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arXiv 2020年

作者： Walton, Ashley E. Collins, Linda M. Klasnja, Predrag Nahum-Shani, Inbal Rabbi, Mashfiqui Walton, Maureen A. Murphy, Susan A. Department of Philosophy Dartmouth College Methodology Center Department of Human Development & Family Studies Pennsylvania State University School of Information University of Michigan Institute for Social Research University of Michigan Department of Statistics Harvard University Department of Psychiatry and Injury Prevention Center University of Michigan Departments of Statistics and Computer Science Harvard University

Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that can deploy a high intensity of adaptation;in other words, use frequent opportunities for the intervention to be adapted-weekly, daily, or even many times a day. This high intensity of adaptation is facilitated by the ability of digital technology to continuously collect information about an individual's current context and make treatment decisions adapted to this information. The micro-randomized trial (MRT) has emerged for use in informing the construction of JITAIs. MRTs operate in, and take advantage of, the rapidly time-varying digital intervention environment. MRTs can be used to address research questions about whether and under what circumstances particular components of a JITAI are effective, with the ultimate objective of developing effective and efficient components. The purpose of this article is to clarify why, when, and how to use MRTs;to highlight elements that must be considered when designing and implementing an MRT;and to discuss the possibilities this emerging optimization trial design offers for future research in the behavioral sciences, education, and other fields. We briefly review key elements of JITAIs, and then describe three case studies of MRTs, each of which highlights research questions that can be addressed using the MRT and experimental design considerations that might arise. We also discuss a variety of considerations that go into planning and designing an MRT, using the case studies as *** Codes 62P15 Copyright © 2020, The Authors. All rights reserved.

关键词： Just in time production

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Comparison of lattice-free and lattice-based sequence discriminative training criteria for LVCSR

arXiv

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arXiv 2019年

作者： Michel, Wilfried Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany

Sequence discriminative training criteria have long been a standard tool in automatic speech recognition for improving the performance of acoustic models over their maximum likelihood / cross entropy trained counterparts. While previously a lattice approximation of the search space has been necessary to reduce computational complexity, recently proposed methods use other approximations to dispense of the need for the computationally expensive step of separate lattice creation. In this work we present a memory efficient implementation of the forward-backward computation that allows us to use unigram word-level language models in the denominator calculation while still doing a full summation on GPU. This allows for a direct comparison of lattice-based and lattice-free sequence discriminative training criteria such as MMI and sMBR, both using the same language model during training. We compared performance, speed of convergence, and stability on large vocabulary continuous speech recognition tasks like Switchboard and Quaero. We found that silence modeling seriously impacts the performance in the lattice-free case and needs special treatment. In our experiments lattice-free MMI comes on par with its lattice-based counterpart. Lattice-based sMBR still outperforms all lattice-free training criteria. Copyright © 2019, The Authors. All rights reserved.

关键词： Acoustic Modeling

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RETRACTION: Complex societies precede moralizing gods throughout world history (Retraction of 10.1038/S41586-019-1043-4, 2019)

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NATURE 2021年第7866期595卷 320-320页

作者： Whitehouse, Harvey Francois, Pieter Savage, Patrick E. Currie, Thomas E. Feeney, Kevin C. Cioni, Enrico Purcell, Rosalind Ross, Robert M. Larson, Jennifer Baines, John ter Haar, Barend Covey, Alan Turchin, Peter Centre for the Study of Social Cohesion University of Oxford Oxford UK St Benet’s Hall Oxford UK Faculty of Environment and Information Studies Keio University Fujisawa Japan ARC Centre of Excellence in Cognition and its Disorders and Department of Psychology Royal Holloway University of London Egham UK Department of Anthropology and Archaeology University of Bristol Bristol UK Human Behaviour & Cultural Evolution Group Department of Biosciences University of Exeter Penryn UK School of Computer Science and Statistics Trinity College Dublin Dublin Ireland Seshat: Global History Databank Evolution Institute San Antonio FL USA Department of Modern & Classical Language Studies Kent State University Kent OH USA Faculty of Oriental Studies University of Oxford Oxford UK Department of Chinese Language and Culture Asia-Africa-Institute University of Hamburg Hamburg Germany Department of Anthropology University of Texas at Austin Austin TX USA Department of Ecology and Evolutionary Biology University of Connecticut Storrs CT USA Complexity Science Hub Vienna Wien Austria

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What contributes to a crowdfunding campaign's success? Evidence and analyses from GoFundMe data

arXiv

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arXiv 2020年

作者： Zhang, Xupin Lyu, Hanjia Luo, Jiebo The Warner School of Education and Human Development University of Rochester RochesterNY14627 United States The Goergen Institute for Data Science University of Rochester RochesterNY14627 United States The Department of Computer Science University of Rochester RochesterNY14627 United States

Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover photo and the text in the title and description could be combined in a fusion classifier to better predict the crowdfunding campaign's success. In this work, we focus on the performance of the crowdfunding campaigns on GoFundMe across a wide variety of funding categories. We analyze the attributes available at the launch of the campaign and identify attributes that are important for each category of the campaigns. Furthermore, we develop a fusion classifier based on the random forest that significantly improves the prediction result, thus suggesting effective ways to make a campaign successful. Copyright © 2020, The Authors. All rights reserved.

关键词： Crowdsourcing

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Ambient heat and human sleep

arXiv

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arXiv 2020年

作者： Minor, Kelton Bjerre-Nielsen, Andreas Jónasdóttir, Sigrídur Svala Lehmann, Sune Obradovich, Nick Copenhagen Center for Social Data Science University of Copenhagen Denmark Department of the Built Environment University of Aalborg Denmark Global Policy Laboratory University of California Berkeley United States Department of Economics University of Copenhagen Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Center for Humans and Machines Max Planck Institute for Human Development Germany

Ambient temperatures are rising globally, with the greatest increases recorded at night. Concurrently, the prevalence of insufficient sleep is increasing in many populations, with substantial costs to human health and well-being. Even though nearly a third of the human lifespan is spent asleep, it remains unknown whether temperature and weather impact objective measures of sleep in real-world settings, globally. Here we link billions of sleep measurements from wearable devices comprising over 7 million nighttime sleep records across 68 countries to local daily meteorological data from 2015 to 2017. Rising nighttime temperatures shorten within-person sleep duration primarily through delayed onset, increasing the probability of insufficient sleep. The effect of temperature on sleep loss is substantially larger for residents from lower income countries and older adults, and females are affected more than are males. Nighttime temperature increases inflict the greatest sleep loss during summer and fall months, and we do not find evidence of short-term acclimatization. Coupling historical behavioral measurements with output from climate models, we project that climate change will further erode human sleep, producing substantial geographic inequalities. Our findings have significant implications for adaptation planning and illuminate a pathway through which rising temperatures may globally impact public health. © 2020, CC-BY-NC-ND.

关键词： Sleep research

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Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3 — Ex vivo imaging: data processing, comparisons with microscopy, and tractography

arXiv

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arXiv 2024年

作者： Schilling, Kurt G. Howard, Amy F.D. Grussu, Francesco Ianus, Andrada Hansen, Brian Barrett, Rachel L.C. Aggarwal, Manisha Michielse, Stijn Nasrallah, Fatima Syeda, Warda Wang, Nian Veraart, Jelle Roebroeck, Alard Bagdasarian, Andrew F. Eichner, Cornelius Sepehrband, Farshid Zimmermann, Jan Soustelle, Lucas Bowman, Christien Tendler, Benjamin C. Hertanu, Andreea Jeurissen, Ben Verhoye, Marleen Frydman, Lucio van de Looij, Yohan Hike, David Dunn, Jeff F. Miller, Karla Landman, Bennett A. Shemesh, Noam Anderson, Adam McKinnon, Emilie Farquharson, Shawna Dell' Acqua, Flavio Pierpaoli, Carlo Drobnjak, Ivana Leemans, Alexander Harkins, Kevin D. Descoteaux, Maxime Xu, Duan Huang, Hao Santin, Mathieu D. Grant, Samuel C. Obenaus, Andre Kim, Gene S. Wu, Dan Le Bihan, Denis Blackband, Stephen J. Ciobanu, Luisa Fieremans, Els Bai, Ruiliang Leergaard, Trygve B. Zhang, Jiangyang Dyrby, Tim B. Johnson, G. Allan Cohen-Adad, Julien Budde, Matthew D. Jelescu, Ileana O. Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN United States Vanderbilt University Institute of Imaging Science Vanderbilt University NashvilleTN United States Department of Bioengineering Imperial College London London United Kingdom FMRIB Centre Wellcome Centre for Integrative Neuroimaging Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom Radiomics Group Vall d’Hebron Institute of Oncology Vall d’Hebron Barcelona Hospital Campus Barcelona Spain Queen Square MS Centre Queen Square Institute of Neurology Faculty of Brain Sciences University College London London United Kingdom Champalimaud Research Champalimaud Foundation Lisbon Portugal Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Department of Neuroimaging Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom NatBrainLab Department of Forensics and Neurodevelopmental Sciences Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States Maastricht University Medical Center Maastricht Netherlands The Queensland Brain Institute The University of Queensland Queensland Australia Melbourne Neuropsychiatry Centre The University of Melbourne ParkvilleVIC Australia Department of Radiology and Imaging Sciences Indiana University IN United States Stark Neurosciences Research Institute Indiana University School of Medicine IN United States Center for Biomedical Imaging NYU Grossman School of Medicine New YorkNY United States Faculty of psychology and Neuroscience Maastricht University Maastricht Netherlands Department of Chemical & Biomedical Engineering FAMU-FSU College of Engineering Florida State University TallahasseeFL United States Center for Interdisciplinary Magnetic Res

Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high signal-to-noise ratio (SNR) images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a 3-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing and model fitting, and tractography. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing, and point towards open-source software and databases specific to small animal and ex vivo imaging. © 2024, CC BY.

关键词： Data Sharing

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UTD HLTRI at TREC 2018: Complex Answer Retrieval Track 27

UTD HLTRI at TREC 2018: Complex Answer Retrieval Track

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27th Text REtrieval Conference, TREC 2018

作者： Maldonado, Ramon Harabagiu, Sanda M. Department of Computer Science Human Language Technology Research Institute University of Texas Dallas United States

Finding answers to complex questions within a corpus of Wikipedia paragraphs needs to account for (a) the similarity between questions and paragraphs as well as (b) their shared semantics. In our participation in the 2018 TREC CAR track, we focused on developing a novel neural paragraph ranking model in our existing CAPAR system, developed for the 2017 TREC CAR track. The new system TRANS-CAPAR, takes advantage of the recently introduced Transformer architecture to encode information from the question and to semantically decode it in each paragraph. The results obtained during the official evaluations indicate that TRANS-CAPAR makes good use of both discourse context and similarity when ranking paragraphs. © 2018 Copyright held by the owner/author(s).

关键词： Semantics

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uniblock: Scoring and Filtering Corpus with Unicode Block Information

arXiv

引用

arXiv 2019年

作者： Gao, Yingbo Wang, Weiyue Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University AachenD-52056 Germany

The preprocessing pipelines in Natural language Processing usually involve a step of removing sentences consisted of illegal characters. The definition of illegal characters and the specific removal strategy depend on the task, language, domain, etc, which often lead to tiresome and repetitive scripting of rules. In this paper, we introduce a simple statistical method, uniblock1, to overcome this problem. For each sentence, uniblock generates a fixed-size feature vector using Unicode block information of the characters. A Gaussian mixture model is then estimated on some clean corpus using variational inference. The learned model can then be used to score sentences and filter corpus. We present experimental results on Sentiment Analysis, language Modeling and Machine Translation, and show the simplicity and effectiveness of our method. Copyright © 2019, The Authors. All rights reserved.

关键词： Gaussian distribution

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Exploring Kernel functions in the softmax layer for contextual word classification

arXiv

引用

arXiv 2019年

作者： Gao, Yingbo Herold, Christian Wang, Weiyue Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University AachenD-52056 Germany

Prominently used in support vector machines and logistic regressions, kernel functions (kernels) can implicitly map data points into high dimensional spaces and make it easier to learn complex decision boundaries. In this work, by replacing the inner product function in the softmax layer, we explore the use of kernels for contextual word classification. In order to compare the individual kernels, experiments are conducted on standard language modeling and machine translation tasks. We observe a wide range of performances across different kernel settings. Extending the results, we look at the gradient properties, investigate various mixture strategies and examine the disambiguation abilities. Copyright © 2019, The Authors. All rights reserved.

关键词： Support vector machines

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A Learning Model to Improve Learning Outcome on Experiential Learning in a Multi-Phase Internship: A Case Study of the Internship Program of a Thai University. 8

A Learning Model to Improve Learning Outcome on Experiential...

引用

8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019

作者： Kingkaew, Chanakarn Supnithi, Thepchai Theeramunkong, Thanaruk Morita, Kai Tanaka, Koji Ikeda, Mitsuru School of Information Computer and Communication Technology Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand Language and Semantic Technology Laboratory National Electronics and Computer Technology Center Pathum Thani Thailand School of Knowledge Science Japan Advanced Institute of Science and Technology Nomi Japan Department of Psychological Science College of Informatics and Human Communication Kanazawa Institute of Technology Nonoichi Japan

ISBN: (纸本)9781728126272

The internship is one of the crucial learning processes that provide a unique experience to combine what they learned in university courses and how to use it in the real society during their university lives as it provides the opportunity to learn through work experience offered by the external organization. Although learner can learn career skills through the internship, most learner cannot make good reflection and cannot learn how to learn from experience. We think the cause of this problem is that most learner cannot reflect their experience and cannot clear the abstract concept and apply it to the next trial. This implies that those learners can improve their learning through internship by acquiring experiential learning skills. In the internship in general, the mentor has the important education roles. One is to foster career skills learning, and the other is to promote experiential learning. However, in most case, the mentor is very good at career skill teaching, but most of the mentor is not well prepared to support experiential learning. In response to the above problems, to support learners to realized good learning, we provide a learning environment for the learner to support experiential learning. A guideline for the learner to let them aware of the critical concept of internship and experiential learning. Also, we provide a web system to practice reflective writing to understand and able to apply experiential learning concepts. In this paper, as the preliminary research to develop learning environment, the analysis of the learner learning activity of the current internship program and show the prototype of the conceptualization of the educational concepts to support the experiential learning. © 2019 IEEE.

关键词： Knowledge management

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