Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice by Jie Zhou

“…For selecting the most relevant features, we utilized the Minimum Redundancy Maximum Relevance (mRMR) and Recursive Feature Elimination (RFE) algorithms. Following this, we developed and assessed Support Vector Machine (SVM) and Logistic Regression (LR) models, measuring their performance through various metrics such as accuracy, specificity, sensitivity, positive predictive value, calibration curves, the Hosmer–Lemeshow goodness-of-fit test, decision curve analysis (DCA), and Kaplan–Meier survival analysis. …”
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Optimal Power Generation from Bagasse in a Sugarcane Plant using PSO Algorithm Compared to SQP Algorithm by Mohammad Askari Khanabadi, Imaneh Dehghani, Shahrokh Shojaeian

“…Due to the high amounts of sugarcane residue or bagasse which was produced by sugarcane plants in Iran, this study was aimed to optimize power generation from bagasse biomass in sugarcane plants using Particle Swarm Optimization (PSO) algorithm by data obtained from several case studies which had been simulated with SQP (Sequential quadratic programming) algorithm. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

Subjects: “…Multi agent reinforcement learning algorithm…”
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Comparative study on RF-BP model prediction of mining water-conducting fracture zone height in Binchang Coal Mine by Yadong JI, Xuan LIU, Kaipeng ZHU, Chunhu ZHAO, Kai LI, Chenhan YUAN, Panpan LI, Pengzhen YAN

“…Back propagation neural network, genetic algorithm and particle swarm optimization were used to optimize BP neural network and random forest algorithm to carry out regression fitting for the interpolated data. …”
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Predicting specific wear rate of laser powder bed fusion AlSi10Mg parts at elevated temperatures using machine learning regression algorithm: Unveiling of microstructural morphology analysis by Vijaykumar S. Jatti, R. Murali Krishnan, A. Saiyathibrahim, V. Preethi, Suganya Priyadharshini G, Abhinav Kumar, Shubham Sharma, Saiful Islam, Dražan Kozak, Jasmina Lozanovic

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The Role of Immersive Experience in Anxiety Reduction: Evidence from Virtual Reality Sessions by Dominika Wilczyńska, Tamara Walczak-Kozłowska, David Alarcón, María José Arenilla, Jose Carlos Jaenes, Marcelina Hejła, Mariusz Lipowski, Joanna Nestorowicz, Henryk Olszewski

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Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography by Singanallur Venkatakrishnan, Obaidullah Rahman, Lynda Amichi, Jose D. Arregui-Mena, Haoran Yu, David A. Cullen, Amirkoushyar Ziabari

“…In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. …”
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Analysis of software methods for metal computed tomography artifact reduction: experimental research by A. V. Petraikin, Yu. A. Vasilev, Z. R. Artyukova, A. K. Smorchkova, D. S. Semenov, А. А. Baulin, A. A. Alikhanov, R. A. Erizhokov, O. V. Omelyanskaya

“…It was also shown that O‑MAR forms additional artifacts near the HJE.Conclusion. Metal artifact reduction algorithms do not distort the X‑ray density without an artifact source. …”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

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CO21 | Viscoelastic testing in inherited bleeding disorders: a cross-sectional comparison between viscoelastic coagulation monitoring (VCM) and rotational thromboelastometry (ROTE...

“…Results: VCM showed significant prolongation of clotting time (CT) and clot-formation time (CFT) and a significant reduction in maximum clot firmness (MCF) in both HA and VWD versus controls (ANOVA p <0.001). …”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

“…A detailed investigation was conducted to examine the effects of various parameters on kerf deviation. The metaheuristic algorithms (i.e., Giant Trevally Optimizer—GTO; and Zebra Optimization Algorithm—ZOA) were implemented to determine the optimum process parameters for producing the best performance measures. …”
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Low-Complexity Distortionless Techniques for Peak Power Reduction in OFDM Communication Systems by A. Ghassemi, T. A. Gulliver

“…The three most effective distortionless techniques for PAPR reduction are partial transmit sequence (PTS), selective mapping (SLM), and tone reservation (TR). …”
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Torque ripple reduction and increasing of torque per volume for hybrid electrical vehicle by A. Hosseinpour

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Gaining transparency in Uber’s algorithmic management by Jessica Pidoux, Sofia Kypraiou, Paul-Olivier Dehaye

“…Nevertheless, this dependence and the resulting economic losses and gains are passed on to drivers individually as “algorithmic predictability risk”. Indeed, drivers’ data are controlled by Uber to make automated predictions of supply and demand for the benefit of the platform exclusively.…”
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Computational complexity, algorithmic scope, and evolution by Leonhard Sidl, Maximilian Faissner, Manuel Uhlir, Cristian A Velandia-Huerto, Maria Waldl, Hua-Ting Yao, Ivo L Hofacker, Peter F Stadler

“…We use RNA secondary structure prediction as a simple surrogate for developmental programs to demonstrate that the salient features of the genotype–phenotype map remain intact even if ‘simpler’ algorithms are employed that correctly compute the structures only for small subsets of instances, albeit quantitative differences depending on the choice of alternative algorithms can be observed.…”
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Molecular Beacon Sequence Design Algorithm by W. Todd Monroe, Frederick R. Haselton

“…This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.…”
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Ideology Critique in the Age of Algorithmic Governance by Christian Filk

“…He combines rigorous analysis with transformative practices like algorithmic deconstruction and commons-based production, transcending conventional digital literacy approaches. …”
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An Antenna Array Sidelobe Level Reduction Approach through Invasive Weed Optimization by Geng Sun, Yanheng Liu, Han Li, Shuang Liang, Aimin Wang, Boyu Li

“…The results show that IWO has a better performance in terms of the accuracy, the convergence rate, and the stability compared with other algorithms for the SLL reductions. Moreover, the electromagnetic simulation results also show that IWO achieves the best performance for the beam pattern synthesis of the antenna arrays in practical conditions.…”
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Algorithm profiling for architectures with dataflow accelerators by Nenad Korolija, Veljko Milutinović, Borko Furht

“…As a result, it is not always obvious whether programming dataflow architectures for certain algorithms is worth the effort needed. Therefore, there is a need for a programmer to be able to predict the outcome of programming for dataflow architectures in terms of accelerating program execution and power savings. …”
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