As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mi...
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As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mine vulnerabilities and crash the *** recent years,considerable efforts have been dedicated by researchers and practitioners towards improving fuzzing,so there aremore and more methods and forms,whichmake it difficult to have a comprehensive understanding of the *** paper conducts a thorough survey of fuzzing,focusing on its general process,classification,common application scenarios,and some state-of-the-art techniques that have been introduced to improve its ***,this paper puts forward key research challenges and proposes possible future research directions that may provide new insights for researchers.
This study utilized laser processing to prepare a wood-based microfluidic chip incorporating two detection methods (microwave detection and colorimetric spectroscopy detection) for detecting lead ions in solutions. By...
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State-of-the-art recommender systems are increasingly focused on optimizing implementation efficiency, such as enabling on-device recommendations under memory constraints. Current methods commonly use lightweight embe...
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State-of-the-art recommender systems are increasingly focused on optimizing implementation efficiency, such as enabling on-device recommendations under memory constraints. Current methods commonly use lightweight embeddings for users and items or employ compact embeddings to enhance reusability and reduce memory usage. However, these approaches consider only the coarse-grained aspects of embeddings, overlooking subtle semantic nuances. This limitation results in an adversarial degradation of meta-embedding performance, impeding the system's ability to capture intricate relationships between users and items, leading to suboptimal recommendations. To address this, we propose a novel approach to efficiently learn meta-embeddings with varying grained and apply fine-grained meta-embeddings to strengthen the representation of their coarse-grained counterparts. Specifically, we introduce a recommender system based on a graph neural network, where each user and item is represented as a node. These nodes are directly connected to coarse-grained virtual nodes and indirectly linked to fine-grained virtual nodes, facilitating learning of multi-grained semantics. Fine-grained semantics are captured through sparse meta-embeddings, which dynamically balance embedding uniqueness and memory constraints. To ensure their sparseness, we rely on initialization methods such as sparse principal component analysis combined with a soft thresholding activation function. Moreover, we propose a weight-bridging update strategy that aligns coarse-grained meta-embedding with several fine-grained meta-embeddings based on the underlying semantic properties of users and items. Comprehensive experiments demonstrate that our method outperforms existing baselines. The code of our proposal is available at https://***/htyjers/C2F-MetaEmbed.
Permissioned blockchain is a promising methodology to build zero-trust storage foundation with trusted data storage and sharing for the zero-trust network. However, the inherent full-backup feature of the permissioned...
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The discriminative correlation filter (DCF) is commonly utilized in UAV tracking because of its high tracking accuracy and computing speed. However, in aerial tracking scenarios, challenges such as target occlusion an...
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The discriminative correlation filter (DCF) is commonly utilized in UAV tracking because of its high tracking accuracy and computing speed. However, in aerial tracking scenarios, challenges such as target occlusion and similar object interference are likely to cause the predicted object position to deviate from the correct motion trajectory. To alleviate this issue, this paper proposes a correlation filter algorithm based on trajectory correction and context interference suppression for real-time aerial tracking. First, a tracking quality evaluation metric is proposed to determine the confidence of the current tracking results. When the object is in a low confidence status, the state matrices of the object position and velocity are constructed, and the Kalman filter strategy is utilized to correct the tracking trajectory automatically. In addition, temporal context-response regularization is designed to fully exploit previous temporal information in order to suppress background interference. Extensive experimental results on four mainstream datasets demonstrate that the proposed algorithm has high tracking performance while achieving a real-time tracking speed of 32 fps on a single CPU. IEEE
Pseudorange observations are essential for global navigation system positioning, which are presented to be time-correlated due to unmodelled errors, limiting GNSS precise positioning applications. To mitigate, an algo...
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1 Introduction On-device deep learning(DL)on mobile and embedded IoT devices drives various applications[1]like robotics image recognition[2]and drone swarm classification[3].Efficient local data processing preserves ...
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1 Introduction On-device deep learning(DL)on mobile and embedded IoT devices drives various applications[1]like robotics image recognition[2]and drone swarm classification[3].Efficient local data processing preserves privacy,enhances responsiveness,and saves ***,current ondevice DL relies on predefined patterns,leading to accuracy and efficiency *** is difficult to provide feedback on data processing performance during the data acquisition stage,as processing typically occurs after data acquisition.
In a local search algorithm,one of its most important features is the definition of its neighborhood which is crucial to the algorithm's *** this paper,we present an analysis of neighborhood combination search for...
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In a local search algorithm,one of its most important features is the definition of its neighborhood which is crucial to the algorithm's *** this paper,we present an analysis of neighborhood combination search for solv-ing the single-machine scheduling problem with sequence-dependent setup time with the objective of minimizing total weighted tardiness(SMSWT).First,We propose a new neighborhood structure named Block Swap(B1)which can be con-sidered as an extension of the previously widely used Block Move(B2)neighborhood,and a fast incremental evaluation technique to enhance its evaluation ***,based on the Block Swap and Block Move neighborhoods,we present two kinds of neighborhood structures:neighborhood union(denoted by B1UB2)and token-ring search(denoted by B1→B2),both of which are combinations of B1 and ***,we incorporate the neighborhood union and token-ring search into two representative metaheuristic algorithms:the Iterated Local Search Algorithm(ILSnew)and the Hybrid Evolutionary Algorithm(HEA_(new))to investigate the performance of the neighborhood union and token-ring ***-sive experiments show the competitiveness of the token-ring search combination mechanism of the two *** on the 120 public benchmark instances,our HEA_(new)has a highly competitive performance in solution quality and computational time compared with both the exact algorithms and recent *** have also tested the HEA,new algorithm with the selected neighborhood combination search to deal with the 64 public benchmark instances of the single-machine scheduling problem with sequence-dependent setup *** is able to match the optimal or the best known results for all the 64 *** particular,the computational time for reaching the best well-known results for five chal-lenging instances is reduced by at least 61.25%.
This paper investigates the impact of flue gas desulfurization(FGD)gypsum's crystal modifier on the characteristics and microcosmic mechanism ofα-high strength *** results demonstrate that all three crystal modif...
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This paper investigates the impact of flue gas desulfurization(FGD)gypsum's crystal modifier on the characteristics and microcosmic mechanism ofα-high strength *** results demonstrate that all three crystal modifiers can convert FGD gypsum toα-high-strength *** acid(CA)has the most significant influence onα-high-strength gypsum,and the preparedα-high-strength gypsum is short columnar,with an aspect ratio in the range of 1-3,and has a faster setting time,a larger specific surface area,and a smaller standard consistency,higher compressive strength,greater surface hardness,and smaller crystal particle *** initial setting time of theα-high-strength gypsum manufactured with CA crystal modifier was decreased by 36%compared to the blank sample,the final setting time was lowered by 37.5%,and the water consumption of the standard consistency was reduced by 8%.The maximum strength is 32 MPa after 2 h,the absolute dry compressive strength is up to 38 MPa,and the surface hardness is improved by 24.43%.
Obtaining the sulfonamides(SAs)concentrations in the water body and sediment bulk was a prerequisite to reveal their transport and partitioning behavior in sediment-water environments and accurately assess their ecolo...
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Obtaining the sulfonamides(SAs)concentrations in the water body and sediment bulk was a prerequisite to reveal their transport and partitioning behavior in sediment-water environments and accurately assess their ecological *** the present study,the influences of multifactor interactions on the performance of o-DGTs with XAD-18 binding gels were analyzed by central combination experiments and response surfaces analysis,in which the target compounds were 9 *** results indicated that dissolved organic matter(DOM),pH,and suspended particulate matter(SS)had significant effects on the o-DGT sampling,whereas this o-DGT was independent of the ionic strength(IS).Concentning the composite influence of the four factors,the interaction between DOM and SS posed the most significant effect on all 9 SAs ***,an o-DGT and DIFSmodel was applied to explore the SAs migration between the water-sediments *** difference between desorption rate(k_(b))and adsorption rates(k_(f))values suggested that the kinetics of SAs was dominated by ***,the short-term sediment-water partitioning of SAs was clarified on the basis of distribution coefficient(K_(dl))for the labile SAs,among which the sulfadiazine(SDZ)had the largest labile *** ability of sediments to release SAs to the liquid phase as a sink was determined by response time(T_(c)).Among the 9 SAs,the longterm release of soseulfamethoxypyridazine(SMP)from the solid phase of sediments would have a potential risk to the aquatic environment,to which more attention should be paid in the future.
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