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Creating expert knowledge by relying on language learners: A generic approach for mass-producing language resources by combining implicit crowdsourcing and language learning 12

Creating expert knowledge by relying on language learners: A...

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12th International Conference on Language Resources and Evaluation, LREC 2020

作者： Nicolas, Lionel Lyding, Verena Borg, Claudia Forascu, Corina Fort, Karën Zdravkova, Katerina Kosem, Iztok Cibej, Jaka Holdt, Špela Arhar Millour, Alice König, Alexander Rodosthenous, Christos Sangati, Federico Ul Hassan, Umair Katinskaia, Anisia Barreiro, Anabela Aparaschivei, Lavinia HaCohen-Kerner, Yaakov Institute for Applied Linguistics Eurac Research Bolzano Italy Faculty of Information and Communication Technology University of Malta Msida Malta Faculty of Computer Science Alexandru Ioan Cuza University of Iasi Romania Sorbonne Université STIH - EA 4509 France Ss. Cyril and Methodius University Faculty of Computer Science and Engineering Macedonia Faculty of Arts University of Ljubljana Slovenia CLARIN ERIC Netherlands Computational Cognition Lab Open University of Cyprus Cyprus Orientale University of Naples Italy Insight Centre for Data Analytics National University of Ireland Galway Ireland Department of Computer Science University of Helsinki Finland Human Languages Technologies Lab INESC-ID Lisbon Portugal Israel

ISBN: (纸本)9791095546344

We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved. We present the approach by explaining its core paradigm that consists in pairing specific types of LRs with specific exercises, by detailing both its strengths and challenges, and by discussing how much these challenges have been addressed at present. Accordingly, we also report on on-going proof-of-concept efforts aiming at developing the first prototypical implementation of the approach in order to correct and extend an LR called ConceptNet based on the input crowdsourced from language learners. We then present an international network called the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect) that provides the context to accelerate the implementation of the generic approach. Finally, we exemplify how it can be used in several language learning scenarios to produce a multitude of NLP resources and how it can therefore alleviate the long-standing NLP issue of the lack of LRs. © European Language Resources Association (ELRA), licensed under CC-BY-NC

关键词： Crowdsourcing

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Quasi-potential as an implicit regularizer for the loss function in the stochastic gradient descent.

arXiv

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arXiv 2019年

作者： Hu, Wenqing Zhu, Zhanxing Xiong, Haoyi Huan, Jun Department of Mathematics and Statistics Missouri University of Science and Technology University of Missouri Rolla Peking University Beijing Institute of Big Data Research Beijing China Big Data Lab Baidu Inc. National Engineering Laboratory of Deep Learning Application and Technology

We interpret the variational inference of the Stochastic Gradient Descent (SGD) as minimizing a new potential function named the quasi-potential. We analytically construct the quasi-potential function in the case when the loss function is convex and admits only one global minimum point. We show in this case that the quasi-potential function is related to the noise covariance structure of SGD via a partial differential equation of Hamilton-Jacobi type. This relation helps us to show that anisotropic noise leads to faster escape than isotropic noise. We then consider the dynamics of SGD in the case when the loss function is non-convex and admits several different local minima. In this case, we demonstrate an example that shows how the noise covariance structure plays a role in "implicit regularization", a phenomenon in which SGD favors some particular local minimum points. This is done through the relation between the noise covariance structure and the quasi-potential function. Our analysis is based on Large Deviations Theory (LDT), and they are validated by numerical experiments. Copyright © 2019, The Authors. All rights reserved.

关键词： Stochastic systems

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Ensemble Learning Based Sleeping Cell Detection in Cloud Radio Access Networks

Ensemble Learning Based Sleeping Cell Detection in Cloud Rad...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Zhao Ming Chuan Sun Xiuhua Li Qilin Fan Xiaofei Wang Victor C. M. Leung School of Big Data & Software Engineering Chongqing University Chongqing China TKLAN College of Intelligence & Computing Tianjin University Tianjin China College of Computer Science & Software Engineering Shenzhen University Shenzhen China Department of Electrical & Computer Engineering The University of British Columbia Vancouver Canada

ISBN: (数字)9781728180861

ISBN: (纸本)9781728180878

Sleeping cell problem refers to the degradation or unavailability of network services without triggered alarm, which is one of the most critical issues in current mobile networks. This problem is generally not detectable by the operators but only revealed after users' complaints occur. Therefore, it leads to the degradations of network performance in the service provision in the long run. To address this problem, we introduce a cloud-based sleeping cell detection platform into radio access networks (RANs) to detect the sleeping cells and deal with them automatically. In the cloud RANs (C-RANs), we combine and improve different methods employed in the pioneering studies in this field, and creatively use labeled training data and ensemble learning method for improving the accuracy. Particularly, we utilize expert optimization experience for further improving the detection framework. To evaluate the proposed ensemble learning based sleeping cell detection framework, we use a time-series dataset of Key Performance Indicator (KPI) in a real-world network. Trace-driven evaluation results show that the proposed framework can achieve up to 14.38% and 20.50% improvements compared with two existing schemes, respectively.

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Deep reinforcement learning for motion planning of mobile robots

arXiv

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arXiv 2019年

作者： Butyrev, Leonid Edelhäußer, Thorsten Mutschler, Christopher Fraunhofer Institute for Integrated Circuits Iis Precise Positioning and Analytics Department Machine Learning and Information Fusion Group Nuremberg Germany Computer Science Department Machine Learning and Data Analytics Lab Erlangen Germany

This paper presents a novel motion and trajectory planning algorithm for nonholonomic mobile robots that uses recent advances in deep reinforcement learning. Starting from a random initial state, i.e., position, velocity and orientation, the robot reaches an arbitrary target state while taking both kinematic and dynamic constraints into account. Our deep reinforcement learning agent not only processes a continuous state space it also executes continuous actions, i.e., the acceleration of wheels and the adaptation of the steering angle. We evaluate our motion and trajectory planning on a mobile robot with a differential drive in a simulation environment. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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Semantic filtering through deep source separation on microscopy images

arXiv

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arXiv 2019年

作者： Javer, Avelino Rittscher, Jens Institute of Biomedical Engineering Department of Engineering Science University of Oxford United Kingdom Big Data Institute University of Oxford United Kingdom

By their very nature microscopy images of cells and tissues consist of a limited number of object types or components. In contrast to most natural scenes, the composition is known a priori. Decomposing biological images into semantically meaningful objects and layers is the aim of this paper. Building on recent approaches to image de-noising we present a framework that achieves state-of-the-art segmentation results requiring little or no manual annotations. Here, synthetic images generated by adding cell crops are sufficient to train the model. Extensive experiments on cellular images, a histology data set, and small animal videos demonstrate that our approach generalizes to a broad range of experimental settings. As the proposed methodology does not require densely labelled training images and is capable of resolving the partially overlapping objects it holds the promise of being of use in a number of different applications. Copyright © 2019, The Authors. All rights reserved.

关键词： Histology

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Synchronized sensor insoles for clinical gait analysis in home-monitoring applications

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Current Directions in Biomedical Engineering 2018年第1期4卷 433-437页

作者： Roth, Nils Martindale, Christine F. Gaßner, Heiko Kohl, Zacharias Klucken, Jochen Eskofer, Bjoern M. Machine Learning and Data Analytics Lab. Department of Computer Science Friedrich-Alexander-University Erlangen-Nürnberg (FAU) Erlangen Germany Department of Molecular Neurology University Hospital Erlangen Germany

Wearable sensor systems are of increasing interest in clinical gait analysis. However, little information about gait dynamics of patients under free living conditions is available, due to the challenges of integrating such systems unobtrusively into a patient's everyday live. To address this limitation, new, fully integrated low power sensor insoles are proposed, to target applications particularly in home-monitoring scenarios. The insoles combine inertial as well as pressure sensors and feature wireless synchronization to acquire biomechanical data of both feet with a mean timing offset of 15.0 μs. The proposed system was evaluated on 15 patients with mild to severe gait disorders against the GAITRite® system as reference. Gait events based on the insoles' pressure sensors were manually extracted to calculate temporal gait features such as double support time and double support. Compared to the reference system a mean error of 0.06 s ± 0.06 s and 3.89 % ± 2.61 % was achieved, respectively. The proposed insoles proved their ability to acquire synchronized gait parameters and address the requirements for home-monitoring scenarios, pushing the boundaries of clinical gait analysis. © 2018 Nils Roth et al.

关键词： Synchronization

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Effects of annotation granularity in deep learning models for histopathological images

Effects of annotation granularity in deep learning models fo...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Jiangbo Shi Zeyu Gao Haichuan Zhang Pargorn Puttapirat Chunbao Wang Xiangrong Zhang Chen Li National Engineering Lab for Big Data Analytics Xi'an Jiao tong University Department of Pathology the First Affiliated Hospital of Xi'an Jiaotong University Institute of Intelligent Information Processing Xidian University

ISBN: (纸本)9781728118680

Pathological is crucial to cancer diagnosis. Usually, Pathologists draw their conclusion based on observed cell and tissue structure on histology slides. Rapid development in machine learning, especially deep learning have established robust and accurate classifiers. They are being used to analyze histopathological slides and assist pathologists in diagnosis. Most machine learning systems rely heavily on annotated data sets to gain experiences and knowledge to correctly and accurately perform various tasks such as classification and segmentation. Generally, annotations made in pathology-related datasets have inherited annotation methods from natural scene images. This work investigates different granularity of annotations in histopathological data set including image-wise, bounding box, ellipse-wise, and pixel-wise to verify the influence of annotation in pathological slide on deep learning models. We design corresponding experiments to test classification and segmentation performance of deep learning models based on annotations with different annotation granularity. In classification, state-of-the-art deep learning-based classifiers perform better when trained by pixel-wise annotation dataset. On average, precision, recall and F1-score improves by 7.87%, 8.83% and 7.85% respectively. Thus, it is suggested that finer granularity annotations are better utilized by deep learning algorithms in classification tasks. Similarly, semantic segmentation algorithms can achieve 8.33% better segmentation accuracy when trained by pixel-wise annotations. Our study shows not only that finer-grained annotation can improve the performance of deep learning models, but also help they extract more accurate phenotypic information from histopathological slides. The accurate and spatially precise acquisitions of phenotypic information can improve the reliability of the model prediction. Intelligence systems trained on granular annotations may help pathologists inspecting certain regions a

关键词： histopathological image annotation granularity deep learning classification semantic segmentation ANNOTATIONS Machine Learning Taxonomy Slide Pathologists Slide dataset slump

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Analysis of IMF Orientation and Pc5 Power During St. Patrick Geomagnetic Storm on 17 March 2015

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Journal of Physics: Conference Series 2021年第1期1805卷

作者： S Filawati Balai Pengamatan Antariksa dan Atmosfer Pasuruan Pasuruan 67155 Indonesia Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia

Solar storms have a hazardous effect on the Earth, one of the most powerful is Coronal Mass Ejection (CME). St. Patrick geomagnetic storm is a severe geomagnetic storm which is caused by partial halo CME. Propagation of CME at interplanetary space is detected by solar wind parameters by speed and magnetic field. Interplanetary Magnetic Field (IMF) has orientation to determine the shift of solar wind particle. IMF orientation can be classified by IMF cone angle and IMF clock angle. Both can be used as an indicator of Kelvin-Helmholtz instability. This study aims to determine the flow of solar wind to the magnetosphere. The solar wind will enter the magnetosphere can be detected by THEMIS satellite orbits at ∼100 km to ∼12 RE at magnetotail and ground-based Fluxgate Magnetometer at LAPAN Pasuruan. Meanwhile, the geomagnetic storm is observed by Dst index. We combine data from interplanetary space, magnetosphere, and ground-based magnetometer and processed to Pc5 power. The results are IMF clock angle was closer to zero and IMF cone angle got wider on 15-18 March 2015, FM and FGM Pc5 power surged since March 16, 2015. Finally, a severe geomagnetic storm observed on March 17, 2015 with Dst index was -222 nT.

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Quantum proportional-integral (PI) control

arXiv

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arXiv 2020年

作者： Chen, Hui Li, Hanhan Motzoi, Felix Martin, Leigh Whaley, K. Birgitta Sarovar, Mohan Berkeley Center for Quantum Information and Computation BerkeleyCA94720 United States Department of Physics University of California BerkeleyCA94720 United States Department of Chemistry University of California BerkeleyCA94720 United States Extreme-Scale Data Science and Analytics Sandia National Laboratories LivermoreCA94550 United States

Feedback control is an essential component of many modern technologies and provides a key capability for emergent quantum technologies. We extend existing approaches of direct feedback control in which the controller applies a function directly proportional to the output signal (P feedback), to strategies in which feedback determined by an integrated output signal (I feedback), and to strategies in which feedback consists of a combination of P and I terms. The latter quantum PI feedback constitutes the analog of the widely used proportional-integral feedback of classical control. All of these strategies are experimentally feasible and require no complex state estimation. We apply the resulting formalism to two canonical quantum feedback control problems, namely, stabilization of a harmonic oscillator under thermal noise, and generation of an entangled state of two remote qubits under conditions of arbitrary measurement efficiency. These two problems allow analysis of the relative benefits of P, I, and PI feedback control. We find that P feedback shows the best performance for harmonic state stabilization when actuation of both position and momentum feedback is possible, while when only actuation of position is available, I feedback consistently shows the best performance, although feedback delay is shown to improve the performance of a P strategy here. In contrast, for the two-qubit remote entanglement generation we find that the best strategy can be a combined PI strategy, when measurement efficiency is not one. Copyright © 2020, The Authors. All rights reserved.

关键词： Two term control systems

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Risks of liver cirrhosis,hepatocellular carcinoma,hepatic-related complications,and mortality in patients with type 2 diabetes in Taiwan

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World Journal of Diabetes 2025年第5期16卷 202-215页

作者： Hua-Fen Chen Yung-Yueh Chang Peter Chen Xiao-Han Shen Chin-Huan Chang Wan-Lun Hsu Department of Endocrinology Far Eastern Memorial HospitalNew Taipei City 220TaiwanChina School of Medicine College of MedicineFu Jen Catholic UniversityNew Taipei City 242TaiwanChina Department of Public Health College of MedicineFu Jen Catholic UniversityNew Taipei City 242TaiwanChina Institute of Epidemiology and Preventive Medicine College of Public HealthNational Taiwan UniversityTaipei City 100TaiwanChina Department of Gastroenterology Choninn HospitalChoninn Medical GroupNew Taipei City 220TaiwanChina Master Program of Big Data in Medical Healthcare Industry College of MedicineFu Jen Catholic UniversityNew Taipei City 242TaiwanChina Data Science Center Fu Jen Catholic UniversityNew Taipei City 242TaiwanChina

BACKGROUND Hepatitis B and C and alcoholic liver disease are the principal causes of hepaticrelated morbidity and ***,evidence of the associations between diabetes without the above risk factors and hepatic-related study endpoints is not well *** addition,the effects of associated metabolic dysfunction and exercise on hepatic outcomes are still not *** To investigate the incidence and relative hazards of cirrhosis of the liver,hepato cellular carcinoma(HCC),hepatic-related complications and mortality in patients with type 2 diabetes(T2D)who were nonalcoholic and serologically negative for hepatitis B and C in *** A total of 33184 T2D patients and 648746 nondiabetic subjects selected from Taiwan’s adult preventive health care service were linked to various National Health Insurance databases,cancer registry,and death registry to identify cirrhosis of the liver,HCC,hepatic-related complications,and *** Poisson assumption and Cox proportional hazard regression model were used to estimate the incidences and relative hazards of all hepatic-related study endpoints,*** also compared the risk of hepatic outcomes stratified by age,sex,associated metabolic dysfunctions,and regular exercise between T2D patients and nondiabetic *** Compared with nondiabetic subjects,T2D patients had a significantly greater incidence(6.32 vs 17.20 per 10000 person-years)and greater risk of cirrhosis of the liver[adjusted hazard ratio(aHR)1.45;95%CI:1.30-1.62].The aHRs for HCC,hepatic complications,and mortality were 1.81,1.87,and 2.08,*** older age,male sex,obesity,hypertension,and dyslipidemia further increased the risks of all hepatic-related study endpoints,and regular exercise decreased the risk,irrespective of diabetes *** Patients with T2D are at increased risk of cirrhosis of the liver,HCC,hepatic-related complications,and mortality,and associated metabolic dysfunctions provide additional

关键词： Type 2 diabetes mellitus Liver cirrhosis Hepatocellular carcinoma Hepatic-related complications Mortality Metabolic dysfunction-associated steatotic liver disease Metabolic dysfunction-associated steatohepatitis

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