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TechRxiv 2022年

作者： Yagis, Ekin Pinpo, Nichapat Jacutprakart, Janadhip Abolghasemi, Vahid Andritsch, Jarutas Chaichulee, Sitthichok Cid, Yashin Dicente Seco de Herrera, Alba G. Ingviya, Thammasin The School of Computer Science and Electronic Engineering University of Essex United Kingdom The Division of Digital Innovation and Data Analytics Faculty of Medicine Prince of Songkla University Thailand Faculty of Business Law and Digital Technologies Solent University United Kingdom The Department of Biomedical Sciences and Biomedical Engineering Faculty of Medicine Prince of Songkla University Thailand Roche Diagnostics Sant Cugat del Vallès Spain The Department of Family and Preventive Medicine Faculty of Medicine Prince of Songkla University Thailand University College London United Kingdom

Tuberculosis (TB) is still a serious public health concern across the world, causing 1.4 million deaths each year. However, there has been a scarcity of radiological interpretation skills in many TB-infected locations, which may cause poor diagnosis rates and poor patient outcomes. A cost-effective and efficient automated technique might help screening evaluations in underprivileged countries and provide early illness diagnosis. In this work, we proposed a deep ensemble learning framework that integrates multisource data of two deep learning-based techniques for the automated diagnosis of TB. The integrated model framework has been tested on two publicly available datasets and one private dataset. While both proposed deep learning-based automated detection systems have shown high accuracy and specificity compared to state-of-the-art, the ensemble method significantly improved prediction accuracy in detecting chest radiographs with active pulmonary TB from a multi-ethnic patient cohort. Extensive experiments were used to validate the methodology, and the results were superior to previous approaches, showing the method’s practicality for application in the real world. By integrating supervised prediction and unsupervised representation, the ensemble method accurately classified TB with the area under the receiver operating characteristic (AUROC) up to 0.98 using chest radiography outperforming the other tested classifiers and achieving state-of-the-art. The methodology and findings provide a viable route for more accurate and quicker TB detection, especially in low and middle-income nations. © 2022, CC BY.

关键词： Cost effectiveness

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Representation degeneration problem in training natural language generation models 7

Representation degeneration problem in training natural lang...

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7th International Conference on Learning Representations, ICLR 2019

作者： Gao, Jun He, Di Tan, Xu Qin, Tao Wang, Liwei Liu, Tie-Yan Department of Computer Science University of Toronto Canada Vector Institute Canada Key Laboratory of Machine Perception MOE School of EECS Peking University China Microsoft Research United States Center for Data Science Peking University Beijing Institute of Big Data Research China

We study an interesting problem in training neural network-based models for natural language generation tasks, which we call the representation degeneration problem. We observe that when training a model for natural language generation tasks through likelihood maximization with the weight tying trick, especially with big training datasets, most of the learnt word embeddings tend to degenerate and be distributed into a narrow cone, which largely limits the representation power of word embeddings. We analyze the conditions and causes of this problem and propose a novel regularization method to address it. Experiments on language modeling and machine translation show that our method can largely mitigate the representation degeneration problem and achieve better performance than baseline algorithms. © 7th International Conference on Learning Representations, ICLR 2019. All Rights Reserved.

关键词： Embeddings

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Application and development of elastic fibers focusing on composition and structure 6

Application and development of elastic fibers focusing on co...

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2021 6th International Seminar on Advances in Materials science and Engineering, ISAMSE 2021

作者： Zhang, Jin Sun, Qinyue Wang, Yumin Dong, Xiongwei Xiong, Yi Zeng, Wei Department of Pharmacy Zhongnan Hospital Wuhan University Wuhan430071 China Science and Technology Institute Key Laboratory of Textile Fiber and Products Ministry of Education Laboratory for Electron Microscopy Wuhan Textile University Hubei Wuhan430073 China National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information Engineering Anhui University Anhui Hefei230601 China School of Physics and Technology MOE Key Laboratory of Artificial Micro- and Nano-Structures Wuhan University Wuhan430072 China

Elastic fabric is comfortable to wear, and has been a consumer textile due to its good shape retention and wrinkle resistance after washing. This paper briefly introduces the types and performance characteristics of several common elastic fibers, and analyzes the relationship between the structure and elasticity of different elastic fibers. Finally, the development trend of elastic fibers is proposed. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Elasticity

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database Intrusion Detection Systems (DIDs): Insider threat detection via behavioural-based Anomaly detection systems - A Brief Survey of concepts and approaches

arXiv

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arXiv 2020年

作者： Khan, Muhammad Imran Foley, Simon N. O'Sullivan, Barry Insight Centre for Data Analytics School of Computer Science and Information Technology University College Cork Ireland Department of Information Security and Communication Technology Norwegian University of Science and Technology Gjøvik Norway

One of the data security and privacy concerns is of insider threats, where legitimate users of the system abuse the access privileges they hold. The insider threat to data security means that an insider steals or leaks sensitive personal information. database Intrusion detection systems, specifically behavioural-based database intrusion detection systems, have been shown effective in detecting insider attacks. This paper presents background concepts on database intrusion detection systems in the context of detecting insider threats and examines existing approaches in the literature on detecting malicious accesses by an insider to database Management Systems (DBMS). Copyright © 2020, The Authors. All rights reserved.

关键词： Relational database systems

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EXISTENCE AND CONTROLLABILITY FOR NONLINEAR FRACTIONAL CONTROL SYSTEMS WITH DAMPING IN HILBERT SPACES

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Acta Mathematica Scientia 2019年第1期39卷 229-242页

作者： Xiuwen LI Zhenhai LIU Jing LI Chris TISDELL School of Science Nanjing University of Sciences and Technology Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Hunan Province Key Laboratory of Mathematical Modelling and Analysis in Engineering Department of Mathematics and Statistics Changsha University of Science and Technology Faculty of Science The University of New South Wales UNSW

In this paper, we are concerned with the existence of mild solution and controllability for a class of nonlinear fractional control systems with damping in Hilbert *** first step is to give the representation of mild solution for this control system by utilizing the general method of Laplace transform and the theory of(α, γ)-regularized families of operators. Next, we study the solvability and controllability of nonlinear fractional control systems with damping under some suitable sufficient conditions. Finally, two examples are given to illustrate the theory.

关键词： existence controllability fractional control systems damping regularized resolvent family

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Learning as we go – An examination of the statistical accuracy of COVID-19 daily death count predictions

arXiv

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arXiv 2020年

作者： Marchant, Roman Samia, Noelle I. Rosen, Ori Tanner, Martin A. Cripps, Sally ARC Centre for Data Analytics for Resources and Environments Australia Centre for Translational Data Science University of Sydney Australia School of Mathematics and Statistics University of Sydney Australia Department of Statistics Northwestern University United States Department of Mathematical Sciences University of Texas El Paso United States

OBJECTIVE: This paper provides a formal evaluation of the predictive performance of a model (and updates) developed by the Institute for Health Metrics and Evaluation (IHME) for predicting daily deaths attributed to COVID-19 for the United States. STUDY DESIGN: To assess the accuracy of the IHME models, we examine both forecast accuracy, as well as the predictive performance of the 95% prediction intervals (PI). RESULTS: The initial model underestimates the uncertainty surrounding the number of daily deaths. Specifically, the true number of next day deaths fell outside the IHME prediction intervals as much as 76% of the time, in comparison to the expected value of 5%. Regarding the updated models, our analyses indicate that the April models show little, if any, improvement in the accuracy of the point estimate predictions. Moreover, while we observe a larger percentage of states having actual values lying inside the 95% PI’s, this observation may be attributed to the widening of the PI’s. A major revised model in early May did result in a decrease in the estimated model uncertainty, albeit at the expense of poorer coverage probability. CONCLUSION: Our analysis calls into question the usefulness of the predictions to drive policy making and resource allocation. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Reusability of lactic acid on hydrolysis of nanocrystalline cellulose from pepper waste (piper nigrum L.)

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Case Studies in Chemical and Environmental Engineering 2024年 10卷

作者： Holilah, Holilah Suryanegara, Lisman Bahruji, Hasliza Hamid, Zuratul Ain Abdul Wahyudi, Muhammad Sapto Masruchin, Nanang Asranudin, Asranudin Faradilla, RH. Fitri Syafri, Edi Melenia, Alvina Tata Jovita, Stella Nugraha, Reva Edra Prasetyoko, Didik Research Center for Biomass and Bioproducts National Research and Innovation Agency of Indonesia (BRIN) Cibinong 16911 Indonesia Research Collaboration Center for Nanocellulose BRIN-Andalas University Padang 25163 Indonesia Centre of Advanced Material and Energy Sciences Universiti Brunei Darussalam Jl. Tungku Link BE 1410 Brunei Darussalam School of Materials & Mineral Resources Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang 14300 Malaysia Department of Food Science and Technology Faculty of Agriculture Halu Oleo University Southeast Sulawesi Kendari Indonesia Department of Agricultural Technology Politeknik Pertanian Negeri Payakumbuh West Sumatra 26271 Indonesia Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Pembangunan Nasional “Veteran” Jawa Timur Surabaya 60294 Indonesia

Lactic acid recovery and reusability for hydrolysis of cellulose offers an economical method and produces fewer waste streams. Successful lactic acid recovery up to three recycle times efficiently hydrolyzed NCs with rod-shape morphology. However, after four cycles, the nanocrystalline cellulose yield reduced from 72.3 % to 48.2 %, forming large nanocelluloses with high crystalline index. Large-size nanocellulose with high zeta potential and thermal stability were obtained with increasing cycles due to inefficient acid diffusion into the rigid crystalline network compared to amorphous cellulose. This study offers a green pathway for hydrolysis nanocellulose using a less corrosive and low toxicity lactic acid than inorganic acids. © 2024 The Authors

关键词： acid recovery hydrolysis lactic acid Nanocrystalline cellulose organic acid

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Proper Orthogonal Decomposition-Based Model-Order Reduction for Smoothed Particle Hydrodynamics Simulation

SSRN

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SSRN 2024年

作者： Fang, Lidong Song, Zilong Fraser, Kirk Habib, Faisal Drummond, Christopher Huaxiong, Huang Mathematics Analytics and Data Science Lab Fields Institute for Research in Mathematical Sciences TorontoONM5T 3J1 Canada Department of Mathematics and Statistics Utah State University LoganUT84322 United States National Research Council Canada SaguenayQCG7H 8C3 Canada NRC Institute for Information Technology OttawaONK1A 0R6 Canada Guangdong Zhuhai519087 China BNU-HKBU United International College Guangdong Zhuhai519087 China Department of Mathematics and Statistics York University TorontoONM3J 1P3 Canada

In this paper, we present a projection-based model-order reduction (MOR) technique for smoothed particle hydrodynamics (SPH) simulations, which is a mesh-free approach within the Lagrangian framework. Our approach utilizes the proper orthogonal decomposition (POD) technique to generate a subspace basis for the reduction process. The main objective of this study is to conduct an initial exploration of the feasibility of employing POD-based MOR (POD-MOR) in SPH simulations and to quantify the associated POD error. To illustrate the effectiveness of our approach, we consider the friction stir spot welding problem, which involves the coupling of flow equations and heat equation. Our findings reveal that, when considering the same degrees of freedom, POD-MOR significantly reduces computational error compared to the uniform reduction of particle numbers in SPH simulations. © 2024, The Authors. All rights reserved.

关键词： Friction

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Quantum generative training using rényi divergences

arXiv

引用

arXiv 2021年

作者： Kieferová, Mária Marrero, Carlos Ortiz Wiebe, Nathan Centre for Quantum Computation and Communication Technology Centre for Quantum Software and Information University of Technology Sydney Data Sciences & Analytics Group Department of Electrical & Computer Engineering Pacific Northwest National Laboratory North Carolina State University Department of Computer Science Department of Physics High Performance Computing Group University of Toronto University of Washington Pacific Northwest National Laboratory

Quantum neural networks (QNNs) are a framework for creating quantum algorithms that promises to combine the speedups of quantum computation with the widespread successes of machine learning. A major challenge in QNN development is a concentration of measure phenomenon known as a barren plateau that leads to exponentially small gradients for a range of QNNs models. In this work, we examine the assumptions that give rise to barren plateaus and show that an unbounded loss function can circumvent the existing no-go results. We propose a training algorithm that minimizes the maximal Rényi divergence of order two and present techniques for gradient computation. We compute the closed form of the gradients for Unitary QNNs and Quantum Boltzmann Machines and provide sufficient conditions for the absence of barren plateaus in these models. We demonstrate our approach in two use cases: thermal state learning and Hamiltonian learning. In our numerical experiments, we observed rapid convergence of our training loss function and frequently archived a 99% average fidelity in fewer than 100 epochs. © 2021, CC BY.

关键词： Quantum computers

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Quality control analysis of tube drain production at Samba Moda Utama Inc. using robust control chart based on Winsorized modified one-step M-estimator (MOM)

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AIP Conference Proceedings 2023年第1期2903卷

作者： Ara Bella Muhammad Ahsan Muhammad Alifian Nuriman Department of Statistics Faculty of Science and Data Analytics Sepuluh Nopember Institute of Technology Jl. Arief Rahman Hakim Surabaya 60111 Indonesia Department of Business Statistics Vocational Faculty Sepuluh Nopember Institute of Technology Keputih Kec. Sukolilo Surabaya 60117 Indonesia

Samba Moda Utama Inc. is one of the automotive component manufacturers focusing on Tube Drain production. As a component manufacturer trusted to meet the demand for vehicle components, Samba Moda Utama Inc. must maintain and improve product quality by doing quality control. The study was conducted on three quality characteristics related to Tube Drain specification parameters that are thought to be related to each other, the outer diameter, inner diameter, and length of the Tube Drain. Using data in which the variability process has been controlled, mean process control uses the Hotelling’s T2 control chart, MEWMA, robust Hotelling’s T2, and robust MEWMA control chart based on Winsorized Modified One-Step M-estimator (MOM). The performance of these four control charts was then compared. Robust control charts, both Hotelling’s T2, and MEWMA, can better detect out-of-control because parameters are estimated from data that has already cleared from outliers, which produce more sensitive control charts. Multivariate measurement of the process capability is carried out through the MCp and MCpk indices. Process capability indices are obtained by considering the correlation between quality characteristics based on the Principal Components Analysis (PCA). Using two components based on the results of the scree plot, it was concluded that the three quality characteristics selected in the Tube Drain production at Samba Moda Utama Inc. had met the specifications determined by the company.

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