检索结果-内蒙古大学图书馆

Methodology for the characterisation of the impact of TEC fluctuations and scintillation on ground positioning quality over South America and North Europe, with implications for forecasts

引用

Advances in Space Research 2024年

作者： Forte, Biagio Allbrook, Tom Arnold, Alex Astin, Ivan César Vani, Bruno Francisco Galera Monico, João Hirokazu Shimabukuro, Milton Koulouri, Alexandra Mormi John, Habila Department of Electronic and Electrical Engineering University of Bath BA2 7AY Bath United Kingdom Federal Institute of Education Science and Technology of São Paulo – IFSP - Department of Informatics - Rua Jose Ramos Junior 27-50 - Presidente Epitacio State of Sao Paulo 19470-000 Brazil Sao Paulo State University - UNESP - Department of Cartography – Rua Roberto Simonsen 305 - Presidente Prudente State of Sao Paulo 19060-900 Brazil Sao Paulo State University – UNESP - Department of Mathematics and Computer Science - Rua Roberto Simonsen 305 - Presidente Prudente State of Sao Paulo 19060-900 Brazil Faculty of Information Technology and Communication Sciences Tampere University P.O. Box 692 Tampere33101 Finland

A variety of economic sectors rely upon the use of Global Navigation Satellite Systems (GNSS) in areas such as autonomous navigation, timing, land management, oil exploration, precision agriculture, civil aviation. Spatial and temporal gradients (or irregularities) in the ionospheric plasma density distribution introduce disturbances on the propagation of GNSS radio signals. These propagation disturbances originate additional errors and outages that degrade the positioning quality, thus producing an impact on GNSS-based applications. The quantification of the impact that ionospheric disturbances can have on GNSS users is important because mitigation strategies can be implemented accordingly. Although the morphology of ionospheric disturbances is well understood, the prediction of their impact on GNSS applications still represents a challenge: in this respect, traditional maps of ionospheric indices do not provide helpful information to users and services regarding the impact. The main limitation is due to the difficulty in accurately describing and forecasting the spatial and temporal variability of ionospheric irregularities and their likely impact on the quality of ground positioning and navigation. Here, a novel method was developed for the characterisation of the spatial and temporal variability of the propagation disturbances associated with the presence of ionospheric irregularities and how this relates to the impact on ground positioning likely to be experienced by users over a given region and a given temporal interval. The method is based on the combination of the concept of sky maps (describing the occurrence of ionospheric disturbances by means of joint probabilities) and the concept of ground maps (describing the impact on the ground positioning quality by means of the 3-D positioning error, the time dilution of precision, and the occurrence of data gaps). The method can be utilised in near real time or in conjunction with a prediction model. The method

关键词： Plasma density

来源：评论

学校读者我要写书评

暂无评论

Continuous prediction of lower-limb kinematics from multi-modal biomedical signals

arXiv

引用

arXiv 2021年

作者： Yi, Chunzhi Jiang, Feng Zhang, Shengping Guo, Hao Yang, Chifu Ding, Zhen Wei, Baichun Lan, Xiangyuan Zhou, Huiyu School of Mechatronics Engineering Harbin Institute of Technology Harbin Heilongjiang150001 China School of Computer Harbin Institute of Technology Harbin Heilongjiang150001 China Pengcheng Laboratory Shenzhen Guangdong China School of Computer Science and Technology Harbin Institute of Technology Weihai264209 China Department of Computer Science Hong Kong Baptist University Hong Kong School of Informatics University of Leicester LeicesterLE1 7RH United Kingdom

The fast-growing techniques of measuring and fusing multi-modal biomedical signals enable advanced motor intent decoding schemes of lower-limb exoskeletons, meeting the increasing demand for rehabilitative or assistive applications of take-home healthcare. Challenges of exoskeletons’ motor intent decoding schemes remain in making a continuous prediction to compensate for the hysteretic response caused by mechanical transmission. In this paper, we solve this problem by proposing an ahead-of-time continuous prediction of lower-limb kinematics, with the prediction of knee angles during level walking as a case study. Firstly, an end-to-end kinematics prediction network(KinPreNet)1, consisting of a feature extractor and an angle predictor, is proposed and experimentally compared with features and methods traditionally used in ahead-of-time prediction of gait phases. Secondly, inspired by the electromechanical delay(EMD), we further explore our algorithm’s capability of compensating response delay of mechanical transmission by validating the performance of the different sections of prediction time. And we experimentally reveal the time boundary of compensating the hysteretic response. Thirdly, a comparison of employing EMG signals or not is performed to reveal the EMG and kinematic signals’ collaborated contributions to the continuous prediction. During the experiments, EMG signals of nine muscles and knee angles calculated from inertial measurement unit (IMU) signals are recorded from ten healthy subjects. Our algorithm can predict knee angles with the averaged RMSE of 3.98 deg which is better than the 15.95-deg averaged RMSE of utilizing the traditional methods of ahead-of-time prediction. The best prediction time is in the interval of 27ms and 108ms. To the best of our knowledge, this is the first study of continuously predicting lower-limb kinematics in an ahead-of-time manner based on the electromechanical delay (EMD). © 2021, CC BY.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs

arXiv

引用

arXiv 2024年

作者： Wang, Fan Zou, Zhilin Sakla, Nicole Partyka, Luke rawal, Nil Singh, Gagandeep Zhao, Wei Ling, Haibin Huang, Chuan Prasanna, Prateek Chen, Chao Department of Computer Science State University of New York Stony BrookNY United States Department of Radiology Newark Beth Israel Medical Center NJ United States Department of Radiology Columbia University Irving Medical Center NY United States Department of Radiology and Imaging Sciences Emory University School of Medicine GA United States Department of Radiology State University of New York Stony BrookNY United States Department of Biomedical Informatics State University of New York Stony BrookNY United States Department of Biomedical Engineering Georgia Institute of Technology Emory University AtlantaGA United States

Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures. Existing quantitative approaches, like radiomics and deep learning models, lack explicit quantification of intricate and subtle parenchymal structures, including fibroglandular tissue. To address this, we propose a novel topological approach that explicitly extracts multi-scale topological structures to better approximate breast parenchymal structures, and then incorporates these structures into a deep-learningbased prediction model via an attention mechanism. Our topology-informed deep learning model, TopoTxR, leverages topology to provide enhanced insights into tissues critical for disease pathophysiology and treatment response. We empirically validate TopoTxR using the VICTRE phantom breast dataset, showing that the topological structures extracted by our model effectively approximate the breast parenchymal structures. We further demonstrate TopoTxR's efficacy in predicting response to neoadjuvant chemotherapy. Our qualitative and quantitative analyses suggest differential topological behavior of breast tissue in treatment-naive imaging, in patients who respond favorably to therapy as achieving pathological complete response (pCR) versus those who do not. In a comparative analysis with several baselines on the publicly available I-SPY 1 dataset (N=161, including 47 patients with pCR and 114 without) and the Rutgers proprietary dataset (N=120, with 69 patients achieving pCR and 51 not), TopoTxR demonstrates a notable improvement, achieving a 2.6% increase in accuracy and a 4.6% enhancement in AUC compared to the state-of-the-art method. © 2024, CC BY-NC-ND.

关键词： Chemotherapy

来源：评论

学校读者我要写书评

暂无评论

Scientific discovery in the age of artificial intelligence

引用

NATURE 2023年第7978期621卷 E33-E33页

作者： Wang, Hanchen Fu, Tianfan Du, Yuanqi Gao, Wenhao Huang, Kexin Liu, Ziming Chandak, Payal Liu, Shengchao Van Katwyk, Peter Deac, Andreea Anandkumar, Anima Bergen, Karianne Gomes, Carla P. Ho, Shirley Kohli, Pushmeet Lasenby, Joan Leskovec, Jure Liu, Tie-Yan Manrai, Arjun Marks, Debora ramsundar, Bharath Song, Le Sun, Jimeng Tang, Jian Velickovic, Petar Welling, Max Zhang, Linfeng Coley, Connor W. Bengio, Yoshua Zitnik, Marinka Department of Engineering University of Cambridge Cambridge UK Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA NVIDIA Santa Clara CA USA Department of Computational Science and Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Science Cornell University Ithaca NY USA Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science Stanford University Stanford CA USA Department of Physics Massachusetts Institute of Technology Cambridge MA USA Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA Mila – Quebec AI Institute Montreal Quebec Canada Université de Montréal Montreal Quebec Canada HEC Montréal Montreal Quebec Canada CIFAR AI Chair Toronto Ontario Canada Department of Earth Environmental and Planetary Sciences Brown University Providence RI USA Data Science Institute Brown University Providence RI USA Center for Computational Astrophysics Flatiron Institute New York NY USA Department of Astrophysical Sciences Princeton University Princeton NJ USA Department of Physics Carnegie Mellon University Pittsburgh PA USA Department of Physics and Center for Data Science New York University New York NY USA Google DeepMind London UK Department of Computer Science and Technology University of Cambridge Cambridge UK Microsoft Research Beijing China Department of Biomedical Informatics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Harvard Data Science Initiative Cambridge MA USA Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Cambridge MA USA Department of Systems Biology Harvard Medical School Boston MA USA Deep Forest Sciences Palo Alto CA USA BioMap Beijing China Mo

来源：评论

学校读者我要写书评

暂无评论

Cybersecurity revisited: Honeytokens meet Google authenticator

arXiv

引用

arXiv 2021年

作者： Papaspirou, Vasilis Papathanasaki, Maria Maglaras, Leandros A. Kantzavelou, Ioanna Douligeris, Christos Ferrag, Mohamed Amine Janicke, Helge Department of Informatics and Computer Engineering University of West Attica Athens Greece Department of CS and Telecommunications University of Thessaly Lamia Greece Cyber Technology Institute De Montfort University Leicester United Kingdom Department of Informatics University of Piraeus Piraeus Greece Department of Computer Science Guelma University Guelma Algeria Cyber Security CRC Edith Cowan University Perth6027 Australia

Although sufficient authentication mechanisms were enhanced by the use of two or more factors that resulted in new multi factor authentication schemes, more sophisticated and targeted attacks have shown they are also vulnerable. This research work proposes a novel two factor authentication system that incorporates honeytokens into the two factor authentication process. The current implementation collaborates with Google authenticator. The novelty and simplicity of the presented approach aims at providing additional layers of security and protection into a system and thus making it more secure through a stronger and more efficient authentication mechanism. © 2021, CC BY.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

A survey on deep learning in medical image reconstruction

引用

Intelligent Medicine 2021年第3期1卷 118-127页

作者： Emmanuel Ahishakiye Martin Bastiaan Van Gijzen Julius Tumwiine Ruth Wario Johnes Obungoloch Department of Computer Science Kyambogo UniversityP.O Box 1KyambogoKampalaUganda Delft University of Technology Delft Institute of Applied MathematicsMekelweg 42628 CDthe Netherlands Department of Mathematics Mbarara University of Science and TechnologyMbarara 1410Uganda Department of Informatics University of Free StateSouth Africa Department of Biomedical Sciences and Engineering Mbarara University of Science and TechnologyMbarara 1410Uganda

Medical image reconstruction aims to acquire high-quality medical images for clinical usage at minimal cost and risk to the *** learning and its applications in medical imaging,especially in image reconstruction have received considerable attention in the literature in recent *** study reviews records obtained elec-tronically through the leading scientific databases(Magnetic Resonance Imaging journal,Google Scholar,Scopus,Science Direct,Elsevier,and from other journal publications)searched using three sets of keywords:(1)Deep learning,image reconstruction,medical imaging;(2)Medical imaging,Deep learning,Image reconstruction;(3)Open science,Open imaging data,Open *** articles reviewed revealed that deep learning-based re-construction methods improve the quality of reconstructed images qualitatively and ***,deep learning techniques are generally computationally expensive,require large amounts of training datasets,lack decent theory to explain why the algorithms work,and have issues of generalization and *** challenge of lack of enough training datasets is currently being addressed by using transfer learning techniques.

关键词： Deep learning Open science Image reconstruction Medical imaging Machine Learning

来源：评论

学校读者我要写书评

暂无评论

Shooting-projection method for a small object moving under the influence of a force 10

Shooting-projection method for a small object moving under t...

引用

202 10th International Conference on engineering Mathematics and Physics, ICEMP 2021

作者： Filipov, S.M. Faragó, I. Avdzhieva, A. Department of Computer Science Faculty of Chemical and System Engineering University of Chemical Technology and Metallurgy 8 St. Kliment Ohridski Blvd. Sofia1756 Bulgaria Department of Differential Equations Institute of Mathematics Budapest University of Technology and Economics MTA-ELTE Research Group Egry József u. 1 Budapest1111 Hungary Department of Numerical Methods Faculty of Mathematics and Informatics Sofia University St. Kliment Ohridski 5 James Bourchier Blvd. Sofia1164 Bulgaria

We consider a small object in 3D moving under the influence of a force that may depend explicitly on time, on the position of the object, and on its velocity. The equations of motion of classical mechanics are assumed to hold. If the position of the object is specified at some initial and some final time, obtaining the trajectory of the object requires the solution of a two-point boundary value problem. To solve the problem various numerical technics can be applied. This paper extends the recently proposed shooting-projection method to 3D. We introduce a Lagrangian from which, applying the principle of least action, the projection trajectory is derived. Analysis of the action reveals the meaning of the projection trajectory. Using the shooting-projection method, the considered two-point boundary value problem is solved for the case of a projectile motion in the presence of air resistance and wind. © 2021 institute of Physics Publishing. All rights reserved.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Retraction Note: Multiclass skin lesion classification using deep learning networks optimal information fusion

引用

Discover Applied Sciences 2025年第1期7卷 1-1页

作者： Khan, Muhammad Attique Hamza, Ameer Shabaz, Mohammad Kadry, Seifeine Rubab, Saddaf Bilal, Muhammad Abdullah Akbar, Muhammad Naeem Kesavan, Suresh Manic Department of Computer Science HITEC University Taxila Pakistan Model Institute of Engineering and Technology Jammu India Department of Applied Data Science Noroff University College Oslo Norway Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of CS SEECS NUST Islamabad Pakistan National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Electrical and Communication Engineering National University of Science and Technology Muscat Sultanate of Oman

来源：评论

学校读者我要写书评

暂无评论

Power of sequential protocols in hidden quantum channel discrimination

arXiv

引用

arXiv 2023年

作者： Sugiura, Sho Dutt, Arkopal Munro, William J. Zeytinoǧlu, Sina Chuang, Isaac L. Physics and Informatics Laboratory Ntt Research Inc. 940 Stewart Dr. SunnyvaleCA94085 United States Laboratory for Nuclear Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Co-Design Center for Quantum Advantage Massachusetts Institute of Technology CambridgeMA02139 United States Ntt Basic Research Laboratories Research Center for Theoretical Quantum Physics 3-1 Morinosato-Wakamiya Kanagawa Atsugi243-0198 Japan Department of Physics Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

In many natural and engineered systems, unknown quantum channels act on a subsystem that cannot be directly controlled and measured, but is instead learned through a controllable subsystem that weakly interacts with it. We study quantum channel discrimination (QCD) under these restrictions, which we call hidden system QCD (HQCD). We find that sequential protocols achieve perfect discrimination and saturate the Heisenberg limit. In contrast, depth-1 parallel and multi-shot protocols cannot solve HQCD. This suggests that sequential protocols are superior in experimentally realistic situations. Copyright © 2023, The Authors. All rights reserved.

关键词： Communication channels (information theory)

来源：评论

学校读者我要写书评

暂无评论

Selecting for positive responses to knock outs in boolean networks 1

引用

14th International Workshop on Artificial Life and Evolutionary Computation, WIVACE 2019

作者： Villani, Marco Magrì, Salvatore Roli, Andrea Serra, Roberto Department of Physics Informatics and Mathematics University of Modena and Reggio Emilia Modena Italy European Centre for Living Technology Venice Italy Department of Computer Science and Engineering University of Bologna Cesena Italy Institute for Advanced Study University of Amsterdam Amsterdam Netherlands

ISBN: (数字)9783030450168

ISBN: (纸本)9783030450151

random Boolean networks are a widely acknowledged model for cell dynamics. Previous studies have shown the possibility of achieving Boolean Networks (BN) with given characteristics by means of evolutionary techniques. In this work we show that it is possible to evolve BNs exhibiting more positive than negative reactions to knock-out stresses. It is also interesting to observe that in the observed runs (i) the evolutionary processes can guide the BNs toward different dynamic regimes, depending on their internal structure and that (ii) the BNs forced to evolve by maintaining a critical dynamical regime achieve better results than those that do not have this characteristic;this observation supports the idea that criticality may be beneficial to an evolving population of dynamical systems. © Springer Nature Switzerland AG 2020.

关键词： Dynamical systems

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：