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Acquisition of robotic surgical skills does not require laparoscopic training: a randomized controlled trial.

Surgical endoscopy
BACKGROUND: Robotic surgery is a valid option for minimally invasive surgery in most surgical specialties. However, the need to master laparoscopy is questionable before starting specific training in robotic surgery. We compared the development of ba...

Stochastic Stability Analysis for Stochastic Coupled Oscillator Networks with Bidirectional Cross-Dispersal.

Computational intelligence and neuroscience
It is well known that stochastic coupled oscillator network (SCON) has been widely applied; however, there are few studies on SCON with bidirectional cross-dispersal (SCONBC). This paper intends to study stochastic stability for SCONBC. A new and sui...

Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent.

IEEE journal of biomedical and health informatics
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learning models has been highly effective in many aspects of e-health analy...

Layout Optimization of Urban Cultural Space Construction Based on Forward Three-Layer Neural Network Model.

Computational intelligence and neuroscience
The change of urban cultural space layout is a multi-variable, multi-objective, and restricted research process. The optimization of urban cultural space construction and layout is a multi-objective decision-making problem that needs to be solved urg...

A Novel Adaptive Linear Neuron Based on DNA Strand Displacement Reaction Network.

IEEE/ACM transactions on computational biology and bioinformatics
Analog DNA strand displacement circuits can be used to build artificial neural network due to the continuity of dynamic behavior. In this study, DNA implementations of novel catalysis, novel degradation and adjustment reaction modules are designed an...

Finite-frequency control for nonlinear semi-Markov jump systems with piecewise transition probabilities.

ISA transactions
Considering the frequency effect of external disturbances, this paper concerns the finite-frequency control problem for nonlinear semi-Markov jump systems (SMJSs) with piecewise transition probabilities (TPs) via the Takagi-Sugeno (T-S) fuzzy modelin...

Approximation properties of Gaussian-binary restricted Boltzmann machines and Gaussian-binary deep belief networks.

Neural networks : the official journal of the International Neural Network Society
Despite the successful use of Gaussian-binary restricted Boltzmann machines (GB-RBMs) and Gaussian-binary deep belief networks (GB-DBNs), little is known about their theoretical approximation capabilities to represent distributions of continuous rand...

A Path-Planning Approach Based on Potential and Dynamic Q-Learning for Mobile Robots in Unknown Environment.

Computational intelligence and neuroscience
The path-planning approach plays an important role in determining how long the mobile robots can travel. To solve the path-planning problem of mobile robots in an unknown environment, a potential and dynamic Q-learning (PDQL) approach is proposed, wh...

Reachable Set Estimation of Delayed Markovian Jump Neural Networks Based on an Improved Reciprocally Convex Inequality.

IEEE transactions on neural networks and learning systems
This brief investigates the reachable set estimation problem of the delayed Markovian jump neural networks (NNs) with bounded disturbances. First, an improved reciprocally convex inequality is proposed, which contains some existing ones as its specia...

Multi-Swarm Algorithm for Extreme Learning Machine Optimization.

Sensors (Basel, Switzerland)
There are many machine learning approaches available and commonly used today, however, the extreme learning machine is appraised as one of the fastest and, additionally, relatively efficient models. Its main benefit is that it is very fast, which mak...