A numerical model is developed for dynamic analysis of large-cylinder breakwaters embedded in soft soil. In the model, the large cylinder is taken as a rigid body divided into elements and the soft soil is replaced by...A numerical model is developed for dynamic analysis of large-cylinder breakwaters embedded in soft soil. In the model, the large cylinder is taken as a rigid body divided into elements and the soft soil is replaced by discrete 3D nonlinear spring-dashpot systems. The numerical model is used to simulate the dynamic response of a large-cylinder breakwater to breaking wave excitation. The effects of the dynamic stress-strain relationship models of the soil, the radius and embedded depth of the cylinder, the nonlinear behaviors of the soil, and the limit strength condition of the soil on the dynamic responses of the large-cylinder structure are investigated with an example given. It is indicated that the above-mentioned factors have significant effects on the dynamic responses of an embedded large cylinder breakwater under breaking wave excitation.展开更多
The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storag...The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.展开更多
Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to en...Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to enhance performance.Among them,resistive random access memory(RRAM)has gained significant attention due to its numerousadvantages over traditional memory devices,including high speed(<1 ns),high density(4 F^(2)·n^(-1)),high scalability(~nm),and low power consumption(~pJ).This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potentialapplications.It provides a brief introduction to the concepts and advantages of RRAM,discusses the key factors that impact its industrial manufacturing,and presents the commercial progress driven by cutting-edge nanotechnology,which has been pursued by manysemiconductor giants.Additionally,it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing,with a particular emphasis on its role in neuromorphic computing.Finally,the review discusses thecurrent challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.展开更多
This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.W...This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.展开更多
The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed wo...The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks.In this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT intrusions.Then,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value precisely.In addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the classifier.The effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other factors.Computational analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.展开更多
Embedded system design is the core course of the telecommunication major in engineering universities,which combines software and hardware through embedded development boards.Aiming at the problems existing in traditio...Embedded system design is the core course of the telecommunication major in engineering universities,which combines software and hardware through embedded development boards.Aiming at the problems existing in traditional teaching,this paper proposes curriculum teaching reform based on the outcome-based education(OBE)concept,including determining course objectives,reforming teaching modes and methods,and improving the curriculum assessment and evaluation system.After two semesters of practice,this method not only enhances students’learning initiative but also improves teaching quality.展开更多
Label-sensor is an essential component of the label printer which is becoming a most significant tool for the development of Internet of Things(IoT).However,some drawbacks of the traditional infrared label-sensor make...Label-sensor is an essential component of the label printer which is becoming a most significant tool for the development of Internet of Things(IoT).However,some drawbacks of the traditional infrared label-sensor make the printer fail to realize the high-speed recognition of labels as well as stable printing.Herein,we propose a selfpowered and highly sensitive tribo-label-sensor(TLS)for accurate label identification,positioning and counting by embedding triboelectric nanogenerator into the indispensable roller structure of a label printer.The sensing mechanism,device parameters and deep comparison with infrared sensor are systematically studied both in theory and experiment.As the results,TLS delivers 6 times higher signal magnitude than traditional one.Moreover,TLS is immune to label jitter and temperature variation during fast printing and can also be used for transparent label directly and shows long-term robustness.This work may provide an alternative toolkit with outstanding advantages to improve current label printer and further promote the development of IoT.展开更多
To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with...To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.展开更多
Cost and safety are important considerations when designing the thickness of a protective reinforced concrete shelter.The blast perforation limit(BPL)is the minimum concrete shelter thickness that resists perforation ...Cost and safety are important considerations when designing the thickness of a protective reinforced concrete shelter.The blast perforation limit(BPL)is the minimum concrete shelter thickness that resists perforation under blast loading.To investigate the influence of the depth of embedment(DOE)and length-to-diameter ratio(L/D)of an explosive charge on the BPL,the results of an explosion test using a slender explosive partially embedded in a reinforced concrete slab were used to validate a refined finite element model.This model was then applied to conduct more than 300 simulations with strictly controlled variables,obtaining the BPLs for various concrete slabs subjected to charge DOEs ranging from0 to∞and L/D values ranging from 0.89 to 6.87.The numerical results were compared with the experimental results from published literature,further verifying the reliability of the simulation.The findings indicate that for the same explosive charge mass and L/D,the greater the DOE,the larger the critical residual thickness(Rc,defined as the difference between the BPL and DOE)up to a certain constant value;for the same explosive charge mass and DOE,the greater the L/D,the smaller the Rc.Thus,corresponding DOE and shape coefficients were introduced to derive a new equation for the BPL,providing a theoretical approach to the design and safety assessment of protective structures.展开更多
In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With th...In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With the embedded printing method,complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity.However,the current sequential multi-material embedded printing method faces a major challenge,which is the inevitable trade-off between the printed structural integrity and printing precision.Here,we propose a simultaneous multi-material embedded printing method.With this method,we can easily print firmly attached and high-precision multilayer structures.With multiple individually controlled nozzles,different biomaterials can be precisely deposited into a single crevasse,minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure.We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally,and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium,on the 3D morphology of the printed filament.We demonstrate the printing of double-layer thin-walled structures,each layer less than 200μm,as well as intestine and liver models with 5%gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination.The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods.The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.展开更多
Taking ARM as the hardware platform, the embedded system is built from both hardware and software aspects with the application as the center. In the hardware design, build the hardware platform scheme, design the sche...Taking ARM as the hardware platform, the embedded system is built from both hardware and software aspects with the application as the center. In the hardware design, build the hardware platform scheme, design the schematic diagram as well as PCB, complete the hardware debugging, and ensure the system hardware platform function;in the software design, optimize the three-stage pipeline structure of ARM instruction system, design the instruction set, install the embedded system on the virtual machine, build the cross-toolchain, and set up the correct NFS network file system. Finish the design of the ARM-based embedded system platform, combined with the hardware requirements of the experimental platform, transplant the powerful Uboot as the Bootloader of the system, and further transplant the Linux-2.6. 32 kernel to the system start the operation normally, and finally, build the root file to finish the study of its portability.展开更多
Let M be a smooth manifold and S ⊆ M a properly embedded smooth submanifold. Suppose that we have a fibre metric on TM|<sub>s</sub> i.e. a positive definite real inner-product on T<sub>p</sub>M...Let M be a smooth manifold and S ⊆ M a properly embedded smooth submanifold. Suppose that we have a fibre metric on TM|<sub>s</sub> i.e. a positive definite real inner-product on T<sub>p</sub>M for all p ∈ S, which depends smoothly on p ∈ S. The purpose of this article is to figure out that the fibre metric on TM|s</sub> can always be extended to a Riemannian metric on TM from a special perspective.展开更多
At 12.8 MHz center frequency,the advanced miniaturized polymer-based planar high quality factor(Q)passive elements embedded bandpassfilter works in the L-band.Because most of the demands operate inside the spectrum,the...At 12.8 MHz center frequency,the advanced miniaturized polymer-based planar high quality factor(Q)passive elements embedded bandpassfilter works in the L-band.Because most of the demands operate inside the spectrum,the wideband or high-speed operation necessary to enhance must be acquired in microwave frequency ranges.The channel has a quiet,high-performance micro-filter with wideband rejection.Capacitors and inductors are used in the high quality factor(Q)passive components,and related networks are incorporated in thefilter.Embedded layers are concatenated using Three-Dimensional Integrated Circuit(3D-IC)integration,parasitics are removed,and interconnection losses are negotiated using de-embedding methods.A wireless application-based Liquid Crystalline Polymer(LCP)viewpoint is employed as a substrate material in this work.The polymer processes,their properties,and the incorporated high-Q Band Pass Filter Framework.The suggestedfilter model is computed and manufactured utilizing the L-band frequency spectrum,decreasing total physical length by 31%while increasing bandwidth by 45%.展开更多
Moso bamboos have attracted excessive attention as a renewable green building material to the concept of sustainable development.In this paper,the 20 bolted Moso bamboo connection specimens with embedded steel plates ...Moso bamboos have attracted excessive attention as a renewable green building material to the concept of sustainable development.In this paper,the 20 bolted Moso bamboo connection specimens with embedded steel plates and grouting materials were designed according to connection configurations with different bolt diameters and end distance of bolt holes,and their bearing capacities and failure modes were analyzed by static tension tests.According to the test results of all connectors,the failure modes of the specimens are divided into four categories,and the effects of bolt diameter and bolt hole end distance on the connection bearing capacity and failure mode are analyzed.The test results show that the deformation and failure process can be divided into four stages.The main influence factor of connector bearing capacity is bolt diameter.Connectors can be divided into four failure modes,and brittle failure can be avoided by adopting certain structural measures.Filling with grouting material can improve the bearing capacity of joints.Due to the large variability of bamboo,further experiments are needed.展开更多
A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete...A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality.展开更多
In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,t...In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.展开更多
Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is desi...Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.展开更多
文摘A numerical model is developed for dynamic analysis of large-cylinder breakwaters embedded in soft soil. In the model, the large cylinder is taken as a rigid body divided into elements and the soft soil is replaced by discrete 3D nonlinear spring-dashpot systems. The numerical model is used to simulate the dynamic response of a large-cylinder breakwater to breaking wave excitation. The effects of the dynamic stress-strain relationship models of the soil, the radius and embedded depth of the cylinder, the nonlinear behaviors of the soil, and the limit strength condition of the soil on the dynamic responses of the large-cylinder structure are investigated with an example given. It is indicated that the above-mentioned factors have significant effects on the dynamic responses of an embedded large cylinder breakwater under breaking wave excitation.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(2021R1A4A2000934).
文摘The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.
基金supported by the Key-Area Research and Development Program of Guangdong Province(Grant No.2021B0909060002)National Natural Science Foundation of China(Grant Nos.62204219,62204140)+1 种基金Major Program of Natural Science Foundation of Zhejiang Province(Grant No.LDT23F0401)Thanks to Professor Zhang Yishu from Zhejiang University,Professor Gao Xu from Soochow University,and Professor Zhong Shuai from Guangdong Institute of Intelligence Science and Technology for their support。
文摘Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to enhance performance.Among them,resistive random access memory(RRAM)has gained significant attention due to its numerousadvantages over traditional memory devices,including high speed(<1 ns),high density(4 F^(2)·n^(-1)),high scalability(~nm),and low power consumption(~pJ).This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potentialapplications.It provides a brief introduction to the concepts and advantages of RRAM,discusses the key factors that impact its industrial manufacturing,and presents the commercial progress driven by cutting-edge nanotechnology,which has been pursued by manysemiconductor giants.Additionally,it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing,with a particular emphasis on its role in neuromorphic computing.Finally,the review discusses thecurrent challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.
基金supported in part by Major Science and Technology Demonstration Project of Jiangsu Provincial Key R&D Program under Grant No.BE2023025in part by the National Natural Science Foundation of China under Grant No.62302238+2 种基金in part by the Natural Science Foundation of Jiangsu Province under Grant No.BK20220388in part by the Natural Science Research Project of Colleges and Universities in Jiangsu Province under Grant No.22KJB520004in part by the China Postdoctoral Science Foundation under Grant No.2022M711689.
文摘This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.
文摘The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks.In this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT intrusions.Then,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value precisely.In addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the classifier.The effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other factors.Computational analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.
基金This paper is one of the phased achievements of the Education and Teaching Reform Project of Guangdong University of Petrochemical Engineering in 2022(71013413080)the Research and Practice Project of Teaching and Teaching Reform of University-Level Higher Vocational Education in 2023(JY202353).
文摘Embedded system design is the core course of the telecommunication major in engineering universities,which combines software and hardware through embedded development boards.Aiming at the problems existing in traditional teaching,this paper proposes curriculum teaching reform based on the outcome-based education(OBE)concept,including determining course objectives,reforming teaching modes and methods,and improving the curriculum assessment and evaluation system.After two semesters of practice,this method not only enhances students’learning initiative but also improves teaching quality.
基金supported by the National Key Research and Development Program(2021YFA1201602)the NSFC(62004017)+2 种基金the Fundamental Research Funds for the Central Universities(2021CDJQY-019)J.C.also want to acknowledge the supporting from the Natural Science Foundation of Chongqing(Grant No.cstc2021jcyjmsxmX0746)the Scientific Research Project of Chongqing Education Committee(Grant No.KJQN202100522).
文摘Label-sensor is an essential component of the label printer which is becoming a most significant tool for the development of Internet of Things(IoT).However,some drawbacks of the traditional infrared label-sensor make the printer fail to realize the high-speed recognition of labels as well as stable printing.Herein,we propose a selfpowered and highly sensitive tribo-label-sensor(TLS)for accurate label identification,positioning and counting by embedding triboelectric nanogenerator into the indispensable roller structure of a label printer.The sensing mechanism,device parameters and deep comparison with infrared sensor are systematically studied both in theory and experiment.As the results,TLS delivers 6 times higher signal magnitude than traditional one.Moreover,TLS is immune to label jitter and temperature variation during fast printing and can also be used for transparent label directly and shows long-term robustness.This work may provide an alternative toolkit with outstanding advantages to improve current label printer and further promote the development of IoT.
基金supported by the National Key R&D Program of China(2019YFC1510305)the National Natural Science Foundation of China(Grant Nos.41705119 and 41575131)+2 种基金Baojun CHEN also acknowledges support from the CMA Key Innovation Team(CMA2022ZD10)Qiujuan FENG was supported by the General Project of Natural Science Research in Shanxi Province(20210302123358)the Key Projects of Shanxi Meteorological Bureau(SXKZDDW20217104).
文摘To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.
基金supported by the National Natural Science Foundation of China(Grant No.51978166)。
文摘Cost and safety are important considerations when designing the thickness of a protective reinforced concrete shelter.The blast perforation limit(BPL)is the minimum concrete shelter thickness that resists perforation under blast loading.To investigate the influence of the depth of embedment(DOE)and length-to-diameter ratio(L/D)of an explosive charge on the BPL,the results of an explosion test using a slender explosive partially embedded in a reinforced concrete slab were used to validate a refined finite element model.This model was then applied to conduct more than 300 simulations with strictly controlled variables,obtaining the BPLs for various concrete slabs subjected to charge DOEs ranging from0 to∞and L/D values ranging from 0.89 to 6.87.The numerical results were compared with the experimental results from published literature,further verifying the reliability of the simulation.The findings indicate that for the same explosive charge mass and L/D,the greater the DOE,the larger the critical residual thickness(Rc,defined as the difference between the BPL and DOE)up to a certain constant value;for the same explosive charge mass and DOE,the greater the L/D,the smaller the Rc.Thus,corresponding DOE and shape coefficients were introduced to derive a new equation for the BPL,providing a theoretical approach to the design and safety assessment of protective structures.
基金the support by National Key Research and Development Program of China(2018YFA0703000)National Natural Science Foundation of China(Grant No.52105310)+1 种基金Natural Science Foundation of Zhejiang Province(Grant No.LDQ23E050001)the Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study(Grant No.SN-ZJU-SIAS-004)。
文摘In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With the embedded printing method,complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity.However,the current sequential multi-material embedded printing method faces a major challenge,which is the inevitable trade-off between the printed structural integrity and printing precision.Here,we propose a simultaneous multi-material embedded printing method.With this method,we can easily print firmly attached and high-precision multilayer structures.With multiple individually controlled nozzles,different biomaterials can be precisely deposited into a single crevasse,minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure.We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally,and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium,on the 3D morphology of the printed filament.We demonstrate the printing of double-layer thin-walled structures,each layer less than 200μm,as well as intestine and liver models with 5%gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination.The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods.The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.
文摘Taking ARM as the hardware platform, the embedded system is built from both hardware and software aspects with the application as the center. In the hardware design, build the hardware platform scheme, design the schematic diagram as well as PCB, complete the hardware debugging, and ensure the system hardware platform function;in the software design, optimize the three-stage pipeline structure of ARM instruction system, design the instruction set, install the embedded system on the virtual machine, build the cross-toolchain, and set up the correct NFS network file system. Finish the design of the ARM-based embedded system platform, combined with the hardware requirements of the experimental platform, transplant the powerful Uboot as the Bootloader of the system, and further transplant the Linux-2.6. 32 kernel to the system start the operation normally, and finally, build the root file to finish the study of its portability.
文摘Let M be a smooth manifold and S ⊆ M a properly embedded smooth submanifold. Suppose that we have a fibre metric on TM|<sub>s</sub> i.e. a positive definite real inner-product on T<sub>p</sub>M for all p ∈ S, which depends smoothly on p ∈ S. The purpose of this article is to figure out that the fibre metric on TM|s</sub> can always be extended to a Riemannian metric on TM from a special perspective.
文摘At 12.8 MHz center frequency,the advanced miniaturized polymer-based planar high quality factor(Q)passive elements embedded bandpassfilter works in the L-band.Because most of the demands operate inside the spectrum,the wideband or high-speed operation necessary to enhance must be acquired in microwave frequency ranges.The channel has a quiet,high-performance micro-filter with wideband rejection.Capacitors and inductors are used in the high quality factor(Q)passive components,and related networks are incorporated in thefilter.Embedded layers are concatenated using Three-Dimensional Integrated Circuit(3D-IC)integration,parasitics are removed,and interconnection losses are negotiated using de-embedding methods.A wireless application-based Liquid Crystalline Polymer(LCP)viewpoint is employed as a substrate material in this work.The polymer processes,their properties,and the incorporated high-Q Band Pass Filter Framework.The suggestedfilter model is computed and manufactured utilizing the L-band frequency spectrum,decreasing total physical length by 31%while increasing bandwidth by 45%.
基金support from 111 Project(Grant No.B18062)the Graduate Research and Innovation Foundation of Chongqing in China(Grant No.CYS20026)the National Key Research and Development Program of China(Grant No.2017YFC0703504).
文摘Moso bamboos have attracted excessive attention as a renewable green building material to the concept of sustainable development.In this paper,the 20 bolted Moso bamboo connection specimens with embedded steel plates and grouting materials were designed according to connection configurations with different bolt diameters and end distance of bolt holes,and their bearing capacities and failure modes were analyzed by static tension tests.According to the test results of all connectors,the failure modes of the specimens are divided into four categories,and the effects of bolt diameter and bolt hole end distance on the connection bearing capacity and failure mode are analyzed.The test results show that the deformation and failure process can be divided into four stages.The main influence factor of connector bearing capacity is bolt diameter.Connectors can be divided into four failure modes,and brittle failure can be avoided by adopting certain structural measures.Filling with grouting material can improve the bearing capacity of joints.Due to the large variability of bamboo,further experiments are needed.
基金supported by the Key Area R&D Program of Guangdong Province (Grant No.2022B0701180001)the National Natural Science Foundation of China (Grant No.61801127)+1 种基金the Science Technology Planning Project of Guangdong Province,China (Grant Nos.2019B010140002 and 2020B111110002)the Guangdong-Hong Kong-Macao Joint Innovation Field Project (Grant No.2021A0505080006)。
文摘A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality.
基金Supported by the National Natural Science Foundation of China(No.62203390)the Science and Technology Project of China TobaccoZhejiang Industrial Co.,Ltd(No.ZJZY2022E004)。
文摘In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.
基金Project supported by the National Natural Science Foundation of China(Grant No.62061014)the Natural Science Foundation of Liaoning province of China(Grant No.2020-MS-274).
文摘Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.