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Aspect-level implicit sentiment analysis model based on semantic wave and knowledge enhancement
Most implicit sentiment sentences in aspect level implicit sentiment analysis lack emotional words, but there are still potential emotional clues....
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Transforming future technology with quantum-based IoT
With the advent of internet-enabled and hybrid technologies, information is becoming increasingly accessible to the general public. Smartphones and...
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Cycle-accurate multi-FPGA platform for accelerated emulation of large on-chip networks
On-chip networks (NoCs) have become a popular choice for designing large multiprocessor architectures. Software-based emulation is often used to...
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An improved SMOTE based on center offset factor and synthesis strategy for imbalanced data classification
It is an enormous challenge for imbalanced data learning in the field of machine learning. To construct balanced datasets, oversampling techniques...
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MOTORS: multi-objective task offloading and resource scheduling algorithm for heterogeneous fog-cloud computing scenario
Along with the rising popularity of pay-as-you-go cloud services, many businesses and communities are deploying their business or scientific workflow...
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Capacity planning and scheduling for jobs with uncertainty in resource usage and duration
Organizations around the world schedule jobs (programs) regularly to perform various tasks dictated by their end users. With the major movement...
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DE2RA-RPL: detection and elimination of resource-related attacks in IoT RPL-based protocol
Resource Attacks in the Internet of Things (IoT) target to attack resource-related things. It affects the memory, processing, energy, and battery of...
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Enhancing differential evolution algorithm with a fitness-distance-based selection strategy
Since the introduction of differential evolution (DE) algorithms, they have achieved remarkable success in the field of evolutionary algorithms and...
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Adaptive multi-object tracking algorithm based on split trajectory
Multi-object tracking (MOT) has wide-ranging applications in unmanned vehicles, military reconnaissance, and video surveillance. However, real-world...
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Enhancing self-adaptation for efficient decision-making at run-time in streaming applications on multicores
Parallel computing is very important to accelerate the performance of computing applications. Moreover, parallel applications are expected to...
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Performance evaluation of complex systems based on hierarchical evidential reasoning rule considering disturbances
To prevent adverse consequences for performance deterioration, it is of great importance to evaluate performance promptly and implement precautions...
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Chebyshev approximation technique: analysis and applications
In many situations, exact solutions to complex problems may be challenging or impossible to obtain, making approximation techniques necessary for...
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Influence maximization under equilibrious groups in social networks
In a market, there are many groups caused by geographical location or other reasons, and consumers in groups have their own brand preferences for a...
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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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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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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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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...
