检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Mikhaylov, Slava Jankin Esteve, Marc Campion, Averill Institute for Analytics and Data Science School of Computer Science Electronic Engineering Department of Government University of Essex School of Public Policy University College London Department of Strategy and General Management ESADE Ramon Llull University

public sector organisations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high uncertainty environments. The long-term success of data science and AI in the public sector relies on effectively embedding it into delivery solutions for policy implementation. However, governments cannot do this integration of AI into public service delivery on their own. The UK Government Industrial Strategy is clear that delivering on the AI grand challenge requires collaboration between universities and public and private sectors. This cross-sectoral collaborative approach is the norm in applied AI centres of excellence around the world. Despite their popularity, cross-sector collaborations entail serious management challenges that hinder their success. In this article we discuss the opportunities and challenges from AI for public sector. Finally, we propose a series of strategies to successfully manage these cross-sectoral collaborations. Copyright © 2018, The Authors. All rights reserved.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Introduction to the Issue on Photonics for Sensing

引用

IEEE Journal of Selected Topics in Quantum Electronics 2017年第2期23卷 5-7页

作者： Xiao, H. Arregui, F.J. Bao, X. Fan, X. Rao, Y. Wysocki, G. Holcombe Department of Electrical and Computer Engineering Clemson University ClemsonSC29631 United States Department of Electrical and Computer Engineering and Bioengineering Public University of Navarre Pampalona31006 Spain Department of Physics University of Ottawa OttawaONK1N 6N5 Canada Department of Biomedical Engineering University of Michigan Ann ArborMI48109 United States Key Lab of Optical Fiber Sensing and Communications University of Electronics Science and Technology of China Chengdu611731 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

The papers in this special section address the use of photonics for sensing applications. Light has long been used for sensing, metrology, imaging, and measurement in human history. The inventions of semiconductor sources and detectors, optical fibers and integrated optical waveguides in the last century have led to the emergence of photonics. The papers cover a wide variety of topics in the design, characterization, packaging and demonstration of new photonic devices, structures, functional materials, fabrication methods, and signal processing principles for sensing various physical, chemical and biological parameters. The sensing scales range from nanometers based on tip enhanced Raman scattering and quantum dots to kilometers based on distributed Raman or Brillouin scattering in optical fibers. The electromagnetic spectra cover microwave, terahertzrange, deep ultraviolet (UV), visible, and mid-infrared (IR).

关键词： Special issues and sections Photonics Sensing Remote sensing Image processing Metrology Electromagnetics

来源：评论

学校读者我要写书评

暂无评论

A Pipeline Extraction on Forward-Looking Sonar Images Using the Self-Organizing Map

A Pipeline Extraction on Forward-Looking Sonar Images Using ...

引用

International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Siwakorn Tulsook Teerasit Kasetkasem Yodyium Tipsuwan Nobuhiko Sugino Thitiporn Chanwimaluang Phakhachon Hoonsuwan Department of Electrical Engineering Kasetsart University Bangkok Thailand Department of Computer Engineering Kasetsart University Bangkok Thailand Department of Information processing Tokyo Institute of Technology Tokyo Japan National Electronics and Computer Technology Center (NECTEC) Pathumthani Thailand PTT Exploration and Production Public Company Limited (PTTEP) Bangkok Thailand

ISBN: (纸本)9781538635568;9781538635551

The underwater pipeline surveillance and inspection using an autonomous underwater vehicle (AUV) is the future of the oil and gas industries since the inspection using a remotely operated underwater vehicle (ROV) is very expensive. However, the successful deployment of AUVs relies on the accurate pipeline path extraction that can automatically navigate along its direction in real-time. Due to the limited visibility of the underwater environment, we proposed to use the forward-looking sonar (FLS) to overcome environment dependencies. However, the sonar images are very noisy from a nature of acoustic imaging itself. Thus, this paper mainly contributes a real-time pipeline extraction to overcome speckle noise and intensity inhomogeneity in FLS by utilizing cell-averaging constant false alarm rate (CACFAR) and the self-organizing map (SOM). In our experiment, the pipeline images data obtained from the Gulf of Thailand were used for the performance analysis where our method can accurately extract more than 89% of the dataset.

关键词： Pipelines Neurons Sonar Self-organizing feature maps Sonar navigation Inspection Data mining

来源：评论

学校读者我要写书评

暂无评论

Complete mitochondrial genome sequence for the black croakerAtrobucca nibe(Perciformes, Sciaenidae) and its phylogeny

引用

Mitochondrial DNA Part B 2019年第1期4卷 1816-1817页

作者： Xiaofei Qin Yimeng Liu Xia Yang Yongmin Mu Liang Zheng Yanming Sui Shanghai Key Laboratory of Contemporary Optics System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China Key Laboratory of East China Sea Fishery Resources Exploitation Ministry of AgricultureEast China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Shanghai China People's Hospital of Linyi Economic and Technological Development Zone Linyi China Institute of forensic science Luozhuang Branch of Linyi Municipal Public Security Bureau Linyi China

The blackmouth croaker,Atrobucca nibe(Jordan & Thompson, 1911), is one of the most important economic fish in China. The mitogenome ofA. nibewas determined in this study. The full circle length of the complete mitochondrial DNA was 16,505 bp. It contained 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and a control region (D-loop). All 21 tRNA genes can fold into a typical cloverleaf structure except for tRNASer (AGY). The phylogenetic analysis revealed thatA. nibeclustered into the three species of Sciaenidae (Pennahia microcephalus, Chrysochi aureusandProtonibea diacanthus).

关键词： Mitochondrial DNA Atrobucca nibe Sciaenidae

来源：评论

学校读者我要写书评

暂无评论

Combination of curcumin or chitosan with photodynamic therapy as an effective alternative therapy for overcoming wound infection associated with multidrug-resistant Acinetobacter baumannii

Microbe (Netherlands)

引用

Microbe (Netherlands) 2025年 7卷

作者： Yonpiam, Manta Wannigama, Dhammika Leshan Shein, Aye Mya Sithu Liao, Tingting Hurst, Cameron Monk, Peter N. Amarasiri, Mohan Phattharapornjaroen, Phatthranit Ounjai, Puey Saethang, Thammakorn Badavath, Vishnu Nayak Luk-in, Sirirat Nilgate, Sumanee Rirerm, Ubolrat Srisakul, Sukrit Ngamwongsatit, Natharin Leelahavanichkul, Asada Ragupathi, Naveen Kumar Devanga Kanjanabuch, Talerngsak Narkban, Phurin Miyanaga, Kazuhiko Cui, Longzhu Boontaveeyuwat, Einapak Higgins, Paul G. Kicic, Anthony Hamamoto, Hiroshi Abe, Shuichi Hongsing, Parichart Chatsuwan, Tanittha Department of Microbiology Faculty of Medicine Chulalongkorn University King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok Thailand Center of Excellence in Antimicrobial Resistance and Stewardship Research Faculty of Medicine Chulalongkorn University Bangkok Thailand Dual degree Medical Science program Faculty of Medicine Chulalongkorn University Bangkok 10330 Thailand Department of Infectious Diseases and Infection Control Yamagata Prefectural Central Hospital Yamagata Japan School of Medicine Faculty of Health and Medical Sciences The University of Western Australia Nedlands WA Australia Biofilms and Antimicrobial Resistance Consortium of ODA receiving countries The University of Sheffield Sheffield United Kingdom Pathogen Hunter's Research Team Department of Infectious Diseases and Infection Control Yamagata Prefectural Central Hospital Yamagata Japan Department of Infectious Diseases Faculty of Medicine Yamagata University Yamagata Japan Department of Clinical Epidemiology Faculty of Medicine Thammasat University Rangsit 10120 Thailand Department of Infection Immunity & Cardiovascular Disease University of Sheffield Medical School United Kingdom Department of Civil and Environmental Engineering Graduate School of Engineering Tohoku University Miyagi Japan Faculty of Health Science Technology Chulabhorn Royal Academy Bangkok 10210 Thailand HRH Princess Chulabhorn Disaster and Emergency Medicine Center Chulabhorn Royal Academy Bangkok 10210 Thailand Department of Biology Faculty of Science Mahidol University Bangkok Thailand Department of Computer Science Faculty of Science Kasetsart University Bangkok Thailand School of Pharmacy & Technology Management SVKM's Narsee Monjee Institute of Management Studies (NMIMS) Hyderabad 509301 India Department of Clinical Microbiology and Applied Technology Faculty of Medical Technology Mahidol University Bangkok Thailand Department of Clinical Sciences and Public Health Faculty of Veteri

The increasing prevalence of multidrug-resistant Acinetobacter baumannii as an opportunistic pathogen in wound infections raises significant concerns due to its antibiotic resistance and biofilm-mediated antibiotic tolerance. This underscores the urgent need to explore an alternative approach to effectively managing wound infections caused by MDR A. baumannii. In this study, combining subinhibitory concentrations of curcumin (25 µg/ml) or chitosan (156 µg/ml) with photodynamic therapy-PDT (10 J/cm²) resulted in a significant reduction of planktonic viabilities and biofilm biovolume of MDR A. baumannii clinical isolates in vitro. In murine A. baumannii-associated wound infection, a combination of curcumin (25 µg/ml) or chitosan (156 µg/ml) with PDT (10 J/cm²) resulted in complete bacterial eradication with wound healing at Day 15 of post-treatments with these combination therapies. Our study demonstrated that combining curcumin or chitosan with PDT at their subinhibitory concentrations represents a promising alternative strategy as localized therapy for effectively managing A. baumannii-associated wound infection. © 2025 The Authors

关键词： Acinetobacter baumannii Alternative therapy Biofilm eradication Chitosan Curcumin Multidrug-resistant (MDR) Photodynamic therapy (PDT) Wound infection

来源：评论

学校读者我要写书评

暂无评论

Global daily CO2 emissions for the year 2020

arXiv

引用

arXiv 2021年

作者： Liu, Zhu Deng, Zhu Ciais, Philippe Tan, Jianguang Zhu, Biqing Davis, Steven J. Andrew, Robbie Boucher, Olivier Arous, Simon Ben Canadell, Pep Dou, Xinyu Friedlingstein, Pierre Gentine, Pierre Guo, Rui Hong, Chaopeng Jackson, Robert B. Kammen, Daniel M. Ke, Piyu Le Quere, Corinne Monica, Crippa Janssens-Maenhout, Greet Peters, Glen Tanaka, Katsumasa Wang, Yilong Zheng, Bo Zhong, Haiwang Sun, Taochun Schellnhuber, Hans Joachim Department of Earth System Science Tsinghua University Beijing100084 China Laboratoire des Sciences du Climate et de l'Environnement LSCE Orme de Merisiers Gif-sur-Yvette91191 France Department of Earth System Science University of California Irvine 3232 Croul Hall IrvineCA92697-3100 United States CICERO Center for International Climate Research Oslo Norway Institute Pierre-Simon Laplace Sorbonne Université/CNRS Paris France Kayrros 33 Rue La Fayette ParisFR 75009 France Global Carbon Project CSIRO Oceans and Atmosphere Australia Capital Territory Australia College of Engineering Mathematics and Physical Sciences University of Exeter Exeter United Kingdom Department of Earth & Environment Sciences Columbia University United States Earth System Science Department Woods Institute for the Environment Precourt Institute for Energy Stanford University StanfordCA United States Energy and Resources Group Goldman School of Public Policy University of California BerkeleyCA United States School of Environmental Science The Tyndall Centre for Climate Change Research University of East Anglia Norwich United Kingdom Ispra Italy Center for Global Environmental Research National Institute for Environmental Studies Tsukuba Japan Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzheng China Department of Electrical Engineering Tsinghua University Beijing100084 China Potsdam Institute for Climate Impact Research Potsdam14412 Germany

The diurnal cycle CO2 emissions from fossil fuel combustion and cement production reflect seasonality, weather conditions, working days, and more recently the impact of the COVID-19 pandemic. Here, for the first time we provide a daily CO2 emission dataset for the whole year of 2020 calculated from inventory and near-real-time activity data (called Carbon Monitor project: https://***) for power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and residential fuel use sectors (which we estimate for 206 countries). It was previously suggested from preliminary estimates that did not cover the entire year of 2020 that the pandemics may have caused more than 8% annual decline of global CO2 emissions. Here we show from detailed estimates of the full year data that the global reduction was only 5.4% (-1,901 MtCO2, ±7.2% for 2-sigma range). This decrease is 5 times larger than the annual emission drop at the peak of the 2008 Global Financial Crisis. However, global CO2 emissions gradually recovered towards 2019 levels from late April with global partial re-opening. More importantly, global CO2 emissions even increased slightly by +0.9% in December 2020 compared with 2019, indicating the trends of rebound of global emissions. Later waves of COVID-19 infections in late 2020 and corresponding lockdowns have caused further CO2 emissions reductions particularly in western countries, but to a much smaller extent than the declines in the first wave. Despite partial mobility restrictions in European countries and in some US States that have been affected by the second and third waves of the pandemics, emission reductions observed in Autumn 2020 were much smaller than those of Spring 2020. That even substantial world-wide lockdowns of activity led to a one-time decline in global CO2 emissions of only 5.4% in one year highlights the significant challenges for climate change mitigation

关键词： Fossil fuels

来源：评论

学校读者我要写书评

暂无评论

Algorithms that remember: model inversion attacks and data protection law

arXiv

引用

arXiv 2018年

作者： Veale, Michael Binns, Reuben Edwards, Lilian Department of Science Technology Engineering and Public Policy University College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom Newcastle Law School Newcastle University Newcastle United Kingdom

Many individuals are concerned about the governance of machine learning systems and the prevention of algorithmic harms. The EU’s recent General Data Protection Regulation (GDPR) has been seen as a core tool for achieving better governance of this area. While the GDPR does apply to the use of models in some limited situations, most of its provisions relate to the governance of personal data, while models have traditionally been seen as intellectual property. We present recent work from the information security literature around ‘model inversion’ and ‘membership inference’ attacks, which indicates that the process of turning training data into machine-learned systems is not one way, and demonstrate how this could lead some models to be legally classified as personal data. Taking this as a probing experiment, we explore the different rights and obligations this would trigger and their utility, and posit future directions for algorithmic governance and regulation. This article is part of the theme issue ‘Governing artificial intelligence: ethical, legal and technical opportunities and challenges’. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

App-delivered self-management intervention trial self BACK for people with low back pain: Protocol for implementation and process evaluation

引用

JMIR Research Protocols 2020年第10期9卷 e20308页

作者： Rasmussen, Charlotte Diana Nørregaard Svendsen, Malene Jagd Wood, Karen Nicholl, Barbara I. Mair, Frances S. Sandal, Louise Fleng Mork, Paul Jarle Søgaard, Karen Bach, Kerstin Stochkendahl, Mette Jensen National Research Centre for the Working Environment Copenhagen Denmark Department of Sports Science and Clinical Biomechanics University of Denmark Odense M Denmark Institute of Health & Wellbeing University of Glasgow Glasgow United Kingdom Department of Public Health and Nursing Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway Department of Clinical Research University of Southern Denmark Odense M Denmark Department of Computer Science Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway Institute of Sports Science and Clinical Biomechanics University of Southern Denmark Odense M Denmark Nordic Institute of Chiropractic and Clinical Biomechanics Odense M Denmark

Background: Implementation and process evaluation is vital for understanding how interventions function in different settings, including if and why interventions have different effects or do not work at all. Objective: This paper presents the protocol for an implementation and process evaluation embedded in a multicenter randomized controlled trial conducted in Denmark and Norway (the selfBACK project). selfBACK is a data-driven decision support system that provides participants with weekly self-management plans for low back pain. These plans are delivered through a smartphone app and tailored to individual participants by using case-based reasoning methodology. In the trial, we compare selfBACK in addition to usual care with usual care alone. Methods: The aim of this study is to conduct a convergent mixed-methods implementation and process evaluation of the selfBACK app by following the reach, effectiveness, adoption, implementation, and maintenance framework. We will evaluate the process of implementing selfBACK and investigate how participants use the intervention in daily life. The evaluation will also cover the reach of the intervention, health care provider willingness to adopt it, and participant satisfaction with the intervention. We will gather quantitative measures by questionnaires and measures of data analytics on app use and perform a qualitative exploration of the implementation using semistructured interviews theoretically informed by normalization process theory. Data collection will be conducted between March 2019 and October 2020. Results: The trial opened for recruitment in February 2019. This mixed-methods implementation and evaluation study is embedded in the randomized controlled trial and will be collecting data from March 2019 to October 2020;dissemination of trial results is planned thereafter. The results from the process evaluation are expected 2021-2022. Conclusions: This study will provide a detailed understanding of how self-management

关键词： Decision support system Digital health intervention Implementation Low back pain MHealth Process evaluation Randomized controlled trial RE-AIM

来源：评论

学校读者我要写书评

暂无评论

Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach

arXiv

引用

arXiv 2018年

作者： Huggins, Jonathan H. Kasprzak, Mikolaj Campbell, Trevor Broderick, Tamara Department of Biostatistics Harvard T. H. Chan School of Public Health Department of Statistics University of Oxford Department of Statistics University of British Columbia Department of Electrical Engineering and Computer Science MIT

Bayesian inference typically requires the computation of an approximation to the posterior distribution. An important requirement for an approximate Bayesian inference algorithm is to output high-accuracy posterior mean and uncertainty estimates. Classical Monte Carlo methods, particularly Markov Chain Monte Carlo, remain the gold standard for approximate Bayesian inference because they have a robust finite-sample theory and reliable convergence diagnostics. However, alternative methods, which are more scalable or apply to problems where Markov Chain Monte Carlo cannot be used, lack the same finite-data approximation theory and tools for evaluating their accuracy. In this work, we develop a flexible new approach to bounding the error of mean and uncertainty estimates of scalable inference algorithms. Our strategy is to control the estimation errors in terms of Wasserstein distance, then bound the Wasserstein distance via a generalized notion of Fisher distance. Unlike computing the Wasserstein distance, which requires access to the normalized posterior distribution, the Fisher distance is tractable to compute because it requires access only to the gradient of the log posterior density. We demonstrate the usefulness of our Fisher distance approach by deriving bounds on the Wasserstein error of the Laplace approximation and Hilbert coresets. We anticipate that our approach will be applicable to many other approximate inference methods such as the integrated Laplace approximation, variational inference, and approximate Bayesian computation. Copyright © 2018, The Authors. All rights reserved.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Validating and modeling the impact of high-frequency rapid antigen screening on COVID-19 spread and outcomes

Research Square

引用

Research Square 2020年

作者： Nash, Beatrice Badea, Anthony Reddy, Ankita Bosch, Miguel Salcedo, Nol Gomez, Adam R. Versiani, Alice Silva, Gislaine Celestino Dutra dos Santos, Thayza Maria Izabel Lopes Milhim, Bruno H.G.A. Moraes, Marilia M. Campos, Guilherme Rodrigues Fernandes Quieroz, Flávia Reis, Andreia Francesli Negri Nogueira, Mauricio L. Naumova, Elena N. Bosch, Irene Herrera, Bobby Brooke E25Bio Inc. CambridgeMA United States Department of Computer Science Harvard University School of Engineering and Applied Sciences CambridgeMA United States Department of Physics Harvard University CambridgeMA United States Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States InfoGeosciences LLC HoustonTX United States São José do Rio Preto Brazil Division of the Nutrition Epidemiology and Data Science Friedman School of Nutrition Science and Policy Tufts University BostonMA United States Department of Medicine Mount Sinai School of Medicine New YorkNY United States Department of Immunology and Infectious Diseases Harvard T.H. Chan School of Public Health BostonMA United States

High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. We use computational modeling, coupled with clinical data from rapid antigen tests, to predict the impact of frequent viral antigen rapid testing on COVID-19 spread and outcomes. Using patient nasal or nasopharyngeal swab specimens, we demonstrate that the sensitivity/specificity of two rapid antigen tests compared to quantitative real-time polymerase chain reaction (qRT-PCR) are 80.0%/91.1% and 84.7%/85.7%, respectively;moreover, sensitivity correlates directly with viral load. Based on COVID-19 data from three regions in the United States and São José do Rio Preto, Brazil, we show that high frequency, strategic population-wide rapid testing, even at varied accuracy levels, diminishes COVID-19 infections, hospitalizations, and deaths at a fraction of the cost of nucleic acid detection via qRT-PCR. We propose large-scale antigen-based surveillance as a viable strategy to control SARSCoV-2 spread and to enable societal re-opening. © 2020, CC BY.

关键词： Antigens

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：