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(OA32) Chronic Radiation-Associated Dysphagia in Oropharyngeal Cancer Survivors: Towards Age-Adjusted Dose Constraints for Deglutitive Muscles

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International Journal of Radiation Oncology*Biology*Physics 2018年第2期101卷 e14-e14页

作者： Kaitlin Christopherson Alokananda Ghosh Abdallah Sherif Radwan Mohamed Mona Jomaa G. Brandon Gunn Liz Marai Guadalupe Canahuate David Vock Timothy Dale Jayashree Kalpathy-Cramer Jay Messer Adam S. Garden Hesham Elhalawani Steven J. Frank Jan Lewin Stephen Y. Lai Beth M. Beadle William H. Morrison Clifton D. Fuller Department of Radiation Oncology The University of Texas MD Anderson Cancer Center Houston TX USA Department of Biostatistics University of Texas School of Public Health Houston TX USA Department of Clinical Oncology University of Alexandria Alexandria Egypt Head and Neck Surgery The University of Texas MD Anderson Cancer Center Houston TX USA Department of Computer Science University of Pittsburgh Pittsburgh PA Thoracic & Head and Neck Oncology The University of Texas MD Anderson Cancer Center Houston TX USA Department of Electrical and Computer Engineering The University of Iowa Iowa City IA Division of Biostatistics School of Public Health University of Minnesota Minneapolis MN Baylor College of Medicine Houston TX USA Athinoula A. Martinos Center for Biomedical Imaging/Massachusetts General Hospital/Massachusetts Institute of Technology Charlestown MA USA Department of Radiation Oncology The University of Texas Medical Branch Galveston TX USA Department of Radiation Oncology Stanford University Palo Alto CA USA Medical Physics Program The University of Texas Graduate School of Biomedical Sciences Houston TX USA

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Provision of differentiated reliable services in distribution systems based on customer preferences

Provision of differentiated reliable services in distributio...

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Annual North-American Power Symposium

作者： Siripha Junlakarn Marija Ilíc Department of Engineering and Public Policy Carnegie Mellon University Department of Electrical and Computer Engineering Carnegie Mellon University

This paper proposes a market mechanism that provides differentiated higher reliability services beyond a standard level in distribution networks. To offer the higher reliability services, switching devices, as one of technologies for enhancing reliability, will be installed in the systems. The decisions on numbers and locations of these switches are made based on information from a service provider and customers.

关键词： Reliability engineering Investment computer network reliability Switches Circuit breakers Standards

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Developing Novel Machine Learning Algorithms to Improve Sedentary Assessment for Youth Health Enhancement

Developing Novel Machine Learning Algorithms to Improve Sede...

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IEEE International Conference on Healthcare Informatics (ICHI)

作者： Gowtham Kumar Golla Jordan A. Carlson Jun Huan Jacqueline Kerr Tarrah Mitchell Kelsey Borner Department of Electrical Engineering and Computer Science University of Kansas Jayhawk Blvd Lawrence KS Center for Children's Healthy Lifestyles and Nutrition Children's Mercy Hospital Department of Family Medicine and Public Health University of California San Diego CA Department of Psychology University of Kansas Lawrence KS

ISBN: (纸本)9781509061181

Sedentary behavior of youth is an important determinant of health. However, better measures are needed to improve understanding of this relationship and the mechanisms at play, as well as to evaluate health promotion interventions. Wearable accelerometers are considered as the standard for assessing physical activity in research, but do not perform well for assessing posture (i.e., sitting vs. standing), a critical component of sedentary behavior. The machine learning algorithms that we propose for assessing sedentary behavior will allow us to re-examine existing accelerometer data to better understand the association between sedentary time and health in various populations. We collected two datasets, a laboratory-controlled dataset and a free-living dataset. We trained machine learning classifiers separately on each dataset and compared performance across datasets. The classifiers predict five postures: sit, stand, sit-stand, stand-sit, and stand\walk. We compared a manually constructed Hidden Markov model (HMM) with an automated HMM from existing software. The manually constructed HMM gave more F1-Macro score on both datasets.

关键词： Hidden Markov models Machine learning algorithms Accelerometers Algorithm design and analysis Standards Prediction algorithms Training

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DC Power Flow Estimation Utilizing Bayesian-based LMMSE Estimator

DC Power Flow Estimation Utilizing Bayesian-based LMMSE Esti...

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IEEE Power and Energy Society General Meeting

作者： M. H. Amini Marija D. Ilic O. Karabasoglu Joint Institute of Engineering Department of Electrical and Computer Engineering Sun Yat-sen University-Carnegie Mellon University Departments of Electrical and Computer Engineering and Engineering and Public Policy Carnegie Mellon University

ISBN: (纸本)9781467380416

In recent years, Smart Grid was introduced to achieve an environmentally-friendly, adequate, secure and fossil fuel-independent power system. The large scale smart grid studies require accurate state estimation to obtain an acceptable adequacy level. There exist some challenges regarding anomalous power flow studies which motivate grid operators to utilize robust and accurate estimation methods. Therefore, power system state estimators play a pivotal role in real-time grid management. In this paper, a sequential linear minimum mean square error (LMMSE) estimator is utilized to solve the DC power flow problem. First, we introduce the classic linear estimator model which assumes that to-be-estimated parameter values are unknown but deterministic. The LMMSE estimator will be discussed which treats the to-be-estimated parameter as a random variable with a known prior probability density function (pdf). We evaluate the accuracy of the LMMSE estimator by comparing it with maximum likelihood estimator (MLE). Finally, the effect of covariance matrix topology will be studied by defining three scenarios with different noise covariance matrices.

关键词： DC Power Flow Estimation Linear Minimum Mean Square Error (LMMSE) Maximum Likelihood Estimator (MLE)

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A New Logistic Map Based Chaotic Biogeography-based Optimization Approach for Cluster Analysis

A New Logistic Map Based Chaotic Biogeography-based Optimiza...

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang School of Computer Science and Technology Nanjing Normal University Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Department of Electrical Engineering The city college of New YorkCUNY Department of Mechanical and Control Engineering Kyushu Institute of Technology School of Information Engineering Yangzhou University School of Physics and Electronic Engineering Taizhou University School of Electronic Information Shanghai Dianji University School of Energy and Mechanical Engineering Nanjing Normal University Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： chaotic biogeography-based optimization cluster analysis centroid-based clustering simulation particle swarm optimization

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Examining uptake of online education on obstructive sleep apnoea in general practitioners: A randomised trial

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BMC Research Notes 2016年第1期9卷 1-6页

作者： Paul, Christine Rose, Shiho Hensley, Michael Pretto, Jeffrey Hardy, Margaret Henskens, Frans Clinton-Mcharg, Tara Carey, Mariko School of Medicine and Public Health University of Newcastle University Drive Callaghan 2308 NSW Australia Hunter Medical Research Institute New Lambton Heights 2308 NSW Australia Department of Respiratory and Sleep Medicine John Hunter Hospital Lookout Road New Lambton Heights 2305 NSW Australia Woolcock Institute of Medical Research 431 Glebe Point Rd Glebe 2307 NSW Australia GP Education Committee Australasian Sleep Association Blacktown Australia School of Electrical Engineering and Computer Science University of Newcastle University Drive Callaghan NSW Australia

Background: Obstructive sleep apnoea (OSA) affects up to 28 % of the adult population in Western countries. The detection and management of OSA by general practitioners (GPs) can be poor. The study aimed to examine what influence enhanced invitations had on uptake of on-line learning modules for OSA by GPs, and whether recent referrals of patients to sleep specialists influenced uptake. Methods: Practicing GPs in regional Australia were identified and randomised to receive either an enhanced or standard invitation letter to a new on-line education module for OSA. The enhanced letter included indication that the module was eligible for professional accreditation and described the prevalence and burden of sleep disorders. Some included extra emphasis if the GP had recently referred a patient for diagnostic investigation of OSA. Two reminder letters were sent. Results: Of 796 eligible GPs who received the letters, sixteen (2 %) accessed the website and four completed the modules over the four-month study period. GPs who received an enhanced invitation letter were not significantly more likely to access the website compared to GPs who received the standard invitation letter. Recent referral of a patient for diagnostic investigation was also not a significant factor in influencing use of the module. Conclusion: GP interest in on-line education about OSA appears low, and emphasis of relevant recent past patient(s) and the opportunity for professional education points was not successful in increasing engagement. There is a need to identify effective approaches to improving the detection and management of OSA in general practice. © 2016 The Author(s).

关键词： Australia Education General practice Obstructive Professional Sleep apnea Sleep disorders

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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Use of social media in the diabetes community: An exploratory analysis of diabetes-related tweets

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JMIR Diabetes 2016年第2期1卷 e4页

作者： Liu, Yang Mei, Qiaozhu Hanauer, David A. Zheng, Kai Lee, Joyce M. School of Information University of Michigan Ann Arbor MI United States Department of Electrical Engineering and Computer Science College of Engineering University of Michigan Ann Arbor MI United States Department of Pediatrics Medical School University of Michigan Ann Arbor MI United States Department of Health Management and Policy School of Public Health University of Michigan Ann Arbor MI United States Department of Pediatric Endocrinology Medical School University of Michigan Ann Arbor MI United States Child Health Evaluation and Research Center University of Michigan Ann Arbor MI United States

Background: Use of social media is becoming ubiquitous, and disease-related communities are forming online, including communities of interest around diabetes. Objective: Our objective was to examine diabetes-related participation on Twitter by describing the frequency and timing of diabetes-related tweets, the geography of tweets, and the types of participants over a 2-year sample of 10% of all tweets. Methods: We identified tweets with diabetes-related search terms and hashtags in a dataset of 29.6 billion tweets for the years 2013 and 2014 and extracted the text, time, location, retweet, and user information. We assessed the frequencies of tweets used across different search terms and hashtags by month and day of week and, for tweets that provided location information, by country. We also performed these analyses for a subset of tweets that used the hashtag #dsma, a social media advocacy community focused on diabetes. Random samples of user profiles in the 2 groups were also drawn and reviewed to understand the types of stakeholders participating online. Results: We found 1,368,575 diabetes-related tweets based on diabetes-related terms and hashtags. There was a seasonality to tweets;a higher proportion occurred during the month of November, which is when World Diabetes Day occurs. The subset of tweets with the #dsma were most frequent on Thursdays (coordinated universal time), which is consistent with the timing of a weekly chat organized by this online community. Approximately 2% of tweets carried geolocation information and were most prominent in the United States (on the east and west coasts), followed by Indonesia and the United Kingdom. For the user profiles randomly selected among overall tweets, we could not identify a relationship to diabetes for the majority of users;for the profiles using the #dsma hashtag, we found that patients with type 1 diabetes and their caregivers represented the largest proportion of individuals. Conclusions: Twitter is increasi

关键词： Content analysis Diabetes community DSMA Social media Spatiotemporal analysis Twitter

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ARIMA-based Demand Forecasting Method Considering Probabilistic Model of Electric Vehicles' Parking Lots

ARIMA-based Demand Forecasting Method Considering Probabilis...

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IEEE Power and Energy Society General Meeting

作者： M. H. Amini O. Karabasoglu Marija D. Ilic Kianoosh G. Boroojeni S. S. Iyengar Joint Institute of Engineering Department of Electrical and Computer Engineering Sun Yat-sen University-Carnegie Mellon University Departments of Electrical and Computer Engineering and Engineering and Public Policy Carnegie Mellon University School of Computing and Information Sciences Florida International University Florida International University's School of Computing and Information Sciences

ISBN: (纸本)9781467380416

Electric transportation is one of the key elements of the future power systems since conventional power networks are rapidly evolving towards smart grids. This transition creates the need for systematic utilization of electric vehicles (EV) in order to avoid unpredictable effects on the power systems. An accurate and efficient method for demand forecasting of EVs is needed to perform a feasible scheduling of resources in order to supply the predicted load sufficiently. This paper presents a method for electricity demand fore-casting considering EV parking lots' charging demand using historical load data. The method is based on auto-regressive integrated moving average (ARIMA) model for medium-term demand forecasting. The proposed approach improves the fore-casting accuracy. Probabilistic hierarchical EVs' parking lot demand modeling is used to estimate the expected load for each parking lots' daily charging demand. In order to evaluate the effectiveness of the proposed approach, it is implemented on PJM historical load data. The simulation results show the high accuracy of the proposed method for electricity demand forecasting.

关键词： Load modeling Predictive models Mathematical model Smart grids Probabilistic logic Demand forecasting

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A randomized study comparing digital imaging to traditional glass slide microscopy for breast biopsy and cancer diagnosis

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Journal of Pathology Informatics 2017年第1期8卷 12-12页

作者： Elmore, Joann G. Longton, Gary M. Pepe, Margaret S. Carney, Patricia A. Nelson, Heidi D. Allison, Kimberly H. Geller, Berta M. Onega, Tracy Tosteson, Anna N.A. Mercan, Ezgi Shapiro, Linda G. Brunyé, Tad T. Morgan, Thomas R. Weaver, Donald L. Department of Medicine University of Washington School of Medicine Seattle 98104 WA United States Fred Hutchinson Cancer Research Center Seattle 98109 WA United States Department of Biostatistics University of Washington School of Public Health Seattle 98104 WA United States Department of Family Medicine Oregon Health and Science University Portland 97239 OR United States Department of Medical Informatics and Clinical Epidemiology Oregon Health and Science University Portland 97239 OR United States Providence Cancer Center Providence Health and Services Oregon Portland 97213 OR United States Department of Pathology Stanford University School of Medicine Stanford 94305 CA United States Department of Family Medicine University of Vermont Burlington 05405 VT United States Department of Biomedical Data Science Geisel School of Medicine at Dartmouth Lebanon 03756 NH United States Dartmouth Institute for Health Policy and Clinical Practice Norris Cotton Cancer Center Geisel School of Medicine at Dartmouth Lebanon 03756 NH United States Department of Computer Science and Engineering University of Washington Seattle 98195 WA United States Department of Psychology Tufts University Medford 02155 MA United States Department of Pathology UVM Cancer Center University of Vermont Burlington 05405 VT United States

Background: Digital whole slide imaging may be useful for obtaining second opinions and is used in many countries. However, the U.S. Food and Drug Administration requires verification studies. Methods: Pathologists were randomized to interpret one of four sets of breast biopsy cases during two phases, separated by ≥9 months, using glass slides or digital format (sixty cases per set, one slide per case, n = 240 cases). Accuracy was assessed by comparing interpretations to a consensus reference standard. Intraobserver reproducibility was assessed by comparing the agreement of interpretations on the same cases between two phases. Estimated probabilities of confirmation by a reference panel (i.e., predictive values) were obtained by incorporating data on the population prevalence of diagnoses. Results: Sixty-five percent of responding pathologists were eligible, and 252 consented to randomization;208 completed Phase I (115 glass, 93 digital);and 172 completed Phase II (86 glass, 86 digital). Accuracy was slightly higher using glass compared to digital format and varied by category: invasive carcinoma, 96% versus 93% (P = 0.04);ductal carcinoma in situ (DCIS), 84% versus 79% (P < 0.01);atypia, 48% versus 43% (P = 0.08);and benign without atypia, 87% versus 82% (P < 0.01). There was a small decrease in intraobserver agreement when the format changed compared to when glass slides were used in both phases (P = 0.08). Predictive values for confirmation by a reference panel using glass versus digital were: invasive carcinoma, 98% and 97% (not significant [NS]);DCIS, 70% and 57% (P = 0.007);atypia, 38% and 28% (P = 0.002);and benign without atypia, 97% and 96% (NS). Conclusions: In this large randomized study, digital format interpretations were similar to glass slide interpretations of benign and invasive cancer cases. However, cases in the middle of the spectrum, where more inherent variability exists, may be more problematic in digital format. Future studies evaluating the

关键词： Breast cancer diagnostic accuracy digital whole-slide imaging intraobserver reproducibility

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