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TechRxiv 2023年

作者： Haque, Ahshanul Chowdhury, Md Naseef-Ur-Rahman Neha, Fariha Ferdous Dept of Computer Science New Mexico Tech SocorroNM United States Personal Systems HP INC AustinTX United States Department of Applied Mathematics University of Dhaka Dhaka Bangladesh

The medical care industry is on the cusp of an extraordinary period, with large language models (LLMs) arising as incredible assets for reclassifying medical care elements. This paper investigates the potential and effect of LLMs in different parts of medication, including diagnostics, patient consideration, drug revelation, and medical services organization. It dives into the open doors and difficulties introduced by LLMs, accentuating the moral contemplations and the requirement for capable reception. By looking at late turns of events and contextual investigations, this paper offers a brief look into the developing scene of medical services, where LLMs are ready to assume a focal part in reshaping the eventual fate of medication. © 2023, CC BY.

关键词： Diagnosis

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On the uniqueness of collections of pennies and marbles

arXiv

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arXiv 2023年

作者： Dewar, Sean Grasegger, Georg Kubjas, Kaie Mohammadi, Fatemeh Nixon, Anthony School of Mathematics University of Bristol Bristol United Kingdom Johann Radon Institute for Computational and Applied Mathematics Austria Department of Mathematics and Systems Analysis Aalto University Finland Departments of Mathematics and Computer Science KU Leuven Belgium Mathematics and Statistics Lancaster University LancasterLA1 4YF United Kingdom

In this note we study the uniqueness problem for collections of pennies and marbles. More generally, consider a collection of unit d-spheres that may touch but not overlap. Given the existence of such a collection, one may analyse the contact graph of the collection. In particular we consider the uniqueness of the collection arising from the contact graph. Using the language of graph rigidity theory, we prove a precise characterisation of uniqueness (global rigidity) in dimensions 2 and 3 when the contact graph is additionally chordal. We then illustrate a wide range of examples in these cases. That is, we illustrate collections of marbles and pennies that can be perturbed continuously (flexible), are locally unique (rigid) and are unique (globally rigid). We also contrast these examples with the usual generic setting of graph *** Codes 05C10, 52C25, 52C17 Copyright © 2023, The Authors. All rights reserved.

关键词： Marble

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The Fréchet Topp Leone-G Family of Distributions: Properties, Characterizations and Applications

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Annals of Data science 2021年第2期8卷 345-366页

作者： Reyad, Hesham Korkmaz, Mustafa Ç. Afify, Ahmed Z. Hamedani, G.G. Othman, Soha Department of Information Systems and Production Management Qassim University Buraydah Saudi Arabia Department of Measurement and Evaluation Artvin Çoruh University Artvin Turkey Department of Statistics Mathematics and Insurance Benha University Benha Egypt Department of Mathematics Statistics and Computer Science Marquette University Milwaukee United States Department of Applied Statistics Cairo University Giza Egypt

A new family of continuous distributions which ensure model flexiblity, is introduced based on the Fréchet distribution and Topp Leone-G family. Two special sub-models of the new family are discussed. We provide some distributional properties of this family in the general setting such as the series expansions of density, moments, generating function, stress strength model, Rényi and Shannon entropies, probability weighted moments and order statistics. Certain characterizations of the proposed family are presented. The maximum likelihood estimates and the observed information matrix are obtained for the model parameters. We assess the performance of the maximum likelihood estimators by means of a graphical simulation study. The potentiality of the new class is shown via two applications to real data sets. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Maximum likelihood estimation

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Towards Improved Cervical Cancer Screening: Vision Transformer-Based Classification and Interpretability

Towards Improved Cervical Cancer Screening: Vision Transform...

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IEEE International Symposium on Biomedical Imaging

作者： Khoa Tuan Nguyen Ho-Min Park Gaeun Oh Joris Vankerschaver Wesley De Neve Department of Environmental Technology Food Technology and Molecular Biotechnology Center for Biosystems and Biotech Data Science Ghent University Global Campus Incheon Korea Department of Electronics and Information Systems IDLab Ghent University Ghent Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

We propose a novel approach to cervical cell image classification for cervical cancer screening using the EVA-02 transformer model. We developed a four-step pipeline: fine-tuning EVA-02, feature extraction, selecting important features through multiple machine learning models, and training a new artificial neural network with optional loss weighting for improved generalization. With this design, our best model achieved an F1-score of 0.85227, outperforming the baseline EVA-02 model (0.84878). We also utilized Kernel SHAP analysis and identified key features correlating with cell morphology and staining characteristics, providing interpretable insights into the decision-making process of the fine-tuned model. Our code is available at https://***/Khoa-NT/isbi2025_ps3c.

关键词： Training Pipelines Decision making Artificial neural networks Feature extraction Transformers Kernel Cervical cancer Image classification Biomedical imaging

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Quality Process Control and Preventive Maintenance Optimization of a Grinding Unit: A Case Study

Quality Process Control and Preventive Maintenance Optimizat...

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International Conference on Optimization and Applications (ICOA)

作者： Youssef Sadraoui Mohamed Er-Ratby Moulay Saddik Kadiri Abdessamad Kobi LIPIM Laboratory of Process Engineering Computer Science and Mathematics National School of Applied Sciences Sultan Moulay Slimane University Khouribga Morocco LASTI Laboratory of Science and Engineering Techniques National School of Applied Sciences Sultan Moulay Slimane University Khouribga Morocco LARIS Angevin Laboratory for Systems Engineering Research Polytech Angers University of Angers France

ISBN: (数字)9798350387353

ISBN: (纸本)9798350387360

The studied process is a grinding and hydroclassification unit designed to ensure that the grain size it processes is in line with the specifications for the pipe's transport mode. Obstacles to the unit's operational process include frequent stops, plant's low reliability, product delivery with an inappropriate grain size, and a lack of control over operating parameters. These factors have a significant impact on the unit's relevance and, consequently, its performance. We created a quality culture among operators with “0 grain quality loss” through the implementation of the quality and processes control study, which was essential to improve the situation. Thus, by completing the seven project stages, we were able to enhance and optimize the grinding and hydroclassification unit's overall performance and capability to regulate the grain size quality. We noticed a notable improvement in regulating the several parameters that affect the targeted particle size after we established tools for unit quality control, such as control and monitoring charts, reaction matrices, intervention flow charts and operational standards. The unit has seen a great deal of satisfaction from the project in terms of quality, process control and resources optimization. Moreover, the incorporation of preventive maintenance into this process has shown to be crucial in guaranteeing the reliability and durability of the installation, thereby substantially improving the unit's overall efficiency.

关键词： Grain size Process control Quality control Particle measurements Product delivery Total quality management Time factors Optimization Preventive maintenance Standards

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Matrix product states for inference in discrete probabilistic models

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2021年第1期22卷 8396-8443页

作者： Rasmus Bonnevie Mikkel N. Schmidt Cognitive Systems Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby Denmark

When faced with problems involving inference in discrete domains, solutions often involve appeals to conditional independence structure or mean-field approximations. We argue that this is insufficient for a number of interesting Bayesian problems, including mixture assignment posteriors and probabilistic relational models (e.g. the stochastic block model). These posteriors exhibit no conditional independence structure, precluding the use of graphical model methods, yet exhibit dependency between every single element of the posterior, making mean-field methods a poor fit. We propose using an expressive yet tractable approximation inspired by tensor factorization methods, alternately known as the tensor train or the matrix product state, and which can be construed of as a direct extension of the mean-field approximation to higher-order dependencies. We give a comprehensive introduction to the application of matrix product state in probabilistic inference, and illustrate how to efficiently perform marginalization, conditioning, sampling, normalization, some expectations, and approximate variational inference in our proposed model.

关键词： variational inference matrix product states tensor trains discrete models symmetry

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New Heuristics for the Operation of an Ambulance Fleet under Uncertainty

arXiv

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arXiv 2024年

作者： Guigues, Vincent Kleywegt, Anton J. Nascimento, Victor Hugo School of Applied Mathematics FGV Rio de Janeiro Praia de Botafogo Brazil Georgia Institute of Technology AtlantaGA30332-0205 United States Computer Science and Systems Engineering UFRJ Cidade Universitaria Rio de Janeiro Brazil

The operation of an ambulance fleet involves ambulance selection decisions about which ambulance to dispatch to each emergency, and ambulance reassignment decisions about what each ambulance should do after it has finished the service associated with an emergency. For ambulance selection decisions, we propose four new heuristics: the Best Myopic (BM) heuristic, a NonMyopic (NM) heuristic, and two greedy heuristics (GHP1 and GHP2). Two variants of the greedy heuristics are also considered. We also propose an optimization problem for an extension of the BM heuristic, useful when a call for several patients arrives. For ambulance reassignment decisions, we propose several strategies to choose which emergency in queue to send an ambulance to or which ambulance station to send an ambulance to when it finishes service. These heuristics are also used in a rollout approach: each time a new decision has to be made (when a call arrives or when an ambulance finishes service), a two-stage stochastic program is solved. The proposed heuristics are used to efficiently compute the second stage cost of these problems. We apply the rollout approach with our heuristics to data of the Emergency Medical Service (EMS) of a large city, and show that these methods outperform other heuristics that have been proposed for ambulance dispatch decisions. We also show that better response times can be obtained using the rollout approach instead of using the heuristics without rollout. Moreover, each decision is computed in a few seconds, which allows these methods to be used for the real-time management of a fleet of ambulances. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Local Thermal Non-Equilibrium Models in Porous Media: A Comparative Study of Conduction Effects

arXiv

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arXiv 2025年

作者： Kostelecky, Anna Mareike Stefansson, Ivar Bringedal, Carina Ghosh, Tufan Dahle, Helge K. Helmig, Rainer Institute for Modelling Hydraulic and Environmental Systems Univeristy of Stuttgart Stuttgart Germany Department of Mathematics University of Bergen Bergen Norway Center for Modeling of Coupled Subsurface Dynamics Department of Mathematics University of Bergen Bergen Norway Department of Computer science Electrical engineering and Mathematical sciences Western Norway University of Applied Sciences Bergen Norway

Instantaneous heat transfer between different phases is a common assumption for modeling heat transfer in porous media, known as Local Thermal Equilibrium (LTE). This assumption may not hold in certain technical and environmental applications, especially in systems with large temperature gradients, large differences in thermal properties, or high velocities. Local Thermal Non-Equilibrium (LTNE) models aim to describe heat transfer processes when the LTE assumption may fail. In this work, we compare three continuum-scale models from the pore to the representative elementary volume (REV) scale. Specifically, dual-network and REV-scale models are evaluated against a pore-resolved model, which we perceive as a reference in the absence of experimental results. Different effective models are used to obtain upscaled properties on the REV scale and to compare resulting temperature profiles. The systems investigated are fully saturated, consisting of one fluid and one solid phase. This study focuses on purely conductive systems without significant differences in thermal properties. Results show that LTE holds then for low interfacial resistances. However, for large interfacial resistances, solid and fluid temperatures differ. The REV-scale model with effective parameters obtained by homogenization leads to similar results as the pore-resolved model, whereas the dual-network model shows greater deviation due to its fixed spatial resolution. Among the evaluated effective parameter formulations for the REV-scale model, only the homogenization-based approach captures the LTNE behavior, as it incorporates the interfacial heat transfer coefficient. Convection is relevant for most practical applications, and its impact will be addressed in a follow-up article. © 2025, CC BY.

关键词： Electric heating

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Cyclic Retrial Queue for Building Data Transmission Networks 15th

Cyclic Retrial Queue for Building Data Transmission Networks

引用

15th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2022

作者： Nazarov, Anatoly Phung-Duc, Tuan Shulgina, Ksenia Lizyura, Olga Paul, Svetlana Shashev, Dmitriy Institute of Applied Mathematics and Computer Science National Research Tomsk State University 36 Lenina ave. Tomsk634050 Russia Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan Faculty of Innovative Technologies National Research Tomsk State University 36/3 Lenina ave. Tomsk634050 Russia

ISBN: (纸本)9783031312335

This paper considers a mathematical model of a cyclic multiple access communication network. The model can be used to build specialized "flying" FANET data transmission networks. We consider a single server retrial queue for modeling one node in such network. The input consists of multiple Poisson processes with different arrival rates. Service and retrial rates depend on the origin flow. Thus, each flow has its own orbit for redial. Under the condition when the retrial rate is low, we obtain an asymptotic probability distribution of the number of customers in the orbits. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Asymptotic analysis

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ProteinGym: large-scale benchmarks for protein fitness prediction and design 23

ProteinGym: large-scale benchmarks for protein fitness predi...

引用

Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Pascal Notin Aaron W. Kollasch Daniel Ritter Lood van Niekerk Steffanie Paul Hansen Spinner Nathan Rollins Ada Shaw Ruben Weitzman Jonathan Frazer Mafalda Dias Dinko Franceschi Rose Orenbuch Yarin Gal Debora S. Marks Computer Science University of Oxford Systems Biology Harvard Medical School Seismic Therapeutic Applied Mathematics Harvard University Centre for Genomic Regulation Universitat Pompeu Fabra Harvard Medical School Broad Institute

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.

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