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A comprehensive study of the genes involved in maintaining pluripotency such as Oct4 in voles will make it possible to obtain new information about the species-specific features of their structure, expression, and regulation, and thereby enhancing optimization of the experiments on obtaining of vole ES cells.
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PROX reactors require careful temperature control systems, in order to enhance optimization and control of the unit.
Meanwhile, a differential evolution mechanism based on neighbourhood and gradient is developed to achieve exploration-exploitation balance and enhance optimization efficiency of the algorithm proposed.
The aim of the model is to investigate the process performance of the reactor in order to enhance optimization and control of the PROX unit.
This paper presents a unified approach to optimal pose trajectory planning for robot manipulators in Cartesian space through a genetic algorithm (GA) enhanced optimization of the pose ruled surface.
A GA enhanced optimization method is used to choose the parameters (coefficients) of space curves such that the pose ruled surface and its area and area change ratios are optimized for achieving good kinematics and dynamics performances.
The proposed DPSO is based on the novel principles for representation, initialization and position-updating of the particles, and brings several benefits for solving the DTCTP, such as an adequate representation of the discrete search space, and enhanced optimization capabilities due to improved quality of the initial swarm.
In this study, an effective method for reliability-based design optimization (RBDO) is proposed enhancing sequential optimization and reliability assessment (SORA) method by convex linearization.
Notwithstanding, determining the optimum selection of on-line signals is crucial to enhancing system optimization requiring a low computational load yet effective prediction of cutting process parameters.
To address this issue, an adaptive reference vector adjustment strategy is designed as a means of enhancing the optimization capabilities of MaOPs with irregular PFs by adjusting the distribution of reference vectors.
To reduce the search space and enhance the optimization efficiency, this paper presents a new constellation optimization strategy based on the ordinal optimization (OO) theory and expands the algorithm realization for constellation optimization including precise and crude models, ordered performance curves, selection rules and selected subsets.
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