Multi-hop question answering (QA), which requires integrating information from multiple sources, poses significant challenges in natural language processing. Existing methods often struggle with effective retrieval ac...
详细信息
Marine communication technology is crucial in scientific research, national security, environmental monitoring and other fields, but facing challenges such as open channel and dynamic topology, secure transmission tec...
详细信息
Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group *** robustness of fuzzy reasoning determines the quality of reasoning algorithms to...
详细信息
Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group *** robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without ***,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy *** begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual ***,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are *** results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,***,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple *** corresponding solutions and their interval perturbations are *** is found that theα-UTI reasoning chain method is stable in the case of chain *** application examples in affective computing are given to verify the stability of theα-*** summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.
In-context learning for large language models (LLMs) is employed to design a novel hybrid optimization framework for multi-robot task allocation. Results show that this approach can improve existing approaches, such a...
详细信息
In crowded settings,mobile robots face challenges like target disappearance and occlusion,impacting tracking *** existing optimisations,tracking in complex environments remains *** address this issue,the authors propo...
详细信息
In crowded settings,mobile robots face challenges like target disappearance and occlusion,impacting tracking *** existing optimisations,tracking in complex environments remains *** address this issue,the authors propose a tailored visual navigation tracking system for crowded *** target disappearance,an autonomous navigation strategy based on target coordinates,utilising a path memory bank for intelligent search and re‐tracking is *** significantly enhances tracking *** handle target occlusion,the system relies on appearance features extracted by a target detection network and a feature memory bank for enhanced *** control technology ensures robust target tracking by fully utilising appearance information and motion characteristics,even in occluded *** testing on the OTB100 dataset validates the system's effectiveness in addressing target tracking challenges in diverse crowded environments,affirming algorithm robustness.
Multi-class classification can be solved by decomposing it into a set of binary classification problems according to some encoding rules,e.g.,one-vs-one,one-vs-rest,error-correcting output *** works solve these binary...
详细信息
Multi-class classification can be solved by decomposing it into a set of binary classification problems according to some encoding rules,e.g.,one-vs-one,one-vs-rest,error-correcting output *** works solve these binary classification problems in the original feature space,while it might be suboptimal as different binary classification problems correspond to different positive and negative *** this paper,we propose to learn label-specific features for each decomposed binary classification problem to consider the specific characteristics containing in its positive and negative ***,to generate the label-specific features,clustering analysis is respectively conducted on the positive and negative examples in each decomposed binary data set to discover their inherent information and then label-specific features for one example are obtained by measuring the similarity between it and all cluster *** clearly validate the effectiveness of learning label-specific features for decomposition-based multi-class classification.
The proposed system is designed to prevent the misidentification of fuel types during the refueling process, ensuring that only the correct fuel type is dispensed into vehicles. This helps to avert potentially severe ...
详细信息
Autonomous drone racing competitions serve as a testing ground for enhancing the perceptual, planning, and control aspects of micro unmanned aerial vehicles (MAVs). This study thoroughly outlines the strategy, methodo...
详细信息
Object Constraint Language(OCL)is one kind of lightweight formal specification,which is widely used for software verification and validation in NASA and Object Management Group *** OCL provides a simple expressive syn...
详细信息
Object Constraint Language(OCL)is one kind of lightweight formal specification,which is widely used for software verification and validation in NASA and Object Management Group *** OCL provides a simple expressive syntax,it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first-order logic,which is approximately half accurate at the first stage of devel-opment.A deep neural network named DeepOCL is proposed,which takes the unre-stricted natural language as inputs and automatically outputs the best-scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule-based generation *** demonstrate the validity of our proposed approach,ablation experiments were conducted on a new sentence-aligned dataset named *** experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation,scored 74.30 on BLEU,and greatly outperformed experienced developers by 35.19%.The proposed approach is the first deep learning approach to generate the OCL expression from the natural *** can be further developed as a CASE tool for the software industry.
Intermodal four-wave mixing (FWM) process in few-mode fibers (FMFs) could be utilized for entangled photon-pair generation. Previous studies mainly performed in single-mode fibers suffered from the significant Raman s...
详细信息
暂无评论