When conducting corrosion fatigue tests on metal materials, it is found that the test results obtained or the process of manually sorting out these experimental data sometimes produce some abnormal data that are obvio...
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Driving scene topology reasoning aims to understand the objects present in the current road scene and model their topology relationships to provide guidance information for downstream tasks. Previous approaches fail t...
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Although deep learning excels in sentence-level relation extraction, document-level extraction poses challenges. To address this, we propose a neural network combining local and global entity representations, sourced ...
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Dynamic graphs are ubiquitous across disciplines where observations usually change over time. Regressions on dynamic graphs often contribute to diverse critical tasks, such as climate early-warning and traffic control...
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The elasticity under varying temperatures and pressures is particularly significant for understanding mechanical properties and structural phase transitions. Consequently, there is an increasing demand for tools capab...
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Existing Vehicular Ad-hoc Networks (VANETs), while enabling vehicles to communicate with each other, share data, and connect to external networks, also face a large number of data security challenges, such as data lea...
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Facial expression feature extraction suffers from high inter-subject variations caused by identity-related personal attributes. The extracted expression features are consistently entangled with other identity-related ...
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Data exploration is increasingly relevant to the average person in our data-driven world, as data is now often open source and available to the general public and other non-expert users via open data portals and other...
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Data exploration is increasingly relevant to the average person in our data-driven world, as data is now often open source and available to the general public and other non-expert users via open data portals and other similar data sources. This has introduced the need for data exploration tools, methods and techniques to engage non-expert users in data exploration, and thus a proliferation of new research in the field of Human Computer Interaction (HCI) that relates to engaging non-expert audiences with data. In particular data exploration that contains a data visualization component can be useful for making data understandable and engaging for non-expert audiences. Currently, the range of design practices most commonly used in the field of HCI to engage non-expert audiences in data exploration that includes a visualization component has yet to be formalized or given a comprehensive overview. This paper is a systematic mapping study (SMS) which aims to fill that gap by analyzing design trends engaging non-expert audiences in visualization driven data exploration via interactive systems, providing an overview of existing design practices and engagement methods, as well as set of three recommendations for how future designers can best engage non-expert audiences in visualization driven data exploration.
Aiming at the problems of insufficient utilization of information about elite particles in archive and instability of particle motion in the population in the multi-objective artificial physics optimization algorithm ...
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ISBN:
(数字)9798350380286
ISBN:
(纸本)9798350380293
Aiming at the problems of insufficient utilization of information about elite particles in archive and instability of particle motion in the population in the multi-objective artificial physics optimization algorithm (MOAPO) in solving multiobjective optimization problems, A multi-objective artificial physics optimization algorithm based on two-phase search (TPMOAPO) is proposed. To begin with, the algorithm improves the calculation of the mass of particles, so that the strength and weakness of the particles can be accurately transformed into the corresponding masses while improving the efficiency of particle mass calculation. Next, a two-phase search strategy is proposed, which makes the algorithm have strong exploration ability in the first phase, and the second phase gradually enhances the exploitation capability with iterations, which solves the problem of instability motion of particles in the search process. Finally, the simulated binary crossover (SBX) and polynomial-based mutation (PM) operators are adopted in the archive to further enhance the search capability of the algorithm. For verifying the performance of TP-MOAPO, 21 benchmark functions were selected to compare with the classical multi-objective particle swarm optimization algorithms: MOPSO, dMOPSO, SMPSO, MMOPSO, and NMPSO, and the experimental results show the superiority of TP-MOAPO in these functions.
Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constrain...
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Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependencyaware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub -task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience.
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