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Annual IEEE Systems Conference

作者： Nader Mohamed Sanja Lazarova-Molnar Jameela Al-Jaroodi Department of Computer Science and Information Systems Pennsylvania Western University California PA USA Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Karlsruhe Germany Faculty of Engineering University of Southern Denmark Odense Denmark Department of Engineering Robert Morris University Pittsburgh PA USA

Some manufacturing industries consume massive energy for their manufacturing and logistics processes. The costs of manufacturing can increase significantly as the energy cost increases. Such increase amplifies the final cost of the created products on the consumers. This makes finding different approaches that utilize innovative technologies to improve energy efficiency in manufacturing extremely important. This paper investigates how digital twins can be utilized to enable improved energy efficiency in manufacturing. Different applications of digital twins for energy-efficient manufacturing are investigated. In addition, the paper discusses some challenges of utilizing digital twins for this purpose. A framework for utilizing digital twins for energy-efficient manufacturing is also discussed.

关键词： Manufacturing industries Costs Manufacturing processes Buildings Energy efficiency Raw materials Manufacturing

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MedFroDetect: Medicare fraud detection with extremely imbalanced class distributions 33

MedFroDetect: Medicare fraud detection with extremely imbala...

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33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020

作者： Su, Yuping Zhu, Xingquan Dong, Bei Zhang, Yumei Wu, Xiaojun Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University Xian China School of Computer Science Shaanxi Normal University Xi'an China Department of Computer and Electrical Engineering and Computer Science Florida Atlantic University Boca Raton United States

ISBN: (纸本)9781577358213

In this paper, we propose to use machine learning to automate Medicare fraud detection. By cross checking Medicare payment database and provider exclusion database, we build datasets with millions of service providers, including a handful of convicted fraudulent service providers. One essential challenge is that the dataset created is extremely imbalanced, making it extremely difficult to learn accurate classifiers for fraud detection. To tackle the challenge, we first use feature engineering to design effective features, by taking the difference between each service provider and its group cohort into consideration. At the instance level, we also use a synthetic instance generation approach to generate positive samples to alleviate the data imbalance challenge. By combining feature engineering, synthetic instance generation, and under sampling based ensemble learning, our method outperforms baseline approaches for Medicare fraud detection. © FLAIRS *** right reserved.

关键词： Crime

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Hardware Data Prefetch for XiangShan Processor

Hardware Data Prefetch for XiangShan Processor

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International Conference on Integrated Circuits and Microsystems (ICICM)

作者： Yuhan Zhu Jiachun Zheng Shuyan Ding Lunbo Li College of Computer Science & Engineering Nanjing University of Science and Technology Nanjing China Technical Research & Development Department Beijing Institute of Open Source Chip Beijing China Electric and Electronic Teaching & Experiment Center School of Electronic and Optical Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781665460583

XiangShan, a rising star of RISC-V-based processors proposed by Chinese Academy of science, is famous for its high performance and agile methodology. At present, the second-generation Yanqi Lake architecture of XiangShan has already reached the frequency of 2GHz at the 14nm process node, which ranks the first in the field of open-source RISC-V-based processors. One of the key approaches that contribute to its high performance is prefetch. A timely and accurate prefetcher can effectively eliminate cache misses and thus hide memory access latency. Aiming at the specific environment of XiangShan, out-of-order and parallel, a stride-based prefetcher for the L1DCache is achieved on the Yanqi Lake structure of XiangShan. Serious benchmarks from SPEC2006 were run on XiangShan, the result of which demonstrates that our prefetcher improves the performance of XiangShan by an average of 2.5% and up to 13.3%.

关键词： Out of order Micromechanical devices Integrated circuits Program processors Codes Prefetching Stars

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Predicting Breast Cancer Survival: A Survival Analysis Approach Using Log Odds and Clinical Variables

arXiv

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arXiv 2024年

作者： Alamu, Opeyemi Sheu Choque, Bismar Jorge Gutierrez Rizvi, Syed Wajeeh Abbs Hammed, Samah Badr Medani, Isameldin Elamin Siam, Md Kamrul Tahir, Waqar Ahmad Departmet of Statistics Federal College of Animal Health and Production Technology Ibadan Nigeria Department of Science Universidad Mayor de San Andres La Paz Bolivia Department of Data Science National University of Computer & Emerging Sciences-FAST City Campus Karachi Pakistan Department of Basic Medical Science University of Khartoum Khartoum Sudan Consultant Obstetrics and Gynecology University Hospital The University of Jazan Jazan Saudi Arabia New York Institute of Technology New York United States Department of Internal Medicine/Casualty Khalifa Gull Nawaz Teaching Hospital Bannu Pakistan

Breast cancer remains a significant global health challenge, with prognosis and treatment decisions largely dependent on clinical characteristics. Accurate prediction of patient outcomes is crucial for personalized treatment strategies. This study employs survival analysis techniques, including Cox proportional hazards and parametric survival models, to enhance the prediction of the log odds of survival in breast cancer patients. Clinical variables such as tumor size, hormone receptor status, HER2 status, age, and treatment history were analyzed to assess their impact on survival outcomes. Data from 1557 breast cancer patients were obtained from a publicly available dataset provided by the University College Hospital, Ibadan, Nigeria. This dataset was preprocessed and analyzed using both univariate and multivariate approaches to evaluate survival outcomes. Kaplan-Meier survival curves were generated to visualize survival probabilities, while the Cox proportional hazards model identified key risk factors influencing mortality. The results showed that older age, larger tumor size, and HER2-positive status were significantly associated with an increased risk of mortality. In contrast, estrogen receptor positivity and breast-conserving surgery were linked to better survival outcomes. The findings suggest that integrating these clinical variables into predictive models improves the accuracy of survival predictions, helping to identify high-risk patients who may benefit from more aggressive interventions. This study demonstrates the potential of survival analysis in optimizing breast cancer care, particularly in resource-limited settings. Future research should focus on integrating genomic data and real-world clinical outcomes to further refine these models. © 2024, CC BY.

关键词： Lung cancer

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Development of a SPOC of computer Ethics for students of computer science degree 11

Development of a SPOC of Computer Ethics for students of Com...

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11th International Conference on Virtual Campus, JICV 2021

作者： García-Holgado, Alicia García-Peñalvo, Francisco J. Therón, Roberto Vázquez-Ingelmo, Andrea Gamazo, Adriana González-González, Carina S. Iranzo, Rosa María Gil Silveira, Ismar Frango Alier Forment, Marc IUCE University of Salamanca GRIAL Research Group Computer Science Department Salamanca Spain IUCE University of Salamanca GRIAL GRIAL Research Group Didactics Organization and Research Methods Department Salamanca Spain University Institute of Women's Studies Universidad de la Laguna Computer and Systems Engineering Department San Cristóbal de la Laguna Spain Universitat de Lleida Computer Science and Industrial Engineering Department Lleida Spain Universidade Presbiteriana Mackenzie Faculdade de Computação e Informática Sao Paulo Brazil BCN-SEER BarcelonaTech Department of Service and Information System Engineering Barcelona Spain

ISBN: (纸本)9781665437035

Technology brings different benefits to society and involves challenges and ethical dilemmas that must be considered during any technology development. In this sense, graduates must recognise the social, legal, ethical and cultural issues inherent to the discipline of computer science. However, there is a lack of integration of computer ethics in the computer science curriculum in Spanish universities. This work introduces a pilot experience to develop a Small Private Open Course (SPOC) to introduce computer ethics as an extracurricular activity in the Bachelor's Degree of computer Engineering at the University of Salamanca. © 2021 IEEE.

关键词： Engineering education

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Bringing the Algorithms to the Data - Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)

arXiv

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arXiv 2022年

作者： de Arruda Botelho Herr, Marius Graf, Michael Placzek, Peter König, Florian Bötte, Felix Stickel, Tyra Hieber, David Zimmermann, Lukas Slupina, Michael Mohr, Christopher Biergans, Stephanie Akgün, Mete Pfeifer, Nico Kohlbacher, Oliver Institute for Translational Bioinformatics University Hospital Tübingen Tübingen Germany Institute for Bioinformatics and Medical Informatics University of Tübingen Tübingen Germany Methods in Medical Informatics Department of Computer Science University of Tübingen Germany Applied Bioinformatics Department of Computer Science University of Tübingen Germany Medical Data Integration Center University Hospital Tübingen Tübingen Germany Medical Data Privacy and Privacy-Preserving ML on Healthcare Data Department of Computer Science University of Tübingen Germany

The need for data privacy and security – enforced through increasingly strict data protection regulations – renders the use of healthcare data for machine learning difficult. In particular, the transfer of data between different hospitals is often not permissible and thus cross-site pooling of data not an option. The Personal Health Train (PHT) paradigm proposed within the GO-FAIR initiative implements an’algorithm to the data’ paradigm that ensures that distributed data can be accessed for analysis without transferring any sensitive data. We present PHT-meDIC, a productively deployed open-source implementation of the PHT concept. Containerization allows us to easily deploy even complex data analysis pipelines (e.g, genomics, image analysis) across multiple sites in a secure and scalable manner. We discuss the underlying technological concepts, security models, and governance processes. The implementation has been successfully applied to distributed analyses of large-scale data, including applications of deep neural networks to medical image data. © 2022, CC BY.

关键词： Bioinformatics

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Equivariant graph hierarchy-based neural networks 22

Equivariant graph hierarchy-based neural networks

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Jiaqi Han Wenbing Huang Tingyang Xu Yu Rong Department of Computer Science and Technology Tsinghua University Gaoling School of Artificial Intelligence Renmin University of China and Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Tencent AI Lab

ISBN: (纸本)9781713871088

Equivariant Graph neural Networks (EGNs) are powerful in characterizing the dynamics of multi-body physical systems. Existing EGNs conduct flat message passing, which, yet, is unable to capture the spatial/dynamical hierarchy for complex systems particularly, limiting substructure discovery and global information fusion. In this paper, we propose Equivariant Hierarchy-based Graph Networks (EGHNs) which consist of the three key components: generalized Equivariant Matrix Message Passing (EMMP), E-Pool and E-UnPool. In particular, EMMP is able to improve the expressivity of conventional equivariant message passing, E-Pool assigns the quantities of the low-level nodes into high-level clusters, while E-UnPool leverages the high-level information to update the dynamics of the low- level nodes. As their names imply, both E-Pool and E-UnPool are guaranteed to be E(n)-equivariant to meet the physical symmetry. Considerable experimental evaluations verify the effectiveness of our EGHN on several applications including multi-object dynamics simulation, motion capture, and protein dynamics modeling.

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RANDOM PLANAR TREES AND THE JACOBIAN CONJECTURE

arXiv

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arXiv 2023年

作者： Bisi, Elia Dyszewski, Piotr Gantert, Nina Johnston, Samuel G.G. Prochno, Joscha Schmid, Dominik Institute of Statistics and Mathematical Methods in Economics TU Vienna Austria Mathematical Institute Wroclaw University Poland Department of Mathematics TU Munich Germany Department of Mathematics King’s College London United Kingdom Faculty of Computer Science and Mathematics University of Passau Germany Mathematical Institute University of Bonn Germany

We develop a probabilistic approach to the celebrated Jacobian conjecture, which states that any Keller map (i.e. any polynomial mapping F: Cn → Cn whose Jacobian determinant is a nonzero constant) has a compositional inverse which is also a polynomial. The Jacobian conjecture may be formulated in terms of a problem involving labellings of rooted trees;we give a new probabilistic derivation of this formulation using multi-type branching processes. Thereafter, we develop a simple and novel approach to the Jacobian conjecture in terms of a problem involving shuffling subtrees of d-Catalan trees, i.e. planar d-ary trees. We also show that, if one can construct a certain Markov chain on large d-Catalan trees which updates its value by randomly shuffling certain nearby subtrees, and in such a way that the stationary distribution of this chain is uniform, then the Jacobian conjecture is true. Finally, we use the local limit theory of large random trees to show that the subtree shuffling conjecture is true in a certain asymptotic sense, and thereafter use our machinery to prove an approximate version of the Jacobian conjecture, stating that inverses of Keller maps have small power series coefficients for their high degree *** Codes 60J80, 05C05, 14R15 (Primary), 60J10, 13F25 (Secondary) Copyright © 2023, The Authors. All rights reserved.

关键词： Polynomials

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University leagues alongside rankings

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Quality and Quantity 2023年第1期57卷 721-736页

作者： Banász, Zsuzsanna Kosztyán, Zsolt T. Csányi, Vivien V. Telcs, András Department of Economics University of Pannonia Egyetem str. 10 Veszprém Hungary MTA-PE Budapest Ranking Research Group Eötvös Loránd Research Network (ELKH) Egyetem str. 10 Veszprém Hungary Department of Quantitative Methods University of Pannonia Egyetem str. 10 Veszprém Hungary Institute of Advanced Studies Koszeg Koszeg Hungary Research Centre of Faculty of Business and Economics University of Pannonia Egyetem str. 10. Veszprém Hungary Head of Department of Computational Sciences MTA Wigner Research Center for Physics Budapest Hungary Department of Computer Science and Information Theory Budapest University of Technology and Economics Budapest Hungary

University rankings can both orient and disorient potential students. In rankings, universities with very different characteristics are compared, which makes interpretation difficult. We propose the application of a clustering method, which creates groups of universities that are close to each other with respect to a subset of indicators, but the indicators also show homogeneity with respect to the universities in that group. We call such groups leagues. These leagues are defined by the data themselves and are not based on subjective criteria. We demonstrate our proposition using one member of the family of the two-way clustering method, namely, biclustering. The case we present is based on the Round University Ranking (RUR) 2020 dataset. The use of leagues could provide better guidance not only for potential applicants but also for university funding organizations and policy-makers. Our case study led to a somewhat surprising observation. In the top league (based on the RUR data and indicators), the three most important indicators measure reputation, not scientific or educational performance. © 2022, The Author(s).

关键词： Biclustering Leagues Rankings Universities

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Identification of Inhomogeneities According to Potential Field Data Using the Near-Boundary Element Method 16

Identification of Inhomogeneities According to Potential Fie...

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16th IEEE International Conference on computer science and Information Technologies, CSIT 2021

作者： Zhuravchak, Liubov Zabrodska, Nataliya National University Lviv Polytechnic Software Department of Institute of Computer Science and Information Technologies Bandera street 12 Lviv Ukraine Branch of S.I Subbotin Institute of Geophysics National Academy of Sciences Department of Geoelectromagnetic Methods of Carpathian Naukova street 3-b Lviv Ukraine

ISBN: (纸本)9781665442572

The step-by-step algorithm for the approximate recognition of inclusions in the object according to potential field data is given. It is based on the repeated solution of a direct problem by high-precision methods of boundary, near-boundary and partly boundary elements. On the example of the use of electrical profiling method data, regularities between the distribution of apparent resistivity at the half-plane boundary and the parameters of inclusions are derived. © 2021 IEEE.

关键词： Boundary element method

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