Multipoint Iterative Methods for Finding All the Simple Zeros in an Interval by T. Lotfi, F. Soleymani, S. Sharifi, S. Shateyi, F. Khaksar Haghani

“…Again by applying Mathematica, we design a hybrid algorithm to capture all the simple real solutions of nonlinear equations in an interval. …”
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Importance Sampling and Feature Fusion Paradigm-Boosted Multi-Modal Convolutional Neural Networks: Deployment in Composite Curing Process Monitored by Electro-Mechanical Impedance by Xin Zhao, Zeyuan Gao, Meng Li, Zhibin Han, Jianjian Zhu

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Assessment of a simple methodology for the identification of inertial parameters of semi-trailers by Tommaso Vannuccini, Riccardo Bartolozzi, Francesco Bucchi, Francesco Frendo, Marco Gabiccini

“…Within this context, models, and algorithms controlling the automated drive need to identify the mass and other inertia parameters related to the actual vehicle condition, which may vary during a mission (due to the transported goods arrangement).In this paper, a simple methodology based on an identification algorithm for the inertial parameters of a semi-trailer is presented, as well as an assessment of its result quality. …”
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Methods of sampling repairs industry are outsourcing by A. V. Shimokhin

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A Simple Highlight Detection and Ｒecovery Methods for Single Grayscale Image by YIN Fang, CHEN Tian-tian, FU Zi-ru, YU Xiao-yang

“…Experimental results show that specular detection algorithm can better deal with the details of specular areas，find specular reflection area effectively in the single grayscale image and improve the repair rate specular areas of the image.…”
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Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

Subjects: “…dam deformation; complete ensemble empirical mode decomposition of adaptive noise; sample entropy reconstruction; k-means clustering algorithm; symbiotic search algorithm; variational mode decomposition…”
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A Simple Computational Approach to Predict Long-Term Hourly Electric Consumption by Eugene Pinsky, Etienne Meunier, Pierre Moreau, Tanvi Sharma

“…By exploiting the patterns in past data points, we could forecast long-term consumption with a computationally simple algorithm. Our approach is simple to interpret. …”
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Generation and processing of chaotic signals BASED ON simple functions in three dimensional space by V. A. Cherdyntsev, S. I. Polovenya, V. V. Dubrovsky

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Genetic clustering algorithm by M. A. Anfyorov

“…The algorithm is simple in its program implementation, which increases its usage reliability. …”
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An investigation into multi-objective decision-making in fresh cold chain supply chain networks within a dual distribution framework by Junyan Sun, Xing Li, Zefei Chen

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Performance Evaluation of a Simple Cluster-Based Aggregation and Routing in Wireless Sensor Networks by Sung-Hwa Hong, Jeong-Min Park, Joon-Min Gil

“…Because sensor nodes tend to have small and often irreplaceable batteries with limited power capacity, energy-efficient aggregation and routing are essential to achieve to a prolonged network lifetime. We propose a simple cluster-based data aggregation and routing algorithm (SCAR) that decreases the incurred overhead during the selection of cluster heads in wireless sensor networks. …”
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Evaluation of the effectiveness of parameters of the global description of words in simple automatic speech recognition systems by Cz. BASZTURA, W. MAJEWSKI, W. BARYCKI

“…In this paper, oriented at the so-called simple systems of speech recognition, the effectiveness of 6 sets of parameters in the global description of words in a given vocabulary was analysed. …”
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Adaptive sequential sampling for reliability estimation of binary functions by Miroslav Vořechovský

“…Two basic tasks are identified: (i) extension of the experimental design (ED) and (ii) estimation of probabilities. The new extension algorithm adds points for limit state evaluation to the ED by balancing the global exploration and local exploitation, and the estimation uses the pointwise information to build a simple surrogate and perform a novel optimized importance sampling. …”
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Regularized Least Square Regression with Unbounded and Dependent Sampling by Xiaorong Chu, Hongwei Sun

“…The standard bound assumption for output data is abandoned and the learning algorithm is implemented with samples drawn from dependent sampling process with a more general output data condition. …”
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A Comparative Study of Hybrid Adaptive Neuro-Fuzzy Inference Systems to Predict the Unconfined Compressive Strength of Rocks by Annabelle Graham, Emma Scott

Subjects: “…unconfined compressive strength of rock sample…”
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Quantum Algorithms for the Pathwise Lasso by Joao F. Doriguello, Debbie Lim, Chi Seng Pun, Patrick Rebentrost, Tushar Vaidya

“…Furthermore, we show that, when the observations are sampled from a Gaussian distribution, our quantum algorithm's complexity only depends polylogarithmically on $n$, exponentially better than the classical LARS algorithm, while keeping the quadratic improvement on $d$. …”
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A Technical Review of MPPT Algorithms for Solar Photovoltaic System: SWOT Analysis of MPPT Algorithms by Muhammad Mateen Afzal Awan

“…To accomplish this, multiple MPP Tracking (MPPT) algorithms have been proposed, which can be portioned into two: 1) Conventional algorithms, have the strengths of a simple structure, fewer computations, and low memory requirement, and cheap implementation. …”
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Sort & Slice: a simple and superior alternative to hash-based folding for extended-connectivity fingerprints by Markus Dablander, Thierry Hanser, Renaud Lambiotte, Garrett M. Morris

“…In contrast, sets of detected ECFP substructures are by default transformed into bit vectors using only a simple hash-based folding procedure. We introduce a general mathematical framework for the vectorisation of structural fingerprints via a formal operation called substructure pooling that encompasses hash-based folding, algorithmic substructure selection, and a wide variety of other potential techniques. …”
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Accelerating RRT* convergence with novel nonuniform and uniform sampling approach by Sivasankar Ganesan, Mohanraj Thangamuthu, Balakrishnan Ramalingam, Madan Mohan Rayguru, Sethu Narayanan Tamilselvan

“…The proposed RRT*-NUS method is evaluated against six baseline algorithms: RRT*, Informed RRT*, RRT*-N (normal sampling RRT*), GS-RRT* (goal-oriented sampling RRT*), DR-RRT* (directional random sampling RRT*), and hybrid-RRT* in three different 384*384 2D simulation scenarios. …”
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Verification of the person’s dynamic signature on a limited number of samples by V. V. Starovoitov

“…It is constructed using 5<N<20 samples of genuine human signatures. The pattern forms a convex object in a multidimensional feature space. …”
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