With the diversification of space-based information network task requirements and the dramatic increase in demand, the efficient scheduling of various tasks in space-based information network becomes a new challenge. ...
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With the diversification of space-based information network task requirements and the dramatic increase in demand, the efficient scheduling of various tasks in space-based information network becomes a new challenge. To address the problems of a limited number of resources and resource heterogeneity in the space-based information network, we propose a bilateral pre-processing model for tasks and resources in the scheduling pre-processing stage. We use an improved fuzzy clustering method to cluster tasks and resources and design coding rules and matching methods to match similar categories to improve the clustering effect. We propose a space-based information network task scheduling strategy based on an ant colony simulated annealing algorithm for the problems of high latency of space-based information network communication and high resource dynamics. The strategy can efficiently complete the task and resource matching and improve the task scheduling performance. The experimental results show that our proposed task scheduling strategy has less task execution time and higher resource utilization than other algorithms under the same experimental conditions. It has significantly improved scheduling performance.
Knowledge tracing aims to track students’knowledge status over time to predict students’future performance *** a real environment,teachers expect knowledge tracing models to provide the interpretable result of knowl...
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Knowledge tracing aims to track students’knowledge status over time to predict students’future performance *** a real environment,teachers expect knowledge tracing models to provide the interpretable result of knowledge *** chain-based knowledge tracing(MCKT)models,such as Bayesian Knowledge Tracing,can track knowledge concept mastery probability over ***,as the number of tracked knowledge concepts increases,the time complexity of MCKT predicting student performance increases exponentially(also called explaining away problem).When the number of tracked knowledge concepts is large,we cannot utilize MCKT to track knowledge concept mastery probability over *** addition,the existing MCKT models only consider the relationship between students’knowledge status and problems when modeling students’responses but ignore the relationship between knowledge concepts in the same *** address these challenges,we propose an inTerpretable pRobAbilistiC gEnerative moDel(TRACED),which can track students’numerous knowledge concepts mastery probabilities over *** solve explain away problem,we design long and short-term memory(LSTM)-based networks to approximate the posterior distribution,predict students’future performance,and propose a heuristic algorithm to train LSTMs and probabilistic graphical model *** better model students’exercise responses,we proposed a logarithmic linear model with three interactive strategies,which models students’exercise responses by considering the relationship among students’knowledge status,knowledge concept,and *** conduct experiments with four real-world datasets in three knowledge-driven *** experimental results show that TRACED outperforms existing knowledge tracing methods in predicting students’future performance and can learn the relationship among students,knowledge concepts,and problems from students’exercise *** also conduct several case *** case studies show that
With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of ...
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With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of the electronic spectrum auction network environment,the security of spectrum auction can not be *** scholars focus on researching the security of the single-sided auctions,while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and *** begin to design the secure double spectrum auction mechanisms,in which two semi-honest agents are introduced to finish the spectrum auction *** these two agents may collude with each other or be bribed by buyers and sellers,which may create security risks,therefore,a secure double spectrum auction is proposed in this *** traditional secure double spectrum auctions,the spectrum auction server with Software Guard Extensions(SGX)component is used in this paper,which is an Ethereum blockchain platform that performs spectrum auctions.A secure double spectrum protocol is also designed,using SGX technology and cryptographic tools such as Paillier cryptosystem,stealth address technology and one-time ring signatures to well protect the private information of spectrum *** addition,the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification,and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum ***,security analysis and performance evaluation of our protocol are discussed.
With the development of information technology and cloud computing,data sharing has become an important part of scientific *** traditional data sharing,data is stored on a third-party storage platform,which causes the...
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With the development of information technology and cloud computing,data sharing has become an important part of scientific *** traditional data sharing,data is stored on a third-party storage platform,which causes the owner to lose control of the *** a result,there are issues of intentional data leakage and tampering by third parties,and the private information contained in the data may lead to more significant ***,data is frequently maintained on multiple storage platforms,posing significant hurdles in terms of enlisting multiple parties to engage in data sharing while maintaining *** this work,we propose a new architecture for applying blockchains to data sharing and achieve efficient and reliable data sharing among heterogeneous *** design a new data sharing transaction mechanism based on the system architecture to protect the security of the raw data and the processing *** also design and implement a hybrid concurrency control protocol to overcome issues caused by the large differences in blockchain performance in our system and to improve the success rate of data sharing *** took Ethereum and Hyperledger Fabric as examples to conduct crossblockchain data sharing *** results show that our system achieves data sharing across heterogeneous blockchains with reasonable performance and has high scalability.
Cognitive diagnosis is the judgment of the student’s cognitive ability, is a wide-spread concern in educational science. The cognitive diagnosis model (CDM) is an essential method to realize cognitive diagnosis measu...
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Cognitive diagnosis is the judgment of the student’s cognitive ability, is a wide-spread concern in educational science. The cognitive diagnosis model (CDM) is an essential method to realize cognitive diagnosis measurement. This paper presents new research on the cognitive diagnosis model and introduces four individual aspects of probability-based CDM and deep learning-based CDM. These four aspects are higher-order latent trait, polytomous responses, polytomous attributes, and multilevel latent traits. The paper also sorts on the contained ideas, model structures and respective characteristics, and provides direction for developing cognitive diagnosis in the future.
With the arrival of 5G,latency-sensitive applications are becoming increasingly *** Edge Computing(MEC)technology has the characteristics of high bandwidth,low latency and low energy consumption,and has attracted much...
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With the arrival of 5G,latency-sensitive applications are becoming increasingly *** Edge Computing(MEC)technology has the characteristics of high bandwidth,low latency and low energy consumption,and has attracted much attention among *** improve the Quality of Service(QoS),this study focuses on computation offloading in *** consider the QoS from the perspective of computational cost,dimensional disaster,user privacy and catastrophic forgetting of new *** QoS model is established based on the delay and energy consumption and is based on DDQN and a Federated Learning(FL)adaptive task offloading algorithm in *** proposed algorithm combines the QoS model and deep reinforcement learning algorithm to obtain an optimal offloading policy according to the local link and node state information in the channel coherence time to address the problem of time-varying transmission channels and reduce the computing energy consumption and task processing *** solve the problems of privacy and catastrophic forgetting,we use FL to make distributed use of multiple users’data to obtain the decision model,protect data privacy and improve the model *** the process of FL iteration,the communication delay of individual devices is too large,which affects the overall delay ***,we adopt a communication delay optimization algorithm based on the unary outlier detection mechanism to reduce the communication delay of *** simulation results indicate that compared with existing schemes,the proposed method significantly reduces the computation cost on a device and improves the QoS when handling complex tasks.
G115 martensitic steel is anticipated to be one of the preferred candidate materials in ultra-super critical(USC)power plants with steam temperatures above 650℃.Microstructure evolutions and mechanical properties of ...
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G115 martensitic steel is anticipated to be one of the preferred candidate materials in ultra-super critical(USC)power plants with steam temperatures above 650℃.Microstructure evolutions and mechanical properties of G115 martensitic steel after applying various heat treatment processes were *** results demonstrate that the main precipitate in G115 martensitic steel after applying various heat treatment processes is M23C6 phase with Cr *** time required for M23C6 phase precipitation decreases with increasing secondary normalizing temperature and the extension in holding time according to its precipitation-temperature-time(PTT)*** fraction of M23C6 phase increases with increasing secondary normalizing temperature and holding time,which strengthens the inhibitory effect of precipitates on dislocations recovery and laths ***,G115 martensitic steel can obtain the best mechanical properties after applying the highest secondary normalizing temperature and the longest holding *** the current work,the excellent strength of G115 martensitic steel mainly derives from precipitates strengthening and laths strengthening.
Equal channel angle pressing is recognized for its ability to refine alloy grains and alter grain orientation, thereby achieve better mechanical performance of the magnesium alloy. This study investigates the microstr...
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Equal channel angle pressing is recognized for its ability to refine alloy grains and alter grain orientation, thereby achieve better mechanical performance of the magnesium alloy. This study investigates the microstructures,dynamic recrystallization mechanism, texture development, and mechanical performance of GW94K(Mg–8.7Gd–4.18Y–0.42Zr wt. %) Mg alloy following ECAP-4 passes at 400°C and 3 mm/min. Results show that when high-temperature deformation is undertaken, twin formation is suppressed while dislocation slip is facilitated, increasing dislocation density during deformation. Following ECAP deformation, the sample displayed higher fracture elongation, TYS, and UTS than the as-solutioned GW94K alloy. In particular, the GW94K alloy performed well mechanically after ECAP-4 passes, with an ultimate TYS of 231 MPa, an UTS of 290 MPa, and an elongation of 14.8 %. DDRX and shear bands induce CDRX, both of which are important in plastic deformation. as well as in modifying microstructure and grain orientation during ECAP deformation.
This paper addresses the controllability measures of composite networks based on graph products, in which the graph product networks are either Kronecker product networks or Kronecker sum *** primary objective pursued...
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This paper addresses the controllability measures of composite networks based on graph products, in which the graph product networks are either Kronecker product networks or Kronecker sum *** primary objective pursued here is to reveal the controllability Gramian-based measure links between the graph product composite network and its subnetworks. First, the analytical expression of the average controllability for the Kronecker product network is derived by using the corresponding controllability measures of its subnetworks. An upper bound of volumetric control energy is further obtained for the Kronecker product network. Then, the upper bounds are derived for the controllability measures of the Kronecker sum network,which provide a valuable reference for designing controllable networks in practical applications. Finally, the controllability of the Kronecker product network is compared with that of the Kronecker sum network, and it is found that when the subnetworks satisfy certain conditions, the Kronecker product network has better average controllability than the Kronecker sum network.
Hydrazine oxidation reaction(Hz OR) plays a crucial role in direct hydrazine fuel cells and holds promise for replacing the kinetics-sluggish oxygen evolution reaction in splitting water. While Ni–Zn alloys exhibit...
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Hydrazine oxidation reaction(Hz OR) plays a crucial role in direct hydrazine fuel cells and holds promise for replacing the kinetics-sluggish oxygen evolution reaction in splitting water. While Ni–Zn alloys exhibit exceptional activity for Hz OR, their synthesis under mild conditions remains a challenge. Herein, a Ni–Zn nanosheet catalyst with Ni Zn inclusion was prepared on Ni foam by controllable chemical etching together with ethylene glycol reduction. X-ray diffraction and transmission electron microscopy confirmed the single-crystalline nature and the presence of intermetallic Ni Zn. The strong interaction between Ni and Zn O, along with defects, facilitated the formation of this intermetallic compound. The Ni–Zn/Ni foam exhibits remarkable catalytic activity(214.3m A cm-2at 0.1 V) and durability(87.8 % retention after 24 h) towards hydrazine electrooxidation, thanks to the combined benefits of intermetallic Ni Zn, mesoporous nanosheets, microscopic defects, single-crystalline characteristics, and a coherent Ni–Ni Zn interface. This study provides a new method for designing highly active Ni–Zn electrocatalysts for Hz OR.
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