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RepEKShot: an evidential k-nearest neighbor classifier with repulsion loss for few-shot named entity recognition
Metric-based models have recently shown promising performance in the few-shot named entity recognition (NER) task. Many methods train their encoders...
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Sequential predictive maintenance and spare parts management with data mining methods: a case study in bus fleet
The sustainability of enterprises in an increasingly competitive environment is proportional to their ability to use the resources efficiently....
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A personalized recommendation model with multimodal preference-based graph attention network
Graph neural networks (GNNs) have indeed shown significant potential in the field of personalized recommendation. The core approach is to reorganize...
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Enhancing multidimensional scaling through a distributed algorithm
Classic multidimensional scaling (MDS) and scaling by majorizing a complex function (SMACOF) are well-known centralized algorithms that are used to...
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A comprehensive analysis of challenges and strategies for software release notes on GitHub
Release notes (RNs) refer to the technical documentation that offers users, developers, and other stakeholders comprehensive information about the...
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Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction
With the increasing complexity and scope of software systems, their dependability is crucial. The analysis of log data recorded during system...
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The h-faulty-block connectivity of alternating group graphs and split-star networks
The connectivity of a network is an important indicator for assessing its reliability and fault-tolerability. In this paper, we study a novel...
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Positioning and tracking with ODE-LSTM algorithm for emerging smart rail systems
In this paper, we propose a NLOS positioning and tracking method in order to be applied in the emerging smart rail systems. By analyzing MIMO scatter...
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Reliability analysis of complete cubic networks based on extra conditional fault
The reliability of multiprocessor systems is now a crucial concern in parallel computing, which can be characterized as connectivity and...
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OpenSCV: an open hierarchical taxonomy for smart contract vulnerabilities
Smart contracts are nowadays at the core of most blockchain systems. Like all computer programs, smart contracts are subject to the presence of...
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Engineering recommender systems for modelling languages: concept, tool and evaluation
Recommender systems (RSs) are ubiquitous in all sorts of online applications, in areas like shop**, media broadcasting, travel and tourism, among...
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A literature review and existing challenges on software logging practices
Software logging is the practice of recording different events and activities that occur within a software system, which are useful for different...
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Evaluating machine learning prediction techniques and their impact on proactive resource provisioning for cloud environments
Cloud computing has several benefits over traditional systems, such as scalability and high availability. However, these benefits, to be eventuated,...
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Blockchain based distributed trust management in IoT and IIoT: a survey
The Internet of Things (IoT) connects objects that sense, communicate, and interact to achieve shared goals, and its integration with manufacturing...
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MiniTomatoNet: a lightweight CNN for tomato leaf disease recognition on heterogeneous FPGA-SoC
Recognition of leaf diseases in agriculture is considered a significant aspect of ensuring food quantity, quality, and production. In general, crop...
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The dynamic analysis, FPGA implementation, and adaptive synchronization control application of a multi‐vortex chaotic system based on nonlinear functions
In this paper, a three-dimensional Jerk chaotic system with saddle-focus equilibrium point and special rotational characteristics of attractors is...
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GPU-accelerated relaxed graph pattern matching algorithms
Graph pattern matching is widely used in real-world applications, such as social network analysis. Since the traditional subgraph isomorphism is...
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Spatiotemporal information complementary modeling and group relationship reasoning for group activity recognition
Exploring spatial-temporal interactions among group members is crucial for group activity recognition. However, most existing approaches cannot...
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A learning-based data and task placement mechanism for IoT applications in fog computing: a context-aware approach
In recent years, with the technological advancement and rapid growth in the Internet of Things (IoT), many physical devices and real-time...
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An empirical study of challenges in machine learning asset management
Context:In machine learning (ML) applications, assets include not only the ML models themselves, but also the datasets, algorithms, and deployment...
