An Active-Set Algorithm for Convex Quadratic Programming Subject to Box Constraints with Applications in Non-Linear Optimization and Machine Learning by Konstantinos Vogklis, Isaac E. Lagaris

“…The algorithm is particularly well suited for machine learning, scientific computing, and engineering applications that require solving box constraint QP subproblems efficiently. Key use cases include Support Vector Machines (SVMs), reinforcement learning, portfolio optimization, and trust-region methods in non-linear programming. …”
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Toward a linear-ramp QAOA protocol: evidence of a scaling advantage in solving some combinatorial optimization problems by J. A. Montañez-Barrera, Kristel Michielsen

“…While most prior work has focused on classically optimizing these parameters, we demonstrate that fixed linear ramp schedules, linear ramp QAOA (LR-QAOA), can efficiently approximate optimal solutions across diverse COPs. …”
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Parallel Gaussian Elimination Method by Muhammad Muhammad Ali

“…The aim of the project is to develop parallel approaches for Gaussian Elimination Methods that are used in linear programming  to solve linear module  systems.             …”
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A modified perturbation method for convective straight fins with temperature-dependent thermal conductivity by Sumio KATO, Shoichi MATSUDA

“…In this method, the nonlinear term is split into linear and nonlinear terms to obtain the perturbation solution. …”
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Remaining Useful Life Prediction Method for Bearings Based on Pruned Exact Linear Time State Segmentation and Time–Frequency Diagram by Xu Wei, Jingjing Fan, Huahua Wang, Lulu Cai

“…First, the PELT (Pruned Exact Linear Time) algorithm is used to segment the vibration signals over the full life cycle of the bearing, accurately identifying critical degradation states and optimizing the stage division of the degradation process. …”
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Machine Learning-Driven Prediction of Offshore Vessel Detention: The Role of Neural Networks in Port State Control by Zlatko Boko, Tatjana Stanivuk, Nenad Radanović, Ivica Skoko

“…The main objective of this research is to improve maritime safety and the efficiency of inspection procedures by applying techniques that can more accurately predict the probability of detention of the offshore vessels. …”
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Bidirectional reduced-order electrothermal modeling of power MOSFETs for electric vehicle thermal management applications by Chih-Chun Hsu, Yi-Hsuan Hsieh, Hsiao Chi Tang, Yu-Min Meng, Ming-Shi Huang, Po-Hsuan Tseng, Hai-Han Lu, Hua-Yi Hsu

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A Study of Some Properties of Fuzzy Laplace Transform with Their Applications in Solving the Second-Order Fuzzy Linear Partial Differential Equations by Elhassan Eljaoui, Said Melliani

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Improving Linearity and Symmetry of Synaptic Update Characteristics and Retentivity of Synaptic States of the Domain-Wall Device Through Addition of Edge Notches by Raman Hissariya, Debanjan Bhowmik

“…Compute-in-memory (CIM) crossbar arrays of non-volatile memory (NVM) synapse devices have been considered very attractive for fast and energy-efficient implementation of various neural network (NN) algorithms. …”
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A Linear Programming Approach for Battery Impairment Analysis and Optimization in Decentralized Power Systems for Agricultural Operations With Solar Energy Integration by M. Saivineeth, Venkateswarlu. B

“…This will let them operate more efficient, robust, and eco-friendly businesses.…”
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Control of an autonomous wind energy conversion system based on doubly fed induction generator supplying a non-linear load by M. L’Hadj Said, M. Ali Moussa, T. Bessaad

“…Simulation results carried out on MATLAB/Simulink show that this filter allows obtaining a quasi-sinusoidal network voltage and it also has the advantage of a simple structure, a good efficiency and a great performance. This proves the feasibility and efficiency of the proposed system for different loads (linear or non-linear). …”
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Estimation of overlapped Eye Fixation Related Potentials: The General Linear Model, a more flexible framework than the ADJAR algorithm by Emmanuelle Kristensen, Bertrand Rivet, Anne Guérin-Dugué

“…The results showed that the ADJAR algorithm was based on assumptions that were too restrictive for EFRP estimation. The General Linear Model appeared to be more robust and efficient. …”
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The Linear Diophantine Fuzzy Z-Numbers Set: Development and Application to Decision Making in Textile Engineering Using the Bonferroni Mean Operator by Muhammad Umar Mirza, Rukhshanda Anjum, Hong Min, Badr S. Alkahtani, Mohd Anjum

“…In this research, we introduce a novel approach to multi-attribute decision making by defining the Linear Diophantine Fuzzy Z-number set and generalizing the Bonferroni mean operator to this framework. …”
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Employment of Vehicle-to-Grid Technology to Decrease the Economic-Environmental Costs Equipped with a Mixed-Integer Non-Linear Programming Approach by Jinkui Li, Huahui Li

“…The proposed solution is developed through the mixed-integer non-linear programming (MINLP) method in the GAMS simulation environment. …”
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A joint reconstruction and model selection approach for large-scale linear inverse modeling (msHyBR v2) by M. Sabaté Landman, J. Chung, J. Jiang, S. M. Miller, A. K. Saibaba

“…In this work, we develop a one-step approach for linear inverse modeling, where model selection and the inverse model are performed in tandem. …”
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Hybrid decision support system disaster management: application of lattice ordered q-rung linear Diophantine fuzzy hypersoft sets by J. Vimala, A. N. Surya, Nasreen Kausar, Dragan Pamucar, Seifedine Kadry, Jungeun Kim

“…The discovery of the lattice-ordered q-rung linear Diophantine fuzzy hypersoft set is a significant extension of fuzzy set theory. …”
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Ensuring Clinical Readiness: Commissioning, Acceptance and Performance Testing of Closed Bore Linear Accelerator Compatible Surface Guided Radiotherapy System by Anand Jadhav, Ajinkya Gupte, Prasad Raj Dandekar, Sachin Rasal, Omkar Awate, Mayank Dhoundiyal

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A Novel Hyper-Heuristic Algorithm with Soft and Hard Constraints for Causal Discovery Using a Linear Structural Equation Model by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…However, in the face of insufficient data, the accuracy and efficiency of DAGs learning are greatly reduced, resulting in a false perception of causality. …”
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Prediction of ball mill power in iron ore concentration plants: A comparison between radial basis functions and linear regression by Javad Taghavi, Mahdi Gharabaghi

“…Findings indicate that the RBF model outperforms linear regression in terms of accuracy and precision, exhibiting a lower standard deviation (0.0782 MW for RBF compared to 0.1207 MW for linear regression) and a smaller average absolute error (0.0585 MW for RBF compared to 0.0899 MW for linear regression).. …”
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A simple triangular finite element model for analysing the linear static behaviour of thick sandwich plates with equivalent material properties by Hichem Belaid, Hassina Ziou, Mohammed Himeur

“…This study presents a simple triangular finite element model for analysing the linear static behaviour of thick sandwich plates. …”
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