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Using social media to perform local influenza surveillance in an inner-city hospital: A retrospective observational study

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JMIR Public Health and Surveillance 2015年第1期1卷 e5页

作者： Broniatowski, David Andre Dredze, Mark Paul, Michael J. Dugas, Andrea Department of Engineering Management and Systems Engineering The George Washington University Washington DC United States Human Language Technology Center of Excellence Johns Hopkins University Baltimore MD United States Department of Computer Science Johns Hopkins University Baltimore MD United States Department of Emergency Medicine Johns Hopkins University Baltimore MD United States

Background: Public health officials and policy makers in the United States expend significant resources at the national, state, county, and city levels to measure the rate of influenza infection. These individuals rely on influenza infection rate information to make important decisions during the course of an influenza season driving vaccination campaigns, clinical guidelines, and medical staffing. Web and social media data sources have emerged as attractive alternatives to supplement existing practices. While traditional surveillance methods take 1-2 weeks, and significant labor, to produce an infection estimate in each locale, web and social media data are available in near real-time for a broad range of locations. Objective: The objective of this study was to analyze the efficacy of flu surveillance from combining data from the websites Google Flu Trends and HealthTweets at the local level. We considered both emergency department influenza-like illness cases and laboratory-confirmed influenza cases for a single hospital in the City of Baltimore. Methods: This was a retrospective observational study comparing estimates of influenza activity of Google Flu Trends and Twitter to actual counts of individuals with laboratory-confirmed influenza, and counts of individuals presenting to the emergency department with influenza-like illness cases. Data were collected from November 20, 2011 through March 16, 2014. Each parameter was evaluated on the municipal, regional, and national scale. We examined the utility of social media data for tracking actual influenza infection at the municipal, state, and national levels. Specifically, we compared the efficacy of Twitter and Google Flu Trends data. Results: We found that municipal-level Twitter data was more effective than regional and national data when tracking actual influenza infection rates in a Baltimore inner-city hospital. When combined, national-level Twitter and Google Flu Trends data outperformed each data source ind

关键词： Social computing Time series analysis Web mining

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Cipher type detection

Cipher type detection

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2014 Conference on Empirical Methods in Natural language Processing, EMNLP 2014

作者： Nuhn, Malte Knight, Kevin Computer Science Department Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany Information Sciences Institute University of Southern California United States

ISBN: (纸本)9781937284961

Manual analysis and decryption of enciphered documents is a tedious and error prone work. Often-even after spending large amounts of time on a particular cipher-no decipherment can be found. Automating the decryption of various types of ciphers makes it possible to sift through the large number of encrypted messages found in libraries and archives, and to focus human effort only on a small but potentially interesting subset of them. In this work, we train a classifier that is able to predict which encipherment method has been used to generate a given ciphertext. We are able to distinguish 50 different cipher types (specified by the American Cryptogram Association) with an accuracy of 58.5%. This is a 11.2% absolute improvement over the best previously published classifier. © 2014 Association for Computational Linguistics.

关键词： Cryptography

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Combining punctuation and disfluency prediction: An empirical study

Combining punctuation and disfluency prediction: An empirica...

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2014 Conference on Empirical Methods in Natural language Processing, EMNLP 2014

作者： Wang, Xuancong Sim, Khe Chai Ng, Hwee Tou NUS Graduate School for Integrative Sciences and Engineering Singapore Department of Computer Science National University of Singapore Singapore Institute for Infocomm Research Human Language Technology Singapore

ISBN: (纸本)9781937284961

Punctuation prediction and disfluency prediction can improve downstream natural language processing tasks such as machine translation and information extraction. Combining the two tasks can potentially improve the efficiency of the overall pipeline system and reduce error propagation. In this work1, we compare various methods for combining punctuation prediction (PU) and disfluency prediction (DF) on the Switchboard corpus. We compare an isolated prediction approach with a cascade approach, a rescoring approach, and three joint model approaches. For the cascade approach, we show that the soft cascade method is better than the hard cascade method. We also use the cascade models to generate an n-best list, use the bi-directional cascade models to perform rescoring, and compare that with the results of the cascade models. For the joint model approach, we compare mixedlabel Linear-chain Conditional Random Field (LCRF), cross-product LCRF and 2- layer Factorial Conditional Random Field (FCRF) with soft-cascade LCRF. Our results show that the various methods linking the two tasks are not significantly different from one another, although they perform better than the isolated prediction method by 0.5-1.5% in the F1 score. Moreover, the clique order of features also shows a marked difference. © 2014 Association for Computational Linguistics.

关键词： Forecasting

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A beam-search decoder for disfluency detection 25

A beam-search decoder for disfluency detection

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25th International Conference on Computational Linguistics, COLING 2014

作者： Wang, Xuancong Ng, Hwee Tou Sim, Khe Chai NUS Graduate School for Integrative Sciences and Engineering Singapore Department of Computer Science National University of Singapore Singapore Institute for Infocomm Research Human Language Technology Singapore

ISBN: (纸本)9781941643266

In this paper1, we present a novel beam-search decoder for disfluency detection. We first propose node-weighted max-margin Markov networks (M3N) to boost the performance on words belonging to specific part-of-speech (POS) classes. Next, we show the importance of measuring the quality of cleaned-up sentences and performing multiple passes of disfluency detection. Finally, we propose using the beam-search decoder to combine multiple discriminative models such as M3N and multiple generative models such as language models (LM) and perform multiple passes of disfluency detection. The decoder iteratively generates new hypotheses from current hypotheses by making incremental corrections to the current sentence based on certain patterns as well as information provided by existing models. It then rescores each hypothesis based on features of lexical correctness and fluency. Our decoder achieves an edit-word F1 score higher than all previous published scores on the same data set, both with and without using external sources of information.

关键词： Speech communication

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Intelligent system for a personalized diet of obese patients with cancer 8

Intelligent system for a personalized diet of obese patients...

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8th International Conference and Exposition on Electrical and Power Engineering, EPE 2014

作者： Geman, Oana Chiuchisan, Iuliana Iuresi, Andrei Coriolan Dimian, Mihai Bosancu, Anca Buliga, Daniela Covasa, Mihai Human Development and Health Department Stefan Cel Mare University of Suceava Suceava Romania Department of Computer Science Electronics and Automation Stefan Cel Mare University of Suceava Suceava Romania

ISBN: (纸本)9781479958498

We have developed a system, called INSPIRED-Intelligent System for a Personalized Cancer Diet to improve the health and quality of life for obese patients with cancer. It is designed for monitoring, alerting, reminding and evaluation of patients as well as storage, access and retrieval of medical and personal data for establishing treatment. Our system provides users (patients or physicians) with personalized dietary plans, rehabilitation and lifestyle information, all tailored to each individual's needs. Obese cancer patients are informed of, and educated about, the role of nutrition as a first and best defense in improving survivability and quality of life. The proposed system analyzes patient data such as vital signs (weight, height, Body Mass Index BMI, blood pressure), physical activity, type of cancer, treatment, side effects and uses the patient's profile to build a custom diet that relies on comprehensive care planning. The Cancer Nutrition Personalized Tips System is based on My SQL (Structured Query language) architecture that is user friendly and can be expanded to future needs. © 2014 IEEE.

关键词： Nutrition

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A Step Towards EEG-based Brain computer Interface for Autism Intervention

A Step Towards EEG-based Brain Computer Interface for Autism...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Jing Fan Joshua W. Wade Dayi Bian Alexandra P. Key Zachary E. Warren Lorraine C. Mion Nilanjan Sarkar the Electrical Engineering and Computer Science Department Vanderbilt University Nashville TN 37212 USA the Vanderbilt Kennedy Center for Research on Human Development and Department of Hearing and Speech Sciences Vanderbilt University 230 Appleton Place PMB 74 Nashville TN 37203 USA the Treatment and Research Institute for Autism Spectrum Disorders (TRIAD) Pediatrics Psychiatry and Special Education Vanderbilt Kennedy Center 230 Appleton Place PMB 74 Nashville TN 37203 USA the Vanderbilt University School of Nursing Nashville TN 37204 USA the Mechanical Engineering Department Electrical Engineering and Computer Science Department Vanderbilt University Nashville TN 37212 USA

ISBN: (纸本)9781424492695

Autism Spectrum Disorder (ASD) is a prevalent and costly neurodevelopmental disorder. Individuals with ASD often have deficits in social communication skills as well as adaptive behavior skills related to daily activities. We have recently designed a novel virtual reality (VR) based driving simulator for driving skill training for individuals with ASD. In this paper, we explored the feasibility of detecting engagement level, emotional states, and mental workload during VR-based driving using EEG as a first step towards a potential EEG-based Brain computer Interface (BCI) for assisting autism intervention. We used spectral features of EEG signals from a 14-channel EEG neuroheadset, together with therapist ratings of behavioral engagement, enjoyment, frustration, boredom, and difficulty to train a group of classification models. Seven classification methods were applied and compared including Bayes network, naive Bayes, Support Vector Machine (SVM), multilayer perceptron, K-nearest neighbors (KNN), random forest, and J48. The classification results were promising, with over 80% accuracy in classifying engagement and mental workload, and over 75% accuracy in classifying emotional states. Such results may lead to an adaptive closed-loop VR-based skill training system for use in autism intervention.

关键词： ASD KNN VR heart atrium septum defect Brain-computer Interfaces Variable reluctance Electroencephalography Bayesian networks autism Skill development Driving simulator Adaptive Behavior Emotional States engaging spectral feature Communication Skills

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A tripartite tensor decomposition fold-in for social tagging

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Journal of Applied science and Engineering 2014年第4期17卷 363-370页

作者： Liao, Zhi-Fang Cai, Fei Zhang, Miao Liao, Zhi-Ning Zhang, Yan School of Software Central South University Changsha Hunan China Department of Computer Science University of Texas at Arlington ArlingtonTX United States Faculty of Engineering Science and the Built Environment London South Bank University London United Kingdom Institute of Human Development University of Manchester United Kingdom

The tripartite tensor decomposition (TTD) model reveals the latent relationship among items, tags and users in social tagging systems in terms of a low order tensor obtained from the high-index sparse data space with the tensor dimensionality reduction technique. The Tripartite decomposition recommendation algorithms can produce high quality recommendations, but have to undergo expensive tensor decomposition steps when new users, new tags, or new items come in, which is significant in light of the tremendous growth in numbers of users, tags and items. In this paper, we present fold-in algorithms for Tripartite tensor decomposition to deal with the new users *** evaluate the fold-in algorithms experimentally on several datasets and the results demonstrate the effectiveness of the algorithm.

关键词： Tensors

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KELVIN: Extracting knowledge from large text collections

KELVIN: Extracting knowledge from large text collections

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2014 AAAI Fall Symposium

作者： Mayfield, James McNamee, Paul Harman, Craig Finin, Tim Lawrie, Dawn Johns Hopkins University Human Language Technology Center of Excellence BaltimoreMD United States Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD United States Computer Science Department Loyola University Maryland BaltimoreMD United States

ISBN: (纸本)9781577356967

We describe the KELVIN system for extracting entities and relations from large text collections and its usc in the TAC Knowledge Base Population Cold Start task run by the U.S. National Institute of Standards and Technology. The Cold Start task starts with an empty knowledge based defined by an ontology of entity types. properties and relations. Evaluations in 2012 and 2013 were done using a collection of text from local Web and news to dc-emphasize the use of entities that appear in a background knowledge base such as Wikipedia. Interesting features of KELVIN include a cross-document ent ity coreference module based on entity mentions, removal of suspect intra-document conference chains, a slot value cons olidator for entities, the application of inference rules to exp and the number of asserted facts and a set of analysis and browsing tools supporting development. Copyright © 2014, Association for the Advancement of Artificial Intelligence.

关键词： Knowledge based systems

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Peer Ratings and Social Problem-solving Skills of 6-8 Years Old Children

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Journal of Psychology 2014年第1期5卷 75-78页

作者： Suneeta Paswan Kumar Sanjeev Indu Bansal Department of Human Development Faculty of Home Science Banasthali Vidyapith Department of Stat Maths and Computer Application Rajendra Agricultural University

For the study Faizabad regions of state Uttar Pradesh were selected as locales. Faizabad region included districts namely-Faizabad, Barabanki, Sultanpur, Ambedkar Nagar and Gonda. Four Schools and hundred children from each district were selected. Hence a total of 500 primary school children were assessed for peer acceptance and rejection and interpersonal social problem-solving skills. Result of this study showed the relationship between peer acceptance and rejection and interpersonal social problem-solving skills. Positively rated children suggested more number of relevant strategies and flexibility than their less accepted counter parts. Also positively rated children were more likely to suggest prosocial strategies for obtaining access to an object in another child’s possession, while reverse was seen among negatively rated children.

关键词： Pro-social Strategies Sociometric Measure Object Acquisition Relevancy Correlation

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Nanotechnology STEM program via research experience for high school teachers

Nanotechnology STEM program via research experience for high...

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Frontiers in Education (FIE) Conference

作者： Mangilal Agarwal Qurat-ul-Ann Mirza Joseph Bondi Brandon Sorge Maher Rizkalla Richard Ward Corbin Feldhaus Amy Hinshaw Kody Varahramyan Director for Research Development and Director of Integrated Nanosystems Development Institute (INDI) at IUPUI IN USA Integrated Nanosystems Development Institute (INDI) Indiana University Purdue University at Indianapolis Indianapolis IN US Purdue School of Science Indiana University-Purdue-University Indianapolis School of Science at IUPUI. Research Associate at the STEM Education Research Institute at IUPUI. Professor & Associate Chair of Department of Electrical and Computer Engineering and Member of Integrated Nanosystems Development Institute (INDI) at IUPUI Professor of Anthropology and Dentistry Faculty of University College High School Teacher at Irvington Public School Teaches Biology and Human Genetics High School Teacher at the Health and Biomedical Sciences Metropolitan School District of Lawrence Township. Professor of Electrical and Computer Engineering at IUPUI

ISBN: (纸本)9781479984558

In this work, we report the outcomes from the IUPUI STEM outreach program “STEMCorp” that inspires high school students to pursue STEM majors. The STEMCorp program was modeled after the Multidisciplinary Undergraduate Research Initiative (MURI) at IUPUI. MURI research program introduces undergraduate students from at least two different departments with mentors from different disciplines to address research issues that may compose both engineering and sciences. The STEMCorp program brings undergraduate students to work with faculty and high school teachers to create a positive impact in enriching the high school students by introducing them to engineering and science with emphasis on nanotechnology for future careers. The program describes the collaborative activities between faculty, undergraduate students and high school STEM teachers in the creation of project-based, student-centered learning modules in the field of nanotechnology. The paper details the activities of the STEMCorp participants including their experiences in developing working partnerships and creating and implementing learning modules in the designated high school courses. The success of the program is assessed by the measurable outcomes of high school students' research projects. Specifically, two different learning modules are presented, including the processes used in the development of these modules and their outcomes. The collaborative research discussions between the faculty, undergraduate students, and high school teachers are detailed, covering research methodologies, hypothesis, and expected outcomes.

关键词： Education Cancer Collaboration computers Nanobioscience Cancer detection

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