When construction was linear. Analysis of the energy sustainability of social housing in Spain (1939-1989) by Aurora Martínez-Corral, Domingo Cuéllar

“…However, until very recent times architecture has been "linear" if we understand this as the opposite of the aim of reuse: the initial purpose was disconnected from the final one. …”
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Broadband, High-Linearity Switches for Millimeter-Wave Mixers Using Scaled SOI CMOS by Cameron Hill, James F. Buckwalter

“…By using seriesstacked devices with optimized gate impedance and voltage swing, both high linearity and fast switching are possible. A theoretical analysis and design framework has been developed and verified through simulation and measurement through two broadband, high-linearity passive mixer designs, one optimized for linearity and the other for bandwidth, using a 45-nm SOI CMOS process. …”
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Linear Response of Rotating and Flattened Stellar Clusters: The Oblate Kuzmin–Kutuzov Stäckel Family by Kerwann Tep, Christophe Pichon, Michael S. Petersen

“…This paper investigates the linear response of a series of spheroidal stellar clusters, the Kuzmin–Kutuzov Stäackel family, which exhibit a continuous range of flattening and rotation, extending from an isochrone sphere to a Toomre disk. …”
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Numerical optimization by the PFEMCT-SIF method of the crack propagation of a linear elastic material by Mohammed Bentahar, Noureddine Mahmoudi, Youcef Moulai Arbi

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A Novel Method for Solving Multiobjective Linear Programming Problems with Triangular Neutrosophic Numbers by Qing Wang, Yi Huang, Shiming Kong, Xinqiang Ma, Youyuan Liu, S. K. Das, S. A. Edalatpanah

“…In the field of operation research, linear programming (LP) is the most utilized apparatus for genuine application in various scales. …”
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G-OPTIMAL DESIGN OF NON-LINEAR MODEL TO INCREASE PURITY LEVELS OF SILICON DIOXIDE by Nindya Wulandari, Erfiani Erfiani, Irzaman Irzaman, Utami Dyah Syafitri

“…The model used to increase silicon dioxide's purity is a non-linear model that follows the exponential decay distribution. …”
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Dataset of non-linear household loads for Validation of Active Power FiltersMendeley Data by Vrindarani Nuñez-Ramírez, Néstor F. Guerrero-Rodríguez, Rafael Omar Batista-Jorge, Robert Mercado-Ravelo, Francisco A. Ramírez-Rivera, Julio A. Ferreira, Rubén D. Ramos-Ciprian, Enrique Reyes-Archundia

“…This paper presents a dataset of non-linear household loads in Santo Domingo, Dominican Republic, obtained through a structured data collection and processing methodology. …”
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A Low Complexity Linear Precoding Method for Extremely Large-Scale MIMO Systems by Salah Berra, Abderrazak Benchabane, Sourav Chakraborty, Kazuki Maruta, Rui Dinis, Marko Beko

“…The XL-MIMO systems can achieve higher spectral efficiency, improve cell coverage, and provide significantly higher data rates than standard MIMO systems. …”
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A review of mixed-integer linear formulations for framework-based energy system models by Maximilian Hoffmann, Bruno U. Schyska, Julian Bartels, Tristan Pelser, Johannes Behrens, Manuel Wetzel, Hans Christian Gils, Chuen-Fung Tang, Marius Tillmanns, Jan Stock, André Xhonneux, Leander Kotzur, Aaron Praktiknjo, Thomas Vogt, Patrick Jochem, Jochen Linßen, Jann M. Weinand, Detlef Stolten

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Bayesian compositional generalized linear mixed models for disease prediction using microbiome data by Li Zhang, Xinyan Zhang, Justin M. Leach, A. K. M. F. Rahman, Carrie R. Howell, Nengjun Yi

“…The random effect term efficiently captures sample-related minor effects by incorporating sample similarities within its variance-covariance matrix. …”
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A Linear Mathematical Model of the Vocational Training Problem in a Company Using Neutrosophic Logic, Hyperfunctions, and SuperHyperFunction by Florentin Smarandache, Maissam Jdid, Takaaki Fujita

“…Operations research methods have the ability to express the concepts of efficiency and scarcity in a well-defined mathematical model for a given situation. …”
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Behavioral Expectations of Business School Students Concerning Extreme Climate Events: Regional Insights and Implications for Southeast Europe by Nikša Alfirević, Darko Rendulić, Sonja Mlaker Kač

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Mixed Balanced Truncation for Reducing the Complexity of Large-Scale Electrical and Electronic System Simulations by Huy-Du Dao, Thanh-Tung Nguyen, Ngoc-Kien Vu, Van-Ta Hoang, Hong-Quang Nguyen

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Large-Diameter Bulk Crystal Growth and Scintillation Characterization of Thallium-Based Ternary Halide Crystals for Detection and Imaging by Rastgo Hawrami, Elsa Ariesanti, Hamid Sabet

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A scalable machine learning strategy for resource allocation in database by Fady Nashat Manhary, Marghny H. Mohamed, Mamdouh Farouk

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Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges by Akvile Giedraityte, Sigitas Rimkevicius, Mantas Marciukaitis, Virginijus Radziukynas, Rimantas Bakas

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Forecasting and Feature Analysis of Ship Fuel Consumption by Explainable Machine Learning Approaches by Pham Nguyen Dang Khoa, Dinh Gia Huy, Nguyen Canh Lam, Dang Hai Quoc, Pham Hoang Thai, Nguyen Quyen Tat, Tran Minh Cong

“…Precision forecasts using machine learning (ML) could offer sophisticated solutions that increase the fuel efficiency and lower emissions. Indeed, five ML techniques, linear regression (LR), decision tree (DT), random forest (RF), XGBoost, and AdaBoost, were used to develop ship fuel consumption models in this study. …”
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PERFORMANCE ANALYSIS OF HUNGARIAN FOOD INDUSTRY ENTERPRISES USING THE DEA METHOD by Orsolya Tünde NAGY, Éva DARABOS, Bernadett Béresné MÁRTHA, Anita KISS

“…Output variables consist of total revenue and gross value added (GVA). The linear programming-based DEA model calculates a relative efficiency score for each decision-making unit, comparing firms with similar input-output structures. …”
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Dark soliton solutions of cubic-quartic non-linear Schrödinger equation via Sumudu HPM by Mamta Kapoor

“…Traditional numerical methods contain discretization and linearization errors, which limits their accuracy and efficiency. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…This systematic review investigates the integration of artificial intelligence (AI) in cost estimation within project management, focusing on its impact on accuracy and efficiency compared to traditional methods. This study synthesizes findings from 39 high-quality articles published between 2016 and 2024, evaluating various machine learning (ML), deep learning (DL), regression, and hybrid models in sectors such as construction, healthcare, manufacturing, and real estate. …”
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