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Extreme learning machines (ELMs) have proven to be efficient and effective learning mechanisms for pattern classification and regression. However, ELMs are primarily applied to supervised learning problems. Only a few existing research papers have used ELMs to explore unlabeled data. In this paper, we extend ELMs for both semi-supervised and unsupervised(More)
The proposed security development lifecycle (SecDLC) model delivers a perpetual cycle of information security management and refinement. Using real-world examples, the authors show how SecDLC ensures the goals of preserving, monitoring, and improving security practices, policies, and standards in private and public sectors. The authors describe the four(More)
This paper presents an overview of the di!erent types of neural network models which are applicable when solving business problems. The history of neural networks in business is outlined, leading to a discussion of the current applications in business including data mining, as well as the current research directions. The role of neural networks as a modern(More)
Makespan minimisation in permutation flow shop scheduling is an OR topic that has been intensively addressed in the last 40 years. Since the problem is known to be NP-complete for more than two machines, most of the research effort has been devoted to the development of heuristic procedures in order to provide good approximate solutions to the problem.(More)