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2nd International Conference on Communication and computer engineering, ICOCOE 2015

作者： Azemin, Mohd Zulfaezal Che Hamid, Fadilah Ab Wang, Jie Jin Kawasaki, Ryo Kumar, Dinesh Kant Kulliyyah of Allied Health Sciences International Islamic University Malaysia Kuantan Malaysia Department of Ophthalmology and Westmead Millenium Institute University of Sydney Sydney Australia Department of Public Health Yamagata University Yamagata Japan School of Electrical and Computer Engineering RMIT University Melbourne Australia

ISBN: (纸本)9783319245829

This research work investigates the influences of FD algorithm variation on the measurement of retinal vasculature complexity. Forty retinal vasculature images from publicly available dataset were subjected to four variations of box-counting FD algorithm. Different positions of box-grid were found to significantly affect the measurement of FD (p © Springer International Publishing Switzerland 2016.

关键词： Fractal dimension

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Dynamic data center load response to variability in private and public electricity costs

Dynamic data center load response to variability in private ...

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IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Nathaniel Horner Inês Azevedo Doug Sicker Yuvraj Agarwal Department of Engineering and Public Policy Carnegie Mellon University Pittsburgh PA School of Computer Science Carnegie Mellon University Pittsburgh PA

ISBN: (纸本)9781509040766

This paper assesses the potential cost-saving incentives for content distribution networks to shift traffic load among geographically distributed data centers in response to hourly variation in electricity prices. Such incentives are likely aligned with benefits to utilities and grid operators, which might take the form of peak-shaving or ancillary services. However, private cost savings are not strictly aligned with public benefits related to the avoidance of health and environmental damages from power plant emissions, so we compare private cost minimization with a strategy that minimizes these externalities. We find that feasible strategies exist to simultaneously realize public and private benefits and that load shifting can result in substantial cost savings and avoided damages in some circumstances. Concerns over increased latency and bandwidth costs can be mitigated with modifications to the model. However, the level of realized savings is dependent upon the specifics of a particular network operator and electricity rate schedule.

关键词： Smart grids Conferences Load modeling Electric potential Power generation Servers Real-time systems

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BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification

arXiv

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arXiv 2017年

作者： Aguiar, Derek Cheng, Li-Fang Dumitrascu, Bianca Mordelet, Fantine Pai, Athma A. Engelhardt, Barbara E. Department of Computer Science Princeton University PrincetonNJ United States Department of Electrical Engineering Princeton University PrincetonNJ United States Lewis Sigler Institute Princeton University PrincetonNJ United States Institute for Genome Sciences and Policy Duke University DurhamNC United States Department of Biology Massachusetts Institute of Technology CambridgeMA United States Center for Statistics and Machine Learning Princeton University PrincetonNJ United States

Most human protein-coding genes can be transcribed into multiple possible distinct mRNA isoforms. These alternative splicing patterns encourage molecular diversity and dysregulation of isoform expression plays an important role in disease etiology. However, isoforms are difficult to characterize from short-read RNA-seq data because they share identical subsequences and exist in tissue- and sample-specific frequencies. Here, we develop BIISQ, a Bayesian nonparametric model to discover Isoforms and Individual Specific Quantification from RNA-seq data. BIISQ does not require known isoform reference sequences but instead estimates isoform composition directly with an isoform catalog shared across samples. We develop a stochastic variational inference approach for efficient and robust posterior inference and demonstrate superior precision and recall for short read RNA-seq simulations and simulated short read data from PacBio long read sequencing when compared to state-of-the-art isoform reconstruction methods. BIISQ achieves the most significant gains for longer (in terms of exons) isoforms and isoforms that are lowly expressed (over 500% more transcripts correctly inferred at low coverage in simulations). Finally, we estimate isoforms in the GEUVADIS RNA-seq data, identify genetic variants that regulate transcript ratios, and demonstrate variant enrichment in functional elements related to mRNA splicing regulation. Copyright © 2017, The Authors. All rights reserved.

关键词： RNA

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Conditional Survival Analysis of Patients With Locally Advanced Laryngeal Cancer: Construction of a Dynamic Risk Model and Clinical Nomogram

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SCIENTIFIC REPORTS 2017年第1期7卷 43928-43928页

作者： Sheu, Tommy Vock, David M. Mohamed, Abdallah S. R. Gross, Neil Mulcahy, Collin Zafereo, Mark Gunn, G. Brandon Garden, Adam S. Sevak, Parag Phan, Jack Lewin, Jan S. Frank, Steven J. Beadle, Beth M. Morrison, William H. Lai, Stephen Y. Hutcheson, Katherine Marai, G. Elisabeta Canahuate, Guadalupe M. Kies, Merrill El-Naggar, Adel Weber, Randal S. Rosenthal, David I. Fuller, Clifton D. Department of Radiation Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Clinical Oncology and Nuclear Medicine University of Alexandria Alexandria Egypt Division of Biostatistics University of Minnesota School of Public Health Minneapolis Minnesota USA Department of Head and Neck Surgery The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Radiation Oncology Henry Ford Hospital Detroit MI USA Department of Computer Science University of Illinois at Chicago Chicago Illinois USA Department of Electrical & Computer Engineering University of Iowa Iowa City IA USA Department of Medical Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Pathology The University of Texas MD Anderson Cancer Center Houston Texas USA

Conditional survival (CS), the survival beyond a pre-defined time interval, can identify periods of higher mortality risk for patients with locally advanced laryngeal cancer who face treatment-related toxicity and comorbidities related to alcohol and smoking in the survivorship setting. Using Weibull regression modeling, we analyzed retrospectively abstracted data from 638 records of patients who received radiation to identify prognostic factors for overall survival (OS) and recurrence free survival (RFS) for the first 3 years of survival and for OS conditional upon 3 years of survival. The CS was iteratively calculated, stratifying on variables that were statistically significant on multivariate regression. Predictive nomograms were generated. The median total follow up time was 175 months. The 3-and 6-year actuarial overall survival (OS) was 68% (95% confidence interval [CI] 65-72%) and 49% (CI 45-53%). The 3-year conditional overall survival (COS) at 3 years was 72% (CI 65-74%). Black patients had worse COS over time. Nodal disease was significantly associated with recurrence, but after 3 years, the 3-year conditional RFS converged for all nodal groups. In conclusion, the CS analysis in this patient cohort identified subgroups and time intervals that may represent opportunities for intervention.

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Smart building energy efficiency via social game: a robust utility learning framework for closing–the–loop

Smart building energy efficiency via social game: a robust u...

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International Workshop on Science of Smart City Operations and Platforms engineering (SCOPE) in partnership with Global City Teams Challenge (GCTC) (SCOPE - GCTC)

作者： Ioannis C. Konstantakopoulos Lillian J. Ratliff Ming Jin Costas Spanos S. Shankar Sastry Scholar of the Alexander S. Onassis Public Benefit Foundation Department of Electrical Engineering and Computer Sciences University of California Berkeley CA

ISBN: (纸本)9781509011704

Given a non-cooperative, continuous game, we describe a framework for parametric utility learning. Using heteroskedasticity inference, we adapt a Constrained Feasible Generalized Least Squares (cFGLS) utility learning method in which estimator variance is reduced, unbiased, and consistent. We extend our utility learning method using bootstrapping and bagging. We show the performance of the proposed method using data from a social game experiment designed to encourage energy efficient behavior amongst building occupants. Using occupant voting data we simulate the game defined by the estimated utility functions and show that the performance of our robust utility learning method and quantify its improvement over classical methods such as Ordinary Least Squares (OLS).

关键词： Games Nash equilibrium Estimation Lighting Robustness Smart buildings

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Advances in Microwave Ablation Antennas for Breast Tumor Treatment

Advances in Microwave Ablation Antennas for Breast Tumor Tre...

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European Conference on Antennas and Propagation

作者： R. Owen Mays L. M. Neira H. Luyen L. G. Wilke N. Behdad S. C. Hagness Department of Electrical and Computer Engineering College of Engineering University of Wisconsin-Madison Madison WI USA Department of Surgery School of Medicine and Public Health University of Wisconsin-Madison Madison WI USA

ISBN: (纸本)9781509022342

In contrast to other types of cancer, breast cancer remains a relatively unexplored target for microwave ablation (MWA) technology. We highlight two recent developments towards the clinical realization of MWA for breast tumor treatment: the design of miniaturized MWA antennas that achieve compact heating patterns without the use of a balun and the investigation of microwave-induced heating in the heterogeneous tissue environment of the breast. Our electromagnetic and thermal simulation results using 3D MRI-derived breast phantoms as testbeds show the potential of MWA as a viable minimally invasive modality for treating breast cancer.

关键词： microwave ablation miniaturized antennas microwave thermal therapy breast cancer treatment breast phantoms

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Correction: Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial

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JMIR research protocols 2020年第12期9卷 e25940页

作者： Rhiannon E Halse Charlene L Shoneye Christina M Pollard Jonine Jancey Jane A Scott Iain S Pratt Satvinder S Dhaliwal Richard Norman Leon M Straker Carol J Boushey Edward J Delp Fengqing Zhu Amelia J Harray Maria A Szybiak Anne Finch Joanne A McVeigh Barbara Mullan Clare E Collins Syed Aqif Mukhtar Kieran N Edwards Janelle D Healy Deborah A Kerr School of Public Health Curtin University Perth Western Australia Australia. East Metropolitan Health Service Perth Western Australia Australia. Cancer Council WA Perth Western Australia Australia. Health Psychology & Behavioural Medicine Research Group School of Psychology Curtin University Perth Western Australia Australia. School of Physiotherapy and Exercise Science Curtin University Perth Western Australia Australia. Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu HI United States. Department of Nutrition Purdue University West Lafayette IN United States. School of Electrical and Computer Engineering Purdue University West Lafayette IN United States. School of Occupational Therapy Speech Therapy & Social Work Curtin University Perth Western Australia Australia. Movement Physiology Laboratory University of Witwatersrand Johannesburg South Africa. School of Health Sciences Faculty of Health and Medicine University of Newcastle Callaghan New South Wales Australia. Priority Research Centre in Physical Activity and Nutrition University of Newcastle Callaghan New South Wales Australia. Curtin Institute of Computation Curtin University Perth Western Australia Australia.

[This corrects the article DOI: 10.2196/12782.].

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MATLAB-based analysis of labor dispatch and work distribution: An example involving caseworkers in central Taiwan

MATLAB-based analysis of labor dispatch and work distributio...

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International Conference on Applied System Innovation (ICASI)

作者： Chin-Yu Oh Meng-Chueh Hsu Chang-Ming Tsai Jyun-Yao Jhang Yu-Ren Chen Bo-Xiang Chen Yi-Chung Chen Chun-Wen Teng Shu-Hui Chen Department of Information Engineering and Computer Science Feng Chia University Taichung Taiwan R.O.C. Ph. D. Program of Business Feng Chia University Taichung Taiwan R.O.C. The Graduate Institute of Public Policy and social innovation Feng Chia University Taichung Taiwan R.O.C. General Education Center Feng Chia University Taichung Taiwan R.O.C.

ISBN: (纸本)9781509048984

The dispatching of labor and distribution of tasks among workers are important aspects of corporate operations. Labor dispatch refers to the dispatching of employees to meet with clients; however, dispatches commonly vary with time. This means that any analysis pertaining to labor dispatch and work distribution should also vary with time. In this study, MATLAB was used to analyze data from anonymous caseworkers in central Taiwan in order to identify relationships between the location of their offices and the homes of their clients. Our aim was to determine the rationality behind labor dispatch and work distribution. This led us to develop a novel method by which to dispatch labor in order to achieve a more equitable distribution of work. Simulations demonstrate the efficacy of the proposed scheme in improving labor dispatch and work distribution.

关键词： Dispatching Technological innovation MATLAB Feature extraction Roads Urban areas Conferences

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Home-based tele-rehabilitation presents comparable and positive impact on self-reported functional outcomes as center-based rehabilitation: Singapore tele-technology aided rehabilitation in stroke (STARS) trial

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Annals of Physical and Rehabilitation Medicine 2018年 61卷 e22-e23页

作者： Asano, M. Tai, B.C. Chen, C. Yen, S.C. Tay, A. Cheong, A. Ng, Y.S. De Silva, D.A. Caves, K. Kumar, Y. Phan, S.W. Cai, V. Wong, N. Chew, E. Chen, Z. Hoenig, H. Koh, G. National University of Singapore Saw Swee Hock School of Public Health Singapore National University of Singapore Department of Electrical & Computer Engineering Singapore Singapore General Hospital Department of Rehabilitation Medicine Singapore National Neuroscience Institute Neurology Singapore Duke University Medical Center Department of Surgery Durham USA National University Hospital Department of Rehabilitation Medicine Singapore National University Health System Investigational Medicine Unit Singapore Durham Veterans Affairs Medical Centre Physical Medicine & Rehabilitation Service Durham USA

Introduction/Background Stroke is a leading cause of disability worldwide. Functional, financial and social barriers commonly prevent individuals with acute stroke and disabilities from receiving rehabilitation following their hospital discharge. Home-based rehabilitation is an alternative to center-based rehabilitation but it is often costlier. Tele-rehabilitation is a promising solution for optimizing rehabilitation utilization, as it can enable clinicians to supervise patients and conversely, patients to receive the recommended care remotely. Our team therefore developed a novel tele-rehabilitation, with the primary aim to estimate the extent to which the proposed tele-rehabilitation resulted in an improvement in function during the first three-months after stroke in comparison to usual rehabilitation. Material and method This was a randomized controlled trial. We used the Late-Life Function and Disability Instrument (FDI) to assess our primary outcome (with adjustment made for baseline covariate). Results We recruited 124 participants and randomized them to receive either 12-week home-based tele-rehabilitation or usual rehabilitation. Rehabilitation Over the 12-week rehabilitation period, the intervention group spent 2246-minutes on their rehabilitation whereas the control group spent 2565-minutes. The median difference between the two groups was not statistically significant ( P = 0.649). Primary Outcome (FDI) The mean FDI frequency score post-rehabilitation for the intervention and control groups were 39.7 (SD 11.7) and 43.0 (SD 10.6) respectively. The mean FDI limitation score post-rehabilitation for the intervention group was 78.5 (SD 20.6) and that for the control group was 85.4 (SD 19.6). The unadjusted and adjusted differences in both FDI scores between the two groups were not statistically significant (Models 1 and 2). Conclusion Both groups reported comparable amount of time spent on rehabilitation and similarly positive impact on the primary outcome. H

关键词： Stroke Telerehabilitation Randomized controlled trial

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Deep learning for multi-messenger astrophysics a gateway for discovery in the big data era

arXiv

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arXiv 2019年

作者： Allen, Gabrielle Andreoni, Igor Bachelet, Etienne Bruce Berriman, G. Bianco, Federica B. Biswas, Rahul Kind, Matias Carrasco Chard, Kyle Cho, Minsik Cowperthwaite, Philip S. Etienne, Zachariah B. George, Daniel Gibbs, Tom Graham, Matthew Gropp, William Gupta, Anushri Haas, Roland Huerta, E.A. Jennings, Elise Katz, Daniel S. Khan, Asad Kindratenko, Volodymyr Kramer, William T.C. Liu, Xin Mahabal, Ashish McHenry, Kenton Miller, J.M. Neubauer, M.S. Oberlin, Steve Olivas, Alexander R. Rosofsky, Shawn Ruiz, Milton Saxton, Aaron Schutz, Bernard Schwing, Alex Seidel, Ed Shapiro, Stuart L. Shen, Hongyu Shen, Yue Sipocz, Brigitta M. Sun, Lunan Towns, John Tsokaros, Antonios Wei, Wei Wells, Jack Williams, Timothy J. Xiong, Jinjun Zhao, Zhizhen NCSA University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Astronomy University of Illinois at Urbana-Champaign UrbanaIL61801 United States California Institute of Technology 1200 E California Blvd PasadenaCA91125 United States Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117 United States Caltech/IPAC-NExScI 1200 E California Blvd PasadenaCA91125 United States Department of Physics and Astronomy University of Delaware NewarkDE19716 United States Joseph R. Biden Jr . School of Public Policy and Administration University of Delaware NewarkDE19716 United States Data Science Institute University of Delaware NewarkDE19716 United States Center for Urban Science and Progress New York University 370 Jay St BrooklynNY11201 United States The Oskar Klein Centre for Cosmoparticle Physics Stockholm University AlbaNova StockholmSE-106 91 Sweden University of Chicago ChicagoIL60605 United States IBM Systems AustinTX78717 United States Observatories of the Carnegie Institution for Science 813 Santa Barbara St. PasadenaCA91101 United States Department of Mathematics West Virginia University MorgantownWV26506 United States Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV26505 United States NVIDIA 2788 San Tomas Expressway Santa ClaraCA95050 United States Center for Data Driven Discovery Caltech PasadenaCA91125 United States Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 United States Argonne National Laboratory Leadership Computing Facility LemontIL60439 United States Department of Electrical & Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States School of Information Sciences University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Physics University of Illinois at Urbana-Champaign UrbanaIL61801 Unit

This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging the transdisciplinary nature of Multi-Messenger Astrophysics, this document has been prepared by members of the physics, astronomy, computer science, data science, software and cyberinfrastructure communities who attended the NSF-, DOE- and NVIDIA-funded "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at the National Center for Supercomputing Applications, October 17-19, 2018. Highlights of this report include unanimous agreement that it is critical to accelerate the development and deployment of novel, signal-processing algorithms that use the synergy between artificial intelligence (AI) and high performance computing to maximize the potential for scientific discovery with Multi-Messenger Astrophysics. We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics;(ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data;(iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups;(iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era;(v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics. Copyright © 2019, The Authors. All rights reserved.

关键词： Big data

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