بدائل البحث:
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث)
algorithm both » algorithm blood (توسيع البحث), algorithm b (توسيع البحث), algorithm etc (توسيع البحث)
algorithm pca » algorithm a (توسيع البحث), algorithm cl (توسيع البحث), algorithm co (توسيع البحث)
pca function » gpcr function (توسيع البحث), a function (توسيع البحث), fc function (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث)
algorithm both » algorithm blood (توسيع البحث), algorithm b (توسيع البحث), algorithm etc (توسيع البحث)
algorithm pca » algorithm a (توسيع البحث), algorithm cl (توسيع البحث), algorithm co (توسيع البحث)
pca function » gpcr function (توسيع البحث), a function (توسيع البحث), fc function (توسيع البحث)
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161
Accelerated MPC Algorithms and Augmented System Design for Legged Robots
منشور في 2025"…The approach is powered by a newly introduced algorithm, named the modified Recursive Newton Euler Algorithm~(mRNEA), which is inspired by classical RNEA, and computes the dynamics information pre-multiplied with a fixed vector. …"
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162
Comparison of different methods.
منشور في 2024"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"
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163
The content of the speech.
منشور في 2025"…The algorithm enhances the traditional Stockwell transform (S-transform) by incorporating a low-pass filtering function and introducing two adjustable parameters. …"
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164
Time domain diagram of speech signal.
منشور في 2025"…The algorithm enhances the traditional Stockwell transform (S-transform) by incorporating a low-pass filtering function and introducing two adjustable parameters. …"
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165
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166
10-fold cross-validation evaluation of accuracy of animal tracking algorithms.
منشور في 2025"…<p>We labeled 1,000 frames per cohort under both day and night conditions (total 6,000 human labeled frames across three cohorts), and studied the accuracy of the animal tracking algorithm (SLEAP) as a function of the number of frames (<i>x</i>-axis) trained. …"
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167
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168
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169
LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery
منشور في 2025"…To address batch effects introduced during the merging process, the Empirical Bayes algorithm from the sva package (via the ComBat function) was applied. …"
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170
Subject characteristics.
منشور في 2025"…<div><p>Among the 32 items of the Motor Function Measure scale, 3 concern the assessment of hand function on a paper-based support. …"
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171
Research data.
منشور في 2025"…<div><p>Among the 32 items of the Motor Function Measure scale, 3 concern the assessment of hand function on a paper-based support. …"
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172
Objective function box diagram.
منشور في 2025"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
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173
Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection
منشور في 2025"…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…"
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174
Ethics of algorithmic invasiveness in beauty apps: an online experimental survey of public perspectives
منشور في 2025"…Results show that functionalities with high degree of algorithmic invasiveness, such as AI-generated attractiveness rankings, are viewed as significantly less socially acceptable than less invasive functionalities. …"
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175
Possible graph filter functions.
منشور في 2025"…<div><p>In this paper, we study a class of non-parametric regression models for predicting graph signals as a function of explanatory variables . Recently, Kernel Graph Regression (KGR) and Gaussian Processes over Graph (GPoG) have emerged as promising techniques for this task. …"
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176
The value functions of comparative policies.
منشور في 2025"…These expressions are determined using the copula function, and an algorithm is designed to construct the corresponding transition probability matrix. …"
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177
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178
Results of the replicated simulations.
منشور في 2024"…We propose a <i>K</i>-means-type algorithm in which each cluster is defined by a function-on-function regression model, which, inter alia, allows for multiple functional explanatory variables. …"
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179
S1 File -
منشور في 2024"…<div><p>In the proposed protection coordination scheme, the depreciation of the operation time of the entire relay in the primary and backup protection modes for all possible fault locations is considered as the objective function. The limitations of this problem include the equations for calculating the operation time of the relays in both forward and reverse directions, the limitation of the coordination time interval, the limitation of the setting parameters of the proposed relays, the restriction of the size of the reactance that limits the fault current, and the limitation of the standing time of distributed generation per small signal fault. …"
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180
Flowchart of SAOA.
منشور في 2024"…<div><p>In the proposed protection coordination scheme, the depreciation of the operation time of the entire relay in the primary and backup protection modes for all possible fault locations is considered as the objective function. The limitations of this problem include the equations for calculating the operation time of the relays in both forward and reverse directions, the limitation of the coordination time interval, the limitation of the setting parameters of the proposed relays, the restriction of the size of the reactance that limits the fault current, and the limitation of the standing time of distributed generation per small signal fault. …"