## What is/are Simple Algorithms?

Simple Algorithms - We study a class of simple algorithms for concurrently computing the connected components of an $n$-vertex, $m$-edge graph.^{[1]}In future, the fast and accurate computational capabilities with simple algorithms are expecting to play important role for the solution of multi-objective optimization tasks in hybrid power generation.

^{[2]}In the present paper, we use efficient and simple algorithms of the fractional power series and Adomain polynomial methods that provide effective tools for solving such linear and nonlinear fractional differential equations in the sense of conformable derivative.

^{[3]}Like Volume I of the Book of Nature being written in the language of mathematics, Volume II, addressing complexity, is composed of simple algorithms decoding reality.

^{[4]}The approach employed in this work is based on the use of attenuated total reflection Fourier transform infrared spectroscopy, and simple algorithms were developed from the spectra to estimate fiber maturity directly.

^{[5]}The minimization of the Joint-Forces is achieved by using simple algorithms as Bisection and Regula-Falsi Illinois.

^{[6]}The Parallel Research Kernels are a set of simple algorithms that correspond to popular classes of high-performance computing applications.

^{[7]}We focus on Certified Propagation Algorithm (CPA), one of the simple algorithms that does not rely on a cryptographic infrastructure and has a proven guarantee on resilience (number of node failures tolerated).

^{[8]}Most of the conventional studies on acoustic event detection adopt limited types of acoustic data and are based on simple algorithms, such as energy-based determination.

^{[9]}Simple algorithms of modeling the arc furnace and the compensating device are presented.

^{[10]}In the present paper the originally suggested control algorithm is equipped with two different and simple algorithms that were developed for noise reduction in the time domain that can be simply applied in a combined way.

^{[11]}This work addresses this lack of lower bounds and rigorously bounds the optimization time of simple algorithms using uniform crossover on the search space {0, 1}n from below via two novel techniques called decoupling and family graphs.

^{[12]}This paper reviews the machine learning techniques used in the literature, following their evolution from simple algorithms such as logistic regression to more advanced methods like support vector machines and modern deep neural networks.

^{[13]}The proposed method uses a phase shifted PWM to produce the injection and simple algorithms of field current response analyzes.

^{[14]}Simple algorithms to calculate the matrices for LMI representation of the proposed convex pole regions are provided in a concise way.

^{[15]}

## geometric intersection number

Given a curve*c*represented by a closed walk of length at most ℓ on a combinatorial surface of complexity

*n*, we describe simple algorithms to (1) compute the geometric intersection number of

*c*in

*O*(

*n*+ ℓ

^{2}) time, (2) construct a curve homotopic to

*c*that realizes this geometric intersection number in

*O*(

*n*+ℓ

^{4}) time, and (3) decide if the geometric intersection number of

*c*is zero, i.

^{[1]}

## Two Simple Algorithms

Two simple algorithms are proposed for implementing the proposed method, by first calculating the distribution of the real parts of all the characteristic roots, then the imaginary parts by using an iteration method.^{[1]}Functionality of our framework was tested on a field programmable gate array (FPGA) using two simple algorithms and compared against software implementations of the same algorithms.

^{[2]}To this end, we propose two simple algorithms for ranking a set of nodes connected by an unobserved set of edges.

^{[3]}The algorithm combined the advantages of both genetic algorithm (GA) in global search and tabu search (TS) in local search, and realized the performance improvement when compared with the above two simple algorithms.

^{[4]}In this work, we present two simple algorithms for the Modular Subset Sum problem running in near-linear time in $m$, both efficiently implementing Bellman's iteration over $\mathbb{Z}_m$.

^{[5]}Two simple algorithms are proposed to solve our nonlinear models and one simple algorithm is proposed to determine the parameters of fairness concern.

^{[6]}Two simple algorithms for faults detection are proposed as well.

^{[7]}

## Relatively Simple Algorithms

Implementing new RF applications has traditionally required significant time and expertise, even for relatively simple algorithms.^{[1]}Although it is mathematically possible to accurately compute the 3D shapes of these stimuli using relatively simple algorithms, the results indicated that human observers are unable to do so.

^{[2]}Our main contribution is to demonstrate that the Relaxed-Voronoi algorithm is applicable to restricted metrics, and actually leads to relatively simple algorithms and analyses.

^{[3]}

## Extremely Simple Algorithms

We demonstrate the potential of our results on three Principal Component Analysis (PCA) models resulting in extremely simple algorithms.^{[1]}Compared to conventional MMC capacitor voltage balancing strategies, YMM features extremely simple algorithms and good reachability to high-level MMCs while maintaining the original half-bridge sub-module topology.

^{[2]}

## Three Simple Algorithms

We show that CIS is NP-complete and present three simple algorithms for it: Deterministic, randomized with zero error and randomized with small one-sided error, with run time O(1.^{[1]}Our main contribution are three simple algorithms which come with provable guarantees and provide interesting resilience-load tradeoffs, significantly outperforming any deterministic fast rerouting algorithm with high probability.

^{[2]}

## Propose Simple Algorithms

Moreover, we give different equivalent characterizations of such graphs and we propose simple algorithms to build these trees from the connections of stars.^{[1]}We propose simple algorithms for computing st-numberings and st-edge-numberings of graphs with running time O ( m ).

^{[2]}

## Present Simple Algorithms

Herein we present simple algorithms and their implementations to perform separation of the LTL with Since and Until, over discrete and complete linear orders, and translation from FOMLO formulas into equivalent temporal logic formulas.^{[1]}We then present simple algorithms to solve eventual consensus in static and dynamic systems.

^{[2]}

## Following Simple Algorithms

Following simple algorithms, the guidelines aim to assist adult and pediatric physicians in the better care of patients with AD.^{[1]}Moreover, while humans are able to exploit computer players following simple algorithms, they are also vulnerable to exploitation by more sophisticated ones.

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