Results 251 to 260 of about 126,229 (309)

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

ZuraNet: a hybrid rule-based intrusion detection system with deep learning for securing SCADA-driven cyber-physical systems. [PDF]

Sci Rep
Sridevi K, Masood W, Tanveer S, Mirza OM, Sivakumar NR, Selvarajan S.   +5 more
europepmc   +1 more source

Posterior-Contact Soft-ZUPT for Foot-Mounted Inertial Navigation: Uncertainty-Aware Pseudo-Observation Modeling. [PDF]

Sensors (Basel)
Gao Y, Deng Z.
europepmc   +1 more source

An Interval Belief Rule Base Method with Attention Enhancement for Bearing Fault Diagnosis Under Variable Operating Conditions. [PDF]

Sensors (Basel)
Chen B, Li J, Li H.
europepmc   +1 more source

A novel nonlinear PID controller design with adaptive gains. [PDF]

Sci Rep
Ozgun AS, Selim E, Bayrak A, Tatlicioglu E.   +3 more
europepmc   +1 more source

Validation of a Rule-Based Automated Method for RPE Cell Detection Using Adaptive Optics Transscleral Flood Illumination. [PDF]

Transl Vis Sci Technol
Hiraoka M, Taniguchi M, Fura L, Kimura S, Mandai M, Takahashi M, Kurimoto Y, Maeda A.   +7 more
europepmc   +1 more source

An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM. [PDF]

IEEE Open J Signal Process
Lozenski L, McCann MT, Wohlberg B.
europepmc   +1 more source

Business rule driven service competition.

Yang, J., Orriëns, B., Papazoglou, M.
core  

Automatic Rule Derivation for Adaptive Architectures

Seventh Working IEEE/IFIP Conference on Software Architecture (WICSA 2008), 2008
This paper discusses on-going work in adaptive architectures concerning automatic adaptation rule derivation. Adaptation is rule-action based but deriving rules that meet the adaptation goals are tedious and error prone. We present an approach that uses model-driven derivation and training for automatically deriving adaptation rules, and exemplify this
Jesper Andersson, Morgan Ericsson, Welf Löwe   +2 more
openaire   +2 more sources

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A new adaptive learning rule

IEEE Transactions on Automatic Control, 1991
Summary: This paper presents a new method for nonlinear function identification and application to learning control. The control objective is to identify and compensate for a nonlinear disturbance function. The nonlinear disturbance function is presented as an integral of a predefined kernel function multiplied by an unknown influence function ...
William C. Messner, Roberto Horowitz, Wei-Wen Kao, Michael Boals   +3 more
openaire   +2 more sources