Developing a Hybrid Morphological Analyzer for Low-Resource Languages by Musica Supriya, Dinesh Acharya Udupi, Ashalatha Nayak, Arjuna Srirangapatna Raghavendra

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MODELS AND ALGORITHMS FOR COMPUTER-AIDED DESIGN OF TECHNOLOGICAL PROCESS OF CASTINGS PRODUCTION, DIRECTED FOR SUPERCOMPUTER SKIF by A. N. Chichko, T. V. Matjushinets, L. V. Markov, S. G. Lihousov, V. F. Sobolev, O. I. Chichko

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Application of Adaptive Search Window-Based Nonlocal Total Variation Filter in Low-Dose Computed Tomography Images: A Phantom Study by Hajin Kim, Bo Kyung Cha, Kyuseok Kim, Youngjin Lee

“…Computed tomography (CT) imaging using low-dose radiation effectively reduces radiation exposure; however, it introduces noise amplification in the resulting image. …”
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Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result by Michael J. Morris, Sheila A. Habib, Maggie L. Do Valle, John E. Schneider

“…Consequently, there is a critical need for advanced diagnostics after an initial low-dose computed tomography (LDCT) scan. # Objectives This study evaluated the potential cost savings for US payers of CyPath® Lung, a novel diagnostic tool utilizing flow cytometry and machine learning for the early detection of lung cancer, in patients with positive LDCT scans with indeterminate pulmonary nodules (IPNs) ranging from 6 to 29 mm…”
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Low Cost Safety Data Storage and Processing Framework Under Cloud Environment by Limin Zhang

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Benchmark VERCORS 2022: blind prediction of time-dependent behavior of concrete containment building with low and high-fidelity models by Štěpán Krátký, Petr Havlásek

“…The previous paper [1] presented the calibration procedure of material models for moisture transport and time-dependent behavior of concrete and summarized the results obtained with a computationally efficient low-fidelity model (LFM). …”
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The Impact of LoRA Adapters on LLMs for Clinical Text Classification Under Computational and Data Constraints by Thanh-Dung Le, Ti Ti Nguyen, Vu Nguyen Ha, Symeon Chatzinotas, Philippe Jouvet, Rita Noumeir

“…These findings demonstrate that, in low-resource clinical settings with limited data and compute, lightweight Transformers trained from scratch offer a more practical and efficient solution than large LLMs, while GRN remains a viable adapter choice when minimal adaptation is needed.…”
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High Quality Dynamic Occlusion Computational Ghost Imaging Guided Through Conditional Diffusion Model by Minze Liang, Enkui Zhang, Xinyi Zheng, Huixing Yang, Liyu Zhang, Xuan Liu, Yongli Zhang

“…High-quality imaging under low sampling is the key to the practical application of computational ghost imaging, and significant progress has been made. …”
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Computationally Efficient Model Predictive Control of Delta-Connected CHB-Based Active Power Filter by Kehl Zdeněk, Glasberger Tomas, Peroutka Zdeněk

“…The control is tailored particularly for low-cost microcontrollers with limited computation power and resources. …”
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Model Selection and Parameter Estimation for an Improved Approximate Bayesian Computation Sequential Monte Carlo Algorithm by Yue Deng, Yongzhen Pei, Changguo Li, Bin Zhu

“…However, the existing methods have many problems, such as low efficiency in model selection and inaccuracy in parameter estimation. …”
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Network Usage and Time Efficient Performance Enhancement Model for IoT Applications in Fog Cloud Computing by Upma Arora, Nipur Singh

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Edge computing based english translation model using fuzzy semantic optimal control technique. by Na Wang

“…Some issues, including ambiguity in English translation and improper word choice in translation techniques, must be addressed to enhance the quality of the English translation model and accuracy based on the corpus. Hence, an edge computing-based translation model (FSRL-P2O) is proposed to improve translation accuracy by using huge bilingual corpora, considering Fuzzy Semantic (FS) properties, and maximizing the translation output using optimal control techniques with the incorporation of Reinforcement Learning and Proximal Policy Optimisation (PPO) techniques. …”
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Development of a Low-Intensity Light Imaging Probe for Childbirth Cervical Dilation Image Acquisition by Temitope O. Takpor, Aderemi A. Atayero, Emmanuel Adetiba, Joke A. Badejo

“…Hence, in this research, a prototype of a novel low-intensity light imaging probe was developed to acquire images of cervical dilation simulation models for further processing and analysis. …”
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Buried No longer: recent computational advances in explicit interfacial modeling of lithium-based all-solid-state battery materials by Julia H. Yang, Xinqiang Rao, Amanda Whai Shin Ooi

“…We also discuss the advantages and limitations of the various computational methods applied. Lastly, we highlight universal machine learning potentials, challenging datasets, and opportunities for tighter integration with experiments, all of which broaden the scope of modeling. …”
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Computational Fluid Dynamics Modeling of Pressure-Retarded Osmosis: Towards a Virtual Lab for Osmotic-Driven Process Simulations by Meisam Mohammadi Amin, Ulrich Krühne

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Leveraging Personalized Customer Experiences in Mobile Edge Computing Through Split Learning Using Smart Data-Driven Modeling by V. Vinoth Kumar, K. M. Karthick Raghunath, Iyappan Perumal, K. Manikandan

“…To solve these issues, we present Enhanced Smart Data-Driven Modeling (ESDDM), which combines Smart Data-Driven Modeling (SDDM) with modern Deep Learning (DL). …”
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Computational modeling of bone allograft reconstruction following femoral shaft tumor resection: Investigating the impact of supplementary plate fixation. by Petr Boháč, Vasileios Apostolopoulos, Petr Marcián, Tomáš Tomáš, Michal Mahdal, Tomáš Návrat

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Compressing Neural Networks on Limited Computing Resources by Seunghyun Lee, Dongjun Lee, Minju Hyun, Heeje Kim, Byung Cheol Song

“…Overall, our framework democratizes deep learning compression by offering a cost-effective and computationally feasible solution, enabling broader adoption in low-resource environments.…”
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Channel Length Modeling and Experimental Demonstration of Adaptive Threshold Under-Sampled CamCom for Low-SNR Transmitters by Muhammad Asim Atta, Babar Hussain, Amine Bermak

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Low-cost quantum mechanical descriptors for data efficient skin sensitization QSAR models by Davy Guan, Raymond Lui, Slade T. Matthews

“…Consequently, we investigate the use of electronic descriptors calculated using the Hartree Fock with 3 corrections (Hf-3c) method, a low-cost ab initio methodology that has higher chemical accuracy than previous semiempirical methodologies for modelling in vitro skin sensitization assay outcomes. …”
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