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Based on the introduced advantages and disadvantages of particular methodologies, an optimum generalized algorithm for precise and reliable evaluation of TNM parameters is proposed, utilizing both curve-fitting and alternative non-fitting techniques.
Specifically, we will develop refinement search semantics for planning, provide a generalized algorithm for refinement planning, and show that planners that search in the space of (partial) plans are specific instantiations of this algorithm.
In the paper entitled "Iterative estimation algorithms using conjugate function lower bound and minorization-maximization with applications in image denoising," G. Deng and W.-Y. Ng propose a generalized algorithm for wavelet domain image denoising by solving the MAP estimation problems under a linear Gaussian observation model.
Duan et al. [22] provide a generalized algorithm for the MLBSDC problem with an approximation ratio of Δ T. They transform the MLBSDC problem into the conventional maximum independent set problem and try to find a maximum set of non-interfering senders in each time slot.
This generalized algorithm for the MPP is implemented in the software package TARGETING, providing a user-friendly and efficient way to solve the MPP as well as some of its variants.
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The versatility of the generalized algorithm makes it suitable for application in the design of the software of modern measuring/control digital systems.
Perhaps that means trying to develop a generalized algorithm that can be reused to solve many problems, when the situation calls for a fast, basic solution to a single problem.
A generalized iterative algorithm for searching and locating particles in arbitrary meshes is presented.
The solution to this optimization problem defines the rate-distortion function R(D) which is defined as the lower bound for the bitrate required to code p ~ with the maximal average distortion D. A computational solution consists in using the generalized Lloyd algorithm for entropy-constrained vector quantization proposed by Chou et al. in[18].
CLARAty provides a framework for generalized algorithms applied to rover platforms irrespective of the implementation details.
Combining the techniques of the working set identification and generalized gradient projection, we present a new generalized gradient projection algorithm for minimax optimization problems with inequality constraints.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com