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Towards artificial general intelligence (agi) in the internet of things (iot): Opportunities and challenges
Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and
execute tasks with human cognitive abilities, engenders significant anticipation and intrigue …
execute tasks with human cognitive abilities, engenders significant anticipation and intrigue …
[HTML][HTML] A review of modeling bioelectrochemical systems: engineering and statistical aspects
Bioelectrochemical systems (BES) are promising technologies to convert organic
compounds in wastewater to electrical energy through a series of complex physical …
compounds in wastewater to electrical energy through a series of complex physical …
Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective
Abstract In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing,
founded upon advanced communication, computation, and control infrastructure …
founded upon advanced communication, computation, and control infrastructure …
A weighted information-gain measure for ordinal classification trees
This paper proposes an ordinal decision-tree model, which applies a new weighted
information-gain ratio (WIGR) measure for selecting the classifying attributes in the tree. The …
information-gain ratio (WIGR) measure for selecting the classifying attributes in the tree. The …
Inn: An interpretable neural network for ai incubation in manufacturing
Both artificial intelligence (AI) and domain knowledge from human experts play an important
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …
[КНИГА][B] Industrial Statistics: A Computer-Based Approach with Python
This innovative textbook presents material for a course on industrial statistics that
incorporates Python as a pedagogical and practical resource. Drawing on many years of …
incorporates Python as a pedagogical and practical resource. Drawing on many years of …
Logistic regression for crystal growth process modeling through hierarchical nonnegative garrote-based variable selection
Single-crystal silicon ingots are produced from a complex crystal growth process. Such a
process is sensitive to subtle process condition changes, which may easily become failed …
process is sensitive to subtle process condition changes, which may easily become failed …
Ensemble active learning by contextual bandits for AI incubation in manufacturing
An Industrial Cyber-physical System (ICPS) provides a digital foundation for data-driven
decision-making by artificial intelligence (AI) models. However, the poor data quality (eg …
decision-making by artificial intelligence (AI) models. However, the poor data quality (eg …
Adaptive and nonlinear control of discharge pressure for variable displacement axial piston pumps
J Koivumäki, J Mattila - Journal of Dynamic Systems …, 2017 - asmedigitalcollection.asme.org
This paper proposes, for the first time without using any linearization or order reduction, an
adaptive and model-based discharge pressure control design for the variable displacement …
adaptive and model-based discharge pressure control design for the variable displacement …
Distributed data filtering and modeling for fog and networked manufacturing
Abstract Fog Manufacturing applies both Fog and Cloud Computing collaboratively in Smart
Manufacturing to create an interconnected network through sensing, actuation, and …
Manufacturing to create an interconnected network through sensing, actuation, and …