contrast,we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle(UAV).The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals,while collecting essential information from them.Then,the UAV uploads the information to remote base stations.Our system verifies the feasibility of the DEIN in practical applications.
基金supported by University of Electronic Science and Technology of China under Grant No.ZYGX2016KYQD103
文摘With the rapid development of the mobile internet and the massive deployment of the Internet of Things, mobile devices, including both the consumer electronics and the sensors, become hungrier for the energy than ever before. Conventional cable based charging largely restrict the movement of the mobile devices. Wireless charging hence emerges as an essential technique for enabling our ultimate goal of charging anytime and anywhere. By efficiently exploiting the legacy of the existing communication infrastructure, we propose a nov- el data and energy integrated network （DEIN） in order to re- alise the radio frequency （RF） based wireless charging with- out degrading the information transmission. In this treatise, we focus on the implementation of the DEIN in both the theoretical and practical aspects, concerning the transceiver architecture design and the rectifier circuit design. Furthermore, we also present a Wi-Fi based testbed for demonstrating the availability of the RF based wireless charging.
文摘This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.
基金Noncommunicable Chronic Diseases-National Science and Technology Major Project(2023ZD0503906)。
文摘Background Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment.However,limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress.In response,our research team has embarked on the development of a specialized clinical research database for cardiology,thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors.Methods The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021.It included comprehensive data on patients'basic information,medical history,non-invasive imaging studies,laboratory test results,as well as peri-procedural information related to interventional surgeries,extracted from the Hospital Information System.Additionally,an innovative artificial intelligence(AI)-powered interactive follow-up system had been developed,ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up,thereby achieving comprehensive data management throughout the entire care continuum for highrisk patients.Results This database integrates extensive cross-sectional and longitudinal patient data,with a focus on higher-risk acute coronary syndrome patients.It achieves the integration of structured and unstructured clinical data,while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency.It creates a comprehensive patient view,thereby improving diagnostic and follow-up quality,and provides high-quality data to support clinical research.Despite limitations in unstructured data standardization and biological sample integrity,the database's development is accompanied by ongoing optimization efforts.Conclusion The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research,which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes.It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.
基金Weaponry Equipment Pre-Research Foundation of PLA Equipment Ministry (No. 9140A06050409JB8102)Pre-Research Foundation of PLA University of Science and Technology (No. 2009JSJ11)
文摘To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.
基金supported in part by theHubei Engineering Research Center for BDS-CloudHigh-Precision Deformation Monitoring Open Funding(No.HBBDGJ202507Y)the National Natural Science Foundation of China(No.62377037).
文摘The large-scale deployment of Internet of Things(IoT)technology across various aspects of daily life has significantly propelled the intelligent development of society.Among them,the integration of IoT and named data networks(NDNs)reduces network complexity and provides practical directions for content-oriented network design.However,ensuring data integrity in NDN-IoT applications remains a challenging issue.Very recently,Wang et al.(Entropy,27(5),471(2025))designed a certificateless aggregate signature(CLAS)scheme for NDN-IoT environments.Wang et al.stated that their construction was provably secure under various types of security attacks.Using theoretical analysis methods,in this work,we reveal that their CLAS design fails to meet unforgeability,a core security requirement for CLAS schemes.In particular,we demonstrate that their scheme is vulnerable to amalicious public-key replacement attack,enabling an adversary to produce authentic signatures for arbitrary fraudulent messages.Therefore,Wang et al.’s design cannot achieve its goal.To address the issue,we systematically examine the root causes behind the vulnerability and propose a security-enhanced CLAS construction for NDN-IoT environments.We prove the security ofour improveddesignunder the standard security assumptionandalsoanalyze its practicalperformanceby comparing the computational and communication costs with several related works.The comparison results show the practicality of our design.
文摘This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
文摘Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.
基金financially supported by the General Program of the National Natural Science Foundation of China(No.52274326)the Fundamental Research Funds for the Central Universities (Nos.2125018 and 2225008)China Baowu Low Carbon Metallurgy Innovation Foundation(BWLCF202109)。
文摘Blast furnace (BF) ironmaking is the most typical “black box” process, and its complexity and uncertainty bring forth great challenges for furnace condition judgment and BF operation. Rich data resources for BF ironmaking are available, and the rapid development of data science and intelligent technology will provide an effective means to solve the uncertainty problem in the BF ironmaking process. This work focused on the application of artificial intelligence technology in BF ironmaking. The current intelligent BF ironmaking technology was summarized and analyzed from five aspects. These aspects include BF data management, the analyses of time delay and correlation, the prediction of BF key variables, the evaluation of BF status, and the multi-objective intelligent optimization of BF operations. Solutions and suggestions were offered for the problems in the current progress, and some outlooks for future prospects and technological breakthroughs were added. To effectively improve the BF data quality, we comprehensively considered the data problems and the characteristics of algorithms and selected the data processing method scientifically. For analyzing important BF characteristics, the effect of the delay was eliminated to ensure an accurate logical relationship between the BF parameters and economic indicators. As for BF parameter prediction and BF status evaluation,a BF intelligence model that integrates data information and process mechanism was built to effectively achieve the accurate prediction of BF key indexes and the scientific evaluation of BF status. During the optimization of BF parameters, low risk, low cost, and high return were used as the optimization criteria, and while pursuing the optimization effect, the feasibility and site operation cost were considered comprehensively.This work will help increase the process operator’s overall awareness and understanding of intelligent BF technology. Additionally, combining big data technology with the process will improve the practicality of data models in actual production and promote the application of intelligent technology in BF ironmaking.
基金the support given by the government and official in Guangnan Countyfunded by[National Natural Science Foundation of China]grant number[41361020,40961031]+3 种基金[Joint Fund of Yunnan Provincial Science and Technology Department and Yunnan University]grant number[2018FY001(-017)][Project of Innovative Talents Cultivation for Graduate Students of Yunnan University]grant number[C176230200][Project of Internationalization and Cultural Inheritance and Innovation of Yunnan University]grant number[C176250202][Science Research Fund of Yunnan Provincial Education Department in 2020:Postgraduate]grant number[2020Y0030]。
文摘The karst mountainous area is an ecologically fragile region with prominent humanland contradictions.The resource-environment carrying capacity(RECC)of this region needs to be further clarified.The development of remote sensing(RS)and geographic information system(GIS)provides data sources and processing platform for RECC monitoring.This study analyzed and established the evaluation index system of RECC by considering particularity in the karst mountainous area of Southwest China;processed multisource RS data(Sentinel-2,Aster-DEM and Landsat-8)to extract the spatial distributions of nine key indexes by GIS techniques(information classification,overlay analysis and raster calculation);proposed the methods of index integration and fuzzy comprehensive evaluation of the RECC by GIS;and took a typical area,Guangnan County in Yunnan Province of China,as an experimental area to explore the effectiveness of the indexes and methods.The results showed that:(1)The important indexes affecting the RECC of karst mountainous area are water resources,tourism resources,position resources,geographical environment and soil erosion environment.(2)Data on cultivated land,construction land,minerals,transportation,water conservancy,ecosystem services,topography,soil erosion and rocky desertification can be obtained from RS data.GIS techniques integrate the information into the RECC results.The data extraction and processing methods are feasible on evaluating RECC.(3)The RECC of Guangnan County was in the mid-carrying level in 2018.The midcarrying and low-carrying levels were the main types,accounting for more than 80.00%of the total study area.The areas with high carrying capacity were mainly distributed in the northern regions of the northwest-southeast line of the county,and other areas have a low carrying capacity comparatively.The coordination between regional resource-environment status and socioeconomic development is the key to improve RECC.This study explores the evaluation index system of RECC in karst mountainous area and the application of multisource RS data and GIS techniques in the comprehensive evaluation.The methods can be applied in related fields to provide suggestions for data/information extraction and integration,and sustainable development.
基金The authors would like to thank the reviewers for their detailed reviews and constructive comments, which have helped improve the quality of this paper. This work is supported by National Natural Science Foundation of China （No： 61379144）, Foundation of Science and Technology on Information Assurance Laboratory （No： KJ-13-002） and the Graduate Innovation Fund of the National University of Defense Technology.
文摘Cloud storage is one of the main application of the cloud computing.With the data services in the cloud,users is able to outsource their data to the cloud,access and share their outsourced data from the cloud server anywhere and anytime.However,this new paradigm of data outsourcing services also introduces new security challenges,among which is how to ensure the integrity of the outsourced data.Although the cloud storage providers commit a reliable and secure environment to users,the integrity of data can still be damaged owing to the carelessness of humans and failures of hardwares/softwares or the attacks from external adversaries.Therefore,it is of great importance for users to audit the integrity of their data outsourced to the cloud.In this paper,we first design an auditing framework for cloud storage and proposed an algebraic signature based remote data possession checking protocol,which allows a third-party to auditing the integrity of the outsourced data on behalf of the users and supports unlimited number of verifications.Then we extends our auditing protocol to support data dynamic operations,including data update,data insertion and data deletion.The analysis and experiment results demonstrate that our proposed schemes are secure and efficient.
文摘There are two key issues in distributed intrusion detection system,that is,maintaining load balance of system and protecting data integrity.To address these issues,this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation.A data allocation strategy based on capacity and workload is introduced to achieve local load balance,and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster.Moreover,data integrity is protected by using session reassemble and session partitioning.The simulation results show that the new model enjoys favorable advantages such as good load balance,higher detection rate and detection efficiency.
基金Supportted by the Natural Science Foundation ofChina (60573091 ,60273018) National Basic Research and Develop-ment Programof China (2003CB317000) the Key Project of Minis-try of Education of China (03044) .
文摘With the rapid development of Web, there are more and more Web databases available for users to access. At the same time, job searchers often have difficulties in first finding the right sources and then querying over them, providing such an integrated job search system over Web databases has become a Web application in high demand. Based on such consideration, we build a deep Web data integration system that supports unified access for users to multiple job Web sites as a job meta-search engine. In this paper, the architecture of the system is given first, and the key components in the system are introduced.
基金Supported by the Beforehand Research for National Defense of China(94J3. 4. 2. JW0 5 15 )
文摘Integration between file systems and multidatabase systems is a necessary approach to support data sharing from distributed and heterogeneous data sources. We first analyses problems about data integration between file systems and multidatabase systems. Then, A common data model named XIDM(XML\|based Integrating Dada Model), which is XML oriented, is presented. XIDM bases on a series of XML standards, especially XML Schema, and can well describe semistructured data. So XIDM is powerfully practicable and multipurpose.
基金Supported by the Doctoral Fund of the Ministry of Education priority Areas of Development Projects(20110141130006)the Natural Science Foundation of Hubei Province(ZRZ0041)
文摘A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improved fairness and dynamic provable data possession scheme that supports public verification and batch auditing while preserves data privacy. The rb23Tree is utilized to facilitate data dynamics. Moreover, the fairness is considered to prevent a dishonest user from accusing the cloud service provider of manipulating the data. The scheme allows a third party auditor （TPA） to verify the data integrity without learning any information about the data content during the auditing process. Furthermore, our scheme also allows batch auditing, which greatly accelerates the auditing process when there are multiple auditing requests. Security analysis and extensive experimental evaluations show that our scheme is secure and efficient.
