As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordin...
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As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordination of multiple robots in a multi-cluster tool,wafer production scheduling becomes rather *** a wafer is processed,due to high-temperature chemical reactions in a chamber,the robot should be controlled to take it out of the processing chamber at the right *** order to ensure the uniformity of integrated circuits on wafers,it is highly desirable to make the differences in wafer post-processing time among the individual tools in a multicluster tool as small as *** achieve this goal,for the first time,this work aims to find an optimal schedule for a dual-arm multi-cluster tool to regulate the wafer post-processing *** do so,we propose polynomial-time algorithms to find an optimal schedule,which can achieve the highest throughput,and minimize the total post-processing time of the processing *** propose a linear program model and another algorithm to balance the differences in the post-processing time between any pair of adjacent cluster *** industrial examples are given to illustrate the application and effectiveness of the proposed method.
Thermal Protection System(TPS) with thick tiles, low thermal conductivity, and a short re-entry stage stands as a critical element within reusable aircraft, whose reliability is related to the function and changes wit...
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Thermal Protection System(TPS) with thick tiles, low thermal conductivity, and a short re-entry stage stands as a critical element within reusable aircraft, whose reliability is related to the function and changes with their physical properties, external conditions, and degradation. Meanwhile, due to the limitation of testing resources, epistemic uncertainties stemming from the small samples are present in TPS reliability modeling. However, current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties, external conditions, degradation, and epistemic uncertainties. Therefore, under the framework of belief reliability theory, a TPS reliability model is constructed, which takes into account the physical principle, external conditions, performance degradation, and epistemic uncertainties. A reliability simulation algorithm is proposed to calculate TPS reliability. Through a case study and comparison analysis, the proposed method is validated as more effective than the existing method. Additionally,reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples, through which suggestions are provided for TPS functional design and improvement.
Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural net...
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Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.
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.
Challenged networks (CNs) contain resource-constrained nodes deployed in regions where human intervention is difficult. Opportunistic networks (OppNets) are CNs with no predefined source-to-destination paths. Due to t...
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If adversaries were to obtain quantum computers in the future, their massive computing power would likely break existing security schemes. Since security is a continuous process, more substantial security schemes must...
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The flow shop scheduling problem is important for the manufacturing *** flow shop scheduling can bring great benefits to the ***,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learni...
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The flow shop scheduling problem is important for the manufacturing *** flow shop scheduling can bring great benefits to the ***,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learning assisted *** work addresses a DHFSP with minimizing the maximum completion time(Makespan).First,a mathematical model is developed for the concerned ***,four Q-learning-assisted meta-heuristics,e.g.,genetic algorithm(GA),artificial bee colony algorithm(ABC),particle swarm optimization(PSO),and differential evolution(DE),are *** to the nature of DHFSP,six local search operations are designed for finding high-quality solutions in local *** of randomselection,Q-learning assists meta-heuristics in choosing the appropriate local search operations during ***,based on 60 cases,comprehensive numerical experiments are conducted to assess the effectiveness of the proposed *** experimental results and discussions prove that using Q-learning to select appropriate local search operations is more effective than the random *** verify the competitiveness of the Q-learning assistedmeta-heuristics,they are compared with the improved iterated greedy algorithm(IIG),which is also for solving *** Friedman test is executed on the results by five *** is concluded that the performance of four Q-learning-assisted meta-heuristics are better than IIG,and the Q-learning-assisted PSO shows the best competitiveness.
This work introduces a novel Custom Question Answering (CQA) model leveraging Adam optimized Bidirectional Encoder Representations from Transformers (BERT-AO). This model tackles the challenge of combining textual and...
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Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal *** of the existing research wo...
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Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal *** of the existing research works on Legal Judgment Prediction(LJP)use traditional optimization algorithms in deep learning techniques falling into local *** research article focuses on using the modified Pelican Optimization method which mimics the collective behavior of Pelicans in the exploration and exploitation phase during cooperative food ***,the selection of search agents within a boundary is done randomly,which increases the time required to achieve global *** address this,the proposed Chaotic Opposition Learning-based Pelican Optimization(COLPO)method incorporates the concept of Opposition-Based Learning combined with a chaotic cubic function,enabling deterministic selection of random numbers and reducing the number of iterations needed to reach global ***,the LJP approach in this work uses improved semantic similarity and entropy features to train a hybrid classifier combining Bi-GRU and Deep *** output scores are fused using improved score level fusion to boost prediction *** proposed COLPO method experiments with real-time Madras High Court criminal cases(Dataset 1)and the Supreme Court of India database(Dataset 2),and its performance is compared with nature-inspired algorithms such as Sparrow Search Algorithm(SSA),COOT,Spider Monkey Optimization(SMO),Pelican Optimization Algorithm(POA),as well as baseline classifier models and transformer neural *** results show that the proposed hybrid classifier with COLPO outperforms other cutting-edge LJP algorithms achieving 93.4%and 94.24%accuracy,respectively.
The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data *** approach allows efficient infrastructure to store and access big real-time data and smart IoE service...
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The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data *** approach allows efficient infrastructure to store and access big real-time data and smart IoE services from the *** IoE-based cloud computing services are located at remote locations without the control of the data *** data owners mostly depend on the untrusted Cloud Service Provider(CSP)and do not know the implemented security *** lack of knowledge about security capabilities and control over data raises several security *** Acid(DNA)computing is a biological concept that can improve the security of IoE big *** IoE big data security scheme consists of the Station-to-Station Key Agreement Protocol(StS KAP)and Feistel cipher *** paper proposed a DNA-based cryptographic scheme and access control model(DNACDS)to solve IoE big data security and access *** experimental results illustrated that DNACDS performs better than other DNA-based security *** theoretical security analysis of the DNACDS shows better resistance capabilities.
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