Wireless Sensor Networks (WSN) can be considered as a self-organizing system that might be a good alternative to wired systems due to their ease of deployment in distant places. The primary goal of this proj...
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Large-scale point cloud semantic segmentation is a challenging task in 3D computer vision. A key challenge is how to resolve ambiguities arising from locally high inter-class similarity. In this study, we introduce a ...
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Distinguishing identity-unrelated background information from discriminative identity information poses a challenge in unsupervised vehicle re-identification(Re-ID).Re-ID models suffer from varying degrees of backgrou...
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Distinguishing identity-unrelated background information from discriminative identity information poses a challenge in unsupervised vehicle re-identification(Re-ID).Re-ID models suffer from varying degrees of background interference caused by continuous scene *** recently proposed segment anything model(SAM)has demonstrated exceptional performance in zero-shot segmentation *** combination of SAM and vehicle Re-ID models can achieve efficient separation of vehicle identity and background *** paper proposes a method that combines SAM-driven mask autoencoder(MAE)pre-training and backgroundaware meta-learning for unsupervised vehicle *** method consists of three ***,the segmentation capacity of SAM is utilized to separate the vehicle identity region from the *** cannot be robustly employed in exceptional situations,such as those with ambiguity or ***,in vehicle Re-ID downstream tasks,a spatiallyconstrained vehicle background segmentation method is presented to obtain accurate background segmentation ***,SAM-driven MAE pre-training utilizes the aforementioned segmentation results to select patches belonging to the vehicle and to mask other patches,allowing MAE to learn identity-sensitive features in a self-supervised ***,we present a background-aware meta-learning method to fit varying degrees of background interference in different scenarios by combining different background region *** experiments demonstrate that the proposed method has state-of-the-art performance in reducing background interference variations.
High-dimensional parametric models and large-scale mathematical computations limit the efficiency of IoT devices. The emergence of serverless edge computing provides a solution where users can deploy models as serverl...
Community smells are sub-optimal developer community structures that hinder *** studies performed smell prediction and provided refactoring guidelines from a top-down aspect to help community ***,refactoring smells al...
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Community smells are sub-optimal developer community structures that hinder *** studies performed smell prediction and provided refactoring guidelines from a top-down aspect to help community ***,refactoring smells also requires bottom-up effort from every ***,supportive measures and guidelines for them are not available at a fine-grained *** recent work revealed developers'personalities and working states could influence community smells'emergence and variation,we build prediction models with experience,sentiment,and development process features of developers considering three smells including Organizational Silo,Lone Wolf,and Bottleneck,as well as two related classes including smelly developer and smelly *** predict the five classes in the individual granularity,and we also generate forecasts for the number of smelly developers in the community *** proposed models achieve F-measures ranging from 0.73 to 0.92 in individual-wide within-project,time-wise,and cross-project prediction,and mean R2 performance of 0.68 in community-wide Smelly Developer *** also exploit SHAP(SHapley Additive exPlanations)to assess feature importance to explain our *** conclusion,we suggest developers with heavy workload should foster more frequent communication in a straightforward and polite way to build healthier communities,and we recommend community shepherds to use the forecasting model for refactoring planning.
To meet the increasingly complex machining needs much better, this paper proposes a 2CPU/2UPC multi-mode mechanism that can achieve the two machining processes of surface drilling and milling. The screw theory is used...
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Pairing Li-free transition-metal-based cathodes（MX） with Li-metal anodes is an emerging trend to overcome the energy-density limitation of current rechargeable Li-ion ***,the development of practical Li-free MX cath...
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Pairing Li-free transition-metal-based cathodes（MX） with Li-metal anodes is an emerging trend to overcome the energy-density limitation of current rechargeable Li-ion ***,the development of practical Li-free MX cathodes is plagued by the existing notion of low voltage due to the long-term overlo oked voltage-tuning/phase-stability ***,we propose a p-type alloying strategy involving three voltage/phase-evolution stages,of which each of the varying trends are quantitated by two improved ligand-field descriptors to balance the above *** this,an intercalation-type 2H-V1.75Cr0.25S4cathode tuned from layered MX2family is successfully designed,which possesses an energy density of 554.3 Wh kg-1at the ele ctrode level accompanied by interfacial compatibility with sulfide solid-state ele *** propos al of this class of materials is expected to break free from scarce or high-cost transition-metal（*** and Ni） reliance in current commercial *** experiments further confirm the voltage and energy-density gains of *** strategy is not limited to specific Li-free cathodes and offers a solution to achieve high voltage and phase stability simultaneously.
Dynamic networks are data structures that represent the interactions among various entities in real-world systems, with their topology and node properties evolving over time. However, prevailing approaches typically d...
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Satisfiability Modulo Theories (SMT) has significant application in various domains. In this paper, we focus on quantifier-free Satisfiablity Modulo Real Arithmetic, referred to as SMT(RA), including both linear and n...
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作者：
Li, ZhilinMa, XutongHu, MengzeYan, Jun
State Key Lab. of Computer Science Ins. of Software CAS University of Chinese Academy of Sciences Beijing China
State Key Lab. of Computer Science Ins. of Software CAS Beijing China
State Key Lab. of Computer Science Ins. of Software CAS Tech. Center of Software Eng. Ins. of Software CAS University of Chinese Academy of Sciences Beijing China
Sequence Containers (SC) in the C++ Standard Template Library (STL), such as the vector, are widely used in large-scale projects for their maintainability and flexibility. However, accessing the elements in an SC is b...
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ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
Sequence Containers (SC) in the C++ Standard Template Library (STL), such as the vector, are widely used in large-scale projects for their maintainability and flexibility. However, accessing the elements in an SC is bug-prone, as such operations will not check their boundaries during compilation or execution, which can lead to memory errors, such as buffer overflow problems. And these bugs are difficult to detect with available static analyzers, since the size of SCs and the target of iterators cannot be precisely tracked without accurate analysis of the behavior of SCs and *** address this problem, we propose a combined model of SC sizes and iterator targets by tracking them simultaneously through a set of meta-operations extracted from corresponding method calls, and report improper operation usages according to three bug patterns. We implement the approach as a static analyzer, Scasa, on the top of the Clang Static Analyzer (CSA) framework, and evaluate its effectiveness and efficiency against CSA and other state-of-the-art static analyzers on a benchmark composed of 2,230 manually created code snippets and eight popular open-source C++ projects with a lot of SC usages. The experimental results reveal that Scasa effectively identifies nearly all inherent bugs within the manual code snippets and generates 125 reports for these projects (with a time loss of 5 - 85%) where 72 of them are marked as correct with a manual revision. And to further confirm these correct reports, we also select some important ones for developers. These results show that accessing elements of SCs is bug-prone, and cooperatively tracking SC sizes and iterator targets can accurately detect these bugs with acceptable overhead. Copyright held by the owner/author(s).
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