Supplier selection is an important business activity in order to realize the purchasing function in supply chain *** supplier selection process includes four stages,i.e.,bidding inviting,bidding,group decision-making,...
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Supplier selection is an important business activity in order to realize the purchasing function in supply chain *** supplier selection process includes four stages,i.e.,bidding inviting,bidding,group decision-making,and results disclosure,involving the participation of manufacturing service demanders(MSDs),manufacturing service suppliers(MSSs),and ***,all the participants have raised concerns about the increased transparency in supplier ***,this study proposes a transparent supplier selection method by considering the engagement of *** this method,the Bayesian best-worst method(Bayesian BWM)is used to aggregate decision-makers'preferences into the overall optimal weights of the alternative MSSs,and the MSS with the largest weight is considered the suitable MSS for ***,blockchain is introduced to record the decision-making process information about supplier selection through a customized smart contract,where MSSs act as supervisors to supervise the decision-making process through the distributed consensus mechanism rather than directly participate in the decision-making ***,a case study of supplier selection in purchasing vibration acceleration sensors is *** result shows that the proposed method can support MSDs in selecting suitable MSS from alternative MSSs by aggregating decision-makers'preferences,and blockchain can provide credible information about the supplier selection process for MSSs,MSDs,and *** this way,the transparency of supplier selection is enhanced.
Point cloud-based large scale place recognition is an important but challenging task for many applications such as Simultaneous Localization and Mapping (SLAM). Taking the task as a point cloud retrieval problem, prev...
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To utilize the limited acoustic spectrum while combating the harsh underwater propagation, we incorporate partial spectrum sharing into an underwater acoustic sensor network and aim to maximize the minimum data collec...
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A remaining useful life (RUL) prediction algorithm considering temporal uncertainty, individual variability uncertainty, and unmodeled dynamic uncertainty is proposed for hidden degradation process with unmeasurable d...
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Exploring the interaction between RGB and thermal infrared modalities is critical to the success of RGB-thermal salient object detection (RGB-T SOD). In order to explore the implicit relationship between the two modal...
Exploring the interaction between RGB and thermal infrared modalities is critical to the success of RGB-thermal salient object detection (RGB-T SOD). In order to explore the implicit relationship between the two modalities, this paper proposes a Cross-modal Attention and Reinforcement Network (CAR-Net), which fully realizes the beneficial expression and complementary fusion of the two modalities. Specifically, CAR-Net has a cross-modal attention module (CAM) that enables efficient interaction and key information extraction through joint attention. It also includes a feature strengthener module (FSM) for improved representation using channel rank and loop methods. A large number of experiments show that the proposed method achieves the best performance on three publicly available datasets.
Multifield coupling is frequently encountered and also an active area of research in geotechnical *** this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid i...
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Multifield coupling is frequently encountered and also an active area of research in geotechnical *** this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain *** this extended technique,an immersed moving boundary(IMB)scheme is used to couple the discrete element method(DEM)and lattice Boltzmann method(LBM),while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid *** resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal *** facilitate the understanding and implementation of this coupled model for non-isothermal problems,a complete list is given for the conversion of relevant physical variables to lattice ***,benchmark tests,including a single-particle sedimentation and a two-particle drafting-kissing-tumbling(DKT)simulation with heat transfer,are carried out to validate the accuracy of our coupled *** further investigate the role of heat transfer in particle-laden flows,two multiple-particle problems with heat transfer are *** examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.
Script Event Prediction (SEP) aims to forecast the next event in a sequence from a list of candidates. Traditional methods often use pre-trained language models to model event associations but struggle with semantic a...
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Current state-of-the-art image captioning models generate captions in a single language, requiring a combination of multiple language specific models to build a multilingual image captioning system. However, as the nu...
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Swarm intelligence has become a hot research field of artificial *** the importance of swarm intelli-gence for the future development of artificial intelligence,we discuss and analyze swarm intelligence from a broader...
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Swarm intelligence has become a hot research field of artificial *** the importance of swarm intelli-gence for the future development of artificial intelligence,we discuss and analyze swarm intelligence from a broader and deeper *** a broader sense,we are talking about not only bio-inspired swarm intelligence,but also human-machine hybrid swarm *** a deeper sense,we discuss the research using a three-layer hierarchy:in the first layer,we divide the research of swarm intelli-gence into bio-inspired swarm intelligence and human-machine hybrid swarm intelligence;in the second layer,the bio-inspired swarm intelligence is divided into single-population swarm intelligence and multi-population swarm intelligence;and in the third layer,we re-view single-population,multi-population and human-machine hybrid models from different ***-population swarm intel-ligence is inspired by biological *** further solve complex optimization problems,researchers have made preliminary explor-ations in multi-population swarm ***,it is difficult for bio-inspired swarm intelligence to realize dynamic cognitive in-telligent behavior that meets the needs of human *** have introduced human intelligence into computing systems and proposed human-machine hybrid swarm *** addition to single-population swarm intelligence,we thoroughly review multi-population and human-machine hybrid swarm intelligence in this *** also discuss the applications of swarm intelligence in optimization,big data analysis,unmanned systems and other ***,we discuss future research directions and key issues to be studied in swarm intelligence.
Transformer tracking always takes paired template and search images as encoder input and conduct feature extraction and target‐search feature correlation by self and/or cross attention operations,thus the model compl...
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Transformer tracking always takes paired template and search images as encoder input and conduct feature extraction and target‐search feature correlation by self and/or cross attention operations,thus the model complexity will grow quadratically with the number of input *** alleviate the burden of this tracking paradigm and facilitate practical deployment of Transformer‐based trackers,we propose a dual pooling transformer tracking framework,dubbed as DPT,which consists of three components:a simple yet efficient spatiotemporal attention model(SAM),a mutual correlation pooling Trans-former(MCPT)and a multiscale aggregation pooling Transformer(MAPT).SAM is designed to gracefully aggregates temporal dynamics and spatial appearance information of multi‐frame templates along space‐time *** aims to capture multi‐scale pooled and correlated contextual features,which is followed by MAPT that aggregates multi‐scale features into a unified feature representation for tracking *** tracker achieves AUC score of 69.5 on LaSOT and precision score of 82.8 on Track-ingNet while maintaining a shorter sequence length of attention tokens,fewer parameters and FLOPs compared to existing state‐of‐the‐art(SOTA)Transformer tracking *** experiments demonstrate that DPT tracker yields a strong real‐time tracking baseline with a good trade‐off between tracking performance and inference efficiency.
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