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A Review on Intelligence Dehazing and Color Restoration for Underwater Images

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020
Underwater image processing is an intelligence research field that has great potential to help developers better explore the underwater environment. Underwater image processing has been used in a wide variety of fields, such as underwater microscopic ...
Min Han, Zhiyu Lyu, Tie Qiu, Meiling Xu
semanticscholar   +1 more source

A cybernetic case study of viable computing systems: A framework for requisite variety via algorithmic hot-swapping

2010 IEEE 9th International Conference on Cyberntic Intelligent Systems, 2010
This paper presents a case study considering algorithmic hot swapping in the context of research surpassing Autonomic Computing, towards Viable Computing Systems. Cybernetic, mathematical and biological metaphors are allied to the human autonomic agent capability of the managerial cybernetics underscoring Beer's Viable System Model (VSM).
R. J. Thompson   +4 more
openaire   +1 more source

An Effective Cooperative Co-Evolutionary Algorithm for Distributed Flowshop Group Scheduling Problems

IEEE Transactions on Cybernetics, 2020
This article addresses a novel scheduling problem, a distributed flowshop group scheduling problem, which has important applications in modern manufacturing systems. The problem considers how to arrange a variety of jobs subject to group constraints at a
Q. Pan, Liang Gao, Ling Wang
semanticscholar   +1 more source

USK-COFFEE Dataset: A Multi-Class Green Arabica Coffee Bean Dataset for Deep Learning

2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom), 2022
Coffee is one of the plantation commodities that plays a big role in the world economy. According to the classification of coffee, each type of coffee has various shapes and textures.
Alifya Febriana   +3 more
semanticscholar   +1 more source

A Feature Space-Restricted Attention Attack on Medical Deep Learning Systems

IEEE Transactions on Cybernetics, 2022
Deep neural network has shown a powerful performance in the medical image analysis of a variety of diseases. However, a number of studies over the past few years have demonstrated that these deep learning systems can be vulnerable to well-designed ...
Zizhou Wang   +5 more
semanticscholar   +1 more source

An Iterative Greedy Algorithm With Q-Learning Mechanism for the Multiobjective Distributed No-Idle Permutation Flowshop Scheduling

IEEE Transactions on Systems, Man, and Cybernetics: Systems
The distributed no-idle permutation flowshop scheduling problem (DNIPFSP) has widely existed in various manufacturing systems. The makespan and total tardiness are optimized simultaneously considering the variety of scales of the problems with ...
Fuqing Zhao   +3 more
semanticscholar   +1 more source

Recognition of variety: considering learning with digital games as cybernetic systems

International Journal of Technology Enhanced Learning, 2011
In this paper, the author proposes cybernetics as a valid scientific and theoretical approach in considering the requisite variety of learners and learning through the application of digital games. The paper challenges anecdotal notions of perceived generational distinctions in respect of their pre-disposition to using games in learning.
openaire   +1 more source

A Community Structure Enhancement-Based Community Detection Algorithm for Complex Networks

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021
Community detection has been recognized as one of the most important tools to discover useful information hidden in complex networks which is usually hard to be obtained by simple observations.
Yansen Su   +4 more
semanticscholar   +1 more source

Failure Mode and Effects Analysis Method on the Air System of an Aircraft Turbofan Engine in Multi-Criteria Open Group Decision-Making Environment

Cybernetics and systems
Failure mode and effects analysis (FMEA), an proactive risk management approach, has been widely applied in a variety of industries, especially in aircraft industry.
Yongchuan Tang   +6 more
semanticscholar   +1 more source

Exploring Temporal Community Structure via Network Embedding

IEEE Transactions on Cybernetics, 2022
Temporal community detection is helpful to discover and analyze significant groups or clusters hidden in dynamic networks in the real world. A variety of methods, such as modularity optimization, spectral method, and statistical network model, has been ...
Tianpeng Li   +7 more
semanticscholar   +1 more source

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